Agile Intelligence: Co-Engineering the Future, Not Just Automating It
summary
Claims that AI cuts ideation‑to‑deployment time by over 50% and can get an MVP in two weeks drive the talk, with evidence from experiments that used third‑party models, multi‑agent platforms and templates to generate UX, system architecture and launch pipelines. A video‑commerce prototype auto‑creates flows and deployable components but scaling is “messy” and needs architecture revamps. Tools mentioned include Copilot‑style assistants and enterprise AI stacks; the presenter expects agents to replace one full‑stack developer, designer, copywriter and strategist within a year. Human judgment remains the gating factor.
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chapters (14)
- 0:00Introduction
- 2:22Software engineering golden era
- 6:16New AI-driven engineering need
- 10:10From how to what in dev
- 14:05Speed and growth mantra
- 16:57AI-powered engineering skills
- 20:26Traditional agile obsolete
- 22:13Outcome-driven engineering
- 25:47AI era continuous learning
- 27:54Career as smartphone pivoting
- 31:26Q&A AI adoption
- 38:27Q&A team dynamics IP
- 40:58Q&A enterprise AI challenges
- 43:47Q&A productivity gains
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