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AI Product Manager

Decide what AI features ship — and what doesn't.

You bridge product, engineering, and ML. You spec AI features, set quality thresholds, run user research, and own the roadmap. The most underrated role in AI orgs — every team needs one and most don't have it.

Start the recommended pathCompare other roles

Skills profile

What hiring managers actually weigh.

Recommended paths

Take them in order. Each builds on the previous.

1

Prompt Engineering

Make any LLM do what you actually want.

2

RAG & Vector Databases

Make models answer from your data, not their guesses.

3

LLMs & Transformers

See inside the model — without the math wall.

90-day roadmap

An honest, week-by-week plan. Adjust to your weekly time budget.

  1. 1

    AI literacy

    ~3 weeks
    • Prompt Engineering path
    • Build a small AI demo end-to-end
    • Read 10 AI product post-mortems
  2. 2

    AI eval mindset

    ~4 weeks
    • RAG path
    • Build a quality eval harness
    • Frame "good enough" thresholds
  3. 3

    Ship

    ~4 weeks
    • Spec a real AI feature
    • Run A/B with quality metric
    • Write a launch post-mortem

Certifications worth taking

Practice & certify on CertQuests after completing the course.

Career outcomes

Realistic next steps after completing the roadmap.

  • PM → AI PM transition
  • AI-native product roles at startups
  • Senior PM positions in AI orgs