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Data scientists already own the skills AI PM job descriptions ask for most: evals, metrics and experiments. The gap is customers, scope and decisions. AllthingsPM's AI PM course, built from 604 real PM postings, closes it and ends in mock interviews built from real AI company job descriptions.
An AI product manager decides what to build and how to judge it, an AI engineer builds it on top of models, and a data scientist finds the truth in the data. AllthingsPM's AI PM course, built from 604 real PM job postings, is the fastest way into the PM side.
Software engineers already meet the technical bar most AI PM job descriptions set. The gap is product judgment, customers and evals. AllthingsPM's AI PM course, built from 604 real PM postings, closes that gap and ends in mock interviews built from real AI company job descriptions.
Learning AI as a product manager takes about 90 days of focused work: 30 days on how models behave, 30 on building and evaluating a real feature, 30 on proof and interviews. AllthingsPM runs the whole plan in one place, with an AI PM course built from 604 real job postings.
AI labs hire five kinds of PM: model and research, API and platform, safety and trust, applied products, and growth. We sorted 34 live PM job descriptions from OpenAI, Anthropic and Cohere to show what each one asks for.
We read 116 live PM job descriptions at 18 AI companies. Strategy (89%), customer focus (87%), technical depth (73%), enterprise work (72%) and AI agents (66%) lead; evals appear in 39%, SQL in just 4 of 116.
Mostly no. In 303 AI company PM job descriptions, 85% ask you to be technical but only 15% ask for coding experience or Python, and 10% ask for SQL. AllthingsPM's AI PM course teaches exactly those skills.
Reading is the easy half.
The course grades the other half.
