{
  "version": 1,
  "home_page_url": "https://digidai.github.io/",
  "index_url": "https://digidai.github.io/content-index.json",
  "research_index_url": "https://digidai.github.io/research/index.json",
  "answers_index_url": "https://digidai.github.io/answers/index.json",
  "description": "All published articles. Use id or html_url when citing; markdown_url provides the same editorial text without the site interface.",
  "count": 424,
  "date_modified": "2026-10-05T00:00:00.000Z",
  "items": [
    {
      "id": "https://digidai.github.io/2026/10/05/amazon-data-center-towns-billion-workforce-promise/",
      "title": "The Local Bill Behind Amazon's $1 Billion Data Center Pledge",
      "summary": "Amazon promises $1 billion for data center towns. Short trade courses, lasting jobs, electricity costs and local control still require separate proof.",
      "html_url": "https://digidai.github.io/2026/10/05/amazon-data-center-towns-billion-workforce-promise/",
      "markdown_url": "https://digidai.github.io/2026/10/05/amazon-data-center-towns-billion-workforce-promise/index.md",
      "date_published": "2026-10-05T00:00:00.000Z",
      "date_modified": "2026-10-05T00:00:00.000Z",
      "tags": [
        "Artificial Intelligence",
        "Data Centers",
        "Workforce",
        "Skilled Trades",
        "Energy",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/10/04/anthropic-frontier-academy-engineer-residency/",
      "title": "A $100 Million Bet on Engineers Who Can Deploy Claude",
      "summary": "Anthropic's Claude Frontier Academy promises to train 10,000 deployment engineers by the end of 2027. Its 12-week residency puts a harder test behind the badge: can a customer run the system after training?",
      "html_url": "https://digidai.github.io/2026/10/04/anthropic-frontier-academy-engineer-residency/",
      "markdown_url": "https://digidai.github.io/2026/10/04/anthropic-frontier-academy-engineer-residency/index.md",
      "date_published": "2026-10-04T00:00:00.000Z",
      "date_modified": "2026-10-04T00:00:00.000Z",
      "tags": [
        "Artificial Intelligence",
        "Enterprise AI",
        "Engineering",
        "Workforce",
        "Skills",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/10/02/workday-product-jobs-dubai-ai-reorganization/",
      "title": "Workday Cut Product Jobs, Then Opened an Office in Dubai",
      "summary": "Workday disclosed a 2.5% workforce cut centered on product and technology, then opened a Dubai office. Its AI expansion leaves a specific question about delivery capacity.",
      "html_url": "https://digidai.github.io/2026/10/02/workday-product-jobs-dubai-ai-reorganization/",
      "markdown_url": "https://digidai.github.io/2026/10/02/workday-product-jobs-dubai-ai-reorganization/index.md",
      "date_published": "2026-10-02T00:00:00.000Z",
      "date_modified": "2026-10-02T00:00:00.000Z",
      "tags": [
        "Artificial Intelligence",
        "Enterprise Software",
        "Workforce",
        "Organization Design",
        "Workday",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/10/01/international-paper-relay-factory-radio-ai-budget/",
      "title": "International Paper Put Relay's Factory Radio in the AI Budget",
      "summary": "International Paper led Relay's $36 million round. Its radios can make worker talk searchable.",
      "html_url": "https://digidai.github.io/2026/10/01/international-paper-relay-factory-radio-ai-budget/",
      "markdown_url": "https://digidai.github.io/2026/10/01/international-paper-relay-factory-radio-ai-budget/index.md",
      "date_published": "2026-10-01T00:00:00.000Z",
      "date_modified": "2026-10-01T00:00:00.000Z",
      "tags": [
        "Artificial Intelligence",
        "Frontline Work",
        "Manufacturing",
        "Voice Technology",
        "Worker Privacy",
        "Enterprise Software",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/09/30/mechanical-turk-shutdown-human-ai-work/",
      "title": "Mechanical Turk Reaches Its Final Day. AI Still Hires Humans",
      "summary": "Amazon set September 30 as Mechanical Turk's final task deadline. Workers, researchers and AI teams now face a different market for paid human judgment, with new costs and unresolved protections.",
      "html_url": "https://digidai.github.io/2026/09/30/mechanical-turk-shutdown-human-ai-work/",
      "markdown_url": "https://digidai.github.io/2026/09/30/mechanical-turk-shutdown-human-ai-work/index.md",
      "date_published": "2026-09-30T00:00:00.000Z",
      "date_modified": "2026-09-30T00:00:00.000Z",
      "tags": [
        "Artificial Intelligence",
        "Crowdwork",
        "Data Labor",
        "Research",
        "Future of Work",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/09/29/databricks-row-zero-ai-spreadsheet-work/",
      "title": "Databricks Acquired Row Zero for Work That Still Ends in Cells",
      "summary": "Databricks is adding Row Zero to Genie after its finance team paired the products. The acquisition shifts the AI coworker contest toward cell-level provenance, review and controlled writeback.",
      "html_url": "https://digidai.github.io/2026/09/29/databricks-row-zero-ai-spreadsheet-work/",
      "markdown_url": "https://digidai.github.io/2026/09/29/databricks-row-zero-ai-spreadsheet-work/index.md",
      "date_published": "2026-09-29T00:00:00.000Z",
      "date_modified": "2026-09-29T00:00:00.000Z",
      "tags": [
        "Artificial Intelligence",
        "Spreadsheets",
        "Databricks",
        "Finance",
        "Future of Work",
        "Enterprise Software",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/09/28/ema-ai-employees-software-services-budget/",
      "title": "Ema Raised $77 Million to Replace Software Seats and Service Hours",
      "summary": "Ema says its AI employees can absorb work sold as software and IT services. A buyer still has to prove which licenses, service hours and review costs actually leave the budget.",
      "html_url": "https://digidai.github.io/2026/09/28/ema-ai-employees-software-services-budget/",
      "markdown_url": "https://digidai.github.io/2026/09/28/ema-ai-employees-software-services-budget/index.md",
      "date_published": "2026-09-28T00:00:00.000Z",
      "date_modified": "2026-09-28T00:00:00.000Z",
      "tags": [
        "Artificial Intelligence",
        "Enterprise Software",
        "IT Services",
        "Future of Work",
        "AI Agents",
        "AI Economics",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/09/27/harver-symphony-talent-job-ads-hiring-tests/",
      "title": "Harver Bought Symphony Talent to Link Job Ads With Hiring Tests",
      "summary": "Harver's acquisition of Symphony Talent joins recruitment ads, CRM, assessments and fraud checks. The buyer test is whether spend can be traced to valid hiring outcomes without hiding candidate risk.",
      "html_url": "https://digidai.github.io/2026/09/27/harver-symphony-talent-job-ads-hiring-tests/",
      "markdown_url": "https://digidai.github.io/2026/09/27/harver-symphony-talent-job-ads-hiring-tests/index.md",
      "date_published": "2026-09-27T00:00:00.000Z",
      "date_modified": "2026-09-27T00:00:00.000Z",
      "tags": [
        "Artificial Intelligence",
        "Recruiting",
        "HR Technology",
        "Candidate Experience",
        "Talent Assessment",
        "Mergers and Acquisitions",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/09/23/ai-skill-erosion-critical-thinking-work-redesign/",
      "title": "Workers Fear Skill Erosion as CHROs Ask for More Judgment",
      "summary": "IBM's new global workforce study finds employees worried about skill erosion as employers demand more judgment around AI. Research on productivity, learning, and overreliance points to a task-level way to protect output and capability.",
      "html_url": "https://digidai.github.io/2026/09/23/ai-skill-erosion-critical-thinking-work-redesign/",
      "markdown_url": "https://digidai.github.io/2026/09/23/ai-skill-erosion-critical-thinking-work-redesign/index.md",
      "date_published": "2026-09-23T00:00:00.000Z",
      "date_modified": "2026-09-23T00:00:00.000Z",
      "tags": [
        "Artificial Intelligence",
        "Future of Work",
        "Workforce Development",
        "Critical Thinking",
        "Employee Experience",
        "HR Strategy",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/09/22/meta-tokenmaxxing-performance-review-guidance/",
      "title": "Meta Rewrote Performance Reviews After Tokenmaxxing",
      "summary": "Meta's September guidance shifted attention from AI usage to contribution as companies link AI skills to promotion without shared standards. A five-level rubric separates tool activity from judgment, verification, and team impact.",
      "html_url": "https://digidai.github.io/2026/09/22/meta-tokenmaxxing-performance-review-guidance/",
      "markdown_url": "https://digidai.github.io/2026/09/22/meta-tokenmaxxing-performance-review-guidance/index.md",
      "date_published": "2026-09-22T00:00:00.000Z",
      "date_modified": "2026-09-22T00:00:00.000Z",
      "tags": [
        "Artificial Intelligence",
        "Performance Management",
        "AI Skills",
        "Meta",
        "Career Development",
        "Future of Work",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/09/21/typesafe-jev-jevable-decision-models/",
      "title": "TypeSafe's Jev, From Model Launch to Jevable's Early Projects",
      "summary": "TypeSafe's Jev returns decisions instead of prose. Jevable's early apps reveal where that design helps, what the low token price leaves out, and how to test its confidence.",
      "html_url": "https://digidai.github.io/2026/09/21/typesafe-jev-jevable-decision-models/",
      "markdown_url": "https://digidai.github.io/2026/09/21/typesafe-jev-jevable-decision-models/index.md",
      "date_published": "2026-09-21T00:00:00.000Z",
      "date_modified": "2026-09-21T00:00:00.000Z",
      "tags": [
        "Artificial Intelligence",
        "TypeSafe",
        "Jev",
        "Software Development",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/09/20/frontline-shift-cost-pay-schedule-ai/",
      "title": "Before an Hourly Shift Starts, Workers Price Gas and Childcare",
      "summary": "A new frontline-worker survey shows that a shift decision starts with transport, care, schedule control, and pay timing before AI enters the workflow.",
      "html_url": "https://digidai.github.io/2026/09/20/frontline-shift-cost-pay-schedule-ai/",
      "markdown_url": "https://digidai.github.io/2026/09/20/frontline-shift-cost-pay-schedule-ai/index.md",
      "date_published": "2026-09-20T00:00:00.000Z",
      "date_modified": "2026-09-21T00:00:00.000Z",
      "tags": [
        "AI",
        "Frontline Workforce",
        "Scheduling",
        "Earned Wage Access",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/09/19/phoenix-education-fuel50-skills-map/",
      "title": "Phoenix Education Agreed to Pay $31.5 Million for Fuel50's Skills Map",
      "summary": "Phoenix Education's Fuel50 deal could connect course skills, enterprise workforce data, and internal moves, but the public record does not yet show the data boundary or outcome test.",
      "html_url": "https://digidai.github.io/2026/09/19/phoenix-education-fuel50-skills-map/",
      "markdown_url": "https://digidai.github.io/2026/09/19/phoenix-education-fuel50-skills-map/index.md",
      "date_published": "2026-09-19T00:00:00.000Z",
      "date_modified": "2026-09-19T00:00:00.000Z",
      "tags": [
        "Artificial Intelligence",
        "HR Tech",
        "Internal Mobility",
        "Education",
        "Skills",
        "Mergers and Acquisitions",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/09/17/aristotle-ai-tutoring-hours-learning-outcomes/",
      "title": "Aristotle Logged 1,500 AI Tutoring Hours Without Publishing a Learning Outcome",
      "summary": "Aristotle launched nationwide after 1,500 tutoring hours, but usage, ratings, price, and testimonials still leave student learning unmeasured.",
      "html_url": "https://digidai.github.io/2026/09/17/aristotle-ai-tutoring-hours-learning-outcomes/",
      "markdown_url": "https://digidai.github.io/2026/09/17/aristotle-ai-tutoring-hours-learning-outcomes/index.md",
      "date_published": "2026-09-17T00:00:00.000Z",
      "date_modified": "2026-09-17T00:00:00.000Z",
      "tags": [
        "Artificial Intelligence",
        "Education",
        "EdTech",
        "Learning and Development",
        "Future of Work",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/09/16/digit-5-orders-humanoid-safety-standard/",
      "title": "Digit 5 Carries a $300 Million Order Book Into an Unfinished Safety Standard",
      "summary": "Agility's Digit 5 pairs a conditional 1,000-robot order with a plan to work near people, while recognized revenue, field proof, and humanoid-specific safety rules remain far behind the pitch.",
      "html_url": "https://digidai.github.io/2026/09/16/digit-5-orders-humanoid-safety-standard/",
      "markdown_url": "https://digidai.github.io/2026/09/16/digit-5-orders-humanoid-safety-standard/index.md",
      "date_published": "2026-09-16T00:00:00.000Z",
      "date_modified": "2026-09-16T00:00:00.000Z",
      "tags": [
        "Artificial Intelligence",
        "Robotics",
        "Manufacturing",
        "Workplace Safety",
        "Future of Work",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/09/15/ionos-450-job-cuts-ai-reinvestment/",
      "title": "IONOS Pairs 450 Planned Job Cuts With AI Reinvestment",
      "summary": "IONOS plans to reduce full-time employment from about 3,800 to 3,350 and expects up to €30 million in annual savings while it expands AI products and cloud capacity.",
      "html_url": "https://digidai.github.io/2026/09/15/ionos-450-job-cuts-ai-reinvestment/",
      "markdown_url": "https://digidai.github.io/2026/09/15/ionos-450-job-cuts-ai-reinvestment/index.md",
      "date_published": "2026-09-15T00:00:00.000Z",
      "date_modified": "2026-09-15T00:00:00.000Z",
      "tags": [
        "Artificial Intelligence",
        "Workforce Restructuring",
        "Cloud Computing",
        "Future of Work",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/09/14/mistral-194-open-roles-beyond-model-lab/",
      "title": "Mistral Has 194 Open Roles Beyond the Model Lab",
      "summary": "Mistral's live job board connects its €3 billion round to solutions, infrastructure, hiring operations, and two explicitly early-career roles.",
      "html_url": "https://digidai.github.io/2026/09/14/mistral-194-open-roles-beyond-model-lab/",
      "markdown_url": "https://digidai.github.io/2026/09/14/mistral-194-open-roles-beyond-model-lab/index.md",
      "date_published": "2026-09-14T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Artificial Intelligence",
        "Startup Hiring",
        "AI Careers",
        "Cloud Infrastructure",
        "Future of Work"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/09/13/oracle-stock-sale-ai-restructuring-plan/",
      "title": "Oracle Sold $20 Billion of Stock as Its AI Restructuring Plan Grew",
      "summary": "Oracle reported 121% infrastructure growth while spending $28.5 billion on capex, selling $20 billion of stock, and expanding an AI-linked restructuring plan.",
      "html_url": "https://digidai.github.io/2026/09/13/oracle-stock-sale-ai-restructuring-plan/",
      "markdown_url": "https://digidai.github.io/2026/09/13/oracle-stock-sale-ai-restructuring-plan/index.md",
      "date_published": "2026-09-13T00:00:00.000Z",
      "date_modified": "2026-09-13T00:00:00.000Z",
      "tags": [
        "Artificial Intelligence",
        "Cloud Infrastructure",
        "Capital Allocation",
        "Workforce Restructuring",
        "Future of Work"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/09/11/chatgpt-work-data-agent-dashboard-labor/",
      "title": "OpenAI Put a Dashboard Builder Inside ChatGPT Work",
      "summary": "OpenAI's Data agent lets business users build dashboards in ChatGPT Work. The harder job moves to metric definitions, benchmarks, permissions, and review.",
      "html_url": "https://digidai.github.io/2026/09/11/chatgpt-work-data-agent-dashboard-labor/",
      "markdown_url": "https://digidai.github.io/2026/09/11/chatgpt-work-data-agent-dashboard-labor/index.md",
      "date_published": "2026-09-11T00:00:00.000Z",
      "date_modified": "2026-09-11T00:00:00.000Z",
      "tags": [
        "Artificial Intelligence",
        "Data Analytics",
        "Future of Work",
        "Employee Experience",
        "Organizational Design"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/09/10/ai-sandbox-141-solutions-hidden-work/",
      "title": "One Employer Reached 141 AI Solutions. Another Kept Three.",
      "summary": "MIT researchers found 141 organization-wide AI solutions at one employer and three at another. The gap points to protected time, shared review, technical support, and career credit.",
      "html_url": "https://digidai.github.io/2026/09/10/ai-sandbox-141-solutions-hidden-work/",
      "markdown_url": "https://digidai.github.io/2026/09/10/ai-sandbox-141-solutions-hidden-work/index.md",
      "date_published": "2026-09-10T00:00:00.000Z",
      "date_modified": "2026-09-10T00:00:00.000Z",
      "tags": [
        "Enterprise AI",
        "Organizational Design",
        "Future of Work",
        "Employee Experience",
        "AI Skills"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/09/09/aslan-six-senior-roles-ai-agents/",
      "title": "Six Senior Roles Surround Aslan's AI Agents",
      "summary": "A ten-person national-security AI startup has six senior openings. Its job board shows the engineering, evaluation, government, and operating work that autonomy does not remove.",
      "html_url": "https://digidai.github.io/2026/09/09/aslan-six-senior-roles-ai-agents/",
      "markdown_url": "https://digidai.github.io/2026/09/09/aslan-six-senior-roles-ai-agents/index.md",
      "date_published": "2026-09-09T00:00:00.000Z",
      "date_modified": "2026-10-02T00:00:00.000Z",
      "tags": [
        "AI jobs",
        "startups",
        "national security",
        "agentic AI",
        "hiring"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/09/08/ai-data-center-switchgear-factory-jobs/",
      "title": "Switchgear Jobs Behind the AI Order Book",
      "summary": "Siemens and Eaton link AI data-center demand to 1,700 planned U.S. jobs. A ledger separates orders, factories, hiring, pay, and production.",
      "html_url": "https://digidai.github.io/2026/09/08/ai-data-center-switchgear-factory-jobs/",
      "markdown_url": "https://digidai.github.io/2026/09/08/ai-data-center-switchgear-factory-jobs/index.md",
      "date_published": "2026-09-08T00:00:00.000Z",
      "date_modified": "2026-09-08T00:00:00.000Z",
      "tags": [
        "Artificial Intelligence",
        "Data Centers",
        "Manufacturing",
        "Electrical Infrastructure",
        "Future of Work",
        "Workforce Planning",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/09/07/ai-hiring-pullback-without-layoffs/",
      "title": "AI Pulls Back Hiring Without Mass Layoffs",
      "summary": "Federal Reserve, payroll, and employer evidence shows how AI can reduce job openings and early-career starts before it produces a layoff notice.",
      "html_url": "https://digidai.github.io/2026/09/07/ai-hiring-pullback-without-layoffs/",
      "markdown_url": "https://digidai.github.io/2026/09/07/ai-hiring-pullback-without-layoffs/index.md",
      "date_published": "2026-09-07T00:00:00.000Z",
      "date_modified": "2026-09-08T00:00:00.000Z",
      "tags": [
        "Artificial Intelligence",
        "Hiring",
        "Early Career",
        "Workforce Planning",
        "Job Postings",
        "Reskilling",
        "Labor Market",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/09/06/ai-providers-one-workday-outage/",
      "title": "Three AI Providers Reported Outages in One Workday",
      "summary": "OpenAI, Anthropic, and xAI reported overlapping AI outages on September 3. A work-continuity ledger shows where model failover and human recovery begin.",
      "html_url": "https://digidai.github.io/2026/09/06/ai-providers-one-workday-outage/",
      "markdown_url": "https://digidai.github.io/2026/09/06/ai-providers-one-workday-outage/index.md",
      "date_published": "2026-09-06T00:00:00.000Z",
      "date_modified": "2026-09-06T00:00:00.000Z",
      "tags": [
        "Artificial Intelligence",
        "Operational Resilience",
        "OpenAI",
        "Anthropic",
        "xAI",
        "Business Continuity",
        "Enterprise AI",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/09/05/ey-human-skills-bonus-pool/",
      "title": "Judgment Gets a $100 Million Bonus Pool at EY",
      "summary": "EY put $100 million behind judgment, adaptability, and business acumen. The harder task is rewarding evidence without turning personality or AI activity into a score.",
      "html_url": "https://digidai.github.io/2026/09/05/ey-human-skills-bonus-pool/",
      "markdown_url": "https://digidai.github.io/2026/09/05/ey-human-skills-bonus-pool/index.md",
      "date_published": "2026-09-05T00:00:00.000Z",
      "date_modified": "2026-09-05T00:00:00.000Z",
      "tags": [
        "Artificial Intelligence",
        "Human Skills",
        "Compensation",
        "Career Development",
        "Performance Management",
        "EY",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/09/04/nvidia-hugging-face-open-platform-promise/",
      "title": "Nvidia and the $12.93 Billion Promise to Keep Hugging Face Open",
      "summary": "Nvidia agreed to spend up to $12.93 billion on Hugging Face while promising model, cloud, provider, and hardware choice. A neutrality scorecard makes that promise testable.",
      "html_url": "https://digidai.github.io/2026/09/04/nvidia-hugging-face-open-platform-promise/",
      "markdown_url": "https://digidai.github.io/2026/09/04/nvidia-hugging-face-open-platform-promise/index.md",
      "date_published": "2026-09-04T00:00:00.000Z",
      "date_modified": "2026-09-04T00:00:00.000Z",
      "tags": [
        "Artificial Intelligence",
        "Nvidia",
        "Hugging Face",
        "Open Weight Models",
        "Developer Platforms",
        "Mergers and Acquisitions",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/09/01/ai-safety-tests-live-systems/",
      "title": "AI Safety Tests Reached Systems They Did Not Own",
      "summary": "OpenAI, Anthropic and the UK AI Security Institute documented three different routes from agent evaluations to live systems. Their response puts sandboxes, staffing and test design on one incident ledger.",
      "html_url": "https://digidai.github.io/2026/09/01/ai-safety-tests-live-systems/",
      "markdown_url": "https://digidai.github.io/2026/09/01/ai-safety-tests-live-systems/index.md",
      "date_published": "2026-09-01T00:00:00.000Z",
      "date_modified": "2026-09-01T00:00:00.000Z",
      "tags": [
        "Artificial Intelligence",
        "AI Agents",
        "Cybersecurity",
        "AI Safety",
        "Enterprise AI",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/08/31/nec-ai-department-four-management-layers/",
      "title": "Inside NEC's AI Department, Where People Still Decide",
      "summary": "NEC has given AI a department with executives, managers and staff. Its internal trial raises concrete questions about human review, hidden work and the price of AI services.",
      "html_url": "https://digidai.github.io/2026/08/31/nec-ai-department-four-management-layers/",
      "markdown_url": "https://digidai.github.io/2026/08/31/nec-ai-department-four-management-layers/index.md",
      "date_published": "2026-08-31T00:00:00.000Z",
      "date_modified": "2026-08-31T00:00:00.000Z",
      "tags": [
        "Artificial Intelligence",
        "NEC",
        "Organizational Design",
        "Future of Work",
        "Enterprise AI",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/08/30/ai-research-equity-grants-base-pay/",
      "title": "AI Research Equity Grants Pass $4 Million While Base Pay Stays Close",
      "summary": "Pave's new dataset puts senior AI research equity above $4 million while base pay stays near engineering bands. The split changes job design, dilution, retention, and pay transparency.",
      "html_url": "https://digidai.github.io/2026/08/30/ai-research-equity-grants-base-pay/",
      "markdown_url": "https://digidai.github.io/2026/08/30/ai-research-equity-grants-base-pay/index.md",
      "date_published": "2026-08-30T00:00:00.000Z",
      "date_modified": "2026-08-30T00:00:00.000Z",
      "tags": [
        "Artificial Intelligence",
        "AI Talent",
        "Compensation",
        "Equity",
        "Workforce Planning",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/08/29/labor-department-ai-vendor-jobs-data/",
      "title": "The Labor Department Turns to AI Vendors for Jobs Data",
      "summary": "The Labor Department says OpenAI, Google, Meta, Amazon, and other companies will share data on AI's labor impact. Its value depends on whether product telemetry can be reconciled with surveys, payroll, and independent methods.",
      "html_url": "https://digidai.github.io/2026/08/29/labor-department-ai-vendor-jobs-data/",
      "markdown_url": "https://digidai.github.io/2026/08/29/labor-department-ai-vendor-jobs-data/index.md",
      "date_published": "2026-08-29T00:00:00.000Z",
      "date_modified": "2026-09-08T00:00:00.000Z",
      "tags": [
        "Artificial Intelligence",
        "Labor Market",
        "Public Data",
        "Workforce Planning",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/08/28/ukg-frontline-ai-350-job-exits/",
      "title": "Four Days Separate UKG's Frontline AI Launch From 350 Job Exits",
      "summary": "UKG released voice actions, bulk apply, and agentic payroll on August 27, four days before 350 reported transition roles were set to end. Buyers need to separate product claims, support capacity, pay accuracy, and accountable human review.",
      "html_url": "https://digidai.github.io/2026/08/28/ukg-frontline-ai-350-job-exits/",
      "markdown_url": "https://digidai.github.io/2026/08/28/ukg-frontline-ai-350-job-exits/index.md",
      "date_published": "2026-08-28T00:00:00.000Z",
      "date_modified": "2026-08-28T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Technology",
        "Frontline Workforce",
        "Payroll",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/08/27/salesforce-agentic-work-units-software-seats/",
      "title": "Software Seats Meet Salesforce's Agentic Work Units",
      "summary": "Salesforce reported 7 billion Agentic Work Units as Headless 360 and Slack Code widened agent work. Buyers must connect seats, credits, human review, and accepted outcomes.",
      "html_url": "https://digidai.github.io/2026/08/27/salesforce-agentic-work-units-software-seats/",
      "markdown_url": "https://digidai.github.io/2026/08/27/salesforce-agentic-work-units-software-seats/index.md",
      "date_published": "2026-08-27T00:00:00.000Z",
      "date_modified": "2026-08-27T00:00:00.000Z",
      "tags": [
        "Artificial Intelligence",
        "Salesforce",
        "Enterprise Software",
        "AI Economics",
        "Work Redesign",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/08/26/hireez-alternatives-agent-native-rebuild/",
      "title": "HireEZ Alternatives After Its Agent-Native Rebuild",
      "summary": "Seven hireEZ alternatives, with updated Metix pricing and AI Agent limits.",
      "html_url": "https://digidai.github.io/2026/08/26/hireez-alternatives-agent-native-rebuild/",
      "markdown_url": "https://digidai.github.io/2026/08/26/hireez-alternatives-agent-native-rebuild/index.md",
      "date_published": "2026-08-26T00:00:00.000Z",
      "date_modified": "2026-10-05T00:00:00.000Z",
      "tags": [
        "AI",
        "Recruiting",
        "HR Tech",
        "Talent Acquisition",
        "Buyer Guide"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/08/26/xpeng-iron-funding-first-shift/",
      "title": "XPENG Raised $900 Million for a Robot Still Training for Work",
      "summary": "XPENG's robotics financing puts a $6.3 billion valuation beside IRON's year-end production target, China's new standards push, and the human work required before a humanoid can hold a reliable shift.",
      "html_url": "https://digidai.github.io/2026/08/26/xpeng-iron-funding-first-shift/",
      "markdown_url": "https://digidai.github.io/2026/08/26/xpeng-iron-funding-first-shift/index.md",
      "date_published": "2026-08-26T00:00:00.000Z",
      "date_modified": "2026-09-27T00:00:00.000Z",
      "tags": [
        "AI",
        "Robotics",
        "Manufacturing",
        "Future of Work",
        "China",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/08/25/ai-products-turn-into-jobs/",
      "title": "Where AI Products Turn Into Jobs",
      "summary": "Four Metix talent maps show that customer deployment, voice, legal software, and inference serving create different labor bottlenecks. The useful signal lies in the work boundary, not a company ranking.",
      "html_url": "https://digidai.github.io/2026/08/25/ai-products-turn-into-jobs/",
      "markdown_url": "https://digidai.github.io/2026/08/25/ai-products-turn-into-jobs/index.md",
      "date_published": "2026-08-25T00:00:00.000Z",
      "date_modified": "2026-08-25T00:00:00.000Z",
      "tags": [
        "AI",
        "Talent Intelligence",
        "Future of Work",
        "AI Infrastructure",
        "Legal Technology",
        "Voice AI",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/08/25/legal-ai-owned-models-frontier-apis/",
      "title": "Legal AI Splits Between Owned Models and Frontier APIs",
      "summary": "Harvey and Thomson Reuters are training legal models they can control while LexisNexis keeps a multi-model stack. The split changes inference cost, proprietary data strategy, engineering work, and the evidence buyers need before choosing build, rent, or hybrid.",
      "html_url": "https://digidai.github.io/2026/08/25/legal-ai-owned-models-frontier-apis/",
      "markdown_url": "https://digidai.github.io/2026/08/25/legal-ai-owned-models-frontier-apis/index.md",
      "date_published": "2026-08-25T00:00:00.000Z",
      "date_modified": "2026-08-25T00:00:00.000Z",
      "tags": [
        "AI",
        "Legal Technology",
        "Large Language Models",
        "Professional Services",
        "Future of Work",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/08/25/water-tank-generator-100-hour-battery/",
      "title": "A Water Tank, a Backup Generator, and a 100-Hour Battery",
      "summary": "VentureDex's latest published startup profiles show how Worldscape, Ranchbot, AGent Energy, Form Energy, Remepy, Yuno, and Silicon Data turn physical and regulated constraints into product evidence.",
      "html_url": "https://digidai.github.io/2026/08/25/water-tank-generator-100-hour-battery/",
      "markdown_url": "https://digidai.github.io/2026/08/25/water-tank-generator-100-hour-battery/index.md",
      "date_published": "2026-08-25T00:00:00.000Z",
      "date_modified": "2026-08-25T00:00:00.000Z",
      "tags": [
        "Startups",
        "Venture Capital",
        "AI",
        "Climate Technology",
        "Health Technology",
        "Market Research",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/08/24/federal-ai-discounts-september-30/",
      "title": "Federal AI Discounts Expire on September 30",
      "summary": "Claude, Gemini, and ChatGPT reach a shared federal discount deadline on September 30. Agencies need renewal evidence that separates access, active use, workflow results, integration cost, and exit rights.",
      "html_url": "https://digidai.github.io/2026/08/24/federal-ai-discounts-september-30/",
      "markdown_url": "https://digidai.github.io/2026/08/24/federal-ai-discounts-september-30/index.md",
      "date_published": "2026-08-24T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "U.S. Government",
        "OneGov",
        "AI Procurement",
        "Future of Work",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/08/23/metix-talent-intelligence-reports/",
      "title": "Metix Reports: The Distance Between a Market Signal and a Hire",
      "summary": "Metix has published 19 talent maps built from public profiles and job postings. Co-founder Gene Dai examines what those samples can show and how they enter a defensible candidate search.",
      "html_url": "https://digidai.github.io/2026/08/23/metix-talent-intelligence-reports/",
      "markdown_url": "https://digidai.github.io/2026/08/23/metix-talent-intelligence-reports/index.md",
      "date_published": "2026-08-23T00:00:00.000Z",
      "date_modified": "2026-08-23T00:00:00.000Z",
      "tags": [
        "Metix AI",
        "Talent Intelligence",
        "AI Hiring",
        "Workforce Planning",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/08/23/target-first-ai-chief-store-workforce/",
      "title": "Before Target's First AI Chief Takes the Job",
      "summary": "Target's first chief AI officer starts with store assistants, a measured supply-chain pilot, 415,000 employees, and no public scorecard connecting AI use to work or customer results.",
      "html_url": "https://digidai.github.io/2026/08/23/target-first-ai-chief-store-workforce/",
      "markdown_url": "https://digidai.github.io/2026/08/23/target-first-ai-chief-store-workforce/index.md",
      "date_published": "2026-08-23T00:00:00.000Z",
      "date_modified": "2026-08-23T00:00:00.000Z",
      "tags": [
        "AI",
        "Target",
        "Chief AI Officer",
        "Retail Technology",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/08/21/cisco-ai-orders-job-cuts/",
      "title": "Cisco's $9.3 Billion AI Order Year Included Nearly 4,000 Job Cuts",
      "summary": "Cisco ended fiscal 2026 with $9.3 billion in hyperscaler AI infrastructure orders, record revenue, and its highest earnings per employee in 30 years. A nearly 4,000-job restructuring shows what companies still fail to disclose when capital moves toward AI.",
      "html_url": "https://digidai.github.io/2026/08/21/cisco-ai-orders-job-cuts/",
      "markdown_url": "https://digidai.github.io/2026/08/21/cisco-ai-orders-job-cuts/index.md",
      "date_published": "2026-08-21T00:00:00.000Z",
      "date_modified": "2026-08-21T00:00:00.000Z",
      "tags": [
        "AI",
        "Cisco",
        "Workforce Restructuring",
        "Enterprise Technology",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/08/20/korea-youth-jobs-ai-exposed-industries/",
      "title": "Korea's AI-Exposed Industries Had 268,000 Fewer Youth Jobs",
      "summary": "Korean and U.S. employment data show why companies must separate AI exposure, adoption, total headcount, and the first rung of a career.",
      "html_url": "https://digidai.github.io/2026/08/20/korea-youth-jobs-ai-exposed-industries/",
      "markdown_url": "https://digidai.github.io/2026/08/20/korea-youth-jobs-ai-exposed-industries/index.md",
      "date_published": "2026-08-20T00:00:00.000Z",
      "date_modified": "2026-09-08T00:00:00.000Z",
      "tags": [
        "Artificial Intelligence",
        "Youth Employment",
        "Workforce Planning",
        "Career Development",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/08/15/workday-take-private-ai-actions/",
      "title": "Workday Drew Take-Private Interest After 1.7 Billion AI Actions",
      "summary": "Reported Silver Lake talks put Workday's contracts, AI acquisitions, support capacity, workforce, and $28.1 billion backlog inside one ownership test.",
      "html_url": "https://digidai.github.io/2026/08/15/workday-take-private-ai-actions/",
      "markdown_url": "https://digidai.github.io/2026/08/15/workday-take-private-ai-actions/index.md",
      "date_published": "2026-08-15T00:00:00.000Z",
      "date_modified": "2026-08-15T00:00:00.000Z",
      "tags": [
        "Artificial Intelligence",
        "HR Technology",
        "Private Equity",
        "Enterprise Software",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/08/14/uber-robotaxi-hybrid-driver-network/",
      "title": "Uber's Robotaxi Network Puts Two Workforces on One App",
      "summary": "Uber says robotaxis and drivers will share one network. Its $10 billion capital plan and fleet partners leave a labor account investors cannot yet see.",
      "html_url": "https://digidai.github.io/2026/08/14/uber-robotaxi-hybrid-driver-network/",
      "markdown_url": "https://digidai.github.io/2026/08/14/uber-robotaxi-hybrid-driver-network/index.md",
      "date_published": "2026-08-14T00:00:00.000Z",
      "date_modified": "2026-08-14T00:00:00.000Z",
      "tags": [
        "Artificial Intelligence",
        "Autonomous Vehicles",
        "Future of Work",
        "Platform Labor",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/08/13/meta-ai-extra-hour-workday/",
      "title": "Meta's CTO Sent AI's Extra Hour Back to Work",
      "summary": "Meta CTO Andrew Bosworth said an AI-saved hour should produce more work. Research from Berkeley, Microsoft, Korea, and corporate executives shows why companies need to record where recovered time actually goes.",
      "html_url": "https://digidai.github.io/2026/08/13/meta-ai-extra-hour-workday/",
      "markdown_url": "https://digidai.github.io/2026/08/13/meta-ai-extra-hour-workday/index.md",
      "date_published": "2026-08-13T00:00:00.000Z",
      "date_modified": "2026-08-13T00:00:00.000Z",
      "tags": [
        "AI",
        "Future of Work",
        "Employee Experience",
        "Work Redesign",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/08/12/cognizant-graduate-hiring-ai-apprenticeship/",
      "title": "Cognizant's 1,500 Graduate Plan Tests the AI Apprenticeship",
      "summary": "Cognizant plans to hire 1,500 U.S. college graduates while building 15,000 Frontier-certified roles. The test is whether recruiting, paid practice, mentor time, client assignments, and promotion form a career path rather than a training announcement.",
      "html_url": "https://digidai.github.io/2026/08/12/cognizant-graduate-hiring-ai-apprenticeship/",
      "markdown_url": "https://digidai.github.io/2026/08/12/cognizant-graduate-hiring-ai-apprenticeship/index.md",
      "date_published": "2026-08-12T00:00:00.000Z",
      "date_modified": "2026-09-08T00:00:00.000Z",
      "tags": [
        "AI",
        "Future of Work",
        "Entry-Level Jobs",
        "Professional Services",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/08/11/noncompete-recruiter-mobility-earnings/",
      "title": "A Noncompete Cut Recruiter Mobility by Half",
      "summary": "A 2026 field experiment across roughly 14,000 recruiter offers found that removing a noncompete raised competing-employer mobility and total earnings. Employers can protect confidential information without turning contract boilerplate into a talent bottleneck.",
      "html_url": "https://digidai.github.io/2026/08/11/noncompete-recruiter-mobility-earnings/",
      "markdown_url": "https://digidai.github.io/2026/08/11/noncompete-recruiter-mobility-earnings/index.md",
      "date_published": "2026-08-11T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Future of Work",
        "Talent Mobility",
        "Compensation",
        "Labor Market",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/08/10/shared-ai-avatars-employee-offboarding/",
      "title": "Shared AI Avatars Can Outlast Employment",
      "summary": "Google, Synthesia, and HeyGen can turn an employee's face and voice into reusable video. Companies need a lifecycle record for consent, scripts, sharing, learning results, offboarding, and every copy that survives deletion.",
      "html_url": "https://digidai.github.io/2026/08/10/shared-ai-avatars-employee-offboarding/",
      "markdown_url": "https://digidai.github.io/2026/08/10/shared-ai-avatars-employee-offboarding/index.md",
      "date_published": "2026-08-10T00:00:00.000Z",
      "date_modified": "2026-08-10T00:00:00.000Z",
      "tags": [
        "Artificial Intelligence",
        "Employee Experience",
        "Workforce Training",
        "Synthetic Media",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/08/09/ai-outsourcing-revenue-workforce-split/",
      "title": "Three Measures of Outsourcing's AI Growth",
      "summary": "Genpact reported 24.1% growth in one technology line. TP counted projects and Concentrix counted deals. Buyers need a common contract measure for revenue, value, and worker transitions.",
      "html_url": "https://digidai.github.io/2026/08/09/ai-outsourcing-revenue-workforce-split/",
      "markdown_url": "https://digidai.github.io/2026/08/09/ai-outsourcing-revenue-workforce-split/index.md",
      "date_published": "2026-08-09T00:00:00.000Z",
      "date_modified": "2026-08-09T00:00:00.000Z",
      "tags": [
        "Artificial Intelligence",
        "Business Process Outsourcing",
        "Future of Work",
        "Enterprise Services",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/08/08/ai-productivity-labor-share-scorecard/",
      "title": "Productivity Rose. Labor's Share Reached a Record Low.",
      "summary": "U.S. productivity rose while labor's share hit 52.9%, with no evidence AI caused either move. Enterprise ROI should also track pay, hours, hiring, and training.",
      "html_url": "https://digidai.github.io/2026/08/08/ai-productivity-labor-share-scorecard/",
      "markdown_url": "https://digidai.github.io/2026/08/08/ai-productivity-labor-share-scorecard/index.md",
      "date_published": "2026-08-08T00:00:00.000Z",
      "date_modified": "2026-09-08T00:00:00.000Z",
      "tags": [
        "Artificial Intelligence",
        "Productivity",
        "Labor Market",
        "Compensation",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/08/07/britain-ai-adoption-training-investment-gap/",
