Learning roadmap
AI for Product Managers
Spec, scope, and ship AI features that survive contact with users: the three product patterns, discovery with LLMs, eval sets as PRD artifacts, and the deship criterion nobody writes down.
4 stages~6 h
That leaves 4 stages, ~6 hours of focused work. You can clear it in any order, but the stages compound — try them top-to-bottom your first time.
- You'll pick up:
copilot pattern, embedded ai, autonomous agents, latency tolerance, cost per interaction
Practice quizzesLab taskBuild a "pattern picker" page: six feature ideas as cards, each assigned to a pattern with a tradeoff note (why not the other two) and a rough cost/latency band — ending with one feature from your own roadmap.
Build it in the LabCheckpointFor your next feature you can name the pattern, the latency budget, and the cost ceiling — and why the alternatives lose.
What you'll be able to do
- Choose the right AI pattern for a feature and defend the latency and cost budget that comes with it.
- Turn weeks of feedback and interviews into themed, counted, evidence-rated insight in an afternoon.
- Write an AI feature spec whose acceptance criteria are an eval set, not a vibe.
- Launch with guardrail metrics — and a written deship rule you actually enforce.
Or try a related path