Lenny's Podcast · January 11, 2026

Why most AI products fail: Lessons from 50+ AI deployments at OpenAI, Google & Amazon

with Aishwarya Naresh Reganti + Kiriti Badam

Two AI veterans from OpenAI, Google, and Amazon reveal why most AI products fail after analyzing 50+ deployments. Learn the Continuous Calibration/Continuous Development (CC/CD) framework for building successful AI products, the critical difference between evals and production monitoring, and why implementation is cheap but design judgment is everything. Discover the agency-control trade-off that makes AI fundamentally different from traditional software, and how behavior calibration determines whether your AI enhances or ruins customer experience. Essential lessons for anyone building AI products in 2026's competitive landscape.

Featured insight

Pain is the new moat - successful companies building AI aren't first to market, they went through the pain of understanding non-negotiable requirements and learning what works through iteration. This knowledge becomes their competitive advantage. — Kiriti Badam

Best for: AI product managers at Series A-C companies, Engineering leaders building AI-first products, Technical founders transitioning from traditional software to AI

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