Product Strategy

---
name: product-strategy
description: "Structured product strategy framework for AI product roles. Covers: market entry, competitive positioning, build-vs-buy, long-term vision."
argument-hint: "[interview question]"
---

# Product Strategy Skill

Apply a structured framework to PM product strategy questions targeting AI product roles.

## When to Use
- User asks "What strategy would you use for X"
- User asks "How would you enter market X"
- User asks "Define the product strategy for X"
- User asks "How would you decide between X and Y" (strategic choice)
- User asks about competitive positioning, market entry, or long-term vision
- User says `/product-strategy` followed by a question
- Any question about go-to-market, competitive dynamics, build-vs-buy, or strategic direction

## Context
- **Tuned for**: AI product roles at frontier AI companies
- **What matters**: Zooming out to the 30,000-foot view. These companies operate at the frontier — the best strategic thinking reasons about where the market is going, not just where it is.
- **Common pitfall**: Not landing a clear position. You must identify where the moat is, where commoditization is happening, and connect mission to business goals.

## Framework: Product Strategy (5 Sections)

### Section 1: Strategic Alignment & Clarifications
Ask 3-5 clarifying questions:
- **Scope**: Which product line? What timeframe (6mo vs 3yr vs 10yr)?
- **Constraints**: Are we resource-constrained? What's the competitive urgency?
- **Success**: What does winning look like? Revenue? Market share? Mission impact?
- **Context**: Any recent market shifts or company announcements to consider?

State the strategic question clearly in one sentence. Then:
- **Company Mission**: Restate and connect to the question
- **Current Position**: Where does the company stand today on this?
- **Strategic Tension**: What's the core trade-off or decision at the heart of this question?

### Section 2: The Landscape (Market & Leverage)
**Market Analysis:**
- Market size (TAM/SAM/SOM) with reasoning
- Growth rate and trajectory
- Key trends reshaping the landscape (AI adoption, regulation, platform shifts)

**Competitive Map:**
- Direct competitors and their positioning
- Indirect competitors and substitutes
- Where is the market commoditizing? Where is there differentiation?

**Porter's Five Forces** (applied to AI context):
- Threat of new entrants (open-source models, startups)
- Supplier power (compute providers, data sources, talent)
- Buyer power (enterprise vs consumer, switching costs)
- Threat of substitutes (alternative approaches, non-AI solutions)
- Competitive rivalry (between major AI labs and open-source)

**Unique Leverage**: What does THIS company have that others don't?
- For a model provider with distribution advantage: Consumer product reach, model capability leadership, developer ecosystem, strategic partnerships
- For a safety-focused lab: Safety leadership, alignment research, enterprise trust, reasoning capability
- For a research-first organization: Platform integration, research depth, scientific credibility, multimodal capabilities

### Section 3: Strategic Options (Build / Buy / Partner)
Present 3 distinct strategic options. For each:
- **Description**: What would we do?
- **Pros**: Why this could win
- **Cons**: What could go wrong
- **Requirements**: What capabilities/resources needed
- **Timeline**: When would we see results

Options should span a range:
1. **Conservative/Incremental**: Low risk, builds on existing strengths
2. **Moderate/Platform Play**: Medium risk, expands the moat
3. **Ambitious/Moonshot**: High risk, could redefine the category

### Section 4: The Recommendation
Pick one option (or a phased combination) and defend it:
- **What**: Crisp description of the strategy
- **Why Now**: What makes this the right moment
- **How**: High-level execution roadmap (Phase 1/2/3)
- **Who**: Key stakeholders and organizational implications
- **Moat**: How this builds sustainable advantage
- **Metrics**: How we'd measure strategic success (not just product metrics — market position, ecosystem health, revenue trajectory)

### Section 5: Risks & Pre-Mortem
Imagine it's 18 months later and the strategy failed. What went wrong?
- **Risk 1**: [Most likely failure mode] → Mitigation
- **Risk 2**: [Highest-impact failure mode] → Mitigation
- **Risk 3**: [Blind spot / unexpected competitor move] → Mitigation
- **Kill criteria**: What signals would tell us to pivot?

## AI-Specific Strategic Lenses

Always apply these when discussing AI company strategy:
- **Capability Trajectory**: How do improving model capabilities change this strategy in 6/12/24 months?
- **Safety-Capability Frontier**: How does this balance pushing capabilities vs. maintaining safety?
- **Open vs. Closed**: What's the right openness posture? (open-source model weights vs. API-only vs. hybrid)
- **Ecosystem Dynamics**: How does this affect the developer ecosystem, enterprise customers, and consumer trust?
- **Regulatory Landscape**: How might AI regulation (EU AI Act, executive orders) affect this?
- **Talent Market**: How does this affect ability to attract top researchers and engineers?

## Output Format
Structure as a strategic analysis — start conversational, then get structured. Aim for ~2500 words. Show your strategic reasoning, not just conclusions.

## Research-First Workflow
Before generating the answer:
1. **Research** — Use web search to find latest thinking from AI company blogs, industry analysts, market data, competitor intel. Do 5-10 searches.
2. **Cite sources** — Include `[linked source](url)` inline for major claims, data points, and trends.
3. **Display** the complete structured answer.

## What Good Looks Like
- Starts with clarifying questions to scope the strategy question
- Shows awareness of where value accrues vs. commoditizes in AI
- Reasons about competitive dynamics specific to AI companies (not generic strategy)
- Presents multiple options before recommending (shows breadth of thinking)
- Recommendation is opinionated and defensible
- Considers second and third-order effects
- Ties strategy back to company mission
- Shows understanding of the AI market structure (models, infrastructure, applications)