From pm-copilot
Use this skill when the user asks to "create user personas", "develop personas", "write a persona", "define our users", "user profile", "who is our user", "help me define the target user", "create a user archetype", or wants to build or update structured user persona definitions grounded in research or known user characteristics.
npx claudepluginhub productfculty-aipm/pm-copilot-by-product-facultyThis skill uses the workspace's default tool permissions.
Dispatches parallel agents to independently tackle 2+ tasks like separate test failures or subsystems without shared state or dependencies.
Executes pre-written implementation plans: critically reviews, follows bite-sized steps exactly, runs verifications, tracks progress with checkpoints, uses git worktrees, stops on blockers.
Guides idea refinement into designs: explores context, asks questions one-by-one, proposes approaches, presents sections for approval, writes/review specs before coding.
You are building user personas grounded in real user behavior and JTBD thinking — not demographic templates. A persona is useful only if it changes what you build or how you communicate. If a persona doesn't make a decision obvious, it's not sharp enough.
Frameworks: Bob Moesta / JTBD (demand-side thinking), Hilary Gridley (AI-embracer vs. skeptic segmentation), Lean Startup (build-measure-learn).
Read memory/user-profile.md for product context and any existing persona notes. Read context/product/personas.md if it exists — understand what's already there and whether it needs updating or creating from scratch.
If research data exists (interview notes, support tickets, survey responses), use it. If not, build a research-grounded hypothesis persona that can be validated.
A good persona answers these questions from the user's perspective:
Who are they? (Role, situation, context — not demographics) What are they trying to do? (The JTBD — what progress are they making?) What's stopping them? (Pain, friction, workaround) What does success look like for them? (Desired outcome — functional, emotional, social) How do they currently handle this? (Current hire — the status quo) What would make them switch? (Switch trigger) How do they feel about AI assistance? (Embracer, neutral, or skeptic)
Write each persona with a demand-side framing:
Triggering situation: "When [specific situation arises], this persona needs to [make progress]."
This is more actionable than "They are 32 years old and work at a startup." The triggering situation tells you when the persona needs the product, not just who they are.
Based on Hilary Gridley's segmentation: "The most meaningful segmentation for AI products is attitudinal: AI embracers vs. AI skeptics."
For each persona, identify their position:
AI Embracer:
AI Skeptic / Cautious:
AI Neutral:
For each persona, fill in:
Name: [Descriptive label — e.g. "The Founding PM" not "Sarah"] Triggering situation: [When they need this product] JTBD: [What progress they're trying to make — functional, emotional, social] Current hire: [What they use today; what's wrong with it] Switch trigger: [What would make them look for something different] Pains: [3 specific frustrations with the current solution] Gains: [3 specific outcomes a new solution would enable] AI stance: [Embracer / Neutral / Skeptic] Onboarding path: [How to onboard this persona given their AI stance] Representative quote: [A real or composite quote that captures their core frustration] What makes them a bad fit: [Who this product isn't for — prevents over-targeting]
Write one anti-persona: the user who looks like a fit but isn't. This prevents wasted sales and support effort, and helps the team say no to feature requests from this segment.
Produce:
Offer to save to context/product/personas.md and update memory/user-profile.md with any new persona insights.