Twenty-Seven Years of Being Early
summary
Argues that the real lie is timing: claims about AI are likely true but the timeline is the lie; recounts manually cataloging the web, Azure announced 2008 and GA 2010, and building community like Global Azure; gives numbers: 94% of enterprises use cloud but about half of workloads run there, AI workloads are ~19% of cloud spend and ~20% of moved workloads return; shows a radiology case where AI + one human replaces two doctors; warns of credit‑card shadow AI, variable cost per transaction, vendor lock‑in as an architectural choice, and urges short‑term trainers and reskilling.
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chapters (24)
- 0:00Introduction
- 1:07Early internet cataloging
- 5:03Cloud computing evolution
- 7:14Early cloud expert trap
- 10:03Cloud promises vs reality
- 12:12Why tech must be boring
- 13:36Cloud hype vs AI hype
- 16:47Governance delays
- 17:53Cloud vs AI differences
- 20:26AI abstraction of judgment
- 21:54Cloud enabling AI
- 22:59AI power demands
- 24:05Hype vs AI reality
- 25:10Leadership in tech adoption
- 26:56Adoption gap in cloud
- 28:21Skills gaps in cloud/AI
- 29:47When AI is right tool
- 31:13Human-in-the-loop AI
- 32:57AI evaluation observability
- 34:01Vendor lock-in decisions
- 35:47Cloud adoption strategy
- 36:50Upskilling for AI readiness
- 37:36Financial risks of hype
- 38:17AI by 2035 and closing
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