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Product Strategy

skill-aroyburman-codes-pm-skills-product-strategy · by aroyburman-codes

Structured product strategy framework for AI product roles. Covers: market entry, competitive positioning, build-vs-buy, long-term vision.

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Install

$ agentstack add skill-aroyburman-codes-pm-skills-product-strategy

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

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About

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)

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

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Versions

  • v0.1.0 Imported from the upstream source.