Blog
Essays on product
& judgment.
Longer-form thinking on product leadership, continuous discovery, and what actually changes for teams in the AI era.
Shorter takes, in the moment. The thinking before it becomes an essay.
89% of executives say AI made their teams faster, but only 6% can point to real ROI. Marty Cagan calls it the AI Productivity Paradox. It stops being one once you see what got cheap (building) and what didn’t (deciding what deserves to be built). The useful question isn’t how to ship faster - you already can - it’s how to get better at knowing what to ship.
Going forward-deployed is the right call, but it’s also where I’ve watched good teams quietly turn into expensive custom shops. Embedding is the easy half. The operating layer around it, real discovery, clear kill-and-keep decisions, the governance to lift learnings back into the product, is the half that decides whether it works.
Every prototype is a promise you didn’t mean to make. AI made prototypes nearly free, so more of them survive for reasons that have nothing to do with what customers actually need. Write down what would make you kill it before it exists, while a “no” is still cheap.
AI made building cheap, but building was never the bottleneck. Delivery becomes a commodity; discovery becomes the differentiator. Five things Michael Albers and I have come to believe about product discovery in the age of AI.
We hire brilliant product people and then treat them like order-takers. After 25 years building and rebuilding product orgs, I’m making the fix my full-time job: coaching product leadership in the age of AI.