      "title": "A Shift Roster With No Time to Train",
      "summary": "Free AI access reached workers as UK employers spent less on training and England changed levy economics. ONS, Airbus, and KPMG show why licenses need paid learning time, role practice, and manager cover.",
      "html_url": "https://digidai.github.io/2026/08/07/britain-ai-adoption-training-investment-gap/",
      "markdown_url": "https://digidai.github.io/2026/08/07/britain-ai-adoption-training-investment-gap/index.md",
      "date_published": "2026-08-07T00:00:00.000Z",
      "date_modified": "2026-08-07T00:00:00.000Z",
      "tags": [
        "Artificial Intelligence",
        "Workforce Training",
        "UK Economy",
        "Skills",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/08/07/metix-ai-interview-on-the-invoice/",
      "title": "We Raised $5.5 Million and Put the Interview on the Invoice",
      "summary": "Metix AI co-founder and CPO Gene Dai explains why OpenJobs AI changed its name, moved beyond recruiting software, and chose the qualified interview as the unit customers pay for.",
      "html_url": "https://digidai.github.io/2026/08/07/metix-ai-interview-on-the-invoice/",
      "markdown_url": "https://digidai.github.io/2026/08/07/metix-ai-interview-on-the-invoice/index.md",
      "date_published": "2026-08-07T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "Recruiting",
        "HR Tech",
        "Startups",
        "Metix AI"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/08/06/google-deepmind-research-veterans-handoff/",
      "title": "Google DeepMind's Research Map Now Extends Beyond Its Payroll",
      "summary": "Google assigned broader scientific strategy and Gemini delivery to different leaders as four research veterans prepared to launch Discovery Loop. The change exposes a frontier lab's hardest talent choice: employee authority, founder autonomy, or a commercial relationship across the boundary.",
      "html_url": "https://digidai.github.io/2026/08/06/google-deepmind-research-veterans-handoff/",
      "markdown_url": "https://digidai.github.io/2026/08/06/google-deepmind-research-veterans-handoff/index.md",
      "date_published": "2026-08-06T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Artificial Intelligence",
        "Google DeepMind",
        "AI Talent",
        "Organization Design",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/08/05/spotify-ai-podcasts-record-margin/",
      "title": "Spotify Launched Personal Podcasts in a Record-Margin Quarter",
      "summary": "Spotify put Personal Podcasts beside a 33.4% record gross margin, EUR655 million in operating income, and rising cloud and AI spend. The unresolved business test is whether generated listening expands creator discovery or replaces it.",
      "html_url": "https://digidai.github.io/2026/08/05/spotify-ai-podcasts-record-margin/",
      "markdown_url": "https://digidai.github.io/2026/08/05/spotify-ai-podcasts-record-margin/index.md",
      "date_published": "2026-08-05T00:00:00.000Z",
      "date_modified": "2026-08-05T00:00:00.000Z",
      "tags": [
        "Artificial Intelligence",
        "Creator Economy",
        "Podcasting",
        "Product Strategy",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/08/04/ups-network-payoff-workforce-exit/",
      "title": "UPS Between a Workforce Exit and a Network Payoff",
      "summary": "UPS's Q2 accounts put an $891 million after-tax charge beside $2.1 billion in adjusted operating profit. The gap traces a network losing Amazon volume, closing facilities, automating package handling, and completing a negotiated driver exit with 7,500 accepted applications.",
      "html_url": "https://digidai.github.io/2026/08/04/ups-network-payoff-workforce-exit/",
      "markdown_url": "https://digidai.github.io/2026/08/04/ups-network-payoff-workforce-exit/index.md",
      "date_published": "2026-08-04T00:00:00.000Z",
      "date_modified": "2026-08-04T00:00:00.000Z",
      "tags": [
        "Workforce Transformation",
        "Automation",
        "Logistics",
        "Labor Strategy",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/08/03/founder-handoff-first-recruiter/",
      "title": "The Founder's Handoff to a First Recruiter",
      "summary": "Current hiring plans at Viktor, Sela AI, OpenEvidence, and Cartesia show lean AI startups adding a recruiting owner while founders retain consequential interviews. Ashby data clarifies when that handoff becomes an operating decision.",
      "html_url": "https://digidai.github.io/2026/08/03/founder-handoff-first-recruiter/",
      "markdown_url": "https://digidai.github.io/2026/08/03/founder-handoff-first-recruiter/index.md",
      "date_published": "2026-08-03T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Startup Hiring",
        "Recruiting",
        "AI Startups",
        "Talent Strategy",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/08/02/eu-ai-labels-hiring-rules-delay/",
      "title": "Chatbot Disclosure Before Europe's Hiring AI Deadline",
      "summary": "Europe began enforcing AI disclosure rules on August 2 while delaying high-risk employment obligations until December 2027, leaving product, HR, legal, and worker teams on different clocks.",
      "html_url": "https://digidai.github.io/2026/08/02/eu-ai-labels-hiring-rules-delay/",
      "markdown_url": "https://digidai.github.io/2026/08/02/eu-ai-labels-hiring-rules-delay/index.md",
      "date_published": "2026-08-02T00:00:00.000Z",
      "date_modified": "2026-08-02T00:00:00.000Z",
      "tags": [
        "EU AI Act",
        "Workplace AI",
        "HR Technology",
        "Enterprise AI",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/08/01/fiverr-upwork-ai-freelance-value-split/",
      "title": "Fiverr Shed Buyers as Upwork Tracked Higher-Value Work",
      "summary": "Fiverr's buyer decline and Upwork's earnings split expose a freelance market that rewards diagnosis and integration while leaving new workers without a funded first rung.",
      "html_url": "https://digidai.github.io/2026/08/01/fiverr-upwork-ai-freelance-value-split/",
      "markdown_url": "https://digidai.github.io/2026/08/01/fiverr-upwork-ai-freelance-value-split/index.md",
      "date_published": "2026-08-01T00:00:00.000Z",
      "date_modified": "2026-08-01T00:00:00.000Z",
      "tags": [
        "AI",
        "Freelancing",
        "Future of Work",
        "Career Ladders",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/07/30/microsoft-copilot-scale-smaller-workforce/",
      "title": "Microsoft Closed FY26 With 30 Million Paid Copilot Seats and a Smaller Workforce",
      "summary": "Microsoft ended FY26 with more than 30 million paid Microsoft 365 Copilot seats, $41 billion in quarterly capital spending, and 2% fewer employees. Those figures expose the workforce evidence every enterprise AI renewal still needs.",
      "html_url": "https://digidai.github.io/2026/07/30/microsoft-copilot-scale-smaller-workforce/",
      "markdown_url": "https://digidai.github.io/2026/07/30/microsoft-copilot-scale-smaller-workforce/index.md",
      "date_published": "2026-07-30T00:00:00.000Z",
      "date_modified": "2026-07-30T00:00:00.000Z",
      "tags": [
        "AI",
        "Microsoft",
        "Future of Work",
        "Workforce Planning",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/07/29/factory-ai-scale-workforce-gap/",
      "title": "The Factory Floor's 62-Point AI Gap",
      "summary": "A survey published in July found that 72% of manufacturers had adopted AI in some form, while 10% had deployed it at scale. The missing 62 percentage points run through legacy equipment, production risk, changed jobs, and field-specific training.",
      "html_url": "https://digidai.github.io/2026/07/29/factory-ai-scale-workforce-gap/",
      "markdown_url": "https://digidai.github.io/2026/07/29/factory-ai-scale-workforce-gap/index.md",
      "date_published": "2026-07-29T00:00:00.000Z",
      "date_modified": "2026-07-29T00:00:00.000Z",
      "tags": [
        "AI",
        "Manufacturing",
        "Future of Work",
        "Skills",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/07/28/small-teams-ai-task-crossover/",
      "title": "Across Small and Large Workspaces: ChatGPT Task Crossover",
      "summary": "Among typical-volume users, OpenAI's July 27 analysis finds 18.9% of work-related ChatGPT messages crossed occupational boundaries in 2-to-5-seat workspaces, compared with 16.3% at 101-plus seats. Small teams now need rules for keeping, reviewing, handing off, or hiring around that work.",
      "html_url": "https://digidai.github.io/2026/07/28/small-teams-ai-task-crossover/",
      "markdown_url": "https://digidai.github.io/2026/07/28/small-teams-ai-task-crossover/index.md",
      "date_published": "2026-07-28T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "Startups",
        "Work Design",
        "Future of Work",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/07/27/codex-30-minute-professional-services-pricing/",
      "title": "Five Engineers Had Three Days. Codex Took 30 Minutes.",
      "summary": "NTT DATA says Codex compressed a complex incident analysis from five experienced engineers over three days to 30 minutes. That result pushes consulting, legal, accounting, agency and IT services firms to decide what clients should pay for when time collapses.",
      "html_url": "https://digidai.github.io/2026/07/27/codex-30-minute-professional-services-pricing/",
      "markdown_url": "https://digidai.github.io/2026/07/27/codex-30-minute-professional-services-pricing/index.md",
      "date_published": "2026-07-27T00:00:00.000Z",
      "date_modified": "2026-07-27T00:00:00.000Z",
      "tags": [
        "AI",
        "Professional Services",
        "Pricing",
        "Workforce",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/07/26/ai-headcount-office-lease-renewal/",
      "title": "At Lease Renewal, AI Has to Show Its Headcount",
      "summary": "JLL says 78% of leaders expect AI to change real estate strategy, yet only 31% are preparing to redesign space. The lease decision needs a workforce range, not an AI slogan.",
      "html_url": "https://digidai.github.io/2026/07/26/ai-headcount-office-lease-renewal/",
      "markdown_url": "https://digidai.github.io/2026/07/26/ai-headcount-office-lease-renewal/index.md",
      "date_published": "2026-07-26T00:00:00.000Z",
      "date_modified": "2026-07-26T00:00:00.000Z",
      "tags": [
        "AI",
        "Future of Work",
        "Corporate Real Estate",
        "Workforce Planning",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/07/25/ai-native-autonomous-recruiter-employers/",
      "title": "Metix Reprices the AI Recruiter Around Credits and Agents",
      "summary": "Metix now charges $99 to $499 a month for usage Credits and AI Agents. The product still books interviews, but the billing meter moved upstream.",
      "html_url": "https://digidai.github.io/2026/07/25/ai-native-autonomous-recruiter-employers/",
      "markdown_url": "https://digidai.github.io/2026/07/25/ai-native-autonomous-recruiter-employers/index.md",
      "date_published": "2026-07-25T00:00:00.000Z",
      "date_modified": "2026-09-16T00:00:00.000Z",
      "tags": [
        "AI",
        "Recruiting",
        "HR Tech",
        "Team Hiring",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/07/25/bank-ai-call-minute-workforce-economics/",
      "title": "A Minute Disappears From 18,000 Bank Calls",
      "summary": "Bank of America and Citi each report 60 seconds saved per call. The harder question is whether that minute improves service, changes work or quietly becomes headcount.",
      "html_url": "https://digidai.github.io/2026/07/25/bank-ai-call-minute-workforce-economics/",
      "markdown_url": "https://digidai.github.io/2026/07/25/bank-ai-call-minute-workforce-economics/index.md",
      "date_published": "2026-07-25T00:00:00.000Z",
      "date_modified": "2026-07-25T00:00:00.000Z",
      "tags": [
        "AI",
        "Banking",
        "Customer Service",
        "Work Redesign",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/07/23/workday-sana-ai-learning-bet/",
      "title": "Inside Workday's $1.1 Billion AI Learning Bet",
      "summary": "Workday's Sana launch, Microsoft, BCG, McKinsey and OECD show why faster course production still needs manager practice, work evidence and real career paths.",
      "html_url": "https://digidai.github.io/2026/07/23/workday-sana-ai-learning-bet/",
      "markdown_url": "https://digidai.github.io/2026/07/23/workday-sana-ai-learning-bet/index.md",
      "date_published": "2026-07-23T00:00:00.000Z",
      "date_modified": "2026-07-23T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Learning and Development",
        "Career Ladders",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/07/22/bls-ai-workforce-split/",
      "title": "BLS Publishes the AI Workforce Split",
      "summary": "BLS, Upwork, Autodesk, PwC, Microsoft and ServiceNow data show why AI workforce planning now has to separate growth roles from support work at risk.",
      "html_url": "https://digidai.github.io/2026/07/22/bls-ai-workforce-split/",
      "markdown_url": "https://digidai.github.io/2026/07/22/bls-ai-workforce-split/index.md",
      "date_published": "2026-07-22T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "Workforce",
        "Labor Market",
        "HR Tech",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/07/16/meta-workers-ai-layoff-score/",
      "title": "Meta Workers Challenge the AI Layoff Score",
      "summary": "A Meta lawsuit over AI-assisted layoff scoring shows why productivity, activity and AI-token metrics need leave adjustments, human review and an audit file before a RIF.",
      "html_url": "https://digidai.github.io/2026/07/16/meta-workers-ai-layoff-score/",
      "markdown_url": "https://digidai.github.io/2026/07/16/meta-workers-ai-layoff-score/index.md",
      "date_published": "2026-07-16T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "Workforce",
        "Employment Law",
        "HR Tech",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/07/15/tcs-forward-deployed-engineers-ai-pilot-gap/",
      "title": "TCS Counts 8,900 Engineers Behind the AI Pilot Gap",
      "summary": "TCS, AWS, Accenture, Google Cloud and model labs are turning AI deployment into a labor plan. The work now needs a handoff file, not another pilot deck.",
      "html_url": "https://digidai.github.io/2026/07/15/tcs-forward-deployed-engineers-ai-pilot-gap/",
      "markdown_url": "https://digidai.github.io/2026/07/15/tcs-forward-deployed-engineers-ai-pilot-gap/index.md",
      "date_published": "2026-07-15T00:00:00.000Z",
      "date_modified": "2026-07-15T00:00:00.000Z",
      "tags": [
        "AI",
        "Enterprise AI",
        "Workforce",
        "Org Design",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/07/12/big-tech-hiring-narrows-around-engineers/",
      "title": "Big Tech Hiring Narrows Around Engineers",
      "summary": "SignalFire's 2026 talent data shows a smaller tech hiring market tilting toward engineers. The missing support work now has to be priced, staffed and reviewed.",
      "html_url": "https://digidai.github.io/2026/07/12/big-tech-hiring-narrows-around-engineers/",
      "markdown_url": "https://digidai.github.io/2026/07/12/big-tech-hiring-narrows-around-engineers/index.md",
      "date_published": "2026-07-12T00:00:00.000Z",
      "date_modified": "2026-07-12T00:00:00.000Z",
      "tags": [
        "AI",
        "Tech Jobs",
        "Org Design",
        "Workforce",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/07/11/ai-job-titles-software-department/",
      "title": "AI Job Titles Leave the Software Department",
      "summary": "Indeed's July job-posting data shows AI moving into ordinary roles. Hiring teams now need clearer titles, proof of workflow change, training budgets and pay signals.",
      "html_url": "https://digidai.github.io/2026/07/11/ai-job-titles-software-department/",
      "markdown_url": "https://digidai.github.io/2026/07/11/ai-job-titles-software-department/index.md",
      "date_published": "2026-07-11T00:00:00.000Z",
      "date_modified": "2026-07-11T00:00:00.000Z",
      "tags": [
        "AI",
        "Jobs",
        "Workforce",
        "HR Tech",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/07/10/connecticut-ai-layoff-memo/",
      "title": "Connecticut Adds AI to the Layoff Memo",
      "summary": "Microsoft's July layoffs and Connecticut's new WARN disclosure rule show how AI workforce changes are moving into layoff notices, redeployment records, vendor evidence and severance files.",
      "html_url": "https://digidai.github.io/2026/07/10/connecticut-ai-layoff-memo/",
      "markdown_url": "https://digidai.github.io/2026/07/10/connecticut-ai-layoff-memo/index.md",
      "date_published": "2026-07-10T00:00:00.000Z",
      "date_modified": "2026-07-10T00:00:00.000Z",
      "tags": [
        "AI",
        "Workforce",
        "HR Tech",
        "Employment Law",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/07/09/ai-talent-raids-retention-budget/",
      "title": "AI Talent Raids Reach the Retention Budget",
      "summary": "Meta, OpenAI and AI startups are turning poaching into a finance problem. Retention now needs cash, equity, project risk and manager ownership in one file.",
      "html_url": "https://digidai.github.io/2026/07/09/ai-talent-raids-retention-budget/",
      "markdown_url": "https://digidai.github.io/2026/07/09/ai-talent-raids-retention-budget/index.md",
      "date_published": "2026-07-09T00:00:00.000Z",
      "date_modified": "2026-07-09T00:00:00.000Z",
      "tags": [
        "AI",
        "Talent Strategy",
        "Compensation",
        "Startups",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/07/08/ai-slop-manager-review-file/",
      "title": "AI Slop Lands in the Manager Review File",
      "summary": "SHRM's July report put a name on a manager problem: AI-assisted work can move fast and still arrive as slop. Reviews need evidence, coaching and skill standards.",
      "html_url": "https://digidai.github.io/2026/07/08/ai-slop-manager-review-file/",
      "markdown_url": "https://digidai.github.io/2026/07/08/ai-slop-manager-review-file/index.md",
      "date_published": "2026-07-08T00:00:00.000Z",
      "date_modified": "2026-07-08T00:00:00.000Z",
      "tags": [
        "AI",
        "Workplace",
        "Management",
        "HR Tech",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/07/07/ai-credits-startup-headcount-plan/",
      "title": "AI Credits Distort the Startup Headcount Plan",
      "summary": "Free AI credits and token-for-equity deals now sit beside seed capital, hiring budgets and vendor choices. Founders need a headcount plan that treats compute as financing, not a coupon.",
      "html_url": "https://digidai.github.io/2026/07/07/ai-credits-startup-headcount-plan/",
      "markdown_url": "https://digidai.github.io/2026/07/07/ai-credits-startup-headcount-plan/index.md",
      "date_published": "2026-07-07T00:00:00.000Z",
      "date_modified": "2026-07-07T00:00:00.000Z",
      "tags": [
        "AI",
        "Startups",
        "Talent Strategy",
        "Venture Capital",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/07/06/botsitting-ai-workweek-operating-cost/",
      "title": "Botsitting Takes Back the AI Workweek",
      "summary": "New work research shows why enterprise AI saves time in one tab and spends it in another, as employees feed context, check outputs, switch tools and carry manager handoffs most dashboards miss.",
      "html_url": "https://digidai.github.io/2026/07/06/botsitting-ai-workweek-operating-cost/",
      "markdown_url": "https://digidai.github.io/2026/07/06/botsitting-ai-workweek-operating-cost/index.md",
      "date_published": "2026-07-06T00:00:00.000Z",
      "date_modified": "2026-07-06T00:00:00.000Z",
      "tags": [
        "AI",
        "Future of Work",
        "Employee Experience",
        "Work Redesign",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/07/05/ai-spend-hiring-adoption-test/",
      "title": "AI Spend Turns Hiring Into an Adoption Test",
      "summary": "Ramp, Revelio Labs, ICIMS, Strada, WEF, PwC, Microsoft, SHRM, BCG and ServiceNow show why AI spend does not automatically shrink payroll. Sustained adoption can expand hiring, but only after workflow redesign, manager ownership and sector readiness.",
      "html_url": "https://digidai.github.io/2026/07/05/ai-spend-hiring-adoption-test/",
      "markdown_url": "https://digidai.github.io/2026/07/05/ai-spend-hiring-adoption-test/index.md",
      "date_published": "2026-07-05T00:00:00.000Z",
      "date_modified": "2026-07-05T00:00:00.000Z",
      "tags": [
        "AI",
        "Future of Work",
        "Workforce Planning",
        "Enterprise AI",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/07/04/coding-agents-code-review-budget/",
      "title": "Coding Agents Make Code Review a Budget Line",
      "summary": "GitHub, OpenAI, Anthropic, GitLab, LinearB and DORA now point to the same engineering problem: coding agents make pull requests cheaper to create, but review capacity, traceability and release risk still need owners and budget.",
      "html_url": "https://digidai.github.io/2026/07/04/coding-agents-code-review-budget/",
      "markdown_url": "https://digidai.github.io/2026/07/04/coding-agents-code-review-budget/index.md",
      "date_published": "2026-07-04T00:00:00.000Z",
      "date_modified": "2026-07-04T00:00:00.000Z",
      "tags": [
        "AI",
        "Software Engineering",
        "Engineering Management",
        "AI Agents",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/07/03/ai-reskilling-state-budget/",
      "title": "AI Reskilling Moves From the LMS to the State Budget",
      "summary": "RAISE US, OpenAI, Microsoft, SHRM, BCG, Deloitte and LinkedIn show why AI workforce transition depends on state delivery, employer incentives, wage support and job redesign.",
      "html_url": "https://digidai.github.io/2026/07/03/ai-reskilling-state-budget/",
      "markdown_url": "https://digidai.github.io/2026/07/03/ai-reskilling-state-budget/index.md",
      "date_published": "2026-07-03T00:00:00.000Z",
      "date_modified": "2026-07-03T00:00:00.000Z",
      "tags": [
        "AI",
        "Future of Work",
        "Workforce Development",
        "HR Tech",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/07/02/ai-data-centers-electricians-talent-plan/",
      "title": "Electricians Enter the AI Data Center Hiring Plan",
      "summary": "Meta, Lightcast, Randstad, ABC and IEA show why AI infrastructure plans now need electricians, HVAC engineers, fiber technicians, robotics trades and local workforce budgets.",
      "html_url": "https://digidai.github.io/2026/07/02/ai-data-centers-electricians-talent-plan/",
      "markdown_url": "https://digidai.github.io/2026/07/02/ai-data-centers-electricians-talent-plan/index.md",
      "date_published": "2026-07-02T00:00:00.000Z",
      "date_modified": "2026-07-02T00:00:00.000Z",
      "tags": [
        "AI",
        "Future of Work",
        "Data Centers",
        "Workforce Planning",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/07/01/flat-ai-org-charts-mentorship-budget/",
      "title": "Flat AI Org Charts Put Mentorship on the Budget",
      "summary": "Coinbase, Gallup, Microsoft, BCG, Mercer and Deloitte show why AI-era flattening cannot cut the mentorship, weekly feedback and review capacity that turn small teams into durable organizations.",
      "html_url": "https://digidai.github.io/2026/07/01/flat-ai-org-charts-mentorship-budget/",
      "markdown_url": "https://digidai.github.io/2026/07/01/flat-ai-org-charts-mentorship-budget/index.md",
      "date_published": "2026-07-01T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "Future of Work",
        "Org Design",
        "Management",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/06/30/ai-talent-corridors-team-hiring/",
      "title": "AI Talent Corridors Decide Where Teams Grow",
      "summary": "Deel, Ashby, CBRE, Lightcast, Carta, PwC and LinkedIn data show how remote AI hiring turns into a corridor decision across cities, compensation, compliance and startup operating models.",
      "html_url": "https://digidai.github.io/2026/06/30/ai-talent-corridors-team-hiring/",
      "markdown_url": "https://digidai.github.io/2026/06/30/ai-talent-corridors-team-hiring/index.md",
      "date_published": "2026-06-30T00:00:00.000Z",
      "date_modified": "2026-10-02T00:00:00.000Z",
      "tags": [
        "AI",
        "Talent Strategy",
        "Startups",
        "Remote Work",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/06/29/ai-deployment-work-org-chart/",
      "title": "AI Deployment Work Enters the Org Chart",
      "summary": "OpenAI, Anthropic, ServiceNow, Stripe, Microsoft and Deloitte show why AI work is moving from model teams into deployment roles, workflow redesign, coaching, governance and operating budgets.",
      "html_url": "https://digidai.github.io/2026/06/29/ai-deployment-work-org-chart/",
      "markdown_url": "https://digidai.github.io/2026/06/29/ai-deployment-work-org-chart/index.md",
      "date_published": "2026-06-29T00:00:00.000Z",
      "date_modified": "2026-06-29T00:00:00.000Z",
      "tags": [
        "AI",
        "Future of Work",
        "Org Design",
        "Emerging Roles",
        "Enterprise AI",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/06/27/interview-hours-hiring-budget/",
      "title": "Interview Hours Hide Inside the Hiring Budget",
      "summary": "AI can screen and schedule candidates faster, but Ashby, Greenhouse, Robert Half and new ATS agent launches show the hiring bill is shifting to interview hours, manager review capacity and signal repair.",
      "html_url": "https://digidai.github.io/2026/06/27/interview-hours-hiring-budget/",
      "markdown_url": "https://digidai.github.io/2026/06/27/interview-hours-hiring-budget/index.md",
      "date_published": "2026-06-27T00:00:00.000Z",
      "date_modified": "2026-06-27T00:00:00.000Z",
      "tags": [
        "AI",
        "Recruiting",
        "HR Tech",
        "Talent Acquisition",
        "Workforce Planning",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/06/26/internal-payroll-ai-talent/",
      "title": "Companies Search Their Own Payroll for AI Talent",
      "summary": "AI hiring pressure is pushing companies to search internal mobility, skills data, and redeployment programs before paying to rehire talent they already had.",
      "html_url": "https://digidai.github.io/2026/06/26/internal-payroll-ai-talent/",
      "markdown_url": "https://digidai.github.io/2026/06/26/internal-payroll-ai-talent/index.md",
      "date_published": "2026-06-26T00:00:00.000Z",
      "date_modified": "2026-06-26T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Internal Mobility",
        "Talent Strategy",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/06/25/small-ai-teams-talent-bill/",
      "title": "Small AI Teams Still Carry a Talent Bill",
      "summary": "Carta, Ashby, Greenhouse, OECD, and Robert Half data show why smaller AI-era startup teams still need a real talent budget for equity, recruiter timing, interview hours, and delivery work.",
      "html_url": "https://digidai.github.io/2026/06/25/small-ai-teams-talent-bill/",
      "markdown_url": "https://digidai.github.io/2026/06/25/small-ai-teams-talent-bill/index.md",
      "date_published": "2026-06-25T00:00:00.000Z",
      "date_modified": "2026-10-02T00:00:00.000Z",
      "tags": [
        "AI",
        "Startups",
        "Talent Strategy",
        "Compensation",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/06/24/ai-training-work-pay-band/",
      "title": "AI Training Work Splits the Pay Band",
      "summary": "Deel, Anthropic, Carta, PwC, DOL, and new data-worker reporting show why AI trainer, evaluator, and domain-review jobs need sharper pay bands before one title hides several labor markets.",
      "html_url": "https://digidai.github.io/2026/06/24/ai-training-work-pay-band/",
      "markdown_url": "https://digidai.github.io/2026/06/24/ai-training-work-pay-band/index.md",
      "date_published": "2026-06-24T00:00:00.000Z",
      "date_modified": "2026-06-24T00:00:00.000Z",
      "tags": [
        "AI",
        "Workforce Planning",
        "Compensation",
        "Emerging Roles",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/06/23/junior-roles-training-ground/",
      "title": "Junior Roles Lost the Work That Taught Judgment",
      "summary": "PwC, NACE, Handshake, LinkedIn, Microsoft, and New York Fed data show that AI is not simply cutting entry-level work. It is moving judgment, review, communication, and mentorship costs to the first rung of the career ladder.",
      "html_url": "https://digidai.github.io/2026/06/23/junior-roles-training-ground/",
      "markdown_url": "https://digidai.github.io/2026/06/23/junior-roles-training-ground/index.md",
      "date_published": "2026-06-23T00:00:00.000Z",
      "date_modified": "2026-06-23T00:00:00.000Z",
      "tags": [
        "AI",
        "Workforce Planning",
        "Entry-Level Jobs",
        "Career Ladders",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/06/22/hr-agents-operating-pager/",
      "title": "When HR Agents Ship, Someone Has to Carry the Pager",
      "summary": "Microsoft, Workday, ServiceNow, and Oracle are moving HR agents into production. Enterprises now need named sponsors, evidence owners, exception paths, and budget proof.",
      "html_url": "https://digidai.github.io/2026/06/22/hr-agents-operating-pager/",
      "markdown_url": "https://digidai.github.io/2026/06/22/hr-agents-operating-pager/index.md",
      "date_published": "2026-06-22T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "HR Tech",
        "AI Agents",
        "Workday",
        "Microsoft",
        "ServiceNow",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/06/21/ai-hiring-vendors-no-show-clock/",
      "title": "No-Shows Put AI Hiring Vendors on the Clock",
      "summary": "Frontline hiring AI can speed screening and scheduling, but buyers still need vendor commitments for no-shows, wrong screens, review delays, and evidence handoffs.",
      "html_url": "https://digidai.github.io/2026/06/21/ai-hiring-vendors-no-show-clock/",
      "markdown_url": "https://digidai.github.io/2026/06/21/ai-hiring-vendors-no-show-clock/index.md",
      "date_published": "2026-06-21T00:00:00.000Z",
      "date_modified": "2026-06-21T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Frontline Hiring",
        "Workforce Operations",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/06/20/hr-ai-agents-budget-meeting/",
      "title": "HR Agents Crowd the Budget Meeting",
      "summary": "Writer, ServiceNow, Microsoft, Workday, Oracle, SAP, ADP, and Colorado's AI law show why HR agent rollouts need budget owners and workflow proof.",
      "html_url": "https://digidai.github.io/2026/06/20/hr-ai-agents-budget-meeting/",
      "markdown_url": "https://digidai.github.io/2026/06/20/hr-ai-agents-budget-meeting/index.md",
      "date_published": "2026-06-20T00:00:00.000Z",
      "date_modified": "2026-06-20T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Enterprise Software",
        "Workforce Planning",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/06/19/ai-skill-premiums-pay-bands/",
      "title": "AI Skill Premiums Put Pay Bands on Trial",
      "summary": "PwC, Payscale, Mercer, Workday, Salary.com, WTW, ADP, and EU pay rules show why AI pay premiums need skill evidence and audit-ready bands.",
      "html_url": "https://digidai.github.io/2026/06/19/ai-skill-premiums-pay-bands/",
      "markdown_url": "https://digidai.github.io/2026/06/19/ai-skill-premiums-pay-bands/index.md",
      "date_published": "2026-06-19T00:00:00.000Z",
      "date_modified": "2026-06-19T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Compensation",
        "Pay Equity",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/06/18/ai-layoffs-redeployment-rehire-bill/",
      "title": "AI Layoffs Carry a Rehire Bill",
      "summary": "LHH, PwC, Meta, Workday, Gloat, and Eightfold show why restructuring teams need a redeployment file before layoffs become premium rehiring.",
      "html_url": "https://digidai.github.io/2026/06/18/ai-layoffs-redeployment-rehire-bill/",
      "markdown_url": "https://digidai.github.io/2026/06/18/ai-layoffs-redeployment-rehire-bill/index.md",
      "date_published": "2026-06-18T00:00:00.000Z",
      "date_modified": "2026-06-18T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Workforce Planning",
        "Internal Mobility",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/06/17/ai-agents-workforce-skills-map/",
      "title": "HR Puts AI Agents Into the Workforce Map",
      "summary": "Workday ASOR, Microsoft Agent 365, ServiceNow Autonomous Workforce, and ADP trends push skills data and agent registries into one workforce planning map.",
      "html_url": "https://digidai.github.io/2026/06/17/ai-agents-workforce-skills-map/",
      "markdown_url": "https://digidai.github.io/2026/06/17/ai-agents-workforce-skills-map/index.md",
      "date_published": "2026-06-17T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Workforce Planning",
        "Skills",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/06/16/ai-hiring-manager-exception-load/",
      "title": "AI Took the Hiring Tasks, Managers Got the Exceptions",
      "summary": "Workday-Paradox, Fountain, iCIMS, and UKG automate high-volume hiring, but managers still inherit review hours, exceptions, explanations, and first-shift recovery.",
      "html_url": "https://digidai.github.io/2026/06/16/ai-hiring-manager-exception-load/",
      "markdown_url": "https://digidai.github.io/2026/06/16/ai-hiring-manager-exception-load/index.md",
      "date_published": "2026-06-16T00:00:00.000Z",
      "date_modified": "2026-06-16T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Frontline Hiring",
        "Workforce Management",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/06/16/venturedex-startup-discovery-evidence-file/",
      "title": "VentureDex Turns Startup Discovery Into an Evidence File",
      "summary": "Explore VentureDex for curated startup profiles, product evidence, funding sources, investor context, launch videos, and original startup research.",
      "html_url": "https://digidai.github.io/2026/06/16/venturedex-startup-discovery-evidence-file/",
      "markdown_url": "https://digidai.github.io/2026/06/16/venturedex-startup-discovery-evidence-file/index.md",
      "date_published": "2026-06-16T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Startups",
        "Venture Capital",
        "Product Research",
        "Market Research"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/06/15/enterprise-ai-seat-rollout-audit/",
      "title": "After 300,000 Copilot Seats, HR Needs the Audit File",
      "summary": "Microsoft's 300,000-seat Copilot rollout shows why HR must prove workflow change, manager adoption, skills movement, review cost, and risk control before renewal.",
      "html_url": "https://digidai.github.io/2026/06/15/enterprise-ai-seat-rollout-audit/",
      "markdown_url": "https://digidai.github.io/2026/06/15/enterprise-ai-seat-rollout-audit/index.md",
      "date_published": "2026-06-15T00:00:00.000Z",
      "date_modified": "2026-06-15T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Enterprise Software",
        "Workforce Planning",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/06/14/ai-performance-review-manager-disputes/",
      "title": "When AI Writes the Review, Managers Still Own the Dispute",
      "summary": "Microsoft's Wipro appraisal agent, Workday-Google agents, SAP and Oracle HCM assistants, and AI rules show why post-hire disputes need an operating desk.",
      "html_url": "https://digidai.github.io/2026/06/14/ai-performance-review-manager-disputes/",
      "markdown_url": "https://digidai.github.io/2026/06/14/ai-performance-review-manager-disputes/index.md",
      "date_published": "2026-06-14T00:00:00.000Z",
      "date_modified": "2026-06-14T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Performance Management",
        "Employee Relations",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/06/13/hr-ai-scorecard-before-renewal/",
      "title": "Finance Wants the HR AI Scorecard Before Renewal",
      "summary": "Workday agents, Microsoft Copilot rollouts, ServiceNow views, and payroll workflows make renewal depend on one HR AI scorecard for productivity, trust, risk, and rework.",
      "html_url": "https://digidai.github.io/2026/06/13/hr-ai-scorecard-before-renewal/",
      "markdown_url": "https://digidai.github.io/2026/06/13/hr-ai-scorecard-before-renewal/index.md",
      "date_published": "2026-06-13T00:00:00.000Z",
      "date_modified": "2026-06-13T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Enterprise Software",
        "HR Analytics",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/06/11/ai-layoffs-agent-review-hours/",
      "title": "CFOs Cut Jobs, Then Count Agent Review Hours",
      "summary": "AI layoffs may free budget, but Gartner, Microsoft, Workday, ServiceNow, SHRM, and McKinsey show workforce plans still need review hours, exceptions, and redeployment work.",
      "html_url": "https://digidai.github.io/2026/06/11/ai-layoffs-agent-review-hours/",
      "markdown_url": "https://digidai.github.io/2026/06/11/ai-layoffs-agent-review-hours/index.md",
      "date_published": "2026-06-11T00:00:00.000Z",
      "date_modified": "2026-06-11T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Workforce Planning",
        "Enterprise Software",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/06/10/hr-redesign-work-old-org-chart/",
      "title": "HR Cannot Redesign Work From the Old Org Chart",
      "summary": "McKinsey, Microsoft, SHRM, Workday, ServiceNow, ADP, and Deloitte show why HR must redesign human-agent work while rebuilding its own metrics and capacity.",
      "html_url": "https://digidai.github.io/2026/06/10/hr-redesign-work-old-org-chart/",
      "markdown_url": "https://digidai.github.io/2026/06/10/hr-redesign-work-old-org-chart/index.md",
      "date_published": "2026-06-10T00:00:00.000Z",
      "date_modified": "2026-06-10T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Workforce Planning",
        "Future of Work",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/06/09/fake-hire-recovery-payroll-security/",
      "title": "Fake Hires Put Payroll and Security on the Bill",
      "summary": "DOJ laptop-farm cases, FBI guidance, Persona, Checkr, First Advantage, Entra, Okta, and SailPoint show why fake-hire recovery spans payroll, security, and HR.",
      "html_url": "https://digidai.github.io/2026/06/09/fake-hire-recovery-payroll-security/",
      "markdown_url": "https://digidai.github.io/2026/06/09/fake-hire-recovery-payroll-security/index.md",
      "date_published": "2026-06-09T00:00:00.000Z",
      "date_modified": "2026-06-09T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Recruiting",
        "Security",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/06/08/hiring-fraud-desk-candidate-verification/",
      "title": "Hiring Teams Start Paying for Fraud Desks",
      "summary": "DPRK laptop-farm cases, Persona, Checkr, iProov, Greenhouse volume, and AI rules are turning candidate verification into a hiring fraud desk.",
      "html_url": "https://digidai.github.io/2026/06/08/hiring-fraud-desk-candidate-verification/",
      "markdown_url": "https://digidai.github.io/2026/06/08/hiring-fraud-desk-candidate-verification/index.md",
      "date_published": "2026-06-08T00:00:00.000Z",
      "date_modified": "2026-06-08T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Recruiting",
        "Security",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/06/07/ai-interview-appeals-recruiting-ops/",
      "title": "Candidate Appeals Move From Legal Inbox to Recruiting Ops",
      "summary": "Greenhouse Voice AI, MCP hiring workflows, Workday volume, ICIMS automation, and Colorado ADMT rules turn AI interview disputes into an ops queue.",
      "html_url": "https://digidai.github.io/2026/06/07/ai-interview-appeals-recruiting-ops/",
      "markdown_url": "https://digidai.github.io/2026/06/07/ai-interview-appeals-recruiting-ops/index.md",
      "date_published": "2026-06-07T00:00:00.000Z",
      "date_modified": "2026-06-07T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Recruiting",
        "Compliance",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/06/06/workday-agent-passport-hr-ai-verification/",
      "title": "Workday Puts a Passport Desk in Front of HR Agents",
      "summary": "Workday Agent Passport, ServiceNow AI Control Tower, Microsoft Agent Registry, MCP tools, and Colorado ADMT rules make signed HR agent verification a buyer requirement.",
      "html_url": "https://digidai.github.io/2026/06/06/workday-agent-passport-hr-ai-verification/",
      "markdown_url": "https://digidai.github.io/2026/06/06/workday-agent-passport-hr-ai-verification/index.md",
      "date_published": "2026-06-06T00:00:00.000Z",
      "date_modified": "2026-06-06T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Workday",
        "Agent Governance",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/06/05/ai-hiring-vendor-renewal-stop-loss/",
      "title": "AI Hiring Vendors Face the Renewal Stop-Loss Test",
      "summary": "Greenhouse, Workable, Workday, HireVue, ICIMS, Zylo, FinOps, and state AI rules make spend, signal quality, evidence export, and review renewal tests.",
      "html_url": "https://digidai.github.io/2026/06/05/ai-hiring-vendor-renewal-stop-loss/",
      "markdown_url": "https://digidai.github.io/2026/06/05/ai-hiring-vendor-renewal-stop-loss/index.md",
