ai-product-canvas

mohitagw15856/pm-claude-skillsProduct ManagementAudit passedSnapshot 153c06f0bd62

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Summary

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.

SKILL.md

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"