Stakeholder roleplay

Rehearse difficult PM conversations before they happen

Stakeholder roleplay is a live voice session in Product Mastery where an AI stakeholder pushes back on customer value, roadmap and investment tradeoffs, so PMs can practice influence without authority before the real meeting.

Why this is more than an AI wrapper

Structured curriculum

Every exercise belongs to one of 7 Product skill areas, and 21 tracks take each area from beginner to advanced, so practice maps to real product responsibilities instead of isolated prompts.

Rubric-based scoring

Each answer is scored against criteria written for that exercise or conversation: what you got right, what you missed, and what a stronger answer would add.

Progress loop

A skill profile, spaced-repetition reviews, a development plan with OKRs, and a certificate create a repeatable path from attempt to improvement.

Evidence inside this product area

  • Session setup takes the situation, the stakeholder's personality and pressure, and your plan for the conversation.
  • Graded sessions are scored against a rubric for that conversation: listening, clarity, closure, customer and business value, evidence, prioritization and tradeoffs, and the decision with its measures.
  • You get the transcript, so feedback can point to what the PM said, what they missed and what to try next.
  • Stakeholder roleplay is part of voice coaching on the Professional and Max plans.

Sample before and after

Typical shallow response

We cannot do that now because engineering has no capacity.

Better PM response

I would validate the revenue urgency, ask what customer commitment depends on this feature, offer a discovery spike, compare it against current roadmap bets, and agree on a decision date with explicit tradeoffs.

What a learner should be able to demonstrate

  • Practice executive updates, priority conflicts, launch risks, customer escalation, and engineering pushback.
  • Use the transcript to prepare the real meeting agenda and follow-up.
  • Compare rubric scores over multiple conversations.

Related public references