Finding AI Gold With Lean Startup Techniques
Most AI efforts start with tools and demos. Better to use product discovery to aim AI at a real business constraint and test the riskiest assumption first.
Read more →Making sense of agility, scaling, OKRs, product operating models, and leadership — written from 15+ years in the field.
Most AI efforts start with tools and demos. Better to use product discovery to aim AI at a real business constraint and test the riskiest assumption first.
Read more →AI speeds up delivery and thins out team-level dependencies. Scaling framework mechanics become optional; flow and WIP first principles matter more.
Read more →When AI coding raises the arrival rate of pull requests, telling reviewers to work faster is the wrong move. Fix reviewability and end-to-end flow instead.
Read more →AI isn't killing Scrum. It's shrinking teams from cross-functional squads to 1-3 people — and that descaling collapses a lot of org complexity with it.
Read more →Why the rise of Forward Deployed Engineering is the next agility problem — and how to scale "unreasonable agility" without it eating itself.
Read more →Spec-driven development looks like a step backward if you read it as requirements theater. The better frame: the spec is a higher-level language for intent.
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