Revolutionizing API Strategy in the AI Era
summary
Claims that 130+ new large language models appeared in seven months and model sizes have jumped from ~1.5B to half‑trillion and beyond drive the talk. Concrete tools cited: ChatGPT, OpenAI/GP4, GitHub Copilot, Microsoft 365 Copilot, Bloom, Dolly, StarCoder, CodeGen, BloombergGPT and Superface. Practical directives: treat APIs as machine consumers, add electronically verifiable audit trails, strengthen API testing/debugging and DevSecOps security scans, standardize docs (markdown/OAS) so automated integration tools can generate safe, explainable predictions like order‑arrival guesstimates.
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chapters (10)
- 0:00AI-driven API strategy intro
- 3:14AI consumerization vs enterprise
- 8:55AI trends shaping engineering
- 9:36Traditional API strategy
- 13:51Regulatory & security for AI APIs
- 17:22Adapting APIs for AI era
- 20:11Automating API dev with AI
- 22:39Context-aware APIs
- 24:47AI API security audits
- 25:28Future-proof API design
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