AI & HR
summary
Claims that LLMs (ChatGPT, Gemini) already generate data‑science analyses, UI critiques, business requirements, Cucumber acceptance tests and working Python, and that this stack can be chained to refactor and test code. Shows examples: headline claim of 18 minutes to 100% test coverage, a founder shrinking a five‑person team to one, and a productivity range of 10–1000×, illustrated as 300 person‑days → 3–30 days. Predicts HR shifts from single‑specialist roles and managers toward multi‑skilled product developer teams where human value is learning and adapting while models remain frozen models today.
AI-written summary · about
chapters (7)
- 0:00AI and HR history
- 1:56AI in data science and UI
- 14:12AI in product development
- 21:51Shift to multi-skilled roles
- 26:33Human value and AI limits
- 30:05AI future with fusion energy
- 33:45Q&A on AI jobs
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