ai-product-strategylisted

# AI Product Strategy Develop AI product strategy and identify AI opportunities for your product. ## When to Use This Skill - Evaluating AI opportunities for your product - Deciding between build, buy, or partner for AI features - Assessing data readiness and moat potential - Planning AI feature roadmap - Evaluating AI vendors or partners ## Process ### Step 1: Check Your Context Read context files to understand product and market position. ### Step 2: Identify AI Opportunity Areas Categories: Automation, Prediction, Personalization, Content Generation, Data Analysis, Decision Support. ### Step 3: Build vs Buy vs Partner Analysis Evaluate approach for top opportunities. ### Step 4: Data Moat Assessment Evaluate proprietary data, flywheel effects, replicability, and time to defensibility. ### Step 5: UX and Trust Considerations Transparency, user control, graceful failures, progressive disclosure, trust building. ### Step 6: Implementation Roadmap Phase 1: MVP → Phase 2: Expansion → Phase 3: Differentiation ### Step 7: Risk and Mitigation Planning Value, usability, feasibility, and viability risks. ## Framework Reference - Marty Cagan's V/U/F/V Risk Framework - Andrew Ng's AI Transformation Playbook - Ben Evans on AI Moats - Julie Zhuo on Product Strategy