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Interactive roadmap

Product Manager + AI

AI product discovery, metrics, economics, and lifecycle

A path for product managers covering AI feature discovery, capabilities, evaluation, AI UX, unit economics, experimentation, safety, and lifecycle management.

8–14 weeksProduct managersProduct ownersAI product leads
Open as course →Every node has an evidence route
3stages
10nodes
2projects and milestones
01 · Shared AI core02 · AI product discovery03 · Metrics, economics, and lifecycle
  1. 01

    Shared AI core

    Model limits, structured outputs, and evaluation for product decisions.

    Stage outcomeThe product manager understands what can be promised to users and how those promises can be verified.
    Materials ready
    Article →
    Materials ready
    Prerequisites: AI literacy and model limits
    Article →
    Materials ready
    Prerequisites: Prompt and context engineering
    Article →Article →
  2. 02

    AI product discovery

    Problem framing, capability fit, and value hypotheses.

    Stage outcomeThe AI feature has a clear problem, a defined user, and measurable success metrics.
    Materials ready
    Article →
    Materials ready
    Topic →
    Materials readyAssessment available
    Prerequisites: Capability fit and problem selection, AI UX, trust, and uncertainty
    Open practicum →Assessment rubric →Practicum →
  3. 03

    Metrics, economics, and lifecycle

    Quality, safety, cost, experimentation, and operations.

    Stage outcomeThe AI feature is governed through measurable gates from prototype to sunset.
    Materials ready
    Article →
    Materials ready
    Article →
    Materials ready
    Article →
    Materials ready
    Prerequisites: Quality and safety metrics, AI unit economics, Evaluation-driven experimentation
    Practicum →