      "date_published": "2026-06-05T00:00:00.000Z",
      "date_modified": "2026-06-05T00:00:00.000Z",
      "tags": [
        "AI",
        "Recruiting",
        "HR Tech",
        "Procurement",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/06/04/proof-of-person-hiring-budget/",
      "title": "Proof of Person Moves Into the Hiring Budget",
      "summary": "GoodTime, GCheck, Checkr, Greenhouse, iCIMS, and Workday show why candidate fraud, AI interviews, work samples, and review now sit inside hiring cost.",
      "html_url": "https://digidai.github.io/2026/06/04/proof-of-person-hiring-budget/",
      "markdown_url": "https://digidai.github.io/2026/06/04/proof-of-person-hiring-budget/index.md",
      "date_published": "2026-06-04T00:00:00.000Z",
      "date_modified": "2026-06-04T00:00:00.000Z",
      "tags": [
        "AI",
        "Recruiting",
        "HR Tech",
        "Assessment",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/06/03/recruiters-signal-ai-hiring-funnel/",
      "title": "Recruiters Are Hunting for Signal in the AI Funnel",
      "summary": "Greenhouse, Workable, Workday, ICIMS, SHRM, and Colorado ADMT rules show why resumes and AI interviews both need proof chains now.",
      "html_url": "https://digidai.github.io/2026/06/03/recruiters-signal-ai-hiring-funnel/",
      "markdown_url": "https://digidai.github.io/2026/06/03/recruiters-signal-ai-hiring-funnel/index.md",
      "date_published": "2026-06-03T00:00:00.000Z",
      "date_modified": "2026-06-03T00:00:00.000Z",
      "tags": [
        "AI",
        "Recruiting",
        "HR Tech",
        "Talent Acquisition",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/06/02/finance-stop-button-hr-ai-agents/",
      "title": "A Stop Button Enters the HR AI Budget Meeting",
      "summary": "Workday, Salesforce, ServiceNow, Microsoft, FinOps, and SaaS spend data show why HR agents need workflow-level pause rights before renewal.",
      "html_url": "https://digidai.github.io/2026/06/02/finance-stop-button-hr-ai-agents/",
      "markdown_url": "https://digidai.github.io/2026/06/02/finance-stop-button-hr-ai-agents/index.md",
      "date_published": "2026-06-02T00:00:00.000Z",
      "date_modified": "2026-06-02T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "FinOps",
        "Enterprise Software",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/06/01/candidate-trust-chargeback-ai-hiring-costs/",
      "title": "The Candidate Who Walked Out Still Shows Up on the Invoice",
      "summary": "AI interview vendors need chargeback terms for candidate walkouts, disclosure failures, human fallback, source-quality loss, and evidence support.",
      "html_url": "https://digidai.github.io/2026/06/01/candidate-trust-chargeback-ai-hiring-costs/",
      "markdown_url": "https://digidai.github.io/2026/06/01/candidate-trust-chargeback-ai-hiring-costs/index.md",
      "date_published": "2026-06-01T00:00:00.000Z",
      "date_modified": "2026-06-01T00:00:00.000Z",
      "tags": [
        "AI",
        "Recruiting",
        "Candidate Experience",
        "HR Tech",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/05/31/workday-sana-copilot-hr-service-agents/",
      "title": "Workday Put the HR Help Desk Inside Copilot",
      "summary": "Workday, Microsoft, ServiceNow, UKG, SAP, Oracle, and ADP are turning HR service agents into a fight over workflow ownership, evidence, and cost.",
      "html_url": "https://digidai.github.io/2026/05/31/workday-sana-copilot-hr-service-agents/",
      "markdown_url": "https://digidai.github.io/2026/05/31/workday-sana-copilot-hr-service-agents/index.md",
      "date_published": "2026-05-31T00:00:00.000Z",
      "date_modified": "2026-05-31T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Employee Service",
        "Enterprise Software",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/05/27/candidates-walk-out-ai-interviews/",
      "title": "Candidates Are Walking Out of AI Interviews",
      "summary": "AI interviews are now mainstream hiring touchpoints. Greenhouse, ICIMS, Workday, and state rules show why disclosure, fallback, and trust decide conversion.",
      "html_url": "https://digidai.github.io/2026/05/27/candidates-walk-out-ai-interviews/",
      "markdown_url": "https://digidai.github.io/2026/05/27/candidates-walk-out-ai-interviews/index.md",
      "date_published": "2026-05-27T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "Recruiting",
        "Candidate Experience",
        "HR Tech",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/05/26/agentic-hiring-unit-costs/",
      "title": "One Hire, Six Meters, and a Budget Meeting",
      "summary": "Agentic recruiting turns one hire into sourcing, screening, scheduling, review, first-shift, evidence, and rework meters that finance can inspect.",
      "html_url": "https://digidai.github.io/2026/05/26/agentic-hiring-unit-costs/",
      "markdown_url": "https://digidai.github.io/2026/05/26/agentic-hiring-unit-costs/index.md",
      "date_published": "2026-05-26T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "Recruiting",
        "HR Tech",
        "FinOps",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/05/25/hr-ai-outcome-scorecard-finance-proof/",
      "title": "When a Hiring Bot Claims Success, Finance Asks for Proof",
      "summary": "Outcome-priced hiring bots force HR and finance to define success across speed, quality, cost, evidence, candidate trust, appeals, and rework.",
      "html_url": "https://digidai.github.io/2026/05/25/hr-ai-outcome-scorecard-finance-proof/",
      "markdown_url": "https://digidai.github.io/2026/05/25/hr-ai-outcome-scorecard-finance-proof/index.md",
      "date_published": "2026-05-25T00:00:00.000Z",
      "date_modified": "2026-05-25T00:00:00.000Z",
      "tags": [
        "AI",
        "Recruiting",
        "HR Tech",
        "FinOps",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/05/24/frontline-hiring-platforms-first-shift-clock/",
      "title": "Four Days to First Shift Sets the Hiring Clock",
      "summary": "Workday Paradox, Fountain, UKG, and ICIMS are racing to compress frontline hiring. The real buyer test is first-shift speed, manager capacity, evidence, and cost.",
      "html_url": "https://digidai.github.io/2026/05/24/frontline-hiring-platforms-first-shift-clock/",
      "markdown_url": "https://digidai.github.io/2026/05/24/frontline-hiring-platforms-first-shift-clock/index.md",
      "date_published": "2026-05-24T00:00:00.000Z",
      "date_modified": "2026-05-24T00:00:00.000Z",
      "tags": [
        "AI",
        "Recruiting",
        "Frontline Workforce",
        "HR Tech",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/05/23/ai-workflow-margin-math-staffing-services/",
      "title": "AI Workflows Are Rewriting Staffing Margins",
      "summary": "AI workflows can protect staffing margins only if firms price SaaS meters, exception handling, evidence work, and client proof into each automated recruiting unit.",
      "html_url": "https://digidai.github.io/2026/05/23/ai-workflow-margin-math-staffing-services/",
      "markdown_url": "https://digidai.github.io/2026/05/23/ai-workflow-margin-math-staffing-services/index.md",
      "date_published": "2026-05-23T00:00:00.000Z",
      "date_modified": "2026-05-23T00:00:00.000Z",
      "tags": [
        "AI",
        "Recruiting",
        "Staffing",
        "HR Tech",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/05/20/hr-agent-cost-exception-desk/",
      "title": "When HR Agents Overrun Budgets, the Exception Desk Decides",
      "summary": "HR agent workflows can now trigger messages, actions, credits, tokens, integrations, audit exports, retries, and human escalations in the same run. Finance will need an exception desk before usage-based AI bills become renewal disputes.",
      "html_url": "https://digidai.github.io/2026/05/20/hr-agent-cost-exception-desk/",
      "markdown_url": "https://digidai.github.io/2026/05/20/hr-agent-cost-exception-desk/index.md",
      "date_published": "2026-05-20T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "HR Tech",
        "AI Agents",
        "FinOps",
        "Enterprise Software",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/05/19/hr-ai-outcome-pricing-refund-rights/",
      "title": "HR AI Vendors Want Outcome Pricing. CFOs Want Refund Rights.",
      "summary": "Intercom, Zendesk, Salesforce, Microsoft, Workday, Oracle, and ServiceNow are training buyers to pay for AI work instead of seats. In HR, the fight will turn on refund windows, dispute rights, and who decides whether a hiring, payroll, or employee service outcome really held.",
      "html_url": "https://digidai.github.io/2026/05/19/hr-ai-outcome-pricing-refund-rights/",
      "markdown_url": "https://digidai.github.io/2026/05/19/hr-ai-outcome-pricing-refund-rights/index.md",
      "date_published": "2026-05-19T00:00:00.000Z",
      "date_modified": "2026-05-19T00:00:00.000Z",
      "tags": [
        "HR Tech",
        "AI Agents",
        "Enterprise Software",
        "FinOps",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/05/18/hr-ai-evidence-workspace-format-war/",
      "title": "HR AI Evidence Has a Workspace Problem",
      "summary": "ChatGPT, Gemini, Agent 365, ServiceNow, Workday, and hiring systems are each keeping different parts of the HR AI record. Buyers now need one evidence schema that can survive audits, invoices, vendor switches, and changing state rules.",
      "html_url": "https://digidai.github.io/2026/05/18/hr-ai-evidence-workspace-format-war/",
      "markdown_url": "https://digidai.github.io/2026/05/18/hr-ai-evidence-workspace-format-war/index.md",
      "date_published": "2026-05-18T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "HR Tech",
        "AI Agents",
        "Enterprise Software",
        "AI Governance",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/05/17/hr-agent-workflow-invoice-audit/",
      "title": "CFOs Want Receipts for HR Agent Workflows",
      "summary": "A payroll correction or candidate-screening run can now touch Copilot, Workday, ServiceNow, Salesforce, Oracle, an ATS, and a model provider. Finance will need workflow-level cost evidence before HR agents scale.",
      "html_url": "https://digidai.github.io/2026/05/17/hr-agent-workflow-invoice-audit/",
      "markdown_url": "https://digidai.github.io/2026/05/17/hr-agent-workflow-invoice-audit/index.md",
      "date_published": "2026-05-17T00:00:00.000Z",
      "date_modified": "2026-05-17T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Enterprise Software",
        "FinOps",
        "Deep Analysis"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/05/15/agent-action-tax-saas-workflow-pricing/",
      "title": "AI Agents Can Skip the UI, Not the SaaS Bill",
      "summary": "As AI agents execute HR, service, finance, and recruiting workflows, SaaS vendors are adding action credits, sponsored users, AI units, and workflow meters to the software bill.",
      "html_url": "https://digidai.github.io/2026/05/15/agent-action-tax-saas-workflow-pricing/",
      "markdown_url": "https://digidai.github.io/2026/05/15/agent-action-tax-saas-workflow-pricing/index.md",
      "date_published": "2026-05-15T00:00:00.000Z",
      "date_modified": "2026-10-01T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Enterprise Software",
        "SaaS Pricing",
        "Deep Analysis"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/05/14/hr-ai-front-door-war-agentic-workflow-platforms/",
      "title": "Who Owns the Front Door to HR Work?",
      "summary": "Workday, Microsoft, ServiceNow, OpenAI, and Google are fighting over where employee requests begin, which system can turn them into actions, and which ledger survives the audit.",
      "html_url": "https://digidai.github.io/2026/05/14/hr-ai-front-door-war-agentic-workflow-platforms/",
      "markdown_url": "https://digidai.github.io/2026/05/14/hr-ai-front-door-war-agentic-workflow-platforms/index.md",
      "date_published": "2026-05-14T00:00:00.000Z",
      "date_modified": "2026-05-14T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Enterprise Software",
        "Governance",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/05/13/hr-ai-post-termination-evidence-support-sla/",
      "title": "After the HR AI Vendor Leaves, the Evidence Questions Remain",
      "summary": "When HR AI vendors power recruiting, employee service, payroll, performance, and workforce agents, employers need exit support that keeps audit evidence usable after the contract ends.",
      "html_url": "https://digidai.github.io/2026/05/13/hr-ai-post-termination-evidence-support-sla/",
      "markdown_url": "https://digidai.github.io/2026/05/13/hr-ai-post-termination-evidence-support-sla/index.md",
      "date_published": "2026-05-13T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Governance",
        "Compliance",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/05/11/hr-ai-evidence-portability/",
      "title": "Can HR AI Evidence Survive a Vendor Switch?",
      "summary": "As employers switch HR AI vendors, terminate contracts, face investigations, or migrate agent platforms, procurement teams need decision evidence that can leave the original vendor intact.",
      "html_url": "https://digidai.github.io/2026/05/11/hr-ai-evidence-portability/",
      "markdown_url": "https://digidai.github.io/2026/05/11/hr-ai-evidence-portability/index.md",
      "date_published": "2026-05-11T00:00:00.000Z",
      "date_modified": "2026-05-11T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Governance",
        "Compliance",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/05/10/hr-ai-runtime-tool-approval-ledger/",
      "title": "Who Approved the Tool Call Before the HR Decision?",
      "summary": "MCP servers, agent gateways, and HR workflow agents turn every tool call into a governance event. Runtime approval records must show who cleared each high-risk tool, model, data source, and write action before it touched an employment decision.",
      "html_url": "https://digidai.github.io/2026/05/10/hr-ai-runtime-tool-approval-ledger/",
      "markdown_url": "https://digidai.github.io/2026/05/10/hr-ai-runtime-tool-approval-ledger/index.md",
      "date_published": "2026-05-10T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Governance",
        "Compliance",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/05/10/hr-ai-subprocessor-chain-of-custody/",
      "title": "The Hidden Chain Behind an HR AI Decision",
      "summary": "Agentic HR workflows now call outside models, MCP servers, identity systems, RAG sources, and workflow platforms. Static subprocessor lists do not show the chain of custody behind employment-impacting outputs.",
      "html_url": "https://digidai.github.io/2026/05/10/hr-ai-subprocessor-chain-of-custody/",
      "markdown_url": "https://digidai.github.io/2026/05/10/hr-ai-subprocessor-chain-of-custody/index.md",
      "date_published": "2026-05-10T00:00:00.000Z",
      "date_modified": "2026-05-10T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Security",
        "Compliance",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/05/08/hr-ai-correction-propagation-sla/",
      "title": "The HR Error That Would Not Stay Corrected",
      "summary": "Correcting one AI-assisted HR record does not fix every copy. Flawed outputs can move through email, ATS, HRIS, payroll, service cases, manager packets, analytics, and vendor logs, requiring a clock for downstream correction.",
      "html_url": "https://digidai.github.io/2026/05/08/hr-ai-correction-propagation-sla/",
      "markdown_url": "https://digidai.github.io/2026/05/08/hr-ai-correction-propagation-sla/index.md",
      "date_published": "2026-05-08T00:00:00.000Z",
      "date_modified": "2026-05-08T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Governance",
        "Compliance",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/05/07/hr-ai-decision-recall-downstream-correction-chain/",
      "title": "When an AI Hiring Note Has to Be Recalled",
      "summary": "As AI agents move into hiring, payroll, performance, scheduling, and employee service workflows, employers need recall paths for flawed outputs that have already entered emails, ATS notes, HRIS records, payroll queues, and manager packets.",
      "html_url": "https://digidai.github.io/2026/05/07/hr-ai-decision-recall-downstream-correction-chain/",
      "markdown_url": "https://digidai.github.io/2026/05/07/hr-ai-decision-recall-downstream-correction-chain/index.md",
      "date_published": "2026-05-07T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Governance",
        "Compliance",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/05/06/hr-ai-evidence-escrow-vendor-proof-layer/",
      "title": "The Evidence HR AI Vendors Must Preserve Before Trouble Starts",
      "summary": "Audit logs are not enough for HR AI buyers. Vendors selling agents into hiring, payroll, performance, scheduling, and employee service need escrowed model versions, prompts, evaluations, logs, subprocessors, and affected-population snapshots before incidents arrive.",
      "html_url": "https://digidai.github.io/2026/05/06/hr-ai-evidence-escrow-vendor-proof-layer/",
      "markdown_url": "https://digidai.github.io/2026/05/06/hr-ai-evidence-escrow-vendor-proof-layer/index.md",
      "date_published": "2026-05-06T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Procurement",
        "Compliance",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/05/05/hr-ai-vendor-remediation-warranty/",
      "title": "The HR AI Contract Starts Charging for Remediation",
      "summary": "As agents enter hiring, payroll, performance, scheduling, and employee service, HR AI buyers are adding contract tests for affected-population discovery, evidence production, reconsideration support, and remediation cost sharing.",
      "html_url": "https://digidai.github.io/2026/05/05/hr-ai-vendor-remediation-warranty/",
      "markdown_url": "https://digidai.github.io/2026/05/05/hr-ai-vendor-remediation-warranty/index.md",
      "date_published": "2026-05-05T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Procurement",
        "Compliance",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/05/04/hr-ai-recovery-sla-remediation-clock/",
      "title": "When an HR AI Error Starts the Recovery Clock",
      "summary": "As AI agents enter hiring, payroll, performance, scheduling, and employee service, HR governance shifts to the recovery clock: correcting affected decisions, notifying people, rerunning review, repairing records, and proving trust was restored.",
      "html_url": "https://digidai.github.io/2026/05/04/hr-ai-recovery-sla-remediation-clock/",
      "markdown_url": "https://digidai.github.io/2026/05/04/hr-ai-recovery-sla-remediation-clock/index.md",
      "date_published": "2026-05-04T00:00:00.000Z",
      "date_modified": "2026-05-04T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Governance",
        "Compliance",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/05/03/agent-quarantine-layer-hr-ai-control-plane/",
      "title": "The First Minute After an HR Agent Goes Out of Bounds",
      "summary": "Unknown and over-scoped AI agents create an operating risk for HR. Companies need to discover a digital worker, isolate it, revoke action rights, freeze affected employment workflows, preserve evidence, and prove it stopped acting.",
      "html_url": "https://digidai.github.io/2026/05/03/agent-quarantine-layer-hr-ai-control-plane/",
      "markdown_url": "https://digidai.github.io/2026/05/03/agent-quarantine-layer-hr-ai-control-plane/index.md",
      "date_published": "2026-05-03T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Security",
        "Governance",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/05/02/hr-ai-governance-audit-room/",
      "title": "Inside the HR AI Audit Room",
      "summary": "HR AI governance is moving from policy decks to audit rooms where HR, IT, legal, security, procurement, and vendors must produce one coherent evidence record covering inventory, risk tier, agent identity, data lineage, review, incidents, appeals, and use.",
      "html_url": "https://digidai.github.io/2026/05/02/hr-ai-governance-audit-room/",
      "markdown_url": "https://digidai.github.io/2026/05/02/hr-ai-governance-audit-room/index.md",
      "date_published": "2026-05-02T00:00:00.000Z",
      "date_modified": "2026-05-02T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Governance",
        "Compliance",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/05/01/decision-evidence-packet-hr-ai-proof-layer/",
      "title": "Inside the Evidence Packet Behind an HR AI Decision",
      "summary": "As HR AI reaches hiring, pay, performance, promotion, scheduling, and employee service, companies need decision packets that reconstruct the data, agent action, human review, notification, change history, and correction path months later.",
      "html_url": "https://digidai.github.io/2026/05/01/decision-evidence-packet-hr-ai-proof-layer/",
      "markdown_url": "https://digidai.github.io/2026/05/01/decision-evidence-packet-hr-ai-proof-layer/index.md",
      "date_published": "2026-05-01T00:00:00.000Z",
      "date_modified": "2026-05-01T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Governance",
        "Compliance",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/04/30/agent-kill-switch-rollback-hr-ai-control-plane/",
      "title": "When the Payroll Agent Has to Stop",
      "summary": "AI agents are entering payroll, recruiting, employee service, promotion, and scheduling workflows. HR buyers now need products that can stop a digital worker, freeze the workflow, preserve evidence, reverse damage, and recover trust.",
      "html_url": "https://digidai.github.io/2026/04/30/agent-kill-switch-rollback-hr-ai-control-plane/",
      "markdown_url": "https://digidai.github.io/2026/04/30/agent-kill-switch-rollback-hr-ai-control-plane/index.md",
      "date_published": "2026-04-30T00:00:00.000Z",
      "date_modified": "2026-04-30T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Governance",
        "Security",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/04/29/agent-access-drift-hr-ai-data-security/",
      "title": "When Digital Workers Keep Their Old Badges",
      "summary": "AI agents are entering payroll, recruiting, performance, and employee service, raising a quieter HR security risk: digital workers can keep permissions after their purpose changes and touch people data no one meant to expose.",
      "html_url": "https://digidai.github.io/2026/04/29/agent-access-drift-hr-ai-data-security/",
      "markdown_url": "https://digidai.github.io/2026/04/29/agent-access-drift-hr-ai-data-security/index.md",
      "date_published": "2026-04-29T00:00:00.000Z",
      "date_modified": "2026-04-29T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Security",
        "Governance",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/04/27/agent-incident-response-hr-ai-operating-system/",
      "title": "When HR Has to Run Incident Response for Digital Workers",
      "summary": "AI agents are entering payroll, recruiting, employee service, promotion workflows, and workforce analytics, forcing HR to run an incident response model that can freeze, investigate, correct, notify, and recover.",
      "html_url": "https://digidai.github.io/2026/04/27/agent-incident-response-hr-ai-operating-system/",
      "markdown_url": "https://digidai.github.io/2026/04/27/agent-incident-response-hr-ai-operating-system/index.md",
      "date_published": "2026-04-27T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Governance",
        "Risk Management",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/04/26/human-override-theater-hr-ai-audit-risk/",
      "title": "When Human Review Becomes Audit Theater",
      "summary": "Companies use human-in-the-loop controls to make workplace AI look accountable, but regulators, auditors, and behavior research show that reviewers need evidence, time, authority, and an override trail.",
      "html_url": "https://digidai.github.io/2026/04/26/human-override-theater-hr-ai-audit-risk/",
      "markdown_url": "https://digidai.github.io/2026/04/26/human-override-theater-hr-ai-audit-risk/index.md",
      "date_published": "2026-04-26T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Governance",
        "Compliance",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/04/24/ai-agent-accountability-gap-human-manager-liability/",
      "title": "When Agent Accountability Lands on Managers",
      "summary": "AI agents are moving from copilots to digital workers in HR, payroll, recruiting, employee service, and workforce planning. New research suggests human-AI teams can increase human responsibility, forcing HR tech to prove ownership, review, and correction.",
      "html_url": "https://digidai.github.io/2026/04/24/ai-agent-accountability-gap-human-manager-liability/",
      "markdown_url": "https://digidai.github.io/2026/04/24/ai-agent-accountability-gap-human-manager-liability/index.md",
      "date_published": "2026-04-24T00:00:00.000Z",
      "date_modified": "2026-04-24T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Governance",
        "Future of Work",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/04/23/human-agent-ratio-workforce-planning-metric/",
      "title": "The Missing Column in the Workforce Plan",
      "summary": "Microsoft, Mercer, S&P Global, Workday, ADP, SHRM, PwC, and KPMG show workforce planning moving from headcount math to a human-agent operating model with agents, supervisors, skills, exceptions, and risk capacity.",
      "html_url": "https://digidai.github.io/2026/04/23/human-agent-ratio-workforce-planning-metric/",
      "markdown_url": "https://digidai.github.io/2026/04/23/human-agent-ratio-workforce-planning-metric/index.md",
      "date_published": "2026-04-23T00:00:00.000Z",
      "date_modified": "2026-04-23T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Workforce Planning",
        "People Analytics",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/04/22/ai-agent-manager-human-agent-teams-management-layer/",
      "title": "Managing Agents Starts Before the Job Title Exists",
      "summary": "Microsoft, Mercer, Workday, ADP, Capgemini, and Gartner point to companies managing AI agents as part of the workforce, forcing ordinary managers to govern scope, access, handoffs, quality, and accountability.",
      "html_url": "https://digidai.github.io/2026/04/22/ai-agent-manager-human-agent-teams-management-layer/",
      "markdown_url": "https://digidai.github.io/2026/04/22/ai-agent-manager-human-agent-teams-management-layer/index.md",
      "date_published": "2026-04-22T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Management",
        "Future of Work",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/04/21/next-hr-ai-fight-performance-management-post-hire-decisions/",
      "title": "After Hiring, HR AI Moves Into Performance Management",
      "summary": "AI is moving from recruiting into reviews, promotions, redeployment, payroll insights, and employee monitoring, pulling Workday, ADP, Mercer, S&P Global, and regulators into post-hire decisions.",
      "html_url": "https://digidai.github.io/2026/04/21/next-hr-ai-fight-performance-management-post-hire-decisions/",
      "markdown_url": "https://digidai.github.io/2026/04/21/next-hr-ai-fight-performance-management-post-hire-decisions/index.md",
      "date_published": "2026-04-21T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Performance Management",
        "Compliance",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/04/20/agent-governance-hr-tech-buying-surface/",
      "title": "The HR Tech Deal Moves to Agent Governance",
      "summary": "Workday, ServiceNow, and Salesforce are converging on the layer that governs agent identity, approvals, model routing, and cross-system execution. Enterprise buyers now treat the control surface as the product.",
      "html_url": "https://digidai.github.io/2026/04/20/agent-governance-hr-tech-buying-surface/",
      "markdown_url": "https://digidai.github.io/2026/04/20/agent-governance-hr-tech-buying-surface/index.md",
      "date_published": "2026-04-20T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Governance",
        "Enterprise Software",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/04/20/ai-literacy-new-white-collar-minimum-hiring-verification-internal-mobility/",
      "title": "AI Literacy Enters the White-Collar Baseline",
      "summary": "LinkedIn, Workday, and U.S. labor data show AI literacy moving from a desirable skill to a baseline expectation across many non-technical roles, while hiring teams still rely on weak proxies and disconnected learning systems.",
      "html_url": "https://digidai.github.io/2026/04/20/ai-literacy-new-white-collar-minimum-hiring-verification-internal-mobility/",
      "markdown_url": "https://digidai.github.io/2026/04/20/ai-literacy-new-white-collar-minimum-hiring-verification-internal-mobility/index.md",
      "date_published": "2026-04-20T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Skills",
        "Internal Mobility",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/04/19/hr-not-at-ai-decision-table-legal-it-governance/",
      "title": "HR Isn't at the AI Decision Table. Legal and IT Are.",
      "summary": "SHRM's 2026 data show legal and compliance commonly leading AI governance while many HR teams remain outside enterprise AI strategy. The article examines what HR must still own.",
      "html_url": "https://digidai.github.io/2026/04/19/hr-not-at-ai-decision-table-legal-it-governance/",
      "markdown_url": "https://digidai.github.io/2026/04/19/hr-not-at-ai-decision-table-legal-it-governance/index.md",
      "date_published": "2026-04-19T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "HR Tech",
        "Governance",
        "Enterprise Software",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/04/18/staffing-ai-margin-reset-revenue-per-recruiter-delivery-engine/",
      "title": "Staffing's AI Margin Reset Starts With Revenue per Recruiter",
      "summary": "Bullhorn, Adecco, Randstad, and ManpowerGroup face the same problem: AI changes how staffing firms defend service margin, centralize delivery, and turn platform leverage into profit.",
      "html_url": "https://digidai.github.io/2026/04/18/staffing-ai-margin-reset-revenue-per-recruiter-delivery-engine/",
      "markdown_url": "https://digidai.github.io/2026/04/18/staffing-ai-margin-reset-revenue-per-recruiter-delivery-engine/index.md",
      "date_published": "2026-04-18T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "Recruiting",
        "Staffing",
        "HR Tech",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/04/17/resume-losing-signal-hiring-verified-identity-work-samples/",
      "title": "After the Resume Lost Its Signal",
      "summary": "AI made job applications faster and weakened recruiting's old trust model. Identity verification, work samples, live simulations, and AI fluency checks are forming a new signal stack in hiring.",
      "html_url": "https://digidai.github.io/2026/04/17/resume-losing-signal-hiring-verified-identity-work-samples/",
      "markdown_url": "https://digidai.github.io/2026/04/17/resume-losing-signal-hiring-verified-identity-work-samples/index.md",
      "date_published": "2026-04-17T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "Recruiting",
        "HR Tech",
        "Assessments",
        "Industry Analysis"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/04/16/frontline-hiring-control-plane-first-shift-readiness/",
      "title": "Frontline Hiring Moves From Offer Letter to First Shift",
      "summary": "Workday, UKG, Fountain, and Legion are linking application, screening, scheduling, onboarding, and first-shift readiness into one operating workflow for frontline labor.",
      "html_url": "https://digidai.github.io/2026/04/16/frontline-hiring-control-plane-first-shift-readiness/",
      "markdown_url": "https://digidai.github.io/2026/04/16/frontline-hiring-control-plane-first-shift-readiness/index.md",
      "date_published": "2026-04-16T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "Recruiting",
        "HR Tech",
        "Frontline Work",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/04/15/ai-hiring-compliance-audit-trail-product/",
      "title": "In AI Hiring, the Deal Moves to the Audit Trail",
      "summary": "Bias audits, worker notices, log retention, and human oversight now shape recruiting software deals from New York and California to Colorado and the EU AI Act.",
      "html_url": "https://digidai.github.io/2026/04/15/ai-hiring-compliance-audit-trail-product/",
      "markdown_url": "https://digidai.github.io/2026/04/15/ai-hiring-compliance-audit-trail-product/index.md",
      "date_published": "2026-04-15T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "Recruiting",
        "Compliance",
        "HR Tech",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/04/14/when-recruiting-and-employee-service-merge-independent-hr-tech/",
      "title": "When Recruiting and Employee Service Merge, Independent HR Tech Has to Choose a Side",
      "summary": "As Workday, SAP, ServiceNow, Salesforce, and Oracle pull hiring into broader employee and service workflows, the middle of HR tech is getting squeezed. The categories that can still stand alone are the ones that own external demand, trust, or hard operational complexity.",
      "html_url": "https://digidai.github.io/2026/04/14/when-recruiting-and-employee-service-merge-independent-hr-tech/",
      "markdown_url": "https://digidai.github.io/2026/04/14/when-recruiting-and-employee-service-merge-independent-hr-tech/index.md",
      "date_published": "2026-04-14T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "Recruiting",
        "HR Tech",
        "Enterprise Software",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/04/13/skills-based-hiring-phase-two-talent-system-index/",
      "title": "Skills-Based Hiring Enters Its Second Phase",
      "summary": "Skills-based hiring has moved beyond job ads and filters. Employers are trying to turn skills into a shared data layer for recruiting, internal mobility, learning, and workforce planning.",
      "html_url": "https://digidai.github.io/2026/04/13/skills-based-hiring-phase-two-talent-system-index/",
      "markdown_url": "https://digidai.github.io/2026/04/13/skills-based-hiring-phase-two-talent-system-index/index.md",
      "date_published": "2026-04-13T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "Recruiting",
        "Skills-Based Hiring",
        "Talent Management",
        "Industry Analysis"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/04/12/recruiting-ai-procurement-auditable-hiring-outcomes/",
      "title": "Recruiting AI Deals Move From Demos to Proof",
      "summary": "Enterprise recruiting software buying is shifting from workflow demos and time-saved claims toward measurable quality of hire, compliance evidence, and platform-level accountability.",
      "html_url": "https://digidai.github.io/2026/04/12/recruiting-ai-procurement-auditable-hiring-outcomes/",
      "markdown_url": "https://digidai.github.io/2026/04/12/recruiting-ai-procurement-auditable-hiring-outcomes/index.md",
      "date_published": "2026-04-12T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "Recruiting",
        "HR Tech",
        "Enterprise Software",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/04/11/linkedin-indeed-candidate-distribution-war/",
      "title": "LinkedIn, Indeed, and the Fight for Candidate Distribution",
      "summary": "How AI is shifting recruiting power from ATS screens to the platforms and agents that control job visibility, candidate ranking, and distribution.",
      "html_url": "https://digidai.github.io/2026/04/11/linkedin-indeed-candidate-distribution-war/",
      "markdown_url": "https://digidai.github.io/2026/04/11/linkedin-indeed-candidate-distribution-war/index.md",
      "date_published": "2026-04-11T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "Recruiting",
        "LinkedIn",
        "Indeed",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/04/10/recruiters-wont-disappear-but-will-be-repriced-talent-advisor-reset/",
      "title": "Recruiters Won't Disappear. They Will Be Repriced.",
      "summary": "How AI is splitting recruiting into low-margin process work and high-value advisory work, repricing the role rather than erasing it.",
      "html_url": "https://digidai.github.io/2026/04/10/recruiters-wont-disappear-but-will-be-repriced-talent-advisor-reset/",
      "markdown_url": "https://digidai.github.io/2026/04/10/recruiters-wont-disappear-but-will-be-repriced-talent-advisor-reset/index.md",
      "date_published": "2026-04-10T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "Recruiting",
        "Talent Acquisition",
        "HR Tech",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/03/31/recruiting-becoming-enterprise-service-workflow-ownership-battle/",
      "title": "ServiceNow, Salesforce, and Workday: who can coordinate the recruiting workflow?",
      "summary": "A source-audited comparison of how three enterprise platforms approach recruiting, employee service, agent governance, and cross-system workflow control.",
      "html_url": "https://digidai.github.io/2026/03/31/recruiting-becoming-enterprise-service-workflow-ownership-battle/",
      "markdown_url": "https://digidai.github.io/2026/03/31/recruiting-becoming-enterprise-service-workflow-ownership-battle/index.md",
      "date_published": "2026-03-31T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "Recruiting",
        "Enterprise Software",
        "Staffing",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/03/30/headhunters-rpo-staffing-ai-operating-model-reset/",
      "title": "How AI is changing staffing and RPO operating models",
      "summary": "A source-audited analysis of staffing and RPO automation, verification, platform dependence, recruiter productivity, service margins, and the evidence buyers should demand.",
      "html_url": "https://digidai.github.io/2026/03/30/headhunters-rpo-staffing-ai-operating-model-reset/",
      "markdown_url": "https://digidai.github.io/2026/03/30/headhunters-rpo-staffing-ai-operating-model-reset/index.md",
      "date_published": "2026-03-30T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "Recruiting",
        "Staffing",
        "RPO",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/03/30/high-volume-hiring-ai-roi-frontline-battlefield/",
      "title": "Where AI recruiting has to prove ROI: frontline hiring",
      "summary": "A source-audited framework for measuring frontline hiring automation through completion, scheduling, time to hire, quality, manager workload, and first-shift readiness.",
      "html_url": "https://digidai.github.io/2026/03/30/high-volume-hiring-ai-roi-frontline-battlefield/",
      "markdown_url": "https://digidai.github.io/2026/03/30/high-volume-hiring-ai-roi-frontline-battlefield/index.md",
      "date_published": "2026-03-30T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "Recruiting",
        "Frontline Hiring",
        "Staffing",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/03/27/from-talent-acquisition-to-talent-readiness-why-internal-mobility-is-overtaking-external-hiring/",
      "title": "When internal mobility can beat another external search",
      "summary": "A source-audited framework for deciding when internal mobility, reskilling, or external hiring is the better response to a capability gap.",
      "html_url": "https://digidai.github.io/2026/03/27/from-talent-acquisition-to-talent-readiness-why-internal-mobility-is-overtaking-external-hiring/",
      "markdown_url": "https://digidai.github.io/2026/03/27/from-talent-acquisition-to-talent-readiness-why-internal-mobility-is-overtaking-external-hiring/index.md",
      "date_published": "2026-03-27T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "Recruiting",
        "Talent Management",
        "Internal Mobility",
        "Industry Analysis"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/03/26/ats-endgame-rebundling-into-hcm-and-enterprise-service-platforms/",
      "title": "ATS rebundling: why recruiting software is moving into larger platforms",
      "summary": "A source-audited analysis of how Workday, SAP, ServiceNow, and adjacent suites are pulling recruiting into skills, workflow, and agent-governance platforms.",
      "html_url": "https://digidai.github.io/2026/03/26/ats-endgame-rebundling-into-hcm-and-enterprise-service-platforms/",
      "markdown_url": "https://digidai.github.io/2026/03/26/ats-endgame-rebundling-into-hcm-and-enterprise-service-platforms/index.md",
      "date_published": "2026-03-26T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "Recruiting",
        "HR Tech",
        "Enterprise Software",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/03/21/ai-recruiting-trust-crisis-deepfakes-identity-verification-arms-race/",
      "title": "AI Recruiting's Trust Crisis: Deepfakes, Identity Proofing, and Fraud",
      "summary": "How deepfake interviews, AI-written resumes, and identity laundering pushed recruiting into a trust crisis, making verification a core hiring workflow.",
      "html_url": "https://digidai.github.io/2026/03/21/ai-recruiting-trust-crisis-deepfakes-identity-verification-arms-race/",
      "markdown_url": "https://digidai.github.io/2026/03/21/ai-recruiting-trust-crisis-deepfakes-identity-verification-arms-race/index.md",
      "date_published": "2026-03-21T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "Recruiting",
        "HR Tech",
        "Enterprise AI",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/03/20/openai-2024-2025-valuation-products-governance-compute-reset/",
