AI product management

How to run an AI feature as a PM when the output is non-deterministic. Ownership models, review cadence, quality bars you can actually defend, and the artifacts (rubrics, error analyses, judge cards) that let you tell engineering, legal and the exec team the same coherent story.

Article10 JUN 2026

Who should own AI features in product teams?

AI defaulted to engineering, but the judgment layer where domain expertise lives is where AI features are won or lost. Who should own AI in product, and why the ownership has to move.

Madalina Turlea

Article14 APR 2026

Should you still write PRDs when building AI features?

The programming language is plain English. The prompt IS the spec, so why is the PM three handoffs away? Why "evals are the new PRDs" makes things worse, and what PM-owned AI development actually looks like.

Madalina Turlea

Article15 JAN 2026

Why AI features should not be owned by engineering alone

Engineers build the technical part. Domain experts hold the context that makes AI intelligent. Why prompt and evaluation work belongs with the people who understand the problem.

Madalina Turlea

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