Description
recommendation-canvas is a skill that evaluates an AI product idea and documents a recommendation for stakeholders. It works through a structured canvas that assesses business outcomes, customer outcomes, problem framing, solution hypotheses, positioning, risks and the justification for the value. The purpose is a defensible recommendation, especially for AI-powered features that carry more uncertainty and risk than conventional features. It is useful for deciding whether an AI product idea deserves real investment, for surfacing the risks and hypotheses behind an AI feature request, and for comparing AI solution options on outcomes rather than on novelty. Example requests include a leader asking for an AI feature that needs evaluating before anyone commits to build it, and a case with three AI solution options that need comparing on outcomes and risk. You pass the AI product idea as the argument. The estimated time is 30 to 45 minutes, and the skill belongs to the validation and experiments theme of the product-manager-skills repository on GitHub.…
Highlights
- Business and customer outcomes
- Solution hypotheses and risks
- Positioning and value justification
- Compares AI solution options
- Estimated 30 to 45 minutes
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deanpeters/recommendation-canvas FAQ
What does the canvas assess?
Business outcomes, customer outcomes, problem framing, solution hypotheses, positioning, risks and value justification.
Why a separate canvas for AI?
The skill is designed for AI features that carry higher uncertainty and risk.
Can it compare options?
Yes. The skill is used to compare AI solution options on outcomes and risk.
What input does it need?
The AI product idea, as the argument.
How long does it take?
The skill estimates 30 to 45 minutes.
What are the best deanpeters/recommendation-canvas alternatives?
Popular alternatives to deanpeters/recommendation-canvas include coreyhaines31/seo-audit, coreyhaines31/copywriting and coreyhaines31/ab-testing. See all deanpeters/recommendation-canvas alternatives