      "title": "OpenAI's $300 Billion Valuation: Compute, Governance, and the Cost of Scale",
      "summary": "A look at the operating math behind OpenAI's $300 billion valuation, from ChatGPT pricing and enterprise mix to governance redesign and compute intensity.",
      "html_url": "https://digidai.github.io/2026/03/20/openai-2024-2025-valuation-products-governance-compute-reset/",
      "markdown_url": "https://digidai.github.io/2026/03/20/openai-2024-2025-valuation-products-governance-compute-reset/index.md",
      "date_published": "2026-03-20T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "OpenAI",
        "ChatGPT",
        "AI Industry",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/03/18/openai-2024-2025-valuation-products-organization-reset/",
      "title": "How ChatGPT became an enterprise distribution engine",
      "summary": "A source-audited analysis of ChatGPT's enterprise growth, product packaging, privacy controls, adoption evidence, and the gap between broad use and embedded workflow value.",
      "html_url": "https://digidai.github.io/2026/03/18/openai-2024-2025-valuation-products-organization-reset/",
      "markdown_url": "https://digidai.github.io/2026/03/18/openai-2024-2025-valuation-products-organization-reset/index.md",
      "date_published": "2026-03-18T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "OpenAI",
        "ChatGPT",
        "AI Industry",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/03/17/anthropic-safety-premium-enterprise-ai-business-logic-2026/",
      "title": "Anthropic's safety premium: enterprise demand, capital, and the evidence behind the thesis",
      "summary": "A source-audited analysis of Anthropic's financing, enterprise positioning, coding wedge, Responsible Scaling Policy, cloud dependencies, and the limits of the safety-premium thesis.",
      "html_url": "https://digidai.github.io/2026/03/17/anthropic-safety-premium-enterprise-ai-business-logic-2026/",
      "markdown_url": "https://digidai.github.io/2026/03/17/anthropic-safety-premium-enterprise-ai-business-logic-2026/index.md",
      "date_published": "2026-03-17T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "Anthropic",
        "Claude",
        "AI Safety",
        "Enterprise AI",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/03/15/building-the-slack-for-human-agent-collaboration/",
      "title": "Building the Slack for Human-Agent Collaboration",
      "summary": "Slack, Teams, and Atlassian are racing to own human-agent collaboration. The winner will control identity, context, action, governance, and distribution.",
      "html_url": "https://digidai.github.io/2026/03/15/building-the-slack-for-human-agent-collaboration/",
      "markdown_url": "https://digidai.github.io/2026/03/15/building-the-slack-for-human-agent-collaboration/index.md",
      "date_published": "2026-03-15T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI Agents",
        "Slack",
        "Microsoft Teams",
        "Atlassian",
        "Enterprise Software"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/03/15/openai-2024-2026-valuation-to-operating-system-race/",
      "title": "OpenAI's platform race: Microsoft, capital, infrastructure, and control",
      "summary": "A source-audited analysis of OpenAI's financing, Microsoft agreements, infrastructure commitments, enterprise reach, and the operating risks behind its platform strategy.",
      "html_url": "https://digidai.github.io/2026/03/15/openai-2024-2026-valuation-to-operating-system-race/",
      "markdown_url": "https://digidai.github.io/2026/03/15/openai-2024-2026-valuation-to-operating-system-race/index.md",
      "date_published": "2026-03-15T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "OpenAI",
        "Deep Investigation",
        "AI Industry",
        "Enterprise AI",
        "Product Strategy"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/03/14/cursor-vs-github-copilot-ai-coding-tools-deep-comparison/",
      "title": "Cursor and GitHub Copilot: A Repository Trial Worksheet",
      "summary": "Run a bounded coding-tool trial on authorized repositories. Record versions, accepted changes, failed runs, review effort and usage costs without inventing a benchmark winner.",
      "html_url": "https://digidai.github.io/2026/03/14/cursor-vs-github-copilot-ai-coding-tools-deep-comparison/",
      "markdown_url": "https://digidai.github.io/2026/03/14/cursor-vs-github-copilot-ai-coding-tools-deep-comparison/index.md",
      "date_published": "2026-03-14T00:00:00.000Z",
      "date_modified": "2026-09-09T00:00:00.000Z",
      "tags": [
        "AI Coding",
        "Cursor",
        "GitHub Copilot",
        "Developer Productivity",
        "AI Agents"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/03/13/ai-regulation-2026-global-policy-map-enterprise-compliance-guide/",
      "title": "AI Regulation in 2026: A Global Policy Map for Product Teams",
      "summary": "A practical map of AI regulation in 2026 across the EU, U.S., China, the UK, and Japan, with an operating model for teams shipping across borders.",
      "html_url": "https://digidai.github.io/2026/03/13/ai-regulation-2026-global-policy-map-enterprise-compliance-guide/",
      "markdown_url": "https://digidai.github.io/2026/03/13/ai-regulation-2026-global-policy-map-enterprise-compliance-guide/index.md",
      "date_published": "2026-03-13T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "AI Regulation",
        "Compliance",
        "Policy",
        "Industry Analysis",
        "AI Industry"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/03/13/chatgpt-vs-claude-vs-gemini-2026-ultimate-comparison/",
      "title": "ChatGPT vs Claude vs Gemini in 2026: A Practical Decision Framework for Real Work",
      "summary": "A source-bound framework for comparing ChatGPT, Claude, and Gemini by workflow fit, controls, failure cost, and measured pilot results.",
      "html_url": "https://digidai.github.io/2026/03/13/chatgpt-vs-claude-vs-gemini-2026-ultimate-comparison/",
      "markdown_url": "https://digidai.github.io/2026/03/13/chatgpt-vs-claude-vs-gemini-2026-ultimate-comparison/index.md",
      "date_published": "2026-03-13T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "ChatGPT",
        "Claude",
        "Gemini",
        "Product Analysis",
        "AI Industry"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/03/13/open-weight-ai-war-llama-mistral-deepseek-qwen/",
      "title": "Llama, Mistral, DeepSeek and Qwen: An Open-Weight Comparison",
      "summary": "Compare version-specific licenses and deployment requirements, then evaluate open-weight models with a reproducible quality, latency and cost protocol.",
      "html_url": "https://digidai.github.io/2026/03/13/open-weight-ai-war-llama-mistral-deepseek-qwen/",
      "markdown_url": "https://digidai.github.io/2026/03/13/open-weight-ai-war-llama-mistral-deepseek-qwen/index.md",
      "date_published": "2026-03-13T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "Open Weight Models",
        "Llama",
        "Mistral",
        "DeepSeek",
        "Qwen"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/03/13/openai-2024-2025-valuation-to-product-governance-repricing/",
      "title": "OpenAI 2024-2025: From Valuation Shock to Product-Stack Reality",
      "summary": "A deep look at OpenAI's shift from breakout product company to infrastructure-scale platform, covering product cadence, governance redesign, and enterprise economics.",
      "html_url": "https://digidai.github.io/2026/03/13/openai-2024-2025-valuation-to-product-governance-repricing/",
      "markdown_url": "https://digidai.github.io/2026/03/13/openai-2024-2025-valuation-to-product-governance-repricing/index.md",
      "date_published": "2026-03-13T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "OpenAI",
        "ChatGPT",
        "GPT-5",
        "Deep Investigation",
        "AI Industry"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/03/06/dario-amodei-anthropic-ai-safety-evangelist-business-path-deep-investigation/",
      "title": "Dario Amodei and Anthropic: scaling frontier AI under a public safety framework",
      "summary": "A source-bound analysis of Dario Amodei's research record, Anthropic leadership, Responsible Scaling Policy, business growth, and unresolved governance tension.",
      "html_url": "https://digidai.github.io/2026/03/06/dario-amodei-anthropic-ai-safety-evangelist-business-path-deep-investigation/",
      "markdown_url": "https://digidai.github.io/2026/03/06/dario-amodei-anthropic-ai-safety-evangelist-business-path-deep-investigation/index.md",
      "date_published": "2026-03-06T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Dario Amodei",
        "Anthropic",
        "AI Safety",
        "Responsible Scaling",
        "AI Governance"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/03/06/google-deepmind-real-fighting-power-two-years-after-merger/",
      "title": "Google DeepMind After the 2023 Merger: Verified Outputs, Integration, and Open Questions",
      "summary": "A source-bound review of Google DeepMind after Google combined DeepMind and Brain, covering Gemini, AlphaFold, product integration, infrastructure, safety, and evidence gaps.",
      "html_url": "https://digidai.github.io/2026/03/06/google-deepmind-real-fighting-power-two-years-after-merger/",
      "markdown_url": "https://digidai.github.io/2026/03/06/google-deepmind-real-fighting-power-two-years-after-merger/index.md",
      "date_published": "2026-03-06T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "Google DeepMind",
        "Gemini",
        "AI Industry",
        "Artificial Intelligence"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/03/06/jensen-huang-nvidia-gpu-empire-ai-bet-deep-investigation/",
      "title": "Jensen Huang and NVIDIA: The Platform Behind the AI Infrastructure Boom",
      "summary": "A source-bound analysis of Jensen Huang, NVIDIA's CUDA and rack-scale strategy, current financial disclosures, and the customer, supply, competition, and policy risks behind its AI growth.",
      "html_url": "https://digidai.github.io/2026/03/06/jensen-huang-nvidia-gpu-empire-ai-bet-deep-investigation/",
      "markdown_url": "https://digidai.github.io/2026/03/06/jensen-huang-nvidia-gpu-empire-ai-bet-deep-investigation/index.md",
      "date_published": "2026-03-06T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "NVIDIA",
        "Jensen Huang",
        "GPU",
        "Semiconductors",
        "AI Infrastructure"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/03/06/openai-2024-2025-valuation-products-organization-full-review/",
      "title": "OpenAI after 2024: products, capital, structure, and open questions",
      "summary": "A source-bound review of OpenAI's product expansion, 2025 restructuring, 2026 financing, user disclosures, Microsoft terms, and infrastructure.",
      "html_url": "https://digidai.github.io/2026/03/06/openai-2024-2025-valuation-products-organization-full-review/",
      "markdown_url": "https://digidai.github.io/2026/03/06/openai-2024-2025-valuation-products-organization-full-review/index.md",
      "date_published": "2026-03-06T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "OpenAI",
        "ChatGPT",
        "GPT-5",
        "Deep Investigation",
        "AI Industry",
        "Corporate Governance"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/03/06/sam-altman-from-yc-to-openai-power-game-deep-investigation/",
      "title": "Sam Altman, OpenAI Governance, and the Limits of Founder Power",
      "summary": "A source-bound examination of Sam Altman's path from Loopt and Y Combinator to OpenAI, the 2023 board crisis, and the company's current control structure.",
      "html_url": "https://digidai.github.io/2026/03/06/sam-altman-from-yc-to-openai-power-game-deep-investigation/",
      "markdown_url": "https://digidai.github.io/2026/03/06/sam-altman-from-yc-to-openai-power-game-deep-investigation/index.md",
      "date_published": "2026-03-06T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "OpenAI",
        "Sam Altman",
        "Governance",
        "AI Industry",
        "Artificial Intelligence"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/02/26/anthropic-ai-safety-first-business-logic-deep-investigation/",
      "title": "Anthropic's Safety Commitments Under Commercial and Government Pressure",
      "summary": "A source-bound investigation of Anthropic's governance, Responsible Scaling Policy revisions, defense dispute, court ruling, financing, and unresolved accountability questions.",
      "html_url": "https://digidai.github.io/2026/02/26/anthropic-ai-safety-first-business-logic-deep-investigation/",
      "markdown_url": "https://digidai.github.io/2026/02/26/anthropic-ai-safety-first-business-logic-deep-investigation/index.md",
      "date_published": "2026-02-26T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "Anthropic",
        "AI Safety",
        "AI Governance",
        "Defense AI",
        "Policy"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/02/18/anthropic-ai-safety-first-business-logic-deep-analysis/",
      "title": "Anthropic's Safety Strategy: Where It Creates Enterprise Value and Where Evidence Stops",
      "summary": "A buyer-focused analysis of Anthropic's Constitution, Responsible Scaling Policy, system cards, governance, and the evidence enterprises still need before deployment.",
      "html_url": "https://digidai.github.io/2026/02/18/anthropic-ai-safety-first-business-logic-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2026/02/18/anthropic-ai-safety-first-business-logic-deep-analysis/index.md",
      "date_published": "2026-02-18T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "Anthropic",
        "Claude",
        "AI Safety",
        "Enterprise AI",
        "AI Governance"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/02/12/perplexity-ai-search-engine-reinvention-deep-analysis/",
      "title": "Perplexity AI Search: Product Model, Publisher Economics, and Unresolved Legal Risk",
      "summary": "A source-bound analysis of Perplexity's answer-engine model, citations, publisher programs, crawler controls, active litigation, and the evidence buyers should request.",
      "html_url": "https://digidai.github.io/2026/02/12/perplexity-ai-search-engine-reinvention-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2026/02/12/perplexity-ai-search-engine-reinvention-deep-analysis/index.md",
      "date_published": "2026-02-12T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "Search",
        "Perplexity AI",
        "Product Analysis",
        "Publishers"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/02/08/cursor-vs-github-copilot-ai-coding-tools-deep-comparison/",
      "title": "Cursor vs GitHub Copilot: Pricing, Privacy and Workflow Fit",
      "summary": "Compare current billing and data-handling boundaries, then test Cursor and GitHub Copilot on accepted code changes rather than suggestion counts.",
      "html_url": "https://digidai.github.io/2026/02/08/cursor-vs-github-copilot-ai-coding-tools-deep-comparison/",
      "markdown_url": "https://digidai.github.io/2026/02/08/cursor-vs-github-copilot-ai-coding-tools-deep-comparison/index.md",
      "date_published": "2026-02-08T00:00:00.000Z",
      "date_modified": "2026-09-08T00:00:00.000Z",
      "tags": [
        "AI Coding",
        "Cursor",
        "GitHub Copilot",
        "Developer Productivity",
        "AI Agents"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/01/20/enterprise-ai-procurement-cto-decision-logic-technology-investment/",
      "title": "Enterprise AI procurement in 2026: an evidence and contract framework",
      "summary": "A practical framework for AI procurement covering use cases, evaluations, total cost, data, security, contracting, production gates, and exit rights.",
      "html_url": "https://digidai.github.io/2026/01/20/enterprise-ai-procurement-cto-decision-logic-technology-investment/",
      "markdown_url": "https://digidai.github.io/2026/01/20/enterprise-ai-procurement-cto-decision-logic-technology-investment/index.md",
      "date_published": "2026-01-20T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "Enterprise Technology",
        "CTO Strategy",
        "Technology Procurement",
        "Digital Transformation",
        "AI Governance"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/01/18/year-of-ai-agents-concept-to-production-reality-gap/",
      "title": "AI agents in production: why reliable workflows still lag demos",
      "summary": "A sourced guide to the AI agent production gap, including task evidence, permissions, MCP security, prompt injection, evaluation, and rollout gates.",
      "html_url": "https://digidai.github.io/2026/01/18/year-of-ai-agents-concept-to-production-reality-gap/",
      "markdown_url": "https://digidai.github.io/2026/01/18/year-of-ai-agents-concept-to-production-reality-gap/index.md",
      "date_published": "2026-01-18T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "AI Agents",
        "Enterprise Technology",
        "Agentic AI",
        "Technology Analysis",
        "AI Security"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/01/16/ai-recruitment-vendor-wars-billion-dollar-battle-future-hiring/",
      "title": "The AI recruitment platform race after SAP and Workday's deals",
      "summary": "A sourced analysis of recruiting platform consolidation, AI workflow control, EU AI Act timing, and the evidence enterprise buyers should demand.",
      "html_url": "https://digidai.github.io/2026/01/16/ai-recruitment-vendor-wars-billion-dollar-battle-future-hiring/",
      "markdown_url": "https://digidai.github.io/2026/01/16/ai-recruitment-vendor-wars-billion-dollar-battle-future-hiring/index.md",
      "date_published": "2026-01-16T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "Recruitment Technology",
        "HR Tech",
        "Market Analysis",
        "Enterprise Software",
        "EU AI Act"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/01/10/great-recruiter-reckoning-ai-professional-evolution-talent-acquisition-future/",
      "title": "The recruiter role after AI: a practical talent acquisition reset",
      "summary": "A source-bound guide to how recruiting work changes with AI, which tasks remain accountable to people, and how leaders should redesign roles, skills, and metrics.",
      "html_url": "https://digidai.github.io/2026/01/10/great-recruiter-reckoning-ai-professional-evolution-talent-acquisition-future/",
      "markdown_url": "https://digidai.github.io/2026/01/10/great-recruiter-reckoning-ai-professional-evolution-talent-acquisition-future/index.md",
      "date_published": "2026-01-10T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Recruiting Careers",
        "Talent Acquisition",
        "AI Literacy",
        "Skills-Based Hiring",
        "Recruiting Operations"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/01/10/navigating-algorithm-job-seeker-survival-guide-ai-powered-hiring/",
      "title": "Algorithmic hiring: an evidence-based job seeker guide",
      "summary": "A practical guide to ATS screening, AI hiring tools, lawful accommodations, age bias, resume choices, data controls, and application records.",
      "html_url": "https://digidai.github.io/2026/01/10/navigating-algorithm-job-seeker-survival-guide-ai-powered-hiring/",
      "markdown_url": "https://digidai.github.io/2026/01/10/navigating-algorithm-job-seeker-survival-guide-ai-powered-hiring/index.md",
      "date_published": "2026-01-10T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "Job Search",
        "Career",
        "ATS",
        "Hiring",
        "Employment Rights",
        "Accessibility"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/01/08/ai-recruitment-practitioner-perspectives-multi-platform-reality-check/",
      "title": "AI recruiting in production: a practitioner evidence review",
      "summary": "A source-audited comparison of recruiting assistants, ATS platforms, frontline automation, assessments, and the implementation controls that determine whether AI helps in production.",
      "html_url": "https://digidai.github.io/2026/01/08/ai-recruitment-practitioner-perspectives-multi-platform-reality-check/",
      "markdown_url": "https://digidai.github.io/2026/01/08/ai-recruitment-practitioner-perspectives-multi-platform-reality-check/index.md",
      "date_published": "2026-01-08T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "Recruiting",
        "HR Tech",
        "Implementation",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/01/08/autonomous-ai-agents-recruitment-self-directed-hiring-systems-future/",
      "title": "Autonomous AI agents in recruitment: control, evidence, and deployment",
      "summary": "A practical guide to recruitment agents, their safe autonomy limits, system architecture, evaluation, legal duties, and production acceptance tests.",
      "html_url": "https://digidai.github.io/2026/01/08/autonomous-ai-agents-recruitment-self-directed-hiring-systems-future/",
      "markdown_url": "https://digidai.github.io/2026/01/08/autonomous-ai-agents-recruitment-self-directed-hiring-systems-future/index.md",
      "date_published": "2026-01-08T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI Agents",
        "Recruitment Technology",
        "AI Governance",
        "Talent Acquisition",
        "Hiring Compliance"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/01/07/future-ai-recruitment-operations-intelligent-hiring-organization-2026/",
      "title": "AI Recruitment Operations in 2026: A Controlled Hiring System",
      "summary": "A source-bound operating model for AI-assisted recruiting, covering workflow ownership, human approvals, measurement, accessibility, vendor evidence, and safe automation boundaries.",
      "html_url": "https://digidai.github.io/2026/01/07/future-ai-recruitment-operations-intelligent-hiring-organization-2026/",
      "markdown_url": "https://digidai.github.io/2026/01/07/future-ai-recruitment-operations-intelligent-hiring-organization-2026/index.md",
      "date_published": "2026-01-07T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI Recruitment",
        "Recruiting Operations",
        "Talent Acquisition",
        "AI Governance",
        "Future of Work"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/01/06/fortune-500-ai-recruitment-case-studies-enterprise-transformation-lessons/",
      "title": "Fortune 500 AI recruitment: what the public case studies prove",
      "summary": "A source-bound review of enterprise AI hiring cases, failure evidence, procurement controls, and the metrics buyers should require before scaling.",
      "html_url": "https://digidai.github.io/2026/01/06/fortune-500-ai-recruitment-case-studies-enterprise-transformation-lessons/",
      "markdown_url": "https://digidai.github.io/2026/01/06/fortune-500-ai-recruitment-case-studies-enterprise-transformation-lessons/index.md",
      "date_published": "2026-01-06T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Fortune 500 AI Recruitment",
        "Enterprise AI",
        "Recruitment Technology",
        "AI Governance",
        "Talent Acquisition"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/01/05/ai-recruitment-compliance-legal-risks-gdpr-eeoc-state-laws-guide/",
      "title": "AI recruitment legal risk across federal, state, and EU rules",
      "summary": "A current, source-audited map of discrimination, disability, audit, notice, privacy, and high-risk AI obligations for employers and hiring-software vendors.",
      "html_url": "https://digidai.github.io/2026/01/05/ai-recruitment-compliance-legal-risks-gdpr-eeoc-state-laws-guide/",
      "markdown_url": "https://digidai.github.io/2026/01/05/ai-recruitment-compliance-legal-risks-gdpr-eeoc-state-laws-guide/index.md",
      "date_published": "2026-01-05T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "Recruiting",
        "Compliance",
        "Employment Law",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/01/04/ai-recruitment-tool-selection-guide-buyers-decision-framework-2026/",
      "title": "AI Recruitment Software Buying Guide: An Evidence-Based Framework",
      "summary": "A practical framework for selecting AI recruitment software through workflow fit, production tests, legal controls, data governance, candidate safeguards and exit readiness.",
      "html_url": "https://digidai.github.io/2026/01/04/ai-recruitment-tool-selection-guide-buyers-decision-framework-2026/",
      "markdown_url": "https://digidai.github.io/2026/01/04/ai-recruitment-tool-selection-guide-buyers-decision-framework-2026/index.md",
      "date_published": "2026-01-04T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI Recruitment",
        "Software Procurement",
        "HR Technology",
        "AI Governance",
        "Vendor Evaluation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/01/03/skills-based-hiring-ai-talent-assessment-credential-revolution/",
      "title": "Skills-based hiring after the degree filter",
      "summary": "A source-audited analysis of degree requirements, work samples, assessments, digital credentials, AI literacy, and the evidence employers need before calling a hiring process skills based.",
      "html_url": "https://digidai.github.io/2026/01/03/skills-based-hiring-ai-talent-assessment-credential-revolution/",
      "markdown_url": "https://digidai.github.io/2026/01/03/skills-based-hiring-ai-talent-assessment-credential-revolution/index.md",
      "date_published": "2026-01-03T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "Recruiting",
        "Skills-Based Hiring",
        "Assessments",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2026/01/01/ai-recruitment-tco-complete-guide-hidden-costs-decision-framework/",
      "title": "AI recruiting TCO: the costs beyond the license fee",
      "summary": "A source-audited decision framework for estimating implementation, integration, governance, internal labor, usage, change, and exit costs before buying AI recruiting software.",
      "html_url": "https://digidai.github.io/2026/01/01/ai-recruitment-tco-complete-guide-hidden-costs-decision-framework/",
      "markdown_url": "https://digidai.github.io/2026/01/01/ai-recruitment-tco-complete-guide-hidden-costs-decision-framework/index.md",
      "date_published": "2026-01-01T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "Recruiting",
        "HR Tech",
        "Procurement",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/12/31/ai-doom-loop-how-automation-broke-job-search-2025/",
      "title": "The AI job-search loop: why application volume and screening feed each other",
      "summary": "A source-bound analysis of the job-search automation loop, separating evidence from anecdotes and giving employers and candidates practical ways to improve signal and trust.",
      "html_url": "https://digidai.github.io/2025/12/31/ai-doom-loop-how-automation-broke-job-search-2025/",
      "markdown_url": "https://digidai.github.io/2025/12/31/ai-doom-loop-how-automation-broke-job-search-2025/index.md",
      "date_published": "2025-12-31T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI Job Search",
        "Candidate Experience",
        "Recruiting Automation",
        "Hiring Systems",
        "Job Scams"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/12/31/ai-recruiting-2025-year-review-what-comes-next/",
      "title": "AI recruiting in 2025: what changed and what did not",
      "summary": "A sourced 2025 review of recruiting AI adoption, workflow change, skills-based hiring, measurement, candidate risk, regulation, and the priorities that followed.",
      "html_url": "https://digidai.github.io/2025/12/31/ai-recruiting-2025-year-review-what-comes-next/",
      "markdown_url": "https://digidai.github.io/2025/12/31/ai-recruiting-2025-year-review-what-comes-next/index.md",
      "date_published": "2025-12-31T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI Recruiting",
        "2025 Review",
        "Talent Acquisition",
        "Hiring Technology",
        "AI Governance"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/12/31/ai-recruiting-roi-complete-guide-measuring-hr-technology-investment/",
      "title": "AI recruiting ROI: an evidence-led measurement guide",
      "summary": "A practical framework for measuring AI recruiting costs, benefits, quality, risk, adoption, and payback without relying on vendor averages or invented savings.",
      "html_url": "https://digidai.github.io/2025/12/31/ai-recruiting-roi-complete-guide-measuring-hr-technology-investment/",
      "markdown_url": "https://digidai.github.io/2025/12/31/ai-recruiting-roi-complete-guide-measuring-hr-technology-investment/index.md",
      "date_published": "2025-12-31T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Recruiting ROI",
        "HR Technology",
        "AI Recruiting",
        "Talent Analytics",
        "AI Governance"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/12/29/ai-hiring-bias-algorithmic-discrimination-fairness-2025/",
      "title": "AI Hiring Bias: What the Evidence Shows and How to Test It",
      "summary": "A source-based guide to algorithmic discrimination in hiring, covering controlled research, enforcement, litigation, regulation and a practical audit protocol.",
      "html_url": "https://digidai.github.io/2025/12/29/ai-hiring-bias-algorithmic-discrimination-fairness-2025/",
      "markdown_url": "https://digidai.github.io/2025/12/29/ai-hiring-bias-algorithmic-discrimination-fairness-2025/index.md",
      "date_published": "2025-12-29T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI Hiring Bias",
        "Algorithmic Discrimination",
        "AI Governance",
        "Employment Law",
        "HR Technology"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/12/27/ai-workforce-transformation-great-reshuffling-labor-2025/",
      "title": "AI and Work in 2026: What Is Actually Being Reshuffled",
      "summary": "A source-based review of AI exposure, early employment evidence, employer forecasts and the controls organizations need when work shifts from people to models and agents.",
      "html_url": "https://digidai.github.io/2025/12/27/ai-workforce-transformation-great-reshuffling-labor-2025/",
      "markdown_url": "https://digidai.github.io/2025/12/27/ai-workforce-transformation-great-reshuffling-labor-2025/index.md",
      "date_published": "2025-12-27T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI Workforce",
        "Future of Work",
        "Labor Market",
        "Reskilling",
        "AI Agents",
        "Workforce Planning"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/12/27/future-global-talent-mobility-borderless-workforce-2025/",
      "title": "Global Talent Mobility in 2026: Remote Does Not Mean Borderless",
      "summary": "A source-based operating guide to cross-border remote work, migration, tax presence, social security, employment models and agent-ready mobility records.",
      "html_url": "https://digidai.github.io/2025/12/27/future-global-talent-mobility-borderless-workforce-2025/",
      "markdown_url": "https://digidai.github.io/2025/12/27/future-global-talent-mobility-borderless-workforce-2025/index.md",
      "date_published": "2025-12-27T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Global Talent Mobility",
        "Remote Work",
        "Cross-Border Employment",
        "Immigration",
        "Employer of Record",
        "Workforce"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/12/26/hr-technology-roadmap-2026-2030-ai-talent-acquisition-future/",
      "title": "HR technology roadmap 2026-2030: an evidence-led talent acquisition plan",
      "summary": "A practical HR technology roadmap for data, skills, AI hiring, governance, integrations, measurement, procurement, and workforce readiness through 2030.",
      "html_url": "https://digidai.github.io/2025/12/26/hr-technology-roadmap-2026-2030-ai-talent-acquisition-future/",
      "markdown_url": "https://digidai.github.io/2025/12/26/hr-technology-roadmap-2026-2030-ai-talent-acquisition-future/index.md",
      "date_published": "2025-12-26T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "HR Technology",
        "Talent Acquisition",
        "AI Governance",
        "Skills",
        "Recruiting Operations",
        "Workforce Planning"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/12/25/ai-recruitment-implementation-guide-by-company-size-2025/",
      "title": "AI Recruitment Implementation: A Pilot Plan by Company Size",
      "summary": "Choose a bounded hiring workflow, assign a human owner and measure the result. A source-linked implementation guide with a reusable pilot worksheet, not a claimed interview study.",
      "html_url": "https://digidai.github.io/2025/12/25/ai-recruitment-implementation-guide-by-company-size-2025/",
      "markdown_url": "https://digidai.github.io/2025/12/25/ai-recruitment-implementation-guide-by-company-size-2025/index.md",
      "date_published": "2025-12-25T00:00:00.000Z",
      "date_modified": "2026-09-09T00:00:00.000Z",
      "tags": [
        "AI Recruitment",
        "Implementation",
        "Hiring",
        "Company Size",
        "Enterprise AI"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/12/24/ai-recruiting-privacy-compliance-global-regulation-2025/",
      "title": "AI Recruiting Compliance in 2026: A Control Map",
      "summary": "A current, source-based guide to GDPR, the EU AI Act, US employment law and state AI rules, organized around the evidence an employer needs before automated hiring tools go live.",
      "html_url": "https://digidai.github.io/2025/12/24/ai-recruiting-privacy-compliance-global-regulation-2025/",
      "markdown_url": "https://digidai.github.io/2025/12/24/ai-recruiting-privacy-compliance-global-regulation-2025/index.md",
      "date_published": "2025-12-24T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI Recruiting Compliance",
        "GDPR",
        "EU AI Act",
        "Bias Audit",
        "Employment Law"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/12/23/asia-pacific-hr-tech-revolution-2025/",
      "title": "Asia-Pacific HR technology: a country-by-country buyer guide",
      "summary": "A sourced guide to HR technology in China, India, Singapore, Japan, Korea, and Australia, with vendor, privacy, localization, and rollout checks.",
      "html_url": "https://digidai.github.io/2025/12/23/asia-pacific-hr-tech-revolution-2025/",
      "markdown_url": "https://digidai.github.io/2025/12/23/asia-pacific-hr-tech-revolution-2025/index.md",
      "date_published": "2025-12-23T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Asia Pacific",
        "HR Technology",
        "Recruitment",
        "AI Governance",
        "Data Privacy",
        "Enterprise Software"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/12/23/autonomous-ai-agents-recruitment-future-2025/",
      "title": "When recruiting software starts acting: what autonomous hiring agents can and cannot do",
      "summary": "A source-audited review of recruiting agents, their real product capabilities, reported customer outcomes, governance risks, and the work that still requires human judgment.",
      "html_url": "https://digidai.github.io/2025/12/23/autonomous-ai-agents-recruitment-future-2025/",
      "markdown_url": "https://digidai.github.io/2025/12/23/autonomous-ai-agents-recruitment-future-2025/index.md",
      "date_published": "2025-12-23T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "autonomous ai agents recruitment",
        "ai recruiting agents",
        "agentic ai hr",
        "linkedin hiring assistant",
        "paradox olivia ai",
        "ai recruiter replacement",
        "autonomous sourcing",
        "ai interview scheduling",
        "generative ai recruitment",
        "ai agents vs chatbots recruiting"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/12/21/asia-pacific-hr-tech-deep-dive-2025/",
      "title": "Asia-Pacific HR Tech: A Country-by-Country Operating Map",
      "summary": "A source-based guide to recruiting platforms, labor-market constraints, privacy rules and AI governance across China, India, Singapore, Japan and Australia.",
      "html_url": "https://digidai.github.io/2025/12/21/asia-pacific-hr-tech-deep-dive-2025/",
      "markdown_url": "https://digidai.github.io/2025/12/21/asia-pacific-hr-tech-deep-dive-2025/index.md",
      "date_published": "2025-12-21T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Asia-Pacific HR Tech",
        "Recruiting",
        "HR Software",
        "Privacy",
        "AI Governance",
        "Labor Markets"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/12/20/fortune-500-ai-recruitment-case-studies-2025/",
      "title": "Enterprise AI Recruiting: Five Public Cases and Their Evidence",
      "summary": "A source-based review of Amazon, Unilever, iTutorGroup, Workday and IBM recruiting or talent systems, separating documented outcomes, allegations and vendor claims.",
      "html_url": "https://digidai.github.io/2025/12/20/fortune-500-ai-recruitment-case-studies-2025/",
      "markdown_url": "https://digidai.github.io/2025/12/20/fortune-500-ai-recruitment-case-studies-2025/index.md",
      "date_published": "2025-12-20T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Enterprise Recruiting",
        "AI Hiring",
        "Case Studies",
        "Hiring Bias",
        "HR Technology"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/12/19/european-hr-tech-ecosystem-analysis-2025/",
      "title": "European HR Tech: One Region, Many Operating Systems",
      "summary": "A source-based map of European HR technology across local payroll, cross-border work, GDPR, the EU AI Act and agent deployment, with vendor claims separated from operating evidence.",
      "html_url": "https://digidai.github.io/2025/12/19/european-hr-tech-ecosystem-analysis-2025/",
      "markdown_url": "https://digidai.github.io/2025/12/19/european-hr-tech-ecosystem-analysis-2025/index.md",
      "date_published": "2025-12-19T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "European HR Tech",
        "HR Software",
        "GDPR",
        "EU AI Act",
        "Payroll",
        "AI Agents"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/12/18/recruitment-efficiency-benchmarks-industry-role-2025/",
      "title": "Recruitment efficiency benchmarks: how to compare hiring performance",
      "summary": "A source-bound guide to time to fill, cost per hire, funnel conversion, quality of hire, and fair hiring metrics, with clear limits on every external benchmark.",
      "html_url": "https://digidai.github.io/2025/12/18/recruitment-efficiency-benchmarks-industry-role-2025/",
      "markdown_url": "https://digidai.github.io/2025/12/18/recruitment-efficiency-benchmarks-industry-role-2025/index.md",
      "date_published": "2025-12-18T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "recruitment benchmarks",
        "time to fill",
        "cost per hire",
        "quality of hire",
        "recruiting analytics"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/12/17/ai-recruitment-data-privacy-compliance-guide-2025/",
      "title": "AI hiring privacy and compliance: a source-audited operating guide",
      "summary": "A practical map of the data, notices, audits, retention rules, human-review controls, and vendor evidence that employers need when AI participates in recruiting decisions.",
      "html_url": "https://digidai.github.io/2025/12/17/ai-recruitment-data-privacy-compliance-guide-2025/",
      "markdown_url": "https://digidai.github.io/2025/12/17/ai-recruitment-data-privacy-compliance-guide-2025/index.md",
      "date_published": "2025-12-17T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "Recruiting",
        "Privacy",
        "Compliance",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/12/17/fortune-500-ai-recruitment-case-studies-lessons/",
      "title": "What enterprise AI recruiting case studies actually prove",
      "summary": "A source-audited review of enterprise hiring automation at Unilever, Amazon, iTutorGroup, Workday customers, IBM, and LinkedIn, with clear limits on vendor-reported results.",
      "html_url": "https://digidai.github.io/2025/12/17/fortune-500-ai-recruitment-case-studies-lessons/",
      "markdown_url": "https://digidai.github.io/2025/12/17/fortune-500-ai-recruitment-case-studies-lessons/index.md",
      "date_published": "2025-12-17T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI",
        "Recruiting",
        "Enterprise",
        "Case Studies",
        "Deep Investigation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/12/16/hr-technology-true-cost-analysis-2025/",
      "title": "The True Cost of HR Technology: A Sourceable TCO Model",
      "summary": "A practical total-cost model for HR and recruiting software, including implementation, integrations, internal labor, AI usage, assurance, incidents and exit.",
      "html_url": "https://digidai.github.io/2025/12/16/hr-technology-true-cost-analysis-2025/",
      "markdown_url": "https://digidai.github.io/2025/12/16/hr-technology-true-cost-analysis-2025/index.md",
      "date_published": "2025-12-16T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "HR Technology Cost",
        "Total Cost of Ownership",
        "HR Software",
        "Recruiting Technology",
        "AI Cost",
        "Procurement"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/12/15/ai-recruitment-data-privacy-compliance-comprehensive-guide/",
      "title": "AI Hiring Compliance: A 2026 Control Map for Employers",
      "summary": "A source-bound guide to US employment law, NYC Local Law 144, the EU AI Act, GDPR, Colorado's 2027 rules, and the operating controls employers need around AI-assisted hiring.",
      "html_url": "https://digidai.github.io/2025/12/15/ai-recruitment-data-privacy-compliance-comprehensive-guide/",
