ABOUT THIS EPISODE
Episode 13 of Agent Mode AI. Abby and Avery walk AM-012, the claim that the enterprise IT operations workforce is structurally the highest-exposure population to autonomous-action AI. The task surface that defines the family — incident triage, configuration management, ticket processing, routine diagnostics, scripted remediation — maps onto the agent-class capability boundary more directly than any other large enterprise job-family. The US Bureau of Labor Statistics Occupational Outlook Handbook projects Computer and Information Technology occupations to grow faster than average through 2033 with substantial role-mix shifts inside the family. The World Economic Forum Future of Jobs Report 2025 reads the same job-family bimodally: routine-task sub-population in the displacement cohort, AI-adjacent sub-population in the creation cohort, 2030 horizon. Anthropic chief executive officer Dario Amodei's twenty-eighth of May 2025 Axios interview projected that AI could eliminate half of entry-level white-collar jobs over the next one to five years. The procurement-deck distinction is between the agent-orchestration posture (team scales toward managing fleets of agents) and the agent-replacement posture (team contracts through churn).
Sources cited:
- US Bureau of Labor Statistics Occupational Outlook Handbook, Computer and Information Technology occupations, 2023-2033 cycle
- World Economic Forum Future of Jobs Report 2025
- Dario Amodei interview with Axios, 28 May 2025
- McKinsey "Seizing the agentic AI advantage" workforce findings
- Atlanta Federal Reserve Workforce Currents data on AI-skill wage premium
Claims tracked:
- AM-012 — IT operations as highest-exposure workforce population — agentmodeai.com/holding/?claim=AM-012
- AM-006 — Atlanta Fed wage-premium and BCG frontline access gap — agentmodeai.com/holding/?claim=AM-006
- AM-010 — Chief information officer playbook five operational characteristics — agentmodeai.com/holding/?claim=AM-010
- AM-011 — Change-management variable in deployment success — agentmodeai.com/holding/?claim=AM-011
Newsletter and the full Holding-up ledger: agentmodeai.com
Sources cited:
- US Bureau of Labor Statistics Occupational Outlook Handbook, Computer and Information Technology occupations, 2023-2033 cycle
- World Economic Forum Future of Jobs Report 2025
- Dario Amodei interview with Axios, 28 May 2025
- McKinsey "Seizing the agentic AI advantage" workforce findings
- Atlanta Federal Reserve Workforce Currents data on AI-skill wage premium
Claims tracked:
- AM-012 — IT operations as highest-exposure workforce population — agentmodeai.com/holding/?claim=AM-012
- AM-006 — Atlanta Fed wage-premium and BCG frontline access gap — agentmodeai.com/holding/?claim=AM-006
- AM-010 — Chief information officer playbook five operational characteristics — agentmodeai.com/holding/?claim=AM-010
- AM-011 — Change-management variable in deployment success — agentmodeai.com/holding/?claim=AM-011
Newsletter and the full Holding-up ledger: agentmodeai.com
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OTHER EPISODES IN THIS PODCAST
Episode 5 of Agent Mode AI. Abby and Avery walk through AM-118, AM-119, and the vendor-economics section of AM-121 — three institutional capital cohorts reading the same AI risk surface from three different angles, behaving in three different directions, in 2026.
Sources cited:
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CORRECTION (10 Jun 2026): The 12/88 statistic central to this episode was retracted on 10 Jun 2026; it does not appear in the cited Stanford source. The audio remains available unchanged as the record. Full correction and restated article: https://agentmodeai.com/why-88-percent-of-agentic-ai-deploy…
Episode 6 of Agent Mode AI. Abby and Avery walk the four claims that interlock around the 2 August 2026 EU AI Act deployer-obligations enforcement window. AM-127 is the falsifiable prediction (three of four operational claims will downgrade by 1 October 2026). AM-135 is the Article 50 transparency …
Episode 4 of Agent Mode AI. The operators edition. Abby and Avery walk through OPS-037, OPS-039, and OPS-041 — three places where SMB AI tools generate visible work that misses the regulatory or algorithmic layer the tool was unaware of.
Sources cited:
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