# AI Product Strategy

> 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: `varunk130/ai-product-strategy` (Agent Skill)
- Install (CLI): `npx skillmds@latest add varunk130/ai-product-strategy`
- Raw SKILL.md: https://api.skillmd.com/api/skills/varunk130/ai-product-strategy/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Product & Planning
- Author: varunk130 (https://skillmd.com/u/varunk130)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/varunk130/ai-product-strategy

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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