      "markdown_url": "https://digidai.github.io/2025/12/15/ai-recruitment-data-privacy-compliance-comprehensive-guide/index.md",
      "date_published": "2025-12-15T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI Hiring",
        "Employment Law",
        "Data Privacy",
        "AI Governance",
        "Recruiting"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/12/15/ai-recruitment-implementation-guide-enterprise-smb/",
      "title": "AI Recruiting Implementation: A Gated Guide for Enterprises and SMBs",
      "summary": "A source-based implementation guide for choosing, testing and operating recruiting AI, with separate enterprise and SMB paths, evidence gates and agent controls.",
      "html_url": "https://digidai.github.io/2025/12/15/ai-recruitment-implementation-guide-enterprise-smb/",
      "markdown_url": "https://digidai.github.io/2025/12/15/ai-recruitment-implementation-guide-enterprise-smb/index.md",
      "date_published": "2025-12-15T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI Recruiting",
        "Implementation",
        "Talent Acquisition",
        "HR Technology",
        "SMB",
        "Enterprise AI"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/12/13/openai-jobs-platform-recruitment-industry-disruption/",
      "title": "OpenAI Jobs Platform in 2026: Announcement, Current Status and Hiring Implications",
      "summary": "A source-checked review of what OpenAI announced, which Academy and credential products are live, what remains upcoming, and how a jobs platform could change recruiting.",
      "html_url": "https://digidai.github.io/2025/12/13/openai-jobs-platform-recruitment-industry-disruption/",
      "markdown_url": "https://digidai.github.io/2025/12/13/openai-jobs-platform-recruitment-industry-disruption/index.md",
      "date_published": "2025-12-13T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "OpenAI Jobs Platform",
        "OpenAI Academy",
        "AI Skills",
        "Recruiting Platforms",
        "Talent Acquisition",
        "Credentials"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/12/04/hr-ai-evolution-comprehensive-analysis/",
      "title": "The Evolution of Recruiting AI: A 30-Year Evidence Timeline",
      "summary": "A documented timeline of recruiting technology from ATS and professional networks to predictive matching and agents, with a buyer's test for what each era really changed.",
      "html_url": "https://digidai.github.io/2025/12/04/hr-ai-evolution-comprehensive-analysis/",
      "markdown_url": "https://digidai.github.io/2025/12/04/hr-ai-evolution-comprehensive-analysis/index.md",
      "date_published": "2025-12-04T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "HR AI",
        "Recruiting Technology",
        "Applicant Tracking",
        "Talent Acquisition",
        "AI Agents",
        "HR Software"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/12/04/real-story-hr-tech-resume-databases-autonomous-agents/",
      "title": "HR Tech from Resume Databases to Agents: What Actually Changed",
      "summary": "A source-based account of recruiting technology's shift from systems of record and job networks to matching models and agents, with an architecture for accountable action.",
      "html_url": "https://digidai.github.io/2025/12/04/real-story-hr-tech-resume-databases-autonomous-agents/",
      "markdown_url": "https://digidai.github.io/2025/12/04/real-story-hr-tech-resume-databases-autonomous-agents/index.md",
      "date_published": "2025-12-04T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "HR Technology",
        "Recruiting Technology",
        "ATS",
        "AI Recruiting",
        "AI Agents",
        "Talent Acquisition"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/12/03/anthropic-350-billion-valuation-ai-bubble-fears-deep-analysis/",
      "title": "Anthropic valuation analysis: what the private-market numbers prove",
      "summary": "A source-bound analysis of Anthropic's 2026 funding, revenue run-rate disclosures, infrastructure commitments, valuation risks, and safety governance.",
      "html_url": "https://digidai.github.io/2025/12/03/anthropic-350-billion-valuation-ai-bubble-fears-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/12/03/anthropic-350-billion-valuation-ai-bubble-fears-deep-analysis/index.md",
      "date_published": "2025-12-03T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Anthropic",
        "Claude",
        "AI Valuation",
        "Frontier AI",
        "Venture Capital"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/12/03/best-job-boards-usa-2025-data-driven-guide/",
      "title": "Best US Job Boards: Choose by Role, Hiring Motion, and Evidence",
      "summary": "A current, source-bound guide to Indeed, LinkedIn, ZipRecruiter, Dice, Wellfound, Handshake, and USAJOBS, with a practical test for choosing channels instead of trusting universal rankings.",
      "html_url": "https://digidai.github.io/2025/12/03/best-job-boards-usa-2025-data-driven-guide/",
      "markdown_url": "https://digidai.github.io/2025/12/03/best-job-boards-usa-2025-data-driven-guide/index.md",
      "date_published": "2025-12-03T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Job Boards",
        "Recruiting Platforms",
        "Hiring",
        "Talent Acquisition",
        "Recruiting Analytics"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/12/02/remote-job-sites-comprehensive-deep-analysis-2025/",
      "title": "Remote job sites: how to choose, verify, and search them effectively",
      "summary": "A source-bound comparison of general, remote-only, startup, and public-sector job sites, plus a practical workflow for location checks and scam prevention.",
      "html_url": "https://digidai.github.io/2025/12/02/remote-job-sites-comprehensive-deep-analysis-2025/",
      "markdown_url": "https://digidai.github.io/2025/12/02/remote-job-sites-comprehensive-deep-analysis-2025/index.md",
      "date_published": "2025-12-02T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Remote Job Sites",
        "Remote Work",
        "Job Search",
        "Recruitment Platforms",
        "Job Scam Prevention"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/28/daniel-gross-ai-pioneer-fund-jerusalem-to-meta-superintelligence-deep-analysis/",
      "title": "Daniel Gross: From Product Builder to AI Investor and Meta",
      "summary": "A sourced analysis of Daniel Gross's path through Cue, Apple, Y Combinator, Pioneer, Safe Superintelligence, and Meta's AI organization.",
      "html_url": "https://digidai.github.io/2025/11/28/daniel-gross-ai-pioneer-fund-jerusalem-to-meta-superintelligence-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/28/daniel-gross-ai-pioneer-fund-jerusalem-to-meta-superintelligence-deep-analysis/index.md",
      "date_published": "2025-11-28T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Daniel Gross",
        "Pioneer",
        "Y Combinator",
        "Safe Superintelligence",
        "Meta",
        "AI Investing",
        "AI Research"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/28/greg-brockman-openai-cofounder-president-builder-chief-deep-analysis/",
      "title": "Greg Brockman at OpenAI: technical leadership, infrastructure, and governance",
      "summary": "A source-bound profile of OpenAI President and co-founder Greg Brockman, separating documented roles and team credits from unsupported builder myths.",
      "html_url": "https://digidai.github.io/2025/11/28/greg-brockman-openai-cofounder-president-builder-chief-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/28/greg-brockman-openai-cofounder-president-builder-chief-deep-analysis/index.md",
      "date_published": "2025-11-28T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Greg Brockman",
        "OpenAI",
        "AI Infrastructure",
        "Codex",
        "AI Governance"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/28/noam-shazeer-character-ai-google-transformer-deep-analysis/",
      "title": "Noam Shazeer: Transformers, Character.AI, and the Talent Market",
      "summary": "A sourced analysis of Noam Shazeer's transformer research, Character.AI, Google licensing deal, and reported 2026 move to OpenAI.",
      "html_url": "https://digidai.github.io/2025/11/28/noam-shazeer-character-ai-google-transformer-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/28/noam-shazeer-character-ai-google-transformer-deep-analysis/index.md",
      "date_published": "2025-11-28T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Noam Shazeer",
        "Transformers",
        "Character.AI",
        "Google DeepMind",
        "OpenAI",
        "AI Research",
        "AI Talent"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/27/brian-singerman-founders-fund-ai-biotech-investment-deep-analysis/",
      "title": "Brian Singerman's Documented Record at Founders Fund",
      "summary": "A sourced profile of Brian Singerman's investing role, biotech bets, and 2024 Founders Fund transition.",
      "html_url": "https://digidai.github.io/2025/11/27/brian-singerman-founders-fund-ai-biotech-investment-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/27/brian-singerman-founders-fund-ai-biotech-investment-deep-analysis/index.md",
      "date_published": "2025-11-27T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Brian Singerman",
        "Founders Fund",
        "Venture Capital",
        "Biotechnology",
        "Affirm",
        "Stemcentrx",
        "Portfolio Strategy"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/27/dan-hendrycks-center-ai-safety-executive-director-deep-analysis/",
      "title": "Dan Hendrycks: Benchmarks, Catastrophic Risk, and the Center for AI Safety",
      "summary": "An evidence-based analysis of Dan Hendrycks's research, the Center for AI Safety, and how to evaluate catastrophic-risk claims without treating forecasts as facts.",
      "html_url": "https://digidai.github.io/2025/11/27/dan-hendrycks-center-ai-safety-executive-director-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/27/dan-hendrycks-center-ai-safety-executive-director-deep-analysis/index.md",
      "date_published": "2025-11-27T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "dan hendrycks",
        "center for ai safety",
        "cais",
        "ai safety",
        "existential risk",
        "gelu",
        "mmlu",
        "xai",
        "elon musk",
        "scale ai"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/27/david-munichiello-gv-google-ventures-ai-investment-strategy-deep-analysis/",
      "title": "Dave Munichiello and GV: An AI Portfolio Built Across the Stack",
      "summary": "A source-bound analysis of GV managing partner Dave Munichiello, his developer-platform and AI-infrastructure investments, and what public evidence does and does not reveal about the strategy.",
      "html_url": "https://digidai.github.io/2025/11/27/david-munichiello-gv-google-ventures-ai-investment-strategy-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/27/david-munichiello-gv-google-ventures-ai-investment-strategy-deep-analysis/index.md",
      "date_published": "2025-11-27T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Dave Munichiello",
        "GV",
        "Venture Capital",
        "AI Infrastructure",
        "Developer Tools"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/27/max-tegmark-mit-ai-safety-existential-risk-deep-analysis/",
      "title": "Max Tegmark: AI-Risk Advocacy and Verifiable Safety",
      "summary": "A source-based analysis of Max Tegmark's AI-safety advocacy, the 2023 pause letter, guaranteed-safe-AI research, and the limits of existential-risk claims.",
      "html_url": "https://digidai.github.io/2025/11/27/max-tegmark-mit-ai-safety-existential-risk-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/27/max-tegmark-mit-ai-safety-existential-risk-deep-analysis/index.md",
      "date_published": "2025-11-27T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "max tegmark",
        "ai safety",
        "existential risk",
        "future of life institute",
        "guaranteed safe ai",
        "provable safety",
        "ai governance"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/27/saam-motamedi-greylock-youngest-partner-enterprise-ai-pricing-revolution-deep-analysis/",
      "title": "Saam Motamedi: Greylock's Enterprise AI Thesis",
      "summary": "A source-based analysis of Saam Motamedi's career, disclosed Greylock portfolio, and public views on enterprise AI infrastructure, applications, and pricing.",
      "html_url": "https://digidai.github.io/2025/11/27/saam-motamedi-greylock-youngest-partner-enterprise-ai-pricing-revolution-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/27/saam-motamedi-greylock-youngest-partner-enterprise-ai-pricing-revolution-deep-analysis/index.md",
      "date_published": "2025-11-27T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "saam motamedi",
        "greylock",
        "enterprise ai",
        "ai infrastructure",
        "software pricing",
        "venture capital",
        "relateiq"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/27/samir-kaul-khosla-ventures-founding-gp-openai-bet-deep-analysis/",
      "title": "Samir Kaul and Khosla Ventures' Deep-Tech Portfolio Strategy",
      "summary": "A source-bound analysis of Samir Kaul's role at Khosla Ventures, cross-sector investing, opportunity funds, portfolio construction, and the limits of OpenAI return claims.",
      "html_url": "https://digidai.github.io/2025/11/27/samir-kaul-khosla-ventures-founding-gp-openai-bet-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/27/samir-kaul-khosla-ventures-founding-gp-openai-bet-deep-analysis/index.md",
      "date_published": "2025-11-27T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI Investors",
        "Venture Capital",
        "Deep Tech",
        "Portfolio Strategy"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/27/stuart-russell-uc-berkeley-ai-safety-textbook-warnings-deep-analysis/",
      "title": "Stuart Russell: From Rational Agents to Human-Compatible AI",
      "summary": "A source-bound profile of UC Berkeley computer scientist Stuart Russell, his AI textbook, his technical case against fixed objectives, and the policy limits of his safety argument.",
      "html_url": "https://digidai.github.io/2025/11/27/stuart-russell-uc-berkeley-ai-safety-textbook-warnings-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/27/stuart-russell-uc-berkeley-ai-safety-textbook-warnings-deep-analysis/index.md",
      "date_published": "2025-11-27T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Stuart Russell",
        "UC Berkeley",
        "AI Safety",
        "Human-Compatible AI",
        "AI Research"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/27/trae-stephens-founders-fund-anduril-defense-tech-billionaire-deep-analysis/",
      "title": "Trae Stephens: Anduril and Founders Fund",
      "summary": "A source-based analysis of Trae Stephens' dual roles, Anduril's public financing and procurement record, and the governance questions around defense autonomy.",
      "html_url": "https://digidai.github.io/2025/11/27/trae-stephens-founders-fund-anduril-defense-tech-billionaire-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/27/trae-stephens-founders-fund-anduril-defense-tech-billionaire-deep-analysis/index.md",
      "date_published": "2025-11-27T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "trae stephens",
        "founders fund",
        "anduril industries",
        "defense technology",
        "autonomous systems",
        "military procurement",
        "palantir technologies"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/27/yann-lecun-meta-ai-godfather-world-models-departure-deep-analysis/",
      "title": "Yann LeCun After Meta: AMI Labs and the World-Model Bet",
      "summary": "An evidence-based analysis of Yann LeCun's move from Meta to AMI Labs, the JEPA world-model thesis, V-JEPA 2 evidence, and what the research has not yet proved.",
      "html_url": "https://digidai.github.io/2025/11/27/yann-lecun-meta-ai-godfather-world-models-departure-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/27/yann-lecun-meta-ai-godfather-world-models-departure-deep-analysis/index.md",
      "date_published": "2025-11-27T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI Leaders",
        "AI Research",
        "World Models",
        "Robotics"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/25/eric-vishria-benchmark-ai-investor-zero-100m-arr-deep-analysis/",
      "title": "Eric Vishria at Benchmark: a source-bound operator and board-investor profile",
      "summary": "A documented analysis of Eric Vishria's Benchmark role, operating background, public-company board work, and AI infrastructure exposure without unsupported return or growth claims.",
      "html_url": "https://digidai.github.io/2025/11/25/eric-vishria-benchmark-ai-investor-zero-100m-arr-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/25/eric-vishria-benchmark-ai-investor-zero-100m-arr-deep-analysis/index.md",
      "date_published": "2025-11-25T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Eric Vishria",
        "Benchmark",
        "Cerebras",
        "Confluent",
        "AI Infrastructure"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/25/winston-weinberg-harvey-ai-legal-tech-revolution-deep-analysis/",
      "title": "Winston Weinberg: Harvey AI",
      "summary": "A source-based profile of Harvey CEO Winston Weinberg, the company's legal-workflow strategy, its disclosed financing, and the professional controls adoption requires.",
      "html_url": "https://digidai.github.io/2025/11/25/winston-weinberg-harvey-ai-legal-tech-revolution-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/25/winston-weinberg-harvey-ai-legal-tech-revolution-deep-analysis/index.md",
      "date_published": "2025-11-25T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "winston weinberg",
        "harvey ai",
        "legal technology",
        "legal workflow",
        "generative ai",
        "law firms",
        "lawyer oversight"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/24/anjney-midha-a16z-gpu-kingmaker-oxygen-amp-deep-analysis/",
      "title": "Anjney Midha: from a16z Oxygen to AMP's compute-and-capital strategy",
      "summary": "A source-bound analysis of Anjney Midha's a16z role, the Oxygen compute program, his move to AMP, and the evidence limits around fund and infrastructure claims.",
      "html_url": "https://digidai.github.io/2025/11/24/anjney-midha-a16z-gpu-kingmaker-oxygen-amp-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/24/anjney-midha-a16z-gpu-kingmaker-oxygen-amp-deep-analysis/index.md",
      "date_published": "2025-11-24T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Anjney Midha",
        "AMP PBC",
        "Andreessen Horowitz",
        "AI Infrastructure",
        "Venture Capital"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/24/ben-horowitz-andreessen-horowitz-hard-thing-ai-empire-deep-analysis/",
      "title": "Ben Horowitz: Operating Experience, a16z, and the AI Fund Strategy",
      "summary": "An evidence-based analysis of Ben Horowitz's Opsware record, a16z's fund model, and how operating advice should be tested in AI companies.",
      "html_url": "https://digidai.github.io/2025/11/24/ben-horowitz-andreessen-horowitz-hard-thing-ai-empire-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/24/ben-horowitz-andreessen-horowitz-hard-thing-ai-empire-deep-analysis/index.md",
      "date_published": "2025-11-24T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "ben horowitz",
        "andreessen horowitz",
        "a16z",
        "opsware",
        "loudcloud",
        "marc andreessen",
        "ai investments",
        "openai",
        "anthropic",
        "mistral ai"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/24/fei-fei-li-stanford-hai-imagenet-godmother-ai-deep-analysis/",
      "title": "Fei-Fei Li: From ImageNet to Spatial Intelligence",
      "summary": "A source-based profile of Fei-Fei Li's ImageNet work, Stanford HAI role, policy record and World Labs strategy, with research facts separated from company claims and speculation.",
      "html_url": "https://digidai.github.io/2025/11/24/fei-fei-li-stanford-hai-imagenet-godmother-ai-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/24/fei-fei-li-stanford-hai-imagenet-godmother-ai-deep-analysis/index.md",
      "date_published": "2025-11-24T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Fei-Fei Li",
        "ImageNet",
        "Stanford HAI",
        "World Labs",
        "Spatial Intelligence"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/24/helen-toner-openai-board-ai-governance-whistleblower-deep-analysis/",
      "title": "Helen Toner and OpenAI: A Documented Case Study in Nonprofit AI Governance",
      "summary": "A source-bound account of Helen Toner's OpenAI board role, the November 2023 leadership crisis, conflicting public explanations, and practical governance lessons.",
      "html_url": "https://digidai.github.io/2025/11/24/helen-toner-openai-board-ai-governance-whistleblower-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/24/helen-toner-openai-board-ai-governance-whistleblower-deep-analysis/index.md",
      "date_published": "2025-11-24T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "helen toner",
        "openai board",
        "ai governance",
        "nonprofit governance",
        "ai safety",
        "cset"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/24/jan-leike-anthropic-superalignment-openai-safety-exodus-deep-analysis/",
      "title": "Jan Leike: Superalignment, Scalable Oversight, and Anthropic",
      "summary": "A source-based analysis of Jan Leike's move from OpenAI to Anthropic, his scalable-oversight research, and what personnel changes can and cannot prove about AI safety.",
      "html_url": "https://digidai.github.io/2025/11/24/jan-leike-anthropic-superalignment-openai-safety-exodus-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/24/jan-leike-anthropic-superalignment-openai-safety-exodus-deep-analysis/index.md",
      "date_published": "2025-11-24T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "jan leike",
        "anthropic",
        "openai",
        "superalignment",
        "scalable oversight",
        "reward modeling",
        "ai safety"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/24/konstantine-buhler-sequoia-capital-agent-economy-trillion-dollar-bet-deep-analysis/",
      "title": "Konstantine Buhler and Sequoia's Agent Economy Thesis",
      "summary": "A sourced analysis of Sequoia partner Konstantine Buhler's agent economy thesis, its operating assumptions, and the evidence buyers should demand.",
      "html_url": "https://digidai.github.io/2025/11/24/konstantine-buhler-sequoia-capital-agent-economy-trillion-dollar-bet-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/24/konstantine-buhler-sequoia-capital-agent-economy-trillion-dollar-bet-deep-analysis/index.md",
      "date_published": "2025-11-24T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Konstantine Buhler",
        "Sequoia Capital",
        "AI Agents",
        "Agent Economy",
        "Enterprise AI",
        "AI Infrastructure",
        "Venture Capital"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/24/reid-hoffman-greylock-linkedin-network-effects-master-deep-analysis/",
      "title": "Reid Hoffman: Network Effects, AI Investments, and Governance Tradeoffs",
      "summary": "An evidence-based analysis of Reid Hoffman's LinkedIn network thesis, Inflection AI transaction, Manas AI, Microsoft board role, and the governance questions around overlapping positions.",
      "html_url": "https://digidai.github.io/2025/11/24/reid-hoffman-greylock-linkedin-network-effects-master-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/24/reid-hoffman-greylock-linkedin-network-effects-master-deep-analysis/index.md",
      "date_published": "2025-11-24T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI Investors",
        "Network Effects",
        "AI Governance",
        "Technology Strategy"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/24/sonya-huang-sequoia-capital-ai-application-layer-bet-deep-analysis/",
      "title": "Sonya Huang and Sequoia's AI Application Thesis",
      "summary": "A sourced analysis of Sonya Huang's AI application thesis, model dependence, product evidence, and the choices founders and buyers should test.",
      "html_url": "https://digidai.github.io/2025/11/24/sonya-huang-sequoia-capital-ai-application-layer-bet-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/24/sonya-huang-sequoia-capital-ai-application-layer-bet-deep-analysis/index.md",
      "date_published": "2025-11-24T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Sonya Huang",
        "Sequoia Capital",
        "AI Applications",
        "AI Agents",
        "Foundation Models",
        "Venture Capital",
        "Enterprise AI"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/24/yoshua-bengio-turing-award-ai-safety-deep-learning-godfather-lawzero-deep-analysis/",
      "title": "Yoshua Bengio: Deep Learning, AI Safety, and LawZero's Scientist AI",
      "summary": "An evidence-based analysis of Yoshua Bengio's deep-learning record, international AI safety work, and LawZero's proposed non-agentic Scientist AI.",
      "html_url": "https://digidai.github.io/2025/11/24/yoshua-bengio-turing-award-ai-safety-deep-learning-godfather-lawzero-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/24/yoshua-bengio-turing-award-ai-safety-deep-learning-godfather-lawzero-deep-analysis/index.md",
      "date_published": "2025-11-24T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "yoshua bengio",
        "turing award",
        "ai safety",
        "deep learning",
        "neural networks",
        "montreal ai",
        "lawzero",
        "artificial intelligence research",
        "silicon valley"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/23/alfred-lin-sequoia-capital-co-steward-operational-vc-deep-analysis/",
      "title": "Alfred Lin: Sequoia's Operator-Investor and Co-Steward",
      "summary": "An evidence-based analysis of Alfred Lin's operating record, Sequoia portfolio work, and the practical meaning of the firm's co-steward role.",
      "html_url": "https://digidai.github.io/2025/11/23/alfred-lin-sequoia-capital-co-steward-operational-vc-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/23/alfred-lin-sequoia-capital-co-steward-operational-vc-deep-analysis/index.md",
      "date_published": "2025-11-23T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "alfred lin",
        "sequoia capital",
        "zappos",
        "airbnb",
        "doordash",
        "openai",
        "venture capital",
        "forbes midas list",
        "operational vc",
        "tony hsieh"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/23/anthony-goldbloom-sumble-kaggle-founder-ai-sales-intelligence-deep-analysis/",
      "title": "Anthony Goldbloom: From Kaggle to Sumble's GTM Data Layer",
      "summary": "A sourced profile of Anthony Goldbloom, Sumble's account intelligence model, its agent tools, and the evidence buyers should demand.",
      "html_url": "https://digidai.github.io/2025/11/23/anthony-goldbloom-sumble-kaggle-founder-ai-sales-intelligence-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/23/anthony-goldbloom-sumble-kaggle-founder-ai-sales-intelligence-deep-analysis/index.md",
      "date_published": "2025-11-23T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Anthony Goldbloom",
        "Sumble",
        "Kaggle",
        "GTM Data",
        "Sales Intelligence",
        "AI Agents"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/23/arvind-jain-glean-enterprise-search-7-billion-deep-analysis/",
      "title": "Arvind Jain: Glean",
      "summary": "A source-based analysis of Arvind Jain's career, Glean's permission-aware enterprise search model, its disclosed financing, and the evidence buyers should demand.",
      "html_url": "https://digidai.github.io/2025/11/23/arvind-jain-glean-enterprise-search-7-billion-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/23/arvind-jain-glean-enterprise-search-7-billion-deep-analysis/index.md",
      "date_published": "2025-11-23T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "arvind jain",
        "glean",
        "enterprise search",
        "google",
        "ai agents",
        "workplace search",
        "enterprise ai"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/23/ben-hamner-sumble-kaggle-ai-sales-intelligence-deep-analysis/",
      "title": "Ben Hamner: From Kaggle Evaluation to Sumble's GTM Data",
      "summary": "An evidence-based analysis of Ben Hamner's path from Kaggle to Sumble and the accuracy, provenance, and workflow tests that AI sales intelligence must pass.",
      "html_url": "https://digidai.github.io/2025/11/23/ben-hamner-sumble-kaggle-ai-sales-intelligence-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/23/ben-hamner-sumble-kaggle-ai-sales-intelligence-deep-analysis/index.md",
      "date_published": "2025-11-23T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "ben hamner",
        "sumble",
        "kaggle",
        "sales intelligence",
        "knowledge graph",
        "ai sales",
        "go-to-market intelligence",
        "anthony goldbloom",
        "coatue",
        "canaan partners"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/23/cristobal-valenzuela-runway-ai-video-hollywood-revolution-deep-analysis/",
      "title": "Cristobal Valenzuela's Runway: From Video Tool to World Models",
      "summary": "Cristobal Valenzuela's Runway role, AI video products, studio deals, and evidence gaps.",
      "html_url": "https://digidai.github.io/2025/11/23/cristobal-valenzuela-runway-ai-video-hollywood-revolution-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/23/cristobal-valenzuela-runway-ai-video-hollywood-revolution-deep-analysis/index.md",
      "date_published": "2025-11-23T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Cristobal Valenzuela",
        "Runway",
        "AI video",
        "World models",
        "Lionsgate",
        "Generative media",
        "Copyright",
        "Film production"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/23/harrison-chase-langchain-ai-agent-framework-deep-analysis/",
      "title": "Harrison Chase and LangChain: From Framework to Agent Platform",
      "summary": "A source-based profile of Harrison Chase and LangChain, separating the open-source stack, LangSmith business, company claims, funding evidence and strategic analysis.",
      "html_url": "https://digidai.github.io/2025/11/23/harrison-chase-langchain-ai-agent-framework-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/23/harrison-chase-langchain-ai-agent-framework-deep-analysis/index.md",
      "date_published": "2025-11-23T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Harrison Chase",
        "LangChain",
        "LangGraph",
        "LangSmith",
        "AI Agents"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/23/ivan-zhao-notion-ceo-augmenting-human-intellect-deep-dive/",
      "title": "Ivan Zhao: Notion's Toolmaking Thesis in the AI Era",
      "summary": "An evidence-based analysis of Ivan Zhao's product philosophy, Notion AI, and the governance tests for a workspace that can search and act across company knowledge.",
      "html_url": "https://digidai.github.io/2025/11/23/ivan-zhao-notion-ceo-augmenting-human-intellect-deep-dive/",
      "markdown_url": "https://digidai.github.io/2025/11/23/ivan-zhao-notion-ceo-augmenting-human-intellect-deep-dive/index.md",
      "date_published": "2025-11-23T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "ivan zhao",
        "notion",
        "productivity software",
        "knowledge management",
        "startup journey",
        "augmented intellect"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/23/jeremy-liew-lightspeed-snapchat-consumer-investing-legend-deep-analysis/",
      "title": "Jeremy Liew: Lightspeed, Snap, and Consumer Product Signals",
      "summary": "An evidence-based analysis of Jeremy Liew's early Snap investment, his consumer-product thesis, and the limits of turning one venture outcome into a formula.",
      "html_url": "https://digidai.github.io/2025/11/23/jeremy-liew-lightspeed-snapchat-consumer-investing-legend-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/23/jeremy-liew-lightspeed-snapchat-consumer-investing-legend-deep-analysis/index.md",
      "date_published": "2025-11-23T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "jeremy liew",
        "lightspeed venture partners",
        "snapchat investor",
        "consumer investing",
        "venture capital",
        "pop culture",
        "silicon valley"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/23/joshua-kushner-thrive-capital-openai-157-billion-bet-deep-analysis/",
      "title": "Joshua Kushner, Thrive Capital, and OpenAI: What the $157 Billion Round Established",
      "summary": "A source-bound analysis of Joshua Kushner's role at Thrive Capital, its leadership of OpenAI's 2024 financing, concentration risk, and the facts private markets do not disclose.",
      "html_url": "https://digidai.github.io/2025/11/23/joshua-kushner-thrive-capital-openai-157-billion-bet-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/23/joshua-kushner-thrive-capital-openai-157-billion-bet-deep-analysis/index.md",
      "date_published": "2025-11-23T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "joshua kushner",
        "thrive capital",
        "openai",
        "venture capital",
        "ai investment",
        "private markets"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/23/marc-andreessen-a16z-ai-empire-20-billion-bet-techno-optimism-deep-analysis/",
      "title": "Marc Andreessen: a16z, AI Investing, and Techno-Optimism",
      "summary": "An evidence-based analysis of Marc Andreessen's public record, a16z's AI strategy, and how to separate investment claims from measurable outcomes.",
      "html_url": "https://digidai.github.io/2025/11/23/marc-andreessen-a16z-ai-empire-20-billion-bet-techno-optimism-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/23/marc-andreessen-a16z-ai-empire-20-billion-bet-techno-optimism-deep-analysis/index.md",
      "date_published": "2025-11-23T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "marc andreessen",
        "andreessen horowitz",
        "a16z",
        "ai investments",
        "venture capital",
        "netscape",
        "mosaic browser",
        "techno-optimism",
        "ai regulation",
        "openai"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/23/munjal-shah-hippocratic-ai-healthcare-abundance-vision-deep-analysis/",
      "title": "Munjal Shah and Hippocratic AI's Healthcare Agent Thesis",
      "summary": "An evidence-based assessment of Munjal Shah's healthcare AI thesis, Hippocratic AI's patient-facing agents, safety evidence, funding claims, and buyer diligence.",
      "html_url": "https://digidai.github.io/2025/11/23/munjal-shah-hippocratic-ai-healthcare-abundance-vision-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/23/munjal-shah-hippocratic-ai-healthcare-abundance-vision-deep-analysis/index.md",
      "date_published": "2025-11-23T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI Leaders",
        "Healthcare AI",
        "Agentic AI",
        "AI Safety"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/23/pat-gelsinger-intel-ceo-idm-2-foundry-crisis-deep-analysis/",
      "title": "Pat Gelsinger After Intel: What IDM 2.0 Proved and Left Unfinished",
      "summary": "An evidence-based review of Pat Gelsinger's Intel tenure, IDM 2.0, foundry economics, and his current roles at Playground Global and Gloo.",
      "html_url": "https://digidai.github.io/2025/11/23/pat-gelsinger-intel-ceo-idm-2-foundry-crisis-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/23/pat-gelsinger-intel-ceo-idm-2-foundry-crisis-deep-analysis/index.md",
      "date_published": "2025-11-23T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "pat gelsinger",
        "intel",
        "ceo",
        "idm 2.0",
        "semiconductor",
        "foundry",
        "nvidia",
        "chip manufacturing",
        "silicon valley"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/23/pat-grady-sequoia-capital-co-steward-ai-enterprise-software-deep-analysis/",
      "title": "Pat Grady: Sequoia, Enterprise Software, and the Agent Thesis",
      "summary": "An evidence-based analysis of Pat Grady's Sequoia role, enterprise software record, and public thesis on AI agents, with practical tests for buyers and founders.",
      "html_url": "https://digidai.github.io/2025/11/23/pat-grady-sequoia-capital-co-steward-ai-enterprise-software-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/23/pat-grady-sequoia-capital-co-steward-ai-enterprise-software-deep-analysis/index.md",
      "date_published": "2025-11-23T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "pat grady",
        "sequoia capital",
        "venture capital",
        "ai investment",
        "enterprise software",
        "zoom",
        "servicenow",
        "snowflake",
        "silicon valley"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/23/peter-thiel-founders-fund-anduril-defense-ai-contrarian-deep-analysis/",
      "title": "Peter Thiel, Founders Fund, and Anduril: A Documented Defense Technology Investment Thesis",
      "summary": "A source-bound analysis of Peter Thiel's role at Founders Fund, the firm's Anduril investment, public procurement evidence, and the risks outsiders cannot verify.",
      "html_url": "https://digidai.github.io/2025/11/23/peter-thiel-founders-fund-anduril-defense-ai-contrarian-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/23/peter-thiel-founders-fund-anduril-defense-ai-contrarian-deep-analysis/index.md",
      "date_published": "2025-11-23T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "peter thiel",
        "founders fund",
        "anduril",
        "defense technology",
        "defense ai",
        "venture capital"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/23/rahul-vohra-superhuman-grammarly-acquisition-pmf-framework-deep-analysis/",
      "title": "Rahul Vohra's Superhuman PMF Method Under the Acquisition Test",
      "summary": "A sourced review of Vohra's PMF method, Superhuman's acquisition, and the limits of its 40% benchmark.",
      "html_url": "https://digidai.github.io/2025/11/23/rahul-vohra-superhuman-grammarly-acquisition-pmf-framework-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/23/rahul-vohra-superhuman-grammarly-acquisition-pmf-framework-deep-analysis/index.md",
      "date_published": "2025-11-23T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Rahul Vohra",
        "Superhuman",
        "Grammarly",
        "Product-Market Fit",
        "SaaS",
        "Email",
        "Product Strategy"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/23/vinod-khosla-khosla-ventures-openai-bet-cleantech-failures-deep-analysis/",
      "title": "Vinod Khosla's OpenAI Bet and High-Risk Venture Strategy",
      "summary": "A source-bound analysis of Vinod Khosla's early OpenAI investment, his high-risk technology thesis, the limits of public return estimates, and lessons from portfolio failure.",
      "html_url": "https://digidai.github.io/2025/11/23/vinod-khosla-khosla-ventures-openai-bet-cleantech-failures-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/23/vinod-khosla-khosla-ventures-openai-bet-cleantech-failures-deep-analysis/index.md",
      "date_published": "2025-11-23T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI Investors",
        "Venture Capital",
        "OpenAI",
        "Deep Tech"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/23/zayd-enam-cresta-leadership-deep-analysis/",
      "title": "Zayd Enam and Cresta: a source-bound founder and product strategy analysis",
      "summary": "A documented profile of Cresta co-founder Zayd Enam, his transition from CEO, and the evidence behind AI-assisted contact center work.",
      "html_url": "https://digidai.github.io/2025/11/23/zayd-enam-cresta-leadership-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/23/zayd-enam-cresta-leadership-deep-analysis/index.md",
      "date_published": "2025-11-23T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Zayd Enam",
        "Cresta",
        "Contact Center AI",
        "Enterprise AI",
        "AI Agents"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/22/gabriel-pereyra-harvey-ai-president-legal-revolution-deep-analysis/",
      "title": "Gabriel Pereyra: Harvey AI",
      "summary": "A source-based profile of Harvey co-founder Gabriel Pereyra, the product choices behind legal AI, the company's disclosed growth, and the controls legal teams still need.",
      "html_url": "https://digidai.github.io/2025/11/22/gabriel-pereyra-harvey-ai-president-legal-revolution-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/22/gabriel-pereyra-harvey-ai-president-legal-revolution-deep-analysis/index.md",
      "date_published": "2025-11-22T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "gabriel pereyra",
        "harvey ai",
        "legal ai",
        "deepmind",
        "legal technology",
        "enterprise ai",
        "lawyer oversight"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/22/mike-ng-ambience-healthcare-ai-operating-system-physician-burnout-deep-analysis/",
      "title": "Mike Ng: Ambience Healthcare",
      "summary": "A source-based profile of Ambience co-founder Mike Ng, the company's leadership change, health-system deployments, and the evidence required for clinical AI.",
      "html_url": "https://digidai.github.io/2025/11/22/mike-ng-ambience-healthcare-ai-operating-system-physician-burnout-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/22/mike-ng-ambience-healthcare-ai-operating-system-physician-burnout-deep-analysis/index.md",
