Skill guide
AI product management
AI product management defines valuable, feasible, and responsible products when core behaviour is probabilistic rather than fully deterministic.
Why this capability matters
AI products need explicit user value, evaluation criteria, fallback behaviour, cost constraints, and honest communication about limitations.
What competent practice includes
AI opportunity framing
AI PRDs
Evaluation and success metrics
Roadmaps and trade-offs
Stakeholder communication
Portfolio evidence
An AI feature brief, PRD, evaluation plan, risk register, and roadmap grounded in a real user problem.
See public project briefsProfessional applications
These are fields of application, not guaranteed job or income outcomes.
AI feature discoveryProduct advisoryEvaluation planningRoadmappingCross-functional delivery
Courses that develop this skill
AI Strategy
AI Product Management
Product management for AI-native products — PRDs, evals, and roadmapping when the core feature is a model, not a form.
AI Engineering
Generative AI (GenAI)
Foundational to advanced generative AI — how these models work and how to build real applications on top of them.
Connect the skill to a market path
Learn how this capability fits inside a complete problem, proof, service, and delivery journey.