Model Online / On-Site
Duration
Modules 5 modules

Course Objective & Scope

Product managers face pressure both to speed up product work with AI and to ship AI features in their products. This programme addresses both: synthesising user interviews, support tickets and app reviews, framing the problem, drafting a PRD, prioritising with RICE and building clickable prototypes with tools such as Lovable, v0 or Figma Make.

The second part covers the use case, success metrics, evaluation approach, token cost and risks of an AI feature. Participants prepare a PRD and evaluation plan for a feature chosen from their own product.

Who Should Attend?

  • Product managers and product owners
  • Product designers and UX researchers
  • Digital channel and growth teams
  • Leaders responsible for product strategy

Key Takeaways

  • Turn scattered customer feedback into themes and opportunity areas
  • Draft and sharpen PRDs and user stories with AI
  • Support backlog prioritisation with RICE or similar models
  • Build a rapid prototype to validate an idea
  • Define success metrics, evals and a risk plan for an AI feature

Curriculum

Discovery and Customer Insight
  • Synthesising interviews, surveys and support tickets
  • Jobs-to-be-done and persona drafts
  • Opportunity–solution tree
Competitor and Market Analysis
  • Competitor scans with deep research tools
  • Feature comparison tables
  • Source verification
PRD and Prioritisation
  • PRD template and AI-assisted drafting
  • RICE scoring and challenging assumptions
  • Roadmap communication
Rapid Prototyping
  • Prototypes with Lovable, v0 and Figma Make
  • User testing scenarios
Adding an AI Feature to Your Product
  • Choosing a suitable use case
  • Evals, success metrics and token cost
  • Guardrails and responsible AI principles

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