      "date_published": "2025-11-22T00:00:00.000Z",
      "date_modified": "2026-10-01T00:00:00.000Z",
      "tags": [
        "mike ng",
        "ambience healthcare",
        "ambient clinical ai",
        "medical documentation",
        "healthcare ai",
        "clinician workflow",
        "patient consent"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/22/nikhil-buduma-ambience-healthcare-ceo-medical-ai-revolution-deep-analysis/",
      "title": "Nikhil Buduma's Ambience Healthcare and Clinical AI",
      "summary": "Nikhil Buduma's Ambience strategy extends clinical documentation with AI.",
      "html_url": "https://digidai.github.io/2025/11/22/nikhil-buduma-ambience-healthcare-ceo-medical-ai-revolution-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/22/nikhil-buduma-ambience-healthcare-ceo-medical-ai-revolution-deep-analysis/index.md",
      "date_published": "2025-11-22T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "nikhil buduma",
        "ambience healthcare",
        "ambient ai",
        "clinical documentation",
        "medical ai",
        "healthcare ai"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/22/shivdev-rao-abridge-cardiologist-ai-documentation-empire-deep-analysis/",
      "title": "Shiv Rao and Abridge: Building Clinical AI Around the Draft Note",
      "summary": "A source-bound profile of Abridge founder Shiv Rao, the evidence behind ambient clinical documentation, and the safety, workflow, and procurement questions health systems still need to answer.",
      "html_url": "https://digidai.github.io/2025/11/22/shivdev-rao-abridge-cardiologist-ai-documentation-empire-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/22/shivdev-rao-abridge-cardiologist-ai-documentation-empire-deep-analysis/index.md",
      "date_published": "2025-11-22T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Shiv Rao",
        "Abridge",
        "Healthcare AI",
        "Clinical Documentation",
        "AI Safety"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/21/aman-sanger-cursor-anysphere-fastest-growing-saas-deep-analysis/",
      "title": "Aman Sanger and Cursor's Technical Operating Model",
      "summary": "A sourced analysis of Cursor co-founder Aman Sanger, the company's product and model strategy, disclosed growth, and its 2026 acquisition by SpaceX.",
      "html_url": "https://digidai.github.io/2025/11/21/aman-sanger-cursor-anysphere-fastest-growing-saas-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/21/aman-sanger-cursor-anysphere-fastest-growing-saas-deep-analysis/index.md",
      "date_published": "2025-11-21T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Aman Sanger",
        "Cursor",
        "Anysphere",
        "AI Coding",
        "Software Engineering",
        "AI Models",
        "SpaceX"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/21/amjad-masad-replit-billion-software-creators-deep-analysis/",
      "title": "Amjad Masad and Replit: From Cloud IDE to Software-Building Agent",
      "summary": "A source-bound analysis of Amjad Masad's Replit strategy, its shift toward AI-assisted app creation, disclosed growth, product controls, and unresolved operating risks.",
      "html_url": "https://digidai.github.io/2025/11/21/amjad-masad-replit-billion-software-creators-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/21/amjad-masad-replit-billion-software-creators-deep-analysis/index.md",
      "date_published": "2025-11-21T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "amjad masad",
        "replit",
        "ai coding",
        "replit agent",
        "cloud ide",
        "software development"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/21/michael-truell-cursor-anysphere-fastest-growing-saas-deep-analysis/",
      "title": "Michael Truell: Cursor",
      "summary": "A source-based analysis of Michael Truell, Cursor's product strategy and financing, and what changed when Anysphere joined SpaceX in August 2026.",
      "html_url": "https://digidai.github.io/2025/11/21/michael-truell-cursor-anysphere-fastest-growing-saas-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/21/michael-truell-cursor-anysphere-fastest-growing-saas-deep-analysis/index.md",
      "date_published": "2025-11-21T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "michael truell",
        "cursor",
        "anysphere",
        "spacex",
        "ai code editor",
        "coding agents",
        "developer tools"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/21/sualeh-asif-cursor-anysphere-fastest-growing-saas-deep-analysis/",
      "title": "Sualeh Asif, Cursor, and the Product Logic of AI Coding Agents",
      "summary": "A source-bound profile of Cursor co-founder Sualeh Asif, the product choices behind AI coding agents, the company's disclosed growth, and what changed after the SpaceX acquisition.",
      "html_url": "https://digidai.github.io/2025/11/21/sualeh-asif-cursor-anysphere-fastest-growing-saas-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/21/sualeh-asif-cursor-anysphere-fastest-growing-saas-deep-analysis/index.md",
      "date_published": "2025-11-21T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI Leaders",
        "Developer Tools",
        "AI Coding",
        "Agentic AI"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/20/clay-magouyrk-oracle-cloud-infrastructure-stargate-ai-deep-analysis/",
      "title": "Clay Magouyrk's Oracle Cloud and Stargate Execution Test",
      "summary": "A sourced review of Magouyrk's rise to Oracle co-CEO and the delivery risks behind its AI backlog.",
      "html_url": "https://digidai.github.io/2025/11/20/clay-magouyrk-oracle-cloud-infrastructure-stargate-ai-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/20/clay-magouyrk-oracle-cloud-infrastructure-stargate-ai-deep-analysis/index.md",
      "date_published": "2025-11-20T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Clay Magouyrk",
        "Oracle",
        "Oracle Cloud Infrastructure",
        "Stargate",
        "OpenAI",
        "Cloud Computing",
        "AI Infrastructure",
        "Data Centers"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/20/daniel-rausch-amazon-alexa-25-billion-loss-ai-transformation-deep-analysis/",
      "title": "Daniel Rausch and Amazon's Alexa+ Business Reset",
      "summary": "A sourced review of Daniel Rausch's Alexa role, Alexa+, and the reported $25 billion devices loss.",
      "html_url": "https://digidai.github.io/2025/11/20/daniel-rausch-amazon-alexa-25-billion-loss-ai-transformation-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/20/daniel-rausch-amazon-alexa-25-billion-loss-ai-transformation-deep-analysis/index.md",
      "date_published": "2025-11-20T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Daniel Rausch",
        "Amazon Alexa",
        "Alexa+",
        "Amazon Echo",
        "Voice Assistants",
        "Generative AI",
        "Smart Home",
        "Privacy"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/20/dinesh-nirmal-ibm-watsonx-enterprise-ai-governance-strategy-deep-analysis/",
      "title": "Dinesh Nirmal and IBM's Enterprise AI Governance Strategy",
      "summary": "An evidence-based analysis of Dinesh Nirmal's IBM software role, watsonx governance, DataStax, and the controls enterprises should verify before adopting IBM AI.",
      "html_url": "https://digidai.github.io/2025/11/20/dinesh-nirmal-ibm-watsonx-enterprise-ai-governance-strategy-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/20/dinesh-nirmal-ibm-watsonx-enterprise-ai-governance-strategy-deep-analysis/index.md",
      "date_published": "2025-11-20T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI Leaders",
        "Enterprise AI",
        "AI Governance",
        "IBM"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/20/kim-vorrath-apple-siri-ai-crisis-fixer-deep-analysis/",
      "title": "Kim Vorrath and Apple's AI Execution Reset",
      "summary": "A source-based account of Kim Vorrath's reported move into Apple's AI organization and the product, privacy and delivery evidence needed to judge Siri execution.",
      "html_url": "https://digidai.github.io/2025/11/20/kim-vorrath-apple-siri-ai-crisis-fixer-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/20/kim-vorrath-apple-siri-ai-crisis-fixer-deep-analysis/index.md",
      "date_published": "2025-11-20T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Kim Vorrath",
        "Apple",
        "Siri",
        "Apple Intelligence",
        "AI Execution"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/20/mike-sicilia-oracle-ceo-ai-everywhere-enterprise-transformation-deep-analysis/",
      "title": "Mike Sicilia's Oracle Applications and AI Strategy",
      "summary": "Mike Sicilia's Oracle brief centers on applications and industry AI.",
      "html_url": "https://digidai.github.io/2025/11/20/mike-sicilia-oracle-ceo-ai-everywhere-enterprise-transformation-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/20/mike-sicilia-oracle-ceo-ai-everywhere-enterprise-transformation-deep-analysis/index.md",
      "date_published": "2025-11-20T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "mike sicilia",
        "oracle",
        "oracle co-ceo",
        "fusion applications",
        "oracle health",
        "enterprise ai"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/20/scott-guthrie-microsoft-azure-ai-cloud-empire-deep-analysis/",
      "title": "Scott Guthrie and Azure's AI Infrastructure Test",
      "summary": "A sourced review of Scott Guthrie's Azure remit, capital demands, and OpenAI risk.",
      "html_url": "https://digidai.github.io/2025/11/20/scott-guthrie-microsoft-azure-ai-cloud-empire-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/20/scott-guthrie-microsoft-azure-ai-cloud-empire-deep-analysis/index.md",
      "date_published": "2025-11-20T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Scott Guthrie",
        "Microsoft Azure",
        "Cloud Computing",
        "AI Infrastructure",
        "OpenAI",
        "Data Centers",
        "Developer Platforms"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/20/sriram-raghavan-ibm-research-watson-enterprise-ai-trust-deep-analysis/",
      "title": "Sriram Raghavan's IBM Research and Enterprise AI Work",
      "summary": "Sriram Raghavan's IBM work connects Granite models and AI runtimes.",
      "html_url": "https://digidai.github.io/2025/11/20/sriram-raghavan-ibm-research-watson-enterprise-ai-trust-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/20/sriram-raghavan-ibm-research-watson-enterprise-ai-trust-deep-analysis/index.md",
      "date_published": "2025-11-20T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "sriram raghavan",
        "ibm research",
        "granite models",
        "enterprise ai",
        "ai governance",
        "watsonx"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/20/swami-sivasubramanian-aws-agentic-ai-neutrality-strategy-deep-analysis/",
      "title": "Swami Sivasubramanian and AWS's Agentic AI Platform Strategy",
      "summary": "An evidence-based analysis of Swami Sivasubramanian's role, Amazon Bedrock AgentCore, model choice, and the controls enterprises should test before deploying agents on AWS.",
      "html_url": "https://digidai.github.io/2025/11/20/swami-sivasubramanian-aws-agentic-ai-neutrality-strategy-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/20/swami-sivasubramanian-aws-agentic-ai-neutrality-strategy-deep-analysis/index.md",
      "date_published": "2025-11-20T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI Leaders",
        "Enterprise AI",
        "Agentic AI",
        "Cloud Infrastructure"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/19/alexandr-wang-meta-scale-ai-youngest-billionaire-superintelligence-bet-deep-analysis/",
      "title": "Alexandr Wang: From Scale AI to Meta",
      "summary": "A source-based analysis of Alexandr Wang's move to Meta, the Scale AI investment, Meta Superintelligence Labs, and the evidence behind the strategy.",
      "html_url": "https://digidai.github.io/2025/11/19/alexandr-wang-meta-scale-ai-youngest-billionaire-superintelligence-bet-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/19/alexandr-wang-meta-scale-ai-youngest-billionaire-superintelligence-bet-deep-analysis/index.md",
      "date_published": "2025-11-19T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "alexandr wang",
        "meta",
        "scale ai",
        "meta superintelligence labs",
        "muse spark",
        "ai data",
        "model evaluation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/19/ali-ghodsi-databricks-ceo-lakehouse-revolution-ipo-deep-analysis/",
      "title": "Ali Ghodsi and Databricks: a source-bound lakehouse and IPO analysis",
      "summary": "A professional analysis of Ali Ghodsi's documented role, Databricks' lakehouse strategy, 2026 company disclosures, competitive risks, and IPO uncertainty.",
      "html_url": "https://digidai.github.io/2025/11/19/ali-ghodsi-databricks-ceo-lakehouse-revolution-ipo-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/19/ali-ghodsi-databricks-ceo-lakehouse-revolution-ipo-deep-analysis/index.md",
      "date_published": "2025-11-19T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Ali Ghodsi",
        "Databricks",
        "Lakehouse Architecture",
        "Apache Spark",
        "Enterprise AI"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/19/jonathan-ross-groq-lpu-nvidia-inference-challenge-deep-analysis/",
      "title": "Jonathan Ross and Groq's Inference Architecture",
      "summary": "A source-based account of Jonathan Ross, Groq's LPU strategy, the December 2025 Nvidia licensing agreement, and how buyers should test inference claims.",
      "html_url": "https://digidai.github.io/2025/11/19/jonathan-ross-groq-lpu-nvidia-inference-challenge-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/19/jonathan-ross-groq-lpu-nvidia-inference-challenge-deep-analysis/index.md",
      "date_published": "2025-11-19T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "jonathan ross",
        "groq",
        "lpu",
        "google tpu",
        "nvidia",
        "ai inference",
        "groqcloud"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/19/sridhar-ramaswamy-snowflake-ceo-google-ads-databricks-ai-transformation-deep-analysis/",
      "title": "Sridhar Ramaswamy: Snowflake's Data and AI Strategy",
      "summary": "Sridhar Ramaswamy's Snowflake strategy brings AI to governed data.",
      "html_url": "https://digidai.github.io/2025/11/19/sridhar-ramaswamy-snowflake-ceo-google-ads-databricks-ai-transformation-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/19/sridhar-ramaswamy-snowflake-ceo-google-ads-databricks-ai-transformation-deep-analysis/index.md",
      "date_published": "2025-11-19T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "sridhar ramaswamy",
        "snowflake",
        "cortex ai",
        "data cloud",
        "enterprise ai",
        "ai agents"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/18/andrew-feldman-cerebras-wafer-scale-nvidia-challenge-deep-analysis/",
      "title": "Andrew Feldman's Cerebras and Wafer-Scale AI Bet",
      "summary": "Andrew Feldman's Cerebras bet puts wafer-scale processors into AI clouds.",
      "html_url": "https://digidai.github.io/2025/11/18/andrew-feldman-cerebras-wafer-scale-nvidia-challenge-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/18/andrew-feldman-cerebras-wafer-scale-nvidia-challenge-deep-analysis/index.md",
      "date_published": "2025-11-18T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "andrew feldman",
        "cerebras systems",
        "wafer-scale engine",
        "ai inference",
        "ai chips",
        "semiconductors"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/18/rodrigo-liang-sambanova-systems-ai-chip-nvidia-challenge-deep-analysis/",
      "title": "Rodrigo Liang: SambaNova's Dataflow Bet",
      "summary": "A source-based analysis of Rodrigo Liang, SambaNova's RDU architecture, its 2026 Intel collaboration and financing, and how to test accelerator claims.",
      "html_url": "https://digidai.github.io/2025/11/18/rodrigo-liang-sambanova-systems-ai-chip-nvidia-challenge-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/18/rodrigo-liang-sambanova-systems-ai-chip-nvidia-challenge-deep-analysis/index.md",
      "date_published": "2025-11-18T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "rodrigo liang",
        "sambanova systems",
        "rdu",
        "dataflow accelerator",
        "sn40l",
        "sn50",
        "intel",
        "ai inference"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/17/adam-evans-salesforce-agentforce-digital-labor-revolution-deep-analysis/",
      "title": "Adam Evans's Salesforce Agentforce Product Thesis",
      "summary": "Adam Evans's public work explains Salesforce's original Agentforce thesis.",
      "html_url": "https://digidai.github.io/2025/11/17/adam-evans-salesforce-agentforce-digital-labor-revolution-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/17/adam-evans-salesforce-agentforce-digital-labor-revolution-deep-analysis/index.md",
      "date_published": "2025-11-17T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "adam evans",
        "salesforce",
        "agentforce",
        "ai agents",
        "crm",
        "enterprise ai"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/17/arvind-krishna-ibm-watsonx-ai-transformation-deep-analysis/",
      "title": "Arvind Krishna: IBM's Watsonx and Hybrid AI Strategy",
      "summary": "Arvind Krishna's IBM strategy links watsonx, Red Hat, and governed AI.",
      "html_url": "https://digidai.github.io/2025/11/17/arvind-krishna-ibm-watsonx-ai-transformation-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/17/arvind-krishna-ibm-watsonx-ai-transformation-deep-analysis/index.md",
      "date_published": "2025-11-17T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "arvind krishna",
        "ibm",
        "watsonx",
        "granite models",
        "hybrid cloud",
        "enterprise ai"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/17/lisa-su-amd-ai-chip-nvidia-challenge-deep-analysis/",
      "title": "Lisa Su's AMD: Building a Credible Alternative for AI Compute",
      "summary": "Lisa Su's AMD strategy joins Instinct accelerators with the ROCm stack.",
      "html_url": "https://digidai.github.io/2025/11/17/lisa-su-amd-ai-chip-nvidia-challenge-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/17/lisa-su-amd-ai-chip-nvidia-challenge-deep-analysis/index.md",
      "date_published": "2025-11-17T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "lisa su",
        "amd",
        "ai chips",
        "instinct",
        "rocm",
        "data center"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/16/clara-shih-meta-business-ai-enterprise-bet-deep-analysis/",
      "title": "Clara Shih and Meta's Business AI Buildout",
      "summary": "A source-based profile of Clara Shih's path from Hearsay and Salesforce to Meta's Business AI group, plus an evidence framework for customer-facing agents.",
      "html_url": "https://digidai.github.io/2025/11/16/clara-shih-meta-business-ai-enterprise-bet-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/16/clara-shih-meta-business-ai-enterprise-bet-deep-analysis/index.md",
      "date_published": "2025-11-16T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Clara Shih",
        "Meta",
        "Business AI",
        "Customer Service",
        "AI Agents"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/16/koray-kavukcuoglu-google-deepmind-ai-architect-research-product-integration-deep-analysis/",
      "title": "Koray Kavukcuoglu's Route From DeepMind Research to Google AI",
      "summary": "A sourced profile of Koray Kavukcuoglu's research, product work, and changing Google DeepMind remit.",
      "html_url": "https://digidai.github.io/2025/11/16/koray-kavukcuoglu-google-deepmind-ai-architect-research-product-integration-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/16/koray-kavukcuoglu-google-deepmind-ai-architect-research-product-integration-deep-analysis/index.md",
      "date_published": "2025-11-16T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Koray Kavukcuoglu",
        "Google DeepMind",
        "Gemini",
        "Deep Reinforcement Learning",
        "WaveNet",
        "AI Research",
        "Product Engineering"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/15/jensen-huang-nvidia-ai-chip-kingmaker-deep-analysis/",
      "title": "Jensen Huang's NVIDIA Platform Strategy and Its Concentration Risks",
      "summary": "NVIDIA's AI growth, Rubin roadmap, customer concentration, and export risks under Jensen Huang.",
      "html_url": "https://digidai.github.io/2025/11/15/jensen-huang-nvidia-ai-chip-kingmaker-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/15/jensen-huang-nvidia-ai-chip-kingmaker-deep-analysis/index.md",
      "date_published": "2025-11-15T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Jensen Huang",
        "NVIDIA",
        "AI infrastructure",
        "GPUs",
        "CUDA",
        "Rubin",
        "Data centers",
        "Export controls"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/15/john-giannandrea-apple-ai-siri-crisis-deep-analysis/",
      "title": "John Giannandrea and Apple's Siri Reset",
      "summary": "A sourced review of John Giannandrea's Apple tenure, Siri delays, and model work.",
      "html_url": "https://digidai.github.io/2025/11/15/john-giannandrea-apple-ai-siri-crisis-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/15/john-giannandrea-apple-ai-siri-crisis-deep-analysis/index.md",
      "date_published": "2025-11-15T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "John Giannandrea",
        "Apple",
        "Siri",
        "Apple Intelligence",
        "Machine Learning",
        "AI Strategy",
        "Privacy",
        "Leadership"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/15/larry-ellison-oracle-stargate-ai-infrastructure-deep-analysis/",
      "title": "Larry Ellison, Oracle, and the Stargate Infrastructure Bet",
      "summary": "A source-based analysis of Larry Ellison's current Oracle role, Oracle's part in Stargate, and how to evaluate the project's investment and capacity claims.",
      "html_url": "https://digidai.github.io/2025/11/15/larry-ellison-oracle-stargate-ai-infrastructure-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/15/larry-ellison-oracle-stargate-ai-infrastructure-deep-analysis/index.md",
      "date_published": "2025-11-15T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "larry ellison",
        "oracle",
        "stargate",
        "openai",
        "ai infrastructure",
        "data centers",
        "oci"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/15/marc-benioff-salesforce-agentforce-digital-labor-revolution-deep-analysis/",
      "title": "Marc Benioff's Agentforce Bet: Revenue Signal, Adoption Questions",
      "summary": "Marc Benioff's Agentforce revenue, metric changes, customer evidence, and labor claims.",
      "html_url": "https://digidai.github.io/2025/11/15/marc-benioff-salesforce-agentforce-digital-labor-revolution-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/15/marc-benioff-salesforce-agentforce-digital-labor-revolution-deep-analysis/index.md",
      "date_published": "2025-11-15T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Marc Benioff",
        "Salesforce",
        "Agentforce",
        "AI agents",
        "Enterprise software",
        "CRM",
        "AI adoption",
        "Workforce automation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/15/matt-garman-aws-ceo-ai-infrastructure-race-deep-analysis/",
      "title": "Matt Garman's AWS AI Infrastructure Strategy",
      "summary": "Matt Garman's AWS strategy spans chips, models, agents, and cloud economics.",
      "html_url": "https://digidai.github.io/2025/11/15/matt-garman-aws-ceo-ai-infrastructure-race-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/15/matt-garman-aws-ceo-ai-infrastructure-race-deep-analysis/index.md",
      "date_published": "2025-11-15T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "matt garman",
        "aws",
        "amazon web services",
        "ai infrastructure",
        "amazon bedrock",
        "trainium"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/15/rohit-prasad-amazon-alexa-agi-25-billion-loss-deep-analysis/",
      "title": "Rohit Prasad: Alexa, Amazon AGI, and the 2026 Transition",
      "summary": "A source-based analysis of Rohit Prasad's work on Alexa and Amazon AGI, the Nova and Alexa+ product layers, and what Amazon's public record does not reveal.",
      "html_url": "https://digidai.github.io/2025/11/15/rohit-prasad-amazon-alexa-agi-25-billion-loss-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/15/rohit-prasad-amazon-alexa-agi-25-billion-loss-deep-analysis/index.md",
      "date_published": "2025-11-15T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "rohit prasad",
        "amazon",
        "alexa plus",
        "amazon agi",
        "nova",
        "nova act",
        "voice assistant"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/15/thomas-kurian-google-cloud-ai-infrastructure-race-deep-analysis/",
      "title": "Thomas Kurian: Google Cloud's Enterprise AI Strategy",
      "summary": "Thomas Kurian's Google Cloud strategy joins TPUs, Gemini, data, and governance.",
      "html_url": "https://digidai.github.io/2025/11/15/thomas-kurian-google-cloud-ai-infrastructure-race-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/15/thomas-kurian-google-cloud-ai-infrastructure-race-deep-analysis/index.md",
      "date_published": "2025-11-15T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "thomas kurian",
        "google cloud",
        "vertex ai",
        "gemini",
        "enterprise ai",
        "cloud infrastructure"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/15/tim-cook-apple-ceo-ai-strategy-crisis-deep-analysis/",
      "title": "Tim Cook's Apple AI Legacy: From Siri Delay to a 2026 Beta",
      "summary": "Tim Cook's Apple AI record, Siri delay, Gemini deal, privacy design, and transition to executive chair.",
      "html_url": "https://digidai.github.io/2025/11/15/tim-cook-apple-ceo-ai-strategy-crisis-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/15/tim-cook-apple-ceo-ai-strategy-crisis-deep-analysis/index.md",
      "date_published": "2025-11-15T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Tim Cook",
        "Apple",
        "Siri AI",
        "Apple Intelligence",
        "Gemini",
        "Private Cloud Compute",
        "AI strategy",
        "Product delivery"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/14/jeff-dean-google-chief-scientist-deep-analysis/",
      "title": "Jeff Dean: Google Chief Scientist, Papers and Engineering Work",
      "summary": "A source-checked guide to Jeff Dean's role and contributions to MapReduce, Bigtable, TensorFlow and TPUs, with a correction on Transformer authorship.",
      "html_url": "https://digidai.github.io/2025/11/14/jeff-dean-google-chief-scientist-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/14/jeff-dean-google-chief-scientist-deep-analysis/index.md",
      "date_published": "2025-11-14T00:00:00.000Z",
      "date_modified": "2026-09-08T00:00:00.000Z",
      "tags": [
        "Jeff Dean",
        "Google",
        "Distributed Systems",
        "Machine Learning",
        "AI Infrastructure"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/14/mark-zuckerberg-meta-ai-superintelligence-bet-deep-analysis/",
      "title": "Mark Zuckerberg's Meta AI Strategy: From MSL to Muse",
      "summary": "A source-based analysis of Meta's superintelligence strategy, Scale AI investment, Muse releases, infrastructure spending, and the evidence still missing.",
      "html_url": "https://digidai.github.io/2025/11/14/mark-zuckerberg-meta-ai-superintelligence-bet-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/14/mark-zuckerberg-meta-ai-superintelligence-bet-deep-analysis/index.md",
      "date_published": "2025-11-14T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "mark zuckerberg",
        "meta",
        "meta ai",
        "meta superintelligence labs",
        "muse spark",
        "scale ai",
        "ai infrastructure"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/14/mustafa-suleyman-microsoft-ai-ceo-deepmind-inflection-deep-analysis/",
      "title": "Mustafa Suleyman's Microsoft AI Remit After the Copilot Reorganization",
      "summary": "Mustafa Suleyman's Microsoft AI role, Inflection deal, MAI models, and governance limits.",
      "html_url": "https://digidai.github.io/2025/11/14/mustafa-suleyman-microsoft-ai-ceo-deepmind-inflection-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/14/mustafa-suleyman-microsoft-ai-ceo-deepmind-inflection-deep-analysis/index.md",
      "date_published": "2025-11-14T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Mustafa Suleyman",
        "Microsoft AI",
        "Copilot",
        "Inflection AI",
        "MAI models",
        "AI governance",
        "Competition policy",
        "Consumer AI"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/14/sarah-friar-openai-cfo-square-nextdoor-deep-analysis/",
      "title": "Sarah Friar at OpenAI: Finance, Structure, and Scale",
      "summary": "A source-based analysis of Sarah Friar's CFO role, OpenAI's recapitalization and financing, and which business-model claims remain company disclosures.",
      "html_url": "https://digidai.github.io/2025/11/14/sarah-friar-openai-cfo-square-nextdoor-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/14/sarah-friar-openai-cfo-square-nextdoor-deep-analysis/index.md",
      "date_published": "2025-11-14T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "sarah friar",
        "openai",
        "chief financial officer",
        "openai recapitalization",
        "microsoft",
        "nextdoor",
        "square"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/14/satya-nadella-microsoft-ceo-ai-transformation-deep-analysis/",
      "title": "Satya Nadella's Microsoft AI Strategy After the OpenAI Reset",
      "summary": "Microsoft's AI economics, Azure growth, OpenAI reset, and execution risks under Satya Nadella.",
      "html_url": "https://digidai.github.io/2025/11/14/satya-nadella-microsoft-ceo-ai-transformation-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/14/satya-nadella-microsoft-ceo-ai-transformation-deep-analysis/index.md",
      "date_published": "2025-11-14T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Satya Nadella",
        "Microsoft",
        "Azure",
        "OpenAI",
        "Copilot",
        "AI infrastructure",
        "Cloud computing",
        "Enterprise AI"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/11/aidan-gomez-cohere-ceo-deep-analysis/",
      "title": "Aidan Gomez: From the Transformer Paper to Cohere",
      "summary": "A source-based profile of Aidan Gomez, his documented role in the Transformer paper, and Cohere's enterprise and sovereign AI strategy, with company claims kept separate from buyer evidence.",
      "html_url": "https://digidai.github.io/2025/11/11/aidan-gomez-cohere-ceo-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/11/aidan-gomez-cohere-ceo-deep-analysis/index.md",
      "date_published": "2025-11-11T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Aidan Gomez",
        "Cohere",
        "Transformer",
        "Enterprise AI",
        "Sovereign AI"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/11/andy-jassy-amazon-ceo-aws-ai-deep-analysis/",
      "title": "Andy Jassy: Amazon, AWS, and the Company's AI Investment Cycle",
      "summary": "A sourced profile of Andy Jassy's path from AWS to Amazon CEO, his operating priorities, and Amazon's generative AI and Anthropic bets.",
      "html_url": "https://digidai.github.io/2025/11/11/andy-jassy-amazon-ceo-aws-ai-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/11/andy-jassy-amazon-ceo-aws-ai-deep-analysis/index.md",
      "date_published": "2025-11-11T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "andy jassy",
        "amazon",
        "aws",
        "generative ai",
        "anthropic",
        "cloud infrastructure"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/11/arthur-mensch-mistral-ai-ceo-deep-analysis/",
      "title": "Arthur Mensch and Mistral AI: Europe's Frontier Model Company",
      "summary": "A sourced profile of Arthur Mensch, Mistral AI's open-weight strategy, funding, product direction, and sovereignty tradeoffs.",
      "html_url": "https://digidai.github.io/2025/11/11/arthur-mensch-mistral-ai-ceo-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/11/arthur-mensch-mistral-ai-ceo-deep-analysis/index.md",
      "date_published": "2025-11-11T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "arthur mensch",
        "mistral ai",
        "european ai",
        "open-weight models",
        "ai sovereignty",
        "enterprise ai"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/11/chris-ciauri-anthropic-international-analysis/",
      "title": "Chris Ciauri and Anthropic's International Expansion",
      "summary": "A source-based profile of Chris Ciauri's international role at Anthropic and the operating questions behind selling Claude across regions, regulations and enterprise workflows.",
      "html_url": "https://digidai.github.io/2025/11/11/chris-ciauri-anthropic-international-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/11/chris-ciauri-anthropic-international-analysis/index.md",
      "date_published": "2025-11-11T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Chris Ciauri",
        "Anthropic",
        "Claude",
        "International Expansion",
        "Enterprise AI"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/11/demis-hassabis-google-deepmind-ceo-deep-analysis/",
      "title": "Demis Hassabis's Record From AlphaFold to Alphabet Chief Scientist",
      "summary": "Demis Hassabis's AlphaFold record, 2024 Nobel Prize, and current Alphabet science role.",
      "html_url": "https://digidai.github.io/2025/11/11/demis-hassabis-google-deepmind-ceo-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/11/demis-hassabis-google-deepmind-ceo-deep-analysis/index.md",
      "date_published": "2025-11-11T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Demis Hassabis",
        "Google DeepMind",
        "AlphaFold",
        "Nobel Prize",
        "Alphabet",
        "Isomorphic Labs",
        "AI for science",
        "Protein structure"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/11/fidji-simo-openai-applications-ceo-deep-analysis/",
      "title": "Fidji Simo: Leading Applications at OpenAI",
      "summary": "A sourced profile of Fidji Simo's move from Instacart to OpenAI, her product background, role boundaries, and application-layer priorities.",
      "html_url": "https://digidai.github.io/2025/11/11/fidji-simo-openai-applications-ceo-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/11/fidji-simo-openai-applications-ceo-deep-analysis/index.md",
      "date_published": "2025-11-11T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "fidji simo",
        "openai applications",
        "instacart",
        "meta",
        "chatgpt",
        "product strategy"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/11/guillaume-lample-mistral-ai-cofounder-analysis/",
      "title": "Guillaume Lample and Mistral's Open-Weight Strategy",
      "summary": "A source-based profile of Mistral co-founder Guillaume Lample, his published language-model research and the evidence buyers need when evaluating open-weight and sovereign AI claims.",
      "html_url": "https://digidai.github.io/2025/11/11/guillaume-lample-mistral-ai-cofounder-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/11/guillaume-lample-mistral-ai-cofounder-analysis/index.md",
      "date_published": "2025-11-11T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Guillaume Lample",
        "Mistral AI",
        "Open-Weight AI",
        "Multilingual AI",
        "Sovereign AI"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/11/ilya-sutskever-safe-superintelligence-deep-analysis/",
      "title": "Ilya Sutskever and Safe Superintelligence's Evidence Gap",
      "summary": "A sourced analysis of Ilya Sutskever's research record, the mission and financing of Safe Superintelligence, and the evidence still missing.",
      "html_url": "https://digidai.github.io/2025/11/11/ilya-sutskever-safe-superintelligence-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/11/ilya-sutskever-safe-superintelligence-deep-analysis/index.md",
      "date_published": "2025-11-11T00:00:00.000Z",
      "date_modified": "2026-10-02T00:00:00.000Z",
      "tags": [
        "Ilya Sutskever",
        "Safe Superintelligence",
        "SSI",
        "AI Safety",
        "OpenAI",
        "Deep Learning",
        "AI Research"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/11/joelle-pineau-cohere-chief-ai-officer-deep-analysis/",
      "title": "Joelle Pineau at Cohere: Research Claims a Buyer Can Check",
      "summary": "A source-based profile of Joelle Pineau's reproducibility work and its relevance to enterprise AI evaluation, with clear limits on what a leadership appointment proves.",
      "html_url": "https://digidai.github.io/2025/11/11/joelle-pineau-cohere-chief-ai-officer-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/11/joelle-pineau-cohere-chief-ai-officer-deep-analysis/index.md",
      "date_published": "2025-11-11T00:00:00.000Z",
      "date_modified": "2026-09-09T00:00:00.000Z",
      "tags": [
        "Joelle Pineau",
        "Cohere",
        "AI Research",
        "Reproducibility",
        "Enterprise AI"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/11/kevin-weil-openai-vp-science-deep-analysis/",
      "title": "Kevin Weil's Product-to-Science Record After OpenAI",
      "summary": "Kevin Weil's OpenAI product and science work, April 2026 departure, and AI-for-science evidence.",
      "html_url": "https://digidai.github.io/2025/11/11/kevin-weil-openai-vp-science-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/11/kevin-weil-openai-vp-science-deep-analysis/index.md",
      "date_published": "2025-11-11T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Kevin Weil",
        "OpenAI",
        "AI for science",
        "Product leadership",
        "Scientific discovery",
        "GPT-5",
        "Research workflows",
        "Stoke Space"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/11/mira-murati-thinking-machines-lab-deep-analysis/",
      "title": "Mira Murati: Building Thinking Machines Lab After OpenAI",
      "summary": "A sourced profile of Mira Murati, Thinking Machines Lab, Tinker, its infrastructure partnership, and the evidence behind its product thesis.",
      "html_url": "https://digidai.github.io/2025/11/11/mira-murati-thinking-machines-lab-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/11/mira-murati-thinking-machines-lab-deep-analysis/index.md",
      "date_published": "2025-11-11T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "mira murati",
        "thinking machines lab",
        "tinker",
        "openai",
        "model customization",
        "nvidia"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/11/paul-smith-anthropic-cco-deep-analysis/",
      "title": "Paul Smith: Anthropic's Commercial Strategy and Enterprise Test",
      "summary": "A sourced profile of Anthropic chief commercial officer Paul Smith, his enterprise background, remit, partnerships, and measurable risks.",
      "html_url": "https://digidai.github.io/2025/11/11/paul-smith-anthropic-cco-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/11/paul-smith-anthropic-cco-deep-analysis/index.md",
      "date_published": "2025-11-11T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "paul smith",
        "anthropic",
        "chief commercial officer",
        "claude enterprise",
        "servicenow",
        "ai go-to-market"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/11/sundar-pichai-google-ceo-deep-analysis/",
      "title": "Sundar Pichai and Alphabet: an evidence-based analysis of the AI-first strategy",
      "summary": "A source-bound profile of Sundar Pichai's verified CEO role, Google's AI organization and product strategy, capital allocation, and antitrust constraints.",
      "html_url": "https://digidai.github.io/2025/11/11/sundar-pichai-google-ceo-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/11/sundar-pichai-google-ceo-deep-analysis/index.md",
      "date_published": "2025-11-11T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Sundar Pichai",
        "Alphabet",
        "Google",
        "Gemini",
        "AI Strategy"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/11/timothee-lacroix-mistral-cofounder-deep-analysis/",
      "title": "Timothée Lacroix at Mistral AI: a source-bound technical profile",
      "summary": "A documented profile of Mistral AI co-founder and CTO Timothée Lacroix, covering his research record, engineering role, model work, and the limits of public evidence.",
      "html_url": "https://digidai.github.io/2025/11/11/timothee-lacroix-mistral-cofounder-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/11/timothee-lacroix-mistral-cofounder-deep-analysis/index.md",
      "date_published": "2025-11-11T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Timothée Lacroix",
        "Mistral AI",
        "AI Leadership",
        "Large Language Models",
        "Open Models"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/08/aravind-srinivas-perplexity-deep-analysis/",
      "title": "Aravind Srinivas and Perplexity: Building an Answer Engine",
