| name | ai-product-strategy |
| description | Develop AI product strategy and identify AI opportunities for your product. Use when: ai strategy, ai product, ai features, ai roadmap, ai opportunities, build vs buy ai. |
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 โ Phase 2: Expansion โ 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
