ai-product-canvas
Structure AI and ML product decisions with the rigour of any product decision. Use when building AI-powered features, evaluating LLM integrations, designing AI products, or assessing AI readiness. Produces a complete AI product canvas covering problem definition, model approach, data requirements, evaluation framework, UX design, responsible AI checklist, and launch monitoring plan.
npx skills add mohitagw15856/pm-claude-skills --skill ai-product-canvas --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# AI Product Canvas Skill Define AI products with the same rigour as any product decision — but with additional layers for data, model, evaluation, and responsible AI. This canvas prevents the most common AI product failure: building a technically impressive feature that doesn't solve a real problem. ## AI Product Anti-Patterns to Check First Before building, flag if any of these apply: - ❌ "We should add AI to [existing feature]" — with no user problem defined - ❌ Accuracy target undefined before build begins - ❌ No plan for what happens when the model is wrong - ❌ User-facing AI output with no human review or fallback - ❌ Training data not audited for bias or quality - ❌ No evaluation metric — "we'll know it when we see it" --- ## AI Product Canvas Output Format ### AI Product Canvas — [Feature Name] — [Date] **PM Owner:** [Name] **ML/AI Lead:** [Name] **Status:** Discovery / Design / Build / Evaluation / Live --- #### 1. Problem Definition **User problem being solved:** > [What specific situation is the user in? What job are they trying to get done?] **Why AI?** > [What makes this problem require AI vs a deterministic solution? If the answer is "because we can," stop here.] **Su
- AI Product Anti-Patterns to Check First
- AI Product Canvas Output Format
- AI Product Canvas — [Feature Name] — [Date]
- Guidelines
- Required Inputs
- Anti-Patterns
- Quality Checks
What does the ai-product-canvas skill do?
Structure AI and ML product decisions with the rigour of any product decision. Use when building AI-powered features, evaluating LLM integrations, designing AI products, or assessing AI readiness. Produces a complete AI product canvas covering problem definition, model approach, data requirements, evaluation framework, UX design, responsible AI checklist, and launch monitoring plan.
How do I install it?
Run `npx skills add mohitagw15856/pm-claude-skills --skill ai-product-canvas --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From mohitagw15856/pm-claude-skills, a repository with 1,255 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.