      "summary": "A sourced profile of Aravind Srinivas, Perplexity's product thesis, publisher tensions, and the evidence needed to judge AI search.",
      "html_url": "https://digidai.github.io/2025/11/08/aravind-srinivas-perplexity-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/08/aravind-srinivas-perplexity-deep-analysis/index.md",
      "date_published": "2025-11-08T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "aravind srinivas",
        "perplexity",
        "answer engine",
        "ai search",
        "citations",
        "publishers"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/08/daniela-amodei-anthropic-president-deep-analysis/",
      "title": "Daniela Amodei and Anthropic's Operating Model",
      "summary": "A sourced analysis of Daniela Amodei's role at Anthropic, the company's safety governance, commercial execution, and evidence buyers should examine.",
      "html_url": "https://digidai.github.io/2025/11/08/daniela-amodei-anthropic-president-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/08/daniela-amodei-anthropic-president-deep-analysis/index.md",
      "date_published": "2025-11-08T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Daniela Amodei",
        "Anthropic",
        "Claude",
        "AI Safety",
        "Responsible Scaling Policy",
        "AI Governance",
        "Enterprise AI"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/08/dario-amodei-anthropic-comprehensive-deep-analysis/",
      "title": "Dario Amodei and Anthropic: Safety, Scale, and Commercial Dependence",
      "summary": "A sourced profile of Dario Amodei, Anthropic's safety framework, cloud partnerships, enterprise strategy, and unresolved tradeoffs.",
      "html_url": "https://digidai.github.io/2025/11/08/dario-amodei-anthropic-comprehensive-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/08/dario-amodei-anthropic-comprehensive-deep-analysis/index.md",
      "date_published": "2025-11-08T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "dario amodei",
        "anthropic",
        "claude",
        "responsible scaling policy",
        "amazon partnership",
        "ai safety",
        "enterprise ai"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/08/elon-musk-xai-deep-investigation/",
      "title": "Elon Musk's xAI: Compute, Distribution and Governance",
      "summary": "A source-based analysis of Elon Musk's xAI, from Grok and the Colossus cluster to funding, product reach, safety disclosures and infrastructure scrutiny.",
      "html_url": "https://digidai.github.io/2025/11/08/elon-musk-xai-deep-investigation/",
      "markdown_url": "https://digidai.github.io/2025/11/08/elon-musk-xai-deep-investigation/index.md",
      "date_published": "2025-11-08T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Elon Musk",
        "xAI",
        "Grok",
        "AI Infrastructure",
        "AI Governance"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/08/mark-chen-openai-cro-deep-analysis/",
      "title": "Mark Chen at OpenAI: research leadership, documented contributions, and limits of attribution",
      "summary": "A source-bound profile of OpenAI Chief Research Officer Mark Chen, covering his documented work on DALL-E, Codex, and reasoning systems without treating team results as solo achievements.",
      "html_url": "https://digidai.github.io/2025/11/08/mark-chen-openai-cro-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/08/mark-chen-openai-cro-deep-analysis/index.md",
      "date_published": "2025-11-08T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Mark Chen",
        "OpenAI",
        "DALL-E",
        "Codex",
        "AI Research"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/08/sam-altman-openai-comprehensive-deep-analysis/",
      "title": "Sam Altman and OpenAI: Product, Capital, and Governance",
      "summary": "A sourced analysis of Sam Altman's leadership, OpenAI's 2023 board crisis, Microsoft partnership, and current nonprofit-controlled structure.",
      "html_url": "https://digidai.github.io/2025/11/08/sam-altman-openai-comprehensive-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/08/sam-altman-openai-comprehensive-deep-analysis/index.md",
      "date_published": "2025-11-08T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "sam altman",
        "openai",
        "chatgpt",
        "openai foundation",
        "microsoft partnership",
        "ai governance"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/07/recooty-comprehensive-deep-analysis/",
      "title": "Recooty: AI ATS for Small Recruiting Teams",
      "summary": "Current analysis of Recooty's applicant tracking, AI ranking, job distribution, candidate workflow, API, privacy, packaging, and buyer controls.",
      "html_url": "https://digidai.github.io/2025/11/07/recooty-comprehensive-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/07/recooty-comprehensive-deep-analysis/index.md",
      "date_published": "2025-11-07T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "recooty",
        "applicant tracking system",
        "ai recruiting software",
        "smb hiring platform",
        "candidate ranking",
        "resume screening",
        "job posting",
        "recruiting api"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/07/sap-successfactors-recruiting-comprehensive-deep-analysis/",
      "title": "SAP SuccessFactors Recruiting: Current Product and Migration Analysis",
      "summary": "Current analysis of SAP SuccessFactors Recruiting, SmartRecruiters for SAP SuccessFactors, Joule and Winston AI, integration, migration, data governance, and buyer controls.",
      "html_url": "https://digidai.github.io/2025/11/07/sap-successfactors-recruiting-comprehensive-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/07/sap-successfactors-recruiting-comprehensive-deep-analysis/index.md",
      "date_published": "2025-11-07T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "sap successfactors recruiting",
        "smartrecruiters",
        "enterprise ats",
        "recruiting crm",
        "joule",
        "winston ai",
        "talent acquisition",
        "recruiting migration"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/07/silicon-valley-ai-100-most-influential-2025/",
      "title": "TIME100 AI 2025: an evidence guide to 100 influential people in AI",
      "summary": "A source-bound guide to the TIME100 AI 2025, its editorial methodology, representative honorees, and a practical framework for evaluating influence beyond a power ranking.",
      "html_url": "https://digidai.github.io/2025/11/07/silicon-valley-ai-100-most-influential-2025/",
      "markdown_url": "https://digidai.github.io/2025/11/07/silicon-valley-ai-100-most-influential-2025/index.md",
      "date_published": "2025-11-07T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "TIME100 AI 2025",
        "AI Leaders",
        "AI Governance",
        "AI Infrastructure",
        "Artificial Intelligence"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/06/bullhorn-comprehensive-strategic-analysis/",
      "title": "Bullhorn: Staffing CRM, ATS, and Amplify Analysis",
      "summary": "Current analysis of Bullhorn's staffing CRM and ATS, Amplify AI, automation, analytics, back-office boundaries, integrations, and buyer controls.",
      "html_url": "https://digidai.github.io/2025/11/06/bullhorn-comprehensive-strategic-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/06/bullhorn-comprehensive-strategic-analysis/index.md",
      "date_published": "2025-11-06T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "bullhorn",
        "staffing software",
        "recruitment crm",
        "applicant tracking system",
        "bullhorn amplify",
        "recruitment automation",
        "staffing ai",
        "pay and bill"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/06/eddy-comprehensive-deep-analysis/",
      "title": "Eddy HR: Small-Business HR, Payroll, and Hiring Analysis",
      "summary": "Current buyer analysis of Eddy's HR records, onboarding, time tracking, U.S. payroll, hiring, permissions, pricing, and operational controls for small businesses.",
      "html_url": "https://digidai.github.io/2025/11/06/eddy-comprehensive-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/06/eddy-comprehensive-deep-analysis/index.md",
      "date_published": "2025-11-06T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "eddy hr",
        "small business hr software",
        "payroll software",
        "applicant tracking system",
        "employee onboarding",
        "time tracking",
        "hris",
        "hourly workforce"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/06/mitratech-talentreef-comprehensive-strategic-analysis/",
      "title": "Mitratech TalentReef: High-Volume Hourly Hiring Analysis",
      "summary": "Current analysis of TalentReef's multi-location hourly recruiting, mobile application, onboarding, AI, integrations, contract boundaries, and compliance controls.",
      "html_url": "https://digidai.github.io/2025/11/06/mitratech-talentreef-comprehensive-strategic-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/06/mitratech-talentreef-comprehensive-strategic-analysis/index.md",
      "date_published": "2025-11-06T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "mitratech talentreef",
        "hourly hiring",
        "high-volume recruiting",
        "multi-location ats",
        "mobile application",
        "recruiting chatbot",
        "employee onboarding",
        "i-9 workflow"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/05/jazzhr-comprehensive-analysis/",
      "title": "JazzHR: SMB Applicant Tracking System Analysis",
      "summary": "Current buyer analysis of JazzHR's plans, applicant workflows, automation, integrations, reporting, and controls for small and midsize employers.",
      "html_url": "https://digidai.github.io/2025/11/05/jazzhr-comprehensive-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/05/jazzhr-comprehensive-analysis/index.md",
      "date_published": "2025-11-05T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "jazzhr",
        "applicant tracking system",
        "ats",
        "small business recruiting",
        "smb hiring software",
        "workflow automation",
        "candidate management",
        "recruiting reporting"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/05/pcrecruiter-comprehensive-analysis/",
      "title": "PCRecruiter: Agency ATS and Recruitment CRM Analysis",
      "summary": "Current analysis of PCRecruiter's PCRM platform, agency workflow, AI features, API controls, data ownership, and fit for recruiting and executive-search firms.",
      "html_url": "https://digidai.github.io/2025/11/05/pcrecruiter-comprehensive-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/05/pcrecruiter-comprehensive-analysis/index.md",
      "date_published": "2025-11-05T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "pcrecruiter",
        "pcrm",
        "staffing agency software",
        "recruitment crm",
        "applicant tracking system",
        "executive search software",
        "recruiting api",
        "candidate database"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/05/recruitee-comprehensive-analysis/",
      "title": "Tellent Recruitee: Collaborative ATS Analysis",
      "summary": "Current analysis of Tellent Recruitee's plans, collaborative hiring, automation, AI screening, integrations, security, and data governance.",
      "html_url": "https://digidai.github.io/2025/11/05/recruitee-comprehensive-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/05/recruitee-comprehensive-analysis/index.md",
      "date_published": "2025-11-05T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "tellent recruitee",
        "recruitee",
        "collaborative hiring",
        "applicant tracking system",
        "ats",
        "recruiting automation",
        "ai screening",
        "employee referrals"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/04/boon-comprehensive-analysis/",
      "title": "Boon Referral Program Implementation: Controls and Tests",
      "summary": "A source-bound implementation guide for the Boon employee and external referral platform, covering attribution, rewards, integrations, security, privacy, and pilot acceptance.",
      "html_url": "https://digidai.github.io/2025/11/04/boon-comprehensive-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/04/boon-comprehensive-analysis/index.md",
      "date_published": "2025-11-04T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "boon",
        "employee referrals",
        "recruiting operations",
        "ats integration",
        "implementation guide"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/04/freshteam-comprehensive-analysis/",
      "title": "Freshteam Sunset Guide: Export, Migration, and Data Controls",
      "summary": "A source-bound guide to the 2026 Freshteam sunset, covering official deadlines, export scope, migration sequencing, privacy, integrations, reconciliation, and closure evidence.",
      "html_url": "https://digidai.github.io/2025/11/04/freshteam-comprehensive-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/04/freshteam-comprehensive-analysis/index.md",
      "date_published": "2025-11-04T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "freshteam",
        "software sunset",
        "ats migration",
        "hr data export",
        "recruiting operations"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/04/gem-comprehensive-analysis/",
      "title": "Gem Recruiting Platform: ATS, CRM, AI, and Buyer Controls",
      "summary": "Current analysis of Gem's ATS, recruiting CRM, AI agents, integrations, data governance, and fit for growth and enterprise teams.",
      "html_url": "https://digidai.github.io/2025/11/04/gem-comprehensive-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/04/gem-comprehensive-analysis/index.md",
      "date_published": "2025-11-04T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "gem",
        "recruiting platform",
        "applicant tracking system",
        "talent crm",
        "candidate sourcing",
        "recruiting analytics",
        "ai recruiting",
        "talent acquisition"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/03/folks-hr-comprehensive-analysis/",
      "title": "Folks HR Review: Canadian HRIS, ATS, Payroll, and AI Terms",
      "summary": "A source-bound Folks HR review covering Canadian product scope, dated pricing, ATS and payroll boundaries, data residency claims, AI terms, and buying tests.",
      "html_url": "https://digidai.github.io/2025/11/03/folks-hr-comprehensive-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/03/folks-hr-comprehensive-analysis/index.md",
      "date_published": "2025-11-03T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "folks hr",
        "canadian hr software",
        "applicant tracking system",
        "payroll software",
        "vendor evaluation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/03/manatal-comprehensive-analysis/",
      "title": "Manatal Implementation Guide: Migration and Acceptance Tests",
      "summary": "A source-bound Manatal implementation guide covering plan limits, ATS migration, AI controls, API access, security diligence, cutover, and measurable acceptance tests.",
      "html_url": "https://digidai.github.io/2025/11/03/manatal-comprehensive-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/03/manatal-comprehensive-analysis/index.md",
      "date_published": "2025-11-03T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "manatal",
        "ats implementation",
        "data migration",
        "recruiting operations",
        "vendor evaluation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/03/pinpoint-comprehensive-deep-analysis/",
      "title": "Pinpoint ATS Review: AI, Integrations, and Buying Tests",
      "summary": "A source-bound review of Pinpoint ATS covering recruiting workflow, AI and interview controls, API and integration maturity, subprocessors, pricing questions, and procurement tests.",
      "html_url": "https://digidai.github.io/2025/11/03/pinpoint-comprehensive-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/03/pinpoint-comprehensive-deep-analysis/index.md",
      "date_published": "2025-11-03T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "pinpoint ats",
        "applicant tracking system",
        "ai recruiting",
        "hr technology",
        "vendor evaluation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/03/recruit-crm-comprehensive-analysis/",
      "title": "Recruit CRM Review: Agency Workflow and Buying Tests",
      "summary": "A source-bound Recruit CRM review for staffing and search firms, covering ATS and CRM boundaries, plans, automation, integrations, data terms, security, and acceptance tests.",
      "html_url": "https://digidai.github.io/2025/11/03/recruit-crm-comprehensive-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/03/recruit-crm-comprehensive-analysis/index.md",
      "date_published": "2025-11-03T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "recruit crm",
        "recruitment agency software",
        "applicant tracking system",
        "crm",
        "vendor evaluation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/02/darwinbox-strategic-deep-research/",
      "title": "Darwinbox: Enterprise HCM Platform Review",
      "summary": "A current review of Darwinbox HCM, Cortex AI, global payroll positioning, pricing limits, and enterprise implementation checks.",
      "html_url": "https://digidai.github.io/2025/11/02/darwinbox-strategic-deep-research/",
      "markdown_url": "https://digidai.github.io/2025/11/02/darwinbox-strategic-deep-research/index.md",
      "date_published": "2025-11-02T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "darwinbox",
        "hcm software",
        "enterprise hr",
        "ai governance"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/02/greenhouse-comprehensive-deep-analysis/",
      "title": "Greenhouse: Hiring Software Platform Review",
      "summary": "A current review of Greenhouse pricing tiers, structured hiring, AI terms, MCP beta, compliance boundaries, and buying checks.",
      "html_url": "https://digidai.github.io/2025/11/02/greenhouse-comprehensive-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/02/greenhouse-comprehensive-deep-analysis/index.md",
      "date_published": "2025-11-02T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "greenhouse",
        "applicant tracking system",
        "structured hiring",
        "recruiting software"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/02/hrone-comprehensive-deep-analysis/",
      "title": "HROne: China's HR Partner for Global Expansion",
      "summary": "A current review of HROne China EOR, PEO, payroll services, compliance boundaries, data risks, and buyer diligence.",
      "html_url": "https://digidai.github.io/2025/11/02/hrone-comprehensive-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/02/hrone-comprehensive-deep-analysis/index.md",
      "date_published": "2025-11-02T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "hrone",
        "china employer of record",
        "payroll outsourcing",
        "global expansion"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/02/keka-hr-comprehensive-analysis/",
      "title": "Keka HR: Cloud HRMS and Payroll Review",
      "summary": "A current review of Keka HRMS, India and US payroll positioning, pricing boundaries, security claims, and implementation checks.",
      "html_url": "https://digidai.github.io/2025/11/02/keka-hr-comprehensive-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/02/keka-hr-comprehensive-analysis/index.md",
      "date_published": "2025-11-02T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "keka hr",
        "payroll software",
        "hrms",
        "india hr technology"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/02/orangehrm-strategic-deep-research/",
      "title": "OrangeHRM: Open Source HRMS Platform Analysis",
      "summary": "A current review of OrangeHRM Starter and Advanced, open-source duties, pricing, security, privacy, and deployment tradeoffs.",
      "html_url": "https://digidai.github.io/2025/11/02/orangehrm-strategic-deep-research/",
      "markdown_url": "https://digidai.github.io/2025/11/02/orangehrm-strategic-deep-research/index.md",
      "date_published": "2025-11-02T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "orangehrm",
        "open source hrms",
        "self hosted software",
        "human resources"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/02/peoplefluent-strategic-deep-research/",
      "title": "PeopleFluent Review: Enterprise Talent Suite and Buying Tests",
      "summary": "A source-bound review of PeopleFluent recruiting and talent management, with integration, security, governance, and procurement tests for enterprise buyers.",
      "html_url": "https://digidai.github.io/2025/11/02/peoplefluent-strategic-deep-research/",
      "markdown_url": "https://digidai.github.io/2025/11/02/peoplefluent-strategic-deep-research/index.md",
      "date_published": "2025-11-02T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "peoplefluent",
        "talent management",
        "recruiting software",
        "enterprise hr technology",
        "vendor evaluation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/02/rippling-recruiting-comprehensive-analysis/",
      "title": "Rippling Recruiting Review: Unified Data and Buying Tests",
      "summary": "A source-bound assessment of Rippling Recruiting, including HRIS dependency, AI screening controls, integrations, pricing questions, and a practical evaluation plan.",
      "html_url": "https://digidai.github.io/2025/11/02/rippling-recruiting-comprehensive-analysis/",
      "markdown_url": "https://digidai.github.io/2025/11/02/rippling-recruiting-comprehensive-analysis/index.md",
      "date_published": "2025-11-02T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "rippling",
        "applicant tracking system",
        "recruiting software",
        "hris",
        "vendor evaluation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/02/sage-hr-strategic-deep-research/",
      "title": "Sage HR Review: Modules, Pricing, API, and Buying Tests",
      "summary": "A source-bound Sage HR review for smaller employers, covering current module boundaries, US pricing, recruitment, API access, privacy, and implementation tests.",
      "html_url": "https://digidai.github.io/2025/11/02/sage-hr-strategic-deep-research/",
      "markdown_url": "https://digidai.github.io/2025/11/02/sage-hr-strategic-deep-research/index.md",
      "date_published": "2025-11-02T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "sage hr",
        "hr software",
        "recruitment software",
        "small business",
        "vendor evaluation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/02/sage-people-enterprise-strategic-deep-research/",
      "title": "Sage People: Global HR for Mid-Sized Organizations",
      "summary": "A sourced review of Sage People, its Fairsail history, Salesforce foundation, global HR capabilities, and implementation tradeoffs.",
      "html_url": "https://digidai.github.io/2025/11/02/sage-people-enterprise-strategic-deep-research/",
      "markdown_url": "https://digidai.github.io/2025/11/02/sage-people-enterprise-strategic-deep-research/index.md",
      "date_published": "2025-11-02T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "sage people",
        "global hr software",
        "mid-sized organizations",
        "salesforce hris",
        "fairsail",
        "people management"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/11/02/zimyo-strategic-deep-research/",
      "title": "Zimyo Review: HRMS Pricing, Data Terms, and Buying Tests",
      "summary": "A source-bound review of Zimyo HRMS and recruitment, with dated pricing, regional scope, privacy and AI questions, integrations, and procurement acceptance tests.",
      "html_url": "https://digidai.github.io/2025/11/02/zimyo-strategic-deep-research/",
      "markdown_url": "https://digidai.github.io/2025/11/02/zimyo-strategic-deep-research/index.md",
      "date_published": "2025-11-02T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "zimyo",
        "hrms",
        "payroll software",
        "recruitment software",
        "vendor evaluation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/10/25/zoho-people-strategic-deep-research/",
      "title": "Zoho People: SMB Human Capital Management Analysis",
      "summary": "A current review of Zoho People pricing, modules, Zia AI, privacy-sensitive attendance features, and buying checks.",
      "html_url": "https://digidai.github.io/2025/10/25/zoho-people-strategic-deep-research/",
      "markdown_url": "https://digidai.github.io/2025/10/25/zoho-people-strategic-deep-research/index.md",
      "date_published": "2025-10-25T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "zoho people",
        "hrms",
        "small business",
        "zia ai"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/10/24/namely-strategic-deep-research/",
      "title": "Namely: Mid-Market Employee Experience Platform",
      "summary": "A current review of Namely HR, payroll, benefits, services, ownership context, and the checks US mid-market buyers should run.",
      "html_url": "https://digidai.github.io/2025/10/24/namely-strategic-deep-research/",
      "markdown_url": "https://digidai.github.io/2025/10/24/namely-strategic-deep-research/index.md",
      "date_published": "2025-10-24T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "namely",
        "payroll",
        "benefits administration",
        "mid-market hr"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/10/24/personio-strategic-deep-research/",
      "title": "Personio: European All-in-One HR Platform",
      "summary": "A current, evidence-based review of Personio core HR, apps, payroll, AI features, pricing, and European compliance questions.",
      "html_url": "https://digidai.github.io/2025/10/24/personio-strategic-deep-research/",
      "markdown_url": "https://digidai.github.io/2025/10/24/personio-strategic-deep-research/index.md",
      "date_published": "2025-10-24T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "personio",
        "european hr software",
        "recruiting",
        "hr automation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/10/23/sage-people-enterprise-strategic-deep-research/",
      "title": "Sage People: Global Mid-Market HR Platform",
      "summary": "A current review of Sage People, its Salesforce foundation, multinational HR scope, limits, and enterprise buying questions.",
      "html_url": "https://digidai.github.io/2025/10/23/sage-people-enterprise-strategic-deep-research/",
      "markdown_url": "https://digidai.github.io/2025/10/23/sage-people-enterprise-strategic-deep-research/index.md",
      "date_published": "2025-10-23T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "sage people",
        "global hr platform",
        "salesforce",
        "human capital management"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/10/21/sage-hr-strategic-deep-research/",
      "title": "Sage HR: Affordable SMB Workforce Platform",
      "summary": "A current, evidence-based review of Sage HR pricing, modules, limits, and the checks small businesses should run before buying.",
      "html_url": "https://digidai.github.io/2025/10/21/sage-hr-strategic-deep-research/",
      "markdown_url": "https://digidai.github.io/2025/10/21/sage-hr-strategic-deep-research/index.md",
      "date_published": "2025-10-21T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "sage hr",
        "hr software",
        "small business",
        "workforce management"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/10/18/paycor-strategic-deep-research/",
      "title": "Paycor After Paychex: HCM Scope, AI, and Buyer Roadmap",
      "summary": "Paycor is now a Paychex-owned HCM platform for larger and more complex employers. This review covers current product scope, ownership, AI controls, payroll evidence, and roadmap questions.",
      "html_url": "https://digidai.github.io/2025/10/18/paycor-strategic-deep-research/",
      "markdown_url": "https://digidai.github.io/2025/10/18/paycor-strategic-deep-research/index.md",
      "date_published": "2025-10-18T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "paycor",
        "paychex",
        "payroll",
        "hcm",
        "paycor assistant"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/10/18/paylocity-strategic-deep-research/",
      "title": "Paylocity: HCM Expansion, AI Actions, and Buyer Controls",
      "summary": "Paylocity now markets a wider HR, payroll, finance, and IT platform. This review maps the current product boundary and the payroll, integration, permission, and AI evidence buyers need.",
      "html_url": "https://digidai.github.io/2025/10/18/paylocity-strategic-deep-research/",
      "markdown_url": "https://digidai.github.io/2025/10/18/paylocity-strategic-deep-research/index.md",
      "date_published": "2025-10-18T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "paylocity",
        "hcm",
        "payroll",
        "ignite ai",
        "workforce management"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/10/17/adp-vantage-hcm-strategic-deep-research/",
      "title": "ADP Vantage HCM: Current Status and Enterprise Roadmap",
      "summary": "ADP continues to support Vantage HCM while positioning Lyric for new global-enterprise demand. This review explains what existing Vantage customers should verify before extending or migrating.",
      "html_url": "https://digidai.github.io/2025/10/17/adp-vantage-hcm-strategic-deep-research/",
      "markdown_url": "https://digidai.github.io/2025/10/17/adp-vantage-hcm-strategic-deep-research/index.md",
      "date_published": "2025-10-17T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "adp vantage hcm",
        "enterprise payroll",
        "hcm migration",
        "adp lyric",
        "workforce management"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/10/17/adp-workforce-now-strategic-deep-research/",
      "title": "ADP Workforce Now: Product Scope and Buyer Controls",
      "summary": "ADP Workforce Now combines North American payroll and HR workflows with optional benefits, time, talent, analytics, and AI. This review separates documented scope from outcome claims.",
      "html_url": "https://digidai.github.io/2025/10/17/adp-workforce-now-strategic-deep-research/",
      "markdown_url": "https://digidai.github.io/2025/10/17/adp-workforce-now-strategic-deep-research/index.md",
      "date_published": "2025-10-17T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "adp workforce now",
        "payroll",
        "hcm",
        "adp assist",
        "workforce management"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/10/17/bamboohr-strategic-deep-research/",
      "title": "BambooHR: Platform Scope, Payroll Boundaries, and AI Controls",
      "summary": "BambooHR spans employee records, hiring, onboarding, payroll, benefits, time, performance, and newer AI workflows. This review shows what growing organizations should verify.",
      "html_url": "https://digidai.github.io/2025/10/17/bamboohr-strategic-deep-research/",
      "markdown_url": "https://digidai.github.io/2025/10/17/bamboohr-strategic-deep-research/index.md",
      "date_published": "2025-10-17T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "bamboohr",
        "hris",
        "payroll",
        "bamboo ai",
        "people operations"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/10/17/ceridian-dayforce-strategic-deep-research/",
      "title": "Dayforce: Unified HCM, Time-to-Pay, and Ownership Update",
      "summary": "Ceridian became Dayforce in 2024 and Dayforce became privately owned in 2026. This review examines its unified HCM claim, time-to-pay controls, privacy, and buyer evidence.",
      "html_url": "https://digidai.github.io/2025/10/17/ceridian-dayforce-strategic-deep-research/",
      "markdown_url": "https://digidai.github.io/2025/10/17/ceridian-dayforce-strategic-deep-research/index.md",
      "date_published": "2025-10-17T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "dayforce",
        "ceridian",
        "payroll",
        "workforce management",
        "hcm"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/10/17/oracle-hcm-cloud-strategic-deep-research/",
      "title": "Oracle Fusion Cloud HCM: Suite Architecture and AI Governance",
      "summary": "Oracle Fusion Cloud HCM connects HR, talent, workforce management, payroll, employee experience, and analytics. This review focuses on release scope, security, integrations, and AI-agent controls.",
      "html_url": "https://digidai.github.io/2025/10/17/oracle-hcm-cloud-strategic-deep-research/",
      "markdown_url": "https://digidai.github.io/2025/10/17/oracle-hcm-cloud-strategic-deep-research/index.md",
      "date_published": "2025-10-17T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "oracle fusion cloud hcm",
        "oracle hcm",
        "ai agents",
        "payroll",
        "enterprise hcm"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/10/17/sap-successfactors-strategic-deep-research/",
      "title": "SAP SuccessFactors Strategy: Data, Joule, and Recruiting Change",
      "summary": "SAP is connecting SuccessFactors with Business Data Cloud, People Intelligence, Joule, and SmartRecruiters. This review tests the strategic architecture and migration questions behind that direction.",
      "html_url": "https://digidai.github.io/2025/10/17/sap-successfactors-strategic-deep-research/",
      "markdown_url": "https://digidai.github.io/2025/10/17/sap-successfactors-strategic-deep-research/index.md",
      "date_published": "2025-10-17T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "sap successfactors",
        "joule",
        "people intelligence",
        "business data cloud",
        "smartrecruiters",
        "strategic deep research",
        "workforce analytics",
        "workforce intelligence"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/10/17/ukg-pro-ready-strategic-deep-research/",
      "title": "UKG Pro vs UKG Ready: Product Boundaries and Buyer Tests",
      "summary": "UKG Pro and UKG Ready target different workforce complexity. This review separates their documented scope, explains the Dimensions rename, and defines payroll, WFM, integration, and AI controls.",
      "html_url": "https://digidai.github.io/2025/10/17/ukg-pro-ready-strategic-deep-research/",
      "markdown_url": "https://digidai.github.io/2025/10/17/ukg-pro-ready-strategic-deep-research/index.md",
      "date_published": "2025-10-17T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "ukg pro",
        "ukg ready",
        "workforce management",
        "payroll",
        "hcm"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/10/17/workday-hcm-strategic-deep-research/",
      "title": "Workday HCM: Platform, Talent AI, and Control Boundaries",
      "summary": "Workday HCM spans workforce records, talent, payroll-related processes, planning, analytics, and AI. This review examines platform claims, acquired talent tools, permissions, and release governance.",
      "html_url": "https://digidai.github.io/2025/10/17/workday-hcm-strategic-deep-research/",
      "markdown_url": "https://digidai.github.io/2025/10/17/workday-hcm-strategic-deep-research/index.md",
      "date_published": "2025-10-17T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "workday hcm",
        "workday illuminate",
        "hiredscore",
        "talent acquisition",
        "enterprise hcm"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/10/16/humanly-comprehensive-deep-analysis/",
      "title": "Humanly's Conversational AI for High-Volume Recruiting",
      "summary": "A source-checked review of Humanly's expanded recruiting platform, AI interviews, privacy, and controls.",
      "html_url": "https://digidai.github.io/2025/10/16/humanly-comprehensive-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/10/16/humanly-comprehensive-deep-analysis/index.md",
      "date_published": "2025-10-16T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "humanly",
        "conversational ai recruiting",
        "high-volume hiring",
        "ai interviewer",
        "recruiting crm",
        "applicant tracking"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/10/11/canditech-comprehensive-deep-analysis/",
      "title": "Canditech Review: The Skills Assessment Platform's Evidence",
      "summary": "A sourced review of Canditech's scoring, proctoring, pricing, security, and validation.",
      "html_url": "https://digidai.github.io/2025/10/11/canditech-comprehensive-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/10/11/canditech-comprehensive-deep-analysis/index.md",
      "date_published": "2025-10-11T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Canditech",
        "Skills Assessment",
        "Job Simulation",
        "AI Hiring",
        "Employment Testing",
        "Candidate Experience",
        "Recruiting Technology"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/10/11/feishu-comprehensive-deep-analysis/",
      "title": "Feishu's ByteDance Collaboration and AI Platform",
      "summary": "A source-checked review of Feishu's collaboration suite, AI pricing, agent access, and data controls.",
      "html_url": "https://digidai.github.io/2025/10/11/feishu-comprehensive-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/10/11/feishu-comprehensive-deep-analysis/index.md",
      "date_published": "2025-10-11T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "feishu",
        "bytedance",
        "collaboration platform",
        "feishu ai",
        "ai agent",
        "enterprise productivity"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/10/11/manatal-strategic-enterprise-implementation-mastery/",
      "title": "Manatal's ATS and Recruiting CRM Implementation Guide",
      "summary": "A source-checked guide to Manatal's product, pricing, AI matching, security, and controlled rollout.",
      "html_url": "https://digidai.github.io/2025/10/11/manatal-strategic-enterprise-implementation-mastery/",
      "markdown_url": "https://digidai.github.io/2025/10/11/manatal-strategic-enterprise-implementation-mastery/index.md",
      "date_published": "2025-10-11T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "manatal",
        "applicant tracking",
        "recruiting crm",
        "recruitment agency software",
        "ai candidate matching",
        "implementation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/10/09/amazinghiring-comprehensive-deep-analysis/",
      "title": "AmazingHiring Review: Technical Sourcing, Outreach, and Workflow Limits",
      "summary": "A source-bound operator review of AmazingHiring's technical-talent search, profile aggregation, outreach, ATS integrations, pricing model, data controls, and pilot requirements.",
      "html_url": "https://digidai.github.io/2025/10/09/amazinghiring-comprehensive-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/10/09/amazinghiring-comprehensive-deep-analysis/index.md",
      "date_published": "2025-10-09T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AmazingHiring",
        "Technical Recruiting",
        "Candidate Sourcing",
        "Recruiting Operations",
        "Recruitment Software"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/10/09/amazinghiring-strategic-enterprise-analysis/",
      "title": "AmazingHiring Enterprise Analysis: Procurement, Data, and Integration",
      "summary": "A source-bound enterprise buying guide to AmazingHiring covering architecture, data provenance, ATS integration, security, AI governance, total cost, implementation, and acceptance tests.",
      "html_url": "https://digidai.github.io/2025/10/09/amazinghiring-strategic-enterprise-analysis/",
      "markdown_url": "https://digidai.github.io/2025/10/09/amazinghiring-strategic-enterprise-analysis/index.md",
      "date_published": "2025-10-09T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AmazingHiring",
        "Enterprise Recruitment",
        "Recruiting Procurement",
        "Data Governance",
        "ATS Integration"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/10/09/boon-ai-referral-platform-deep-analysis/",
      "title": "Boon Referral Platform Review: Workflow, AI Claims, and Buying Tests",
      "summary": "A source-bound review of Boon's employee and external referral platform, covering workflow, matching, rewards, ATS integration, security, pricing, measurement, and procurement tests.",
      "html_url": "https://digidai.github.io/2025/10/09/boon-ai-referral-platform-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/10/09/boon-ai-referral-platform-deep-analysis/index.md",
      "date_published": "2025-10-09T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Boon",
        "Employee Referrals",
        "Recruitment Software",
        "Talent Sourcing",
        "AI Hiring"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/10/09/heymilo-comprehensive-deep-analysis/",
      "title": "HeyMilo Review: AI Screening, Interviews, and Deployment Controls",
      "summary": "A source-bound review of HeyMilo's AI recruiting agents for forms, SMS, voice, and video, including ATS integration, scoring, privacy, accessibility, compliance, pricing, and pilot tests.",
      "html_url": "https://digidai.github.io/2025/10/09/heymilo-comprehensive-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/10/09/heymilo-comprehensive-deep-analysis/index.md",
      "date_published": "2025-10-09T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "HeyMilo",
        "AI Interviews",
        "Candidate Screening",
        "Recruitment Technology",
