AI PMs define failure modes first, not features first.
A traditional PM defines requirements, manages a roadmap, and optimizes for conversion and retention. The job was to find the most average workflow that fits everyone. That is changing. The AI Product Manager assumes every workflow is feasible. Success is no longer “did we build the feature?” but “how often does the system behave correctly, and how bad is the failure when it does not?” Evaluation happens before the first line of code. You define failure modes before features, build golden datasets not just user stories, and design end-to-end outcomes across agents, tools, and human handoffs.
— Meta Laid Off 8,000 And Launched AI - Why Jobs Need Different Skills · Forbes