recommendation-canvaslisted

## Purpose Evaluate and propose AI product solutions using a structured canvas that assesses business outcomes, customer outcomes, problem framing, solution hypotheses, positioning, risks, and value justification. Use this to build a comprehensive, defensible recommendation for stakeholders and decision-makers—especially when proposing AI-powered features or products that carry higher uncertainty and risk. This is not a feature spec—it's a strategic proposal that articulates *why* this AI solution is worth building, *what* assumptions need validating, and *how* you'll measure success. ## Key Concepts ### The Recommendation Canvas Framework Created for Dean Peters' Productside "AI Innovation for Product Managers" class, the canvas synthesizes multiple PM frameworks into one strategic view: **Core Components:** 1. **Business Outcome:** What's in it for the business? 2. **Product Outcome:** What's in it for the customer? 3. **Problem Statement:** Persona-centric problem framing 4. **Solution Hypothesis:** If/then hypothesis with experiments 5. **Positioning Statement:** Value prop and differentiation 6. **Assumptions & Unknowns:** What could invalidate this? 7. **PESTEL Risks:** Political, Economic, Social, Technological, Environmental, Legal 8. **Value Justification:** Why this is worth doing 9. **Success Metrics:** SMART metrics to measure impact 10. **What's Next:** Strategic next steps ### Why This Works - **Outcome-driven:** Forces clarity on business AND customer valu