        "AI Governance"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/10/09/manatal-ats-comprehensive-deep-analysis/",
      "title": "Manatal ATS Review: Workflow, AI Features, Pricing, and Buying Tests",
      "summary": "A source-bound review of Manatal's applicant tracking system, current pricing, AI recommendations, API, migration, security, privacy, implementation, and procurement evidence.",
      "html_url": "https://digidai.github.io/2025/10/09/manatal-ats-comprehensive-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/10/09/manatal-ats-comprehensive-deep-analysis/index.md",
      "date_published": "2025-10-09T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Manatal",
        "Applicant Tracking System",
        "AI Recruitment",
        "Recruiting Operations",
        "HR Technology"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/10/09/sonara-ai-comprehensive-deep-analysis/",
      "title": "Sonara.ai Review: Current Ownership, Auto-Apply Workflow, and Risks",
      "summary": "A source-bound review of Sonara.ai under BOLD, covering its current AI job search and auto-apply service, data sharing, subscriptions, application quality, accessibility, safety, and user controls.",
      "html_url": "https://digidai.github.io/2025/10/09/sonara-ai-comprehensive-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/10/09/sonara-ai-comprehensive-deep-analysis/index.md",
      "date_published": "2025-10-09T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Sonara.ai",
        "Job Search",
        "AI Automation",
        "Career Technology",
        "Job Applications"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/10/09/willo-video-comprehensive-deep-analysis/",
      "title": "Willo Review: Asynchronous Interviews, AI Assistance, and Buying Tests",
      "summary": "A source-bound review of Willo's asynchronous candidate screening, AI summaries, integrations, identity and anti-cheating tools, pricing, accessibility, security, and procurement controls.",
      "html_url": "https://digidai.github.io/2025/10/09/willo-video-comprehensive-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/10/09/willo-video-comprehensive-deep-analysis/index.md",
      "date_published": "2025-10-09T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Willo",
        "Video Interviews",
        "Candidate Screening",
        "Recruitment Technology",
        "AI Governance"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/09/16/linkedin-hiring-assistant-2025-deep-research/",
      "title": "LinkedIn's Hiring Assistant for Recruiter",
      "summary": "A source-checked review of LinkedIn's Hiring Assistant, data use, controls, packaging, and risks.",
      "html_url": "https://digidai.github.io/2025/09/16/linkedin-hiring-assistant-2025-deep-research/",
      "markdown_url": "https://digidai.github.io/2025/09/16/linkedin-hiring-assistant-2025-deep-research/index.md",
      "date_published": "2025-09-16T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "linkedin hiring assistant",
        "linkedin recruiter",
        "ai recruiting agent",
        "candidate search",
        "recruiter ai"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/08/12/ai-interview-systems-2025-revolutionary-developments-in-auto/",
      "title": "AI Interview Systems in 2025: A Buyer Map for Coordination, Evidence, and Scoring",
      "summary": "A vendor-neutral framework for distinguishing interview scheduling, recording, transcription, question delivery, summarization, and automated assessment.",
      "html_url": "https://digidai.github.io/2025/08/12/ai-interview-systems-2025-revolutionary-developments-in-auto/",
      "markdown_url": "https://digidai.github.io/2025/08/12/ai-interview-systems-2025-revolutionary-developments-in-auto/index.md",
      "date_published": "2025-08-12T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI interviews",
        "HR technology",
        "candidate assessment",
        "software procurement"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/08/12/ai-powered-skills-assessment-platforms-revolutionizing-techn/",
      "title": "AI Skills Assessment Platforms: A Build-or-Buy and Validation Guide",
      "summary": "A vendor-neutral guide to skill taxonomies, work samples, adaptive tests, evidence mapping, validation, accessibility, and platform change control.",
      "html_url": "https://digidai.github.io/2025/08/12/ai-powered-skills-assessment-platforms-revolutionizing-techn/",
      "markdown_url": "https://digidai.github.io/2025/08/12/ai-powered-skills-assessment-platforms-revolutionizing-techn/index.md",
      "date_published": "2025-08-12T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "skills assessment",
        "HR technology",
        "work samples",
        "software procurement"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/08/09/ukg-pro-comprehensive-enterprise-analysis/",
      "title": "UKG Pro: Modules, Pricing Questions and Implementation Checks",
      "summary": "Understand UKG Pro versus Ready, separate HCM from workforce management, and build a quote and implementation checklist from current UKG documentation.",
      "html_url": "https://digidai.github.io/2025/08/09/ukg-pro-comprehensive-enterprise-analysis/",
      "markdown_url": "https://digidai.github.io/2025/08/09/ukg-pro-comprehensive-enterprise-analysis/index.md",
      "date_published": "2025-08-09T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "UKG",
        "HCM",
        "Workforce Management",
        "HR Technology",
        "Procurement"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/08/07/criteria-corp-comprehensive-assessment-analysis/",
      "title": "Criteria: Pre-Employment Assessments and Talent Development",
      "summary": "A sourced review of Criteria cognitive, emotional-intelligence, and development products, with guidance on validation and candidate safeguards.",
      "html_url": "https://digidai.github.io/2025/08/07/criteria-corp-comprehensive-assessment-analysis/",
      "markdown_url": "https://digidai.github.io/2025/08/07/criteria-corp-comprehensive-assessment-analysis/index.md",
      "date_published": "2025-08-07T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "criteria corp",
        "ccat",
        "pre-employment assessment",
        "emotional intelligence",
        "coach bo",
        "hiring validation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/08/06/hackerrank-comprehensive-platform-analysis/",
      "title": "HackerRank's Developer Assessment Platform",
      "summary": "A source-checked review of HackerRank's assessments, interviews, proctoring, AI, and hiring controls.",
      "html_url": "https://digidai.github.io/2025/08/06/hackerrank-comprehensive-platform-analysis/",
      "markdown_url": "https://digidai.github.io/2025/08/06/hackerrank-comprehensive-platform-analysis/index.md",
      "date_published": "2025-08-06T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "hackerrank",
        "developer assessment",
        "coding interview",
        "technical hiring",
        "proctoring",
        "ai interviewer"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/08/04/hackerrank-platform-study/",
      "title": "HackerRank: Developer Skills Assessment and Interviewing",
      "summary": "A sourced review of HackerRank assessments, interviews, AI use, integrity signals, and the metrics technical-hiring teams should verify.",
      "html_url": "https://digidai.github.io/2025/08/04/hackerrank-platform-study/",
      "markdown_url": "https://digidai.github.io/2025/08/04/hackerrank-platform-study/index.md",
      "date_published": "2025-08-04T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "hackerrank",
        "developer assessment",
        "coding interview",
        "technical hiring",
        "ai skills",
        "test integrity"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/08/03/codility-deep-technical-analysis/",
      "title": "Codility: Technical Assessment in an AI-Assisted Engineering Market",
      "summary": "A sourced analysis of Codility assessments, the Engineering Skills Model, AI-assisted coding, integrity controls, and buyer validation.",
      "html_url": "https://digidai.github.io/2025/08/03/codility-deep-technical-analysis/",
      "markdown_url": "https://digidai.github.io/2025/08/03/codility-deep-technical-analysis/index.md",
      "date_published": "2025-08-03T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "codility",
        "technical assessment",
        "engineering skills model",
        "ai-assisted coding",
        "developer hiring",
        "assessment validation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/07/26/bamboohr-comprehensive-deep-analysis/",
      "title": "BambooHR's SMB Human Capital Management Platform",
      "summary": "A source-checked review of BambooHR's HR suite, pricing, AI release, add-ons, and buyer controls.",
      "html_url": "https://digidai.github.io/2025/07/26/bamboohr-comprehensive-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/07/26/bamboohr-comprehensive-deep-analysis/index.md",
      "date_published": "2025-07-26T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "bamboohr",
        "hris",
        "hcm",
        "payroll",
        "applicant tracking",
        "bamboo ai"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/07/26/hirevue-deep-analysis/",
      "title": "HireVue: Video Interviewing, Assessments, and AI Governance",
      "summary": "A sourced analysis of HireVue video interviews, assessments, explainability controls, and the evidence employers should request.",
      "html_url": "https://digidai.github.io/2025/07/26/hirevue-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/07/26/hirevue-deep-analysis/index.md",
      "date_published": "2025-07-26T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "hirevue",
        "video interviewing",
        "hiring assessments",
        "ai governance",
        "candidate accommodation",
        "talent acquisition"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/07/26/icims-deep-platform-analysis/",
      "title": "iCIMS' Enterprise Talent Acquisition Platform",
      "summary": "A source-checked analysis of iCIMS' ATS, CRM, AI recruiting features, governance, and buying fit.",
      "html_url": "https://digidai.github.io/2025/07/26/icims-deep-platform-analysis/",
      "markdown_url": "https://digidai.github.io/2025/07/26/icims-deep-platform-analysis/index.md",
      "date_published": "2025-07-26T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "icims",
        "talent cloud",
        "applicant tracking",
        "recruiting crm",
        "ai recruiting",
        "talent acquisition"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/07/26/jobvite-platform-deep-dive/",
      "title": "Jobvite: ATS, CRM, Recruitment Marketing, and AI Matching",
      "summary": "A sourced review of Jobvite recruiting workflows, integrations, AI matching, and the controls buyers should verify.",
      "html_url": "https://digidai.github.io/2025/07/26/jobvite-platform-deep-dive/",
      "markdown_url": "https://digidai.github.io/2025/07/26/jobvite-platform-deep-dive/index.md",
      "date_published": "2025-07-26T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "jobvite",
        "applicant tracking system",
        "recruitment crm",
        "recruitment marketing",
        "ai matching",
        "talent acquisition"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/07/26/pymetrics-comprehensive-analysis/",
      "title": "Pymetrics and Harver: Game-Based Talent Assessment",
      "summary": "A sourced review of the Pymetrics assessment approach, its acquisition by Harver, bias-audit tooling, and employer validation duties.",
      "html_url": "https://digidai.github.io/2025/07/26/pymetrics-comprehensive-analysis/",
      "markdown_url": "https://digidai.github.io/2025/07/26/pymetrics-comprehensive-analysis/index.md",
      "date_published": "2025-07-26T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "pymetrics",
        "harver",
        "game-based assessment",
        "pre-employment testing",
        "audit-ai",
        "hiring validation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/07/26/smartrecruiters-comprehensive-study/",
      "title": "SmartRecruiters' SAP-Owned Recruiting Platform",
      "summary": "A source-checked review of SmartRecruiters' current product, SAP ownership, pricing, AI, and risks.",
      "html_url": "https://digidai.github.io/2025/07/26/smartrecruiters-comprehensive-study/",
      "markdown_url": "https://digidai.github.io/2025/07/26/smartrecruiters-comprehensive-study/index.md",
      "date_published": "2025-07-26T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "smartrecruiters",
        "sap",
        "applicant tracking",
        "recruiting crm",
        "ai hiring agent",
        "talent acquisition"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/07/26/workday-hcm-comprehensive-deep-analysis/",
      "title": "Workday HCM's Enterprise Skills and HR Platform",
      "summary": "A source-checked assessment of Workday HCM's suite, Skills Cloud, AI, governance, and buying fit.",
      "html_url": "https://digidai.github.io/2025/07/26/workday-hcm-comprehensive-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/07/26/workday-hcm-comprehensive-deep-analysis/index.md",
      "date_published": "2025-07-26T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "workday hcm",
        "skills cloud",
        "hris",
        "talent management",
        "workforce management",
        "responsible ai"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/07/26/yello-comprehensive-deep-analysis/",
      "title": "Yello's Campus Recruiting and Early Talent Platform",
      "summary": "A source-checked review of Yello's campus workflows, AI agent, Symba acquisition, privacy, and fit.",
      "html_url": "https://digidai.github.io/2025/07/26/yello-comprehensive-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/07/26/yello-comprehensive-deep-analysis/index.md",
      "date_published": "2025-07-26T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "yello",
        "campus recruiting",
        "early talent",
        "recruiting events",
        "symba",
        "ai recruiting"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/07/19/ai-recruitment-future-trends-2025-2030/",
      "title": "AI Recruitment 2025-2030: Scenarios, Leading Indicators, and No-Regret Controls",
      "summary": "A scenario framework for planning recruiting AI through 2030 without presenting model forecasts, vendor claims, or task exposure as settled outcomes.",
      "html_url": "https://digidai.github.io/2025/07/19/ai-recruitment-future-trends-2025-2030/",
      "markdown_url": "https://digidai.github.io/2025/07/19/ai-recruitment-future-trends-2025-2030/index.md",
      "date_published": "2025-07-19T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI recruitment",
        "scenario planning",
        "recruiting operations",
        "future of work"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/07/18/linkedin-hiring-assistant-deep-analysis/",
      "title": "LinkedIn Hiring Assistant: Workflow, Data, and Controls",
      "summary": "LinkedIn Hiring Assistant supports project setup, sourcing, candidate review, outreach, and prescreening. This review maps current functions, data sources, automation boundaries, and buyer tests.",
      "html_url": "https://digidai.github.io/2025/07/18/linkedin-hiring-assistant-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/07/18/linkedin-hiring-assistant-deep-analysis/index.md",
      "date_published": "2025-07-18T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "linkedin hiring assistant",
        "linkedin recruiter",
        "ai sourcing",
        "applicant review",
        "recruiting automation"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/07/17/lever-deep-analysis/",
      "title": "Lever: ATS, CRM, Workflow, and Buyer Controls",
      "summary": "Lever combines applicant tracking and candidate relationship workflows. This review maps documented capabilities, ownership context, integration boundaries, and evidence buyers should require.",
      "html_url": "https://digidai.github.io/2025/07/17/lever-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/07/17/lever-deep-analysis/index.md",
      "date_published": "2025-07-17T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "lever",
        "applicant tracking system",
        "recruitment crm",
        "candidate data",
        "recruiting operations"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/07/17/shl-deep-analysis/",
      "title": "SHL Assessments: Practice Tests, Scores and Buyer Checks",
      "summary": "Find official SHL practice help and learn how employers should evaluate test validity, scoring, accommodations and AI assessment claims.",
      "html_url": "https://digidai.github.io/2025/07/17/shl-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/07/17/shl-deep-analysis/index.md",
      "date_published": "2025-07-17T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "SHL",
        "Talent Assessment",
        "Psychometric Testing",
        "AI Recruitment",
        "Hiring"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/07/17/talview-deep-analysis/",
      "title": "Talview: Remote Hiring Workflow and Candidate Safeguards",
      "summary": "Talview offers interviewing, assessment, proctoring, and workflow tools. This review maps the documented product surface and the privacy, accessibility, and decision controls buyers must test.",
      "html_url": "https://digidai.github.io/2025/07/17/talview-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/07/17/talview-deep-analysis/index.md",
      "date_published": "2025-07-17T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "talview",
        "video interviewing",
        "candidate assessment",
        "remote hiring",
        "hiring governance"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/07/17/textio-comprehensive-analysis/",
      "title": "Textio: Augmented Writing, Evidence, and Buyer Controls",
      "summary": "Textio assists with recruiting and workplace language. This review separates the vendor's product claims from independent evidence and provides a testable evaluation framework.",
      "html_url": "https://digidai.github.io/2025/07/17/textio-comprehensive-analysis/",
      "markdown_url": "https://digidai.github.io/2025/07/17/textio-comprehensive-analysis/index.md",
      "date_published": "2025-07-17T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "textio",
        "augmented writing",
        "inclusive language",
        "job descriptions",
        "performance feedback"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/07/16/ziprecruiter-comprehensive-analysis/",
      "title": "ZipRecruiter: Marketplace Mechanics and Buyer Controls",
      "summary": "ZipRecruiter connects employers and job seekers through posting, distribution, matching, and outreach tools. This review separates documented functions from marketing claims and hiring outcomes.",
      "html_url": "https://digidai.github.io/2025/07/16/ziprecruiter-comprehensive-analysis/",
      "markdown_url": "https://digidai.github.io/2025/07/16/ziprecruiter-comprehensive-analysis/index.md",
      "date_published": "2025-07-16T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "ziprecruiter",
        "job marketplace",
        "smb hiring",
        "candidate matching",
        "recruitment technology"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/07/15/indeed-comprehensive-analysis/",
      "title": "Indeed: Job Marketplace Products, AI, and Buyer Controls",
      "summary": "Indeed operates a two-sided job marketplace with postings, sponsored distribution, sourcing, screening, and candidate management. This review separates documented functions from scale and outcome claims.",
      "html_url": "https://digidai.github.io/2025/07/15/indeed-comprehensive-analysis/",
      "markdown_url": "https://digidai.github.io/2025/07/15/indeed-comprehensive-analysis/index.md",
      "date_published": "2025-07-15T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "indeed",
        "job marketplace",
        "talent acquisition",
        "smart sourcing",
        "ai hiring"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/07/14/linkedin-deep-analysis/",
      "title": "LinkedIn: Network, Hiring Products, and Data Boundaries",
      "summary": "LinkedIn combines a professional network with jobs, recruiting, learning, advertising, and subscriptions. Its durable advantage and main risk both come from how profile and activity data connect those products.",
      "html_url": "https://digidai.github.io/2025/07/14/linkedin-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/07/14/linkedin-deep-analysis/index.md",
      "date_published": "2025-07-14T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "linkedin",
        "professional networking",
        "talent acquisition",
        "job marketplace",
        "data governance"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/07/08/cornerstone-ondemand-deep-analysis/",
      "title": "Cornerstone OnDemand's Enterprise Learning Platform",
      "summary": "A source-bound review of Cornerstone's Galaxy platform, AI, ownership, trust claims, and buying criteria.",
      "html_url": "https://digidai.github.io/2025/07/08/cornerstone-ondemand-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/07/08/cornerstone-ondemand-deep-analysis/index.md",
      "date_published": "2025-07-08T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "cornerstone ondemand",
        "learning management",
        "talent development",
        "cornerstone galaxy ai"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/07/08/glassdoor-comprehensive-analysis/",
      "title": "Glassdoor's Workplace Transparency and Employer Brand",
      "summary": "Glassdoor's reviews, salary data, Indeed integration, employer products, and governance.",
      "html_url": "https://digidai.github.io/2025/07/08/glassdoor-comprehensive-analysis/",
      "markdown_url": "https://digidai.github.io/2025/07/08/glassdoor-comprehensive-analysis/index.md",
      "date_published": "2025-07-08T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "glassdoor",
        "employer branding",
        "workplace reviews",
        "job search"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/07/08/myalerts-comprehensive-analysis/",
      "title": "MyAlerts: Which Product Does the Name Refer To?",
      "summary": "The name MyAlerts is used by unrelated retail, workforce, public-safety, and web-monitoring products. This evidence-led guide separates them before a buyer evaluates features.",
      "html_url": "https://digidai.github.io/2025/07/08/myalerts-comprehensive-analysis/",
      "markdown_url": "https://digidai.github.io/2025/07/08/myalerts-comprehensive-analysis/index.md",
      "date_published": "2025-07-08T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "myalerts",
        "product identity",
        "alert management",
        "vendor due diligence"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/07/08/peoplefluent-comprehensive-analysis/",
      "title": "PeopleFluent: A Buyer-Focused Talent Management Review",
      "summary": "PeopleFluent combines configurable talent management, learning, recruiting, compensation, and org-charting tools. The buying question is which modules and controls a specific deployment includes.",
      "html_url": "https://digidai.github.io/2025/07/08/peoplefluent-comprehensive-analysis/",
      "markdown_url": "https://digidai.github.io/2025/07/08/peoplefluent-comprehensive-analysis/index.md",
      "date_published": "2025-07-08T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "peoplefluent",
        "talent-management",
        "learning-management",
        "recruitment",
        "compensation",
        "workforce-planning",
        "hr-software"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/07/08/sap-successfactors-deep-analysis/",
      "title": "SAP SuccessFactors: Suite Architecture and Buyer Controls",
      "summary": "SAP SuccessFactors spans core HR, talent, learning, recruiting, analytics, and AI. This review focuses on suite boundaries, configuration, data governance, and current recruiting changes.",
      "html_url": "https://digidai.github.io/2025/07/08/sap-successfactors-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/07/08/sap-successfactors-deep-analysis/index.md",
      "date_published": "2025-07-08T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "sap successfactors",
        "hcm",
        "cloud hr",
        "recruiting",
        "enterprise software"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/07/07/oracle-peoplesoft-deep-analysis/",
      "title": "Oracle PeopleSoft's HCM Platform and Modernization Path",
      "summary": "PeopleSoft's support horizon, modernization paths, operating costs, and migration choice.",
      "html_url": "https://digidai.github.io/2025/07/07/oracle-peoplesoft-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/07/07/oracle-peoplesoft-deep-analysis/index.md",
      "date_published": "2025-07-07T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "oracle peoplesoft",
        "hcm",
        "peoplesoft support",
        "enterprise modernization"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/07/06/digital-nomadism-global-talent-renaissance/",
      "title": "Digital Nomad and Cross-Border Remote Work: An Employer Control Checklist",
      "summary": "A practical guide to separating travel flexibility from authorized cross-border work, with controls for tax, employment, security, payroll, and continuity.",
      "html_url": "https://digidai.github.io/2025/07/06/digital-nomadism-global-talent-renaissance/",
      "markdown_url": "https://digidai.github.io/2025/07/06/digital-nomadism-global-talent-renaissance/index.md",
      "date_published": "2025-07-06T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "digital nomads",
        "remote work",
        "global mobility",
        "workforce operations"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/07/05/eightfold-ai-deep-dive/",
      "title": "Eightfold AI's Talent Intelligence Platform",
      "summary": "Eightfold's talent platform, recruiting agents, evidence limits, and governance requirements.",
      "html_url": "https://digidai.github.io/2025/07/05/eightfold-ai-deep-dive/",
      "markdown_url": "https://digidai.github.io/2025/07/05/eightfold-ai-deep-dive/index.md",
      "date_published": "2025-07-05T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "eightfold ai",
        "talent intelligence",
        "talent agents",
        "internal mobility"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/07/05/moonhub-in-depth-analysis/",
      "title": "Moonhub's AI-Powered Recruiter Platform",
      "summary": "Moonhub's product history, reported shutdown, Salesforce team move, and current status.",
      "html_url": "https://digidai.github.io/2025/07/05/moonhub-in-depth-analysis/",
      "markdown_url": "https://digidai.github.io/2025/07/05/moonhub-in-depth-analysis/index.md",
      "date_published": "2025-07-05T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "moonhub",
        "ai recruiting",
        "salesforce",
        "vendor status"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/07/05/neuroadaptive-recruitment-brain-interfaces/",
      "title": "Neurotechnology in Hiring: Why Brain Data Is Not a Shortcut to Candidate Ability",
      "summary": "A risk-based review of brain-computer interfaces, neural data, cognitive inference, and the high evidence threshold for any employment use.",
      "html_url": "https://digidai.github.io/2025/07/05/neuroadaptive-recruitment-brain-interfaces/",
      "markdown_url": "https://digidai.github.io/2025/07/05/neuroadaptive-recruitment-brain-interfaces/index.md",
      "date_published": "2025-07-05T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "neurotechnology",
        "candidate assessment",
        "neural data",
        "hiring ethics"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/07/05/paradox-ai-olivia-deep-dive/",
      "title": "Paradox AI's Olivia Conversational Recruiter",
      "summary": "Paradox's Workday ownership, candidate automation, evidence limits, and hiring governance.",
      "html_url": "https://digidai.github.io/2025/07/05/paradox-ai-olivia-deep-dive/",
      "markdown_url": "https://digidai.github.io/2025/07/05/paradox-ai-olivia-deep-dive/index.md",
      "date_published": "2025-07-05T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "paradox ai",
        "olivia",
        "workday",
        "conversational recruiting"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/07/05/taleo-deep-analysis/",
      "title": "Oracle Taleo's Talent Acquisition Suite",
      "summary": "Taleo's recruiting scope, integrations, documentation, and migration choices.",
      "html_url": "https://digidai.github.io/2025/07/05/taleo-deep-analysis/",
      "markdown_url": "https://digidai.github.io/2025/07/05/taleo-deep-analysis/index.md",
      "date_published": "2025-07-05T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "oracle taleo",
        "applicant tracking system",
        "talent acquisition",
        "enterprise software"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/07/05/workday-ai-deep-dive/",
      "title": "Workday's AI Platform for Enterprise HR and Finance",
      "summary": "A current analysis of Workday's AI, data foundation, product evidence, governance, and buying questions.",
      "html_url": "https://digidai.github.io/2025/07/05/workday-ai-deep-dive/",
      "markdown_url": "https://digidai.github.io/2025/07/05/workday-ai-deep-dive/index.md",
      "date_published": "2025-07-05T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "workday ai",
        "hcm",
        "financial management",
        "enterprise agents"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/07/04/ai-reshaping-global-employment-ecosystems/",
      "title": "AI and Global Employment: A Task-Level Framework for Workforce Decisions",
      "summary": "A grounded way to assess AI exposure, job redesign, worker impact, skills investment, and governance without converting forecasts into outcomes.",
      "html_url": "https://digidai.github.io/2025/07/04/ai-reshaping-global-employment-ecosystems/",
      "markdown_url": "https://digidai.github.io/2025/07/04/ai-reshaping-global-employment-ecosystems/index.md",
      "date_published": "2025-07-04T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI and jobs",
        "workforce strategy",
        "task automation",
        "labor markets"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/07/04/mercor-comprehensive-platform-analysis/",
      "title": "Mercor's AI Talent Acquisition Platform",
      "summary": "Mercor's expert marketplace, AI interviews, enterprise expansion, security, and buyer controls.",
      "html_url": "https://digidai.github.io/2025/07/04/mercor-comprehensive-platform-analysis/",
      "markdown_url": "https://digidai.github.io/2025/07/04/mercor-comprehensive-platform-analysis/index.md",
      "date_published": "2025-07-04T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "mercor",
        "ai interview",
        "expert marketplace",
        "enterprise ai"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/07/03/hireez-comprehensive-platform-analysis/",
      "title": "HireEZ's AI-Powered Talent Sourcing Platform",
      "summary": "A source-bound review of hireEZ's recruiting workflows, pricing, integrations, evidence, and governance.",
      "html_url": "https://digidai.github.io/2025/07/03/hireez-comprehensive-platform-analysis/",
      "markdown_url": "https://digidai.github.io/2025/07/03/hireez-comprehensive-platform-analysis/index.md",
      "date_published": "2025-07-03T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "hireez",
        "talent sourcing",
        "recruiting crm",
        "ai recruiting"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/07/03/post-pandemic-global-workforce-transformation-en/",
      "title": "Post-Pandemic Workforce Design: Remote Work, Skills, and Operating Evidence",
      "summary": "A measured guide to hybrid-work design, cross-border hiring, skills change, and AI adoption using current labor data and explicit operating controls.",
      "html_url": "https://digidai.github.io/2025/07/03/post-pandemic-global-workforce-transformation-en/",
      "markdown_url": "https://digidai.github.io/2025/07/03/post-pandemic-global-workforce-transformation-en/index.md",
      "date_published": "2025-07-03T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "remote work",
        "workforce strategy",
        "skills",
        "future of work"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/07/03/us-headhunting-market-comprehensive-analysis/",
      "title": "US Executive Search: How to Evaluate Firms, Fees, Evidence, and Outcomes",
      "summary": "A buyer-oriented analysis of retained search, professional search, contingent recruiting, sourcing platforms, and the evidence needed to compare them.",
      "html_url": "https://digidai.github.io/2025/07/03/us-headhunting-market-comprehensive-analysis/",
      "markdown_url": "https://digidai.github.io/2025/07/03/us-headhunting-market-comprehensive-analysis/index.md",
      "date_published": "2025-07-03T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "executive search",
        "recruiting services",
        "talent acquisition",
        "procurement"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/07/02/ai-democratization-global-equity-transformation/",
      "title": "AI Access and Global Equity: Measuring the Foundations Behind Adoption",
      "summary": "A framework for evaluating whether AI access is useful and inclusive across connectivity, compute, local context, skills, governance, and outcomes.",
      "html_url": "https://digidai.github.io/2025/07/02/ai-democratization-global-equity-transformation/",
      "markdown_url": "https://digidai.github.io/2025/07/02/ai-democratization-global-equity-transformation/index.md",
      "date_published": "2025-07-02T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI access",
        "global equity",
        "digital infrastructure",
        "AI governance"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/07/02/ai-ethics-recruitment-fairness-en/",
      "title": "AI Ethics in Recruitment: A Jurisdiction-Aware Control Framework",
      "summary": "Turn fairness, privacy, transparency, and human oversight into concrete controls for sourcing, screening, interviews, and employment decisions.",
      "html_url": "https://digidai.github.io/2025/07/02/ai-ethics-recruitment-fairness-en/",
      "markdown_url": "https://digidai.github.io/2025/07/02/ai-ethics-recruitment-fairness-en/index.md",
      "date_published": "2025-07-02T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI ethics",
        "recruitment compliance",
        "algorithmic fairness",
        "hiring governance"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/07/02/us-ai-healthcare-industry-comprehensive-analysis/",
      "title": "US Healthcare AI: A Deployment Map from Research to Clinical Operations",
      "summary": "A practical map of US healthcare AI across research, devices, certified health IT, clinical workflow, data governance, and post-deployment monitoring.",
      "html_url": "https://digidai.github.io/2025/07/02/us-ai-healthcare-industry-comprehensive-analysis/",
      "markdown_url": "https://digidai.github.io/2025/07/02/us-ai-healthcare-industry-comprehensive-analysis/index.md",
      "date_published": "2025-07-02T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "healthcare AI",
        "medical devices",
        "clinical workflow",
        "AI governance"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/07/01/global-hr-digital-transformation-en/",
      "title": "Global HR Digital Transformation: An Evidence and Workflow Architecture",
      "summary": "A practical architecture for modernizing HR systems, data, and AI workflows while preserving decision ownership, traceability, and worker access.",
      "html_url": "https://digidai.github.io/2025/07/01/global-hr-digital-transformation-en/",
      "markdown_url": "https://digidai.github.io/2025/07/01/global-hr-digital-transformation-en/index.md",
      "date_published": "2025-07-01T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "HR transformation",
        "people operations",
        "AI governance",
        "HR technology"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/06/30/us-recruitment-market/",
      "title": "US Recruitment Market: Hiring Signals and Operating Priorities",
      "summary": "An evidence-based view of US hiring demand, recruiting technology, regulation, and the decisions talent teams should revisit.",
      "html_url": "https://digidai.github.io/2025/06/30/us-recruitment-market/",
      "markdown_url": "https://digidai.github.io/2025/06/30/us-recruitment-market/index.md",
      "date_published": "2025-06-30T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "us recruitment market",
        "talent acquisition trends",
        "american hiring",
        "recruitment technology",
        "workforce planning"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/06/29/ai-recruitment-revolution/",
      "title": "AI Recruitment: Where Automation Helps and Where It Fails",
      "summary": "A source-bound guide to AI in sourcing, screening, interviews, scheduling, and hiring analytics, with a practical framework for validation, human review, and candidate protection.",
      "html_url": "https://digidai.github.io/2025/06/29/ai-recruitment-revolution/",
      "markdown_url": "https://digidai.github.io/2025/06/29/ai-recruitment-revolution/index.md",
      "date_published": "2025-06-29T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI Recruitment",
        "Talent Acquisition",
        "Algorithmic Hiring",
        "Recruiting Technology",
        "Future of Work"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/06/28/remote-hiring-transformation/",
      "title": "Remote Hiring: Design the Role Before Expanding the Map",
      "summary": "A source-bound guide to remote hiring, covering role feasibility, location rules, worker classification, asynchronous assessment, onboarding, and the limited role of AI.",
      "html_url": "https://digidai.github.io/2025/06/28/remote-hiring-transformation/",
      "markdown_url": "https://digidai.github.io/2025/06/28/remote-hiring-transformation/index.md",
      "date_published": "2025-06-28T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "Remote Hiring",
        "Global Talent",
        "Distributed Teams",
        "Recruiting Operations",
        "Future of Work"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/06/27/skills-based-hiring-ai/",
      "title": "Skills-Based Hiring with AI: From Degree Filters to Verifiable Work Evidence",
      "summary": "A skills-first hiring system works only when employers define the job, collect valid evidence, and keep AI-generated inferences open to review.",
      "html_url": "https://digidai.github.io/2025/06/27/skills-based-hiring-ai/",
      "markdown_url": "https://digidai.github.io/2025/06/27/skills-based-hiring-ai/index.md",
      "date_published": "2025-06-27T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "skills-based hiring",
        "talent assessment",
        "AI recruitment",
        "workforce development"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/06/26/ai-diversity-inclusive-hiring/",
      "title": "AI and Inclusive Hiring: What Employers Can Measure, Validate, and Correct",
      "summary": "AI does not create fair hiring by itself. Inclusive deployment requires job-related criteria, outcome monitoring, accommodations, and a correction path.",
      "html_url": "https://digidai.github.io/2025/06/26/ai-diversity-inclusive-hiring/",
      "markdown_url": "https://digidai.github.io/2025/06/26/ai-diversity-inclusive-hiring/index.md",
      "date_published": "2025-06-26T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "inclusive hiring",
        "algorithmic bias",
        "candidate assessment",
        "hiring governance"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/06/25/ai-interview-automation/",
      "title": "AI Interview Automation: A Control Model for Scheduling, Transcription, and Assessment",
      "summary": "Separate low-risk interview coordination from consequential scoring, then validate job-related evidence, accommodations, and human review before deployment.",
      "html_url": "https://digidai.github.io/2025/06/25/ai-interview-automation/",
      "markdown_url": "https://digidai.github.io/2025/06/25/ai-interview-automation/index.md",
      "date_published": "2025-06-25T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI interviews",
        "candidate assessment",
        "hiring governance",
        "recruiting operations"
      ],
      "language": "en",
      "author": "Gene Dai"
    },
    {
      "id": "https://digidai.github.io/2025/05/01/ai-recruitment-era/",
      "title": "AI Recruitment in 2025: Where Automation Helps and Where Employers Remain Accountable",
      "summary": "A practical guide to using AI in recruiting without confusing workflow automation with a valid, fair, or defensible hiring decision.",
      "html_url": "https://digidai.github.io/2025/05/01/ai-recruitment-era/",
      "markdown_url": "https://digidai.github.io/2025/05/01/ai-recruitment-era/index.md",
      "date_published": "2025-05-01T00:00:00.000Z",
      "date_modified": "2026-09-14T00:00:00.000Z",
      "tags": [
        "AI recruitment",
        "recruiting operations",
        "hiring governance",
        "HR technology"
      ],
      "language": "en",
      "author": "Gene Dai"
    }
  ]
}