AI Product Management

Who this course is for

If you're a PM, or want to move into product management, and you keep hitting the same wall — AI features are pitched like normal features but break like nothing else (nondeterministic output, no clean "done", costs that scale with usage in ways a subscription model doesn't) — this course is built around that exact gap. It builds on the AI Fundamentals roadmap, so basic familiarity with how LLMs work is assumed; no engineering background is required.

What you'll actually build

The course moves through five practical skills, in order: product management fundamentals as they specifically apply to AI features, writing AI feature specs with real success criteria instead of vague "make it smart" requirements, treating evals as a first-class product metric rather than an engineering afterthought, navigating the AI-specific cost/risk/ vendor tradeoffs that don't come up in traditional PM work, and actually shipping and iterating on an AI feature with real users. Every module pairs a concepts lesson with a hands-on exercise built around a realistic product scenario.

The capstone

You finish by shipping a complete AI feature spec paired with an evaluation plan — the two artifacts a hiring manager or a cross-functional team would actually expect from someone doing this job, built to a standard you could bring directly into an interview or a real work sample.

Why this matters right now

Companies are hiring specifically for PMs who understand AI product work, not just PMs who've used ChatGPT. The eval-as-metric mindset and the cost/risk/vendor tradeoffs covered here are the parts that traditional PM training doesn't cover at all, and they're exactly what separates someone who can spec a normal feature from someone who can responsibly own an AI one.