The Impact of AI on the future of software engineering
summary
Claims that AI increases demand for software engineers—arguing not fewer but exponentially more—supported by a virtuous-cycle explanation and a precedent (Jevons/jeans paradox) and tracking ~40 startups in AI evals and observability. Recommends eval-driven development as tests for nondeterministic models, building a parallel trust stack alongside the tech stack, internal platform teams offering intelligence as a service, agents enabling async work, models that don’t internalize learning, and a pathway toward a zero friction SDLC if security and context handoffs are solved.
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chapters (8)
- 0:00AI's impact on software engineering
- 1:34AI transforming software teams
- 6:11Developer creativity vs productivity
- 9:42Trustworthy intelligent applications
- 13:54Responsible AI with evals and gateways
- 16:43AI's effect on development lifecycle
- 20:37AI-driven development challenges
- 23:08What would you build?
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