Individual skill
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.
skills/ai-product-canvas/SKILL.md
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# 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"
