recommendation-canvas
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:
- Business Outcome: What's in it for the business?
- Product Outcome: What's in it for the customer?
- Problem Statement: Persona-centric problem framing
- Solution Hypothesis: If/then hypothesis with experiments
- Positioning Statement: Value prop and differentiation
- Assumptions & Unknowns: What could invalidate this?
- PESTEL Risks: Political, Economic, Social, Technological, Environmental, Legal
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