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Ai product strategy

Skill varunk130/claude-code-skills/skills/product-management/ai-product-strategy

A curated, categorized library of 29 production-grade Claude Code custom skills across finance, product, strategy, game theory, and document processing.

Install
npx -y skills add varunk130/claude-code-skills --skill ai-product-strategy

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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.

SKILL.md

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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

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