PM Frameworks Skill
Expert knowledge of proven product management frameworks for discovery, growth, measurement, planning, and AI-era practices.
When to Invoke
Auto-invoke this skill when users discuss:
- Discovery: Feature validation, user research, testing assumptions, "should we build this?", risk assessment
- Growth: Acquisition, retention, virality, growth loops, product-led growth, network effects
- Planning: Roadmaps, prioritization, now-next-later, LNO framework, scoping projects
- Measurement: PMF surveys, metrics, success criteria, measuring product-market fit
- AI Products: Evals, fine-tuning vs RAG, prompt engineering, AI unit economics, production AI systems
- Strategy: Four fits, market-product fit, competitive positioning, business model
- Execution: PRDs, specs, issues vs stories, prototype-first development
Core Frameworks
Discovery Frameworks
Located in /frameworks/discovery/
Four Risks (Marty Cagan)
- Value Risk: Will customers buy/use this?
- Usability Risk: Can users figure it out?
- Feasibility Risk: Can we build it?
- Business Viability Risk: Does it work for the business?
Continuous Discovery (Teresa Torres)
- Weekly touchpoints with customers
- Opportunity Solution Trees
- Assumption testing
- Small experiments over big bets
Growth Frameworks
Located in /frameworks/growth/
Growth Loops (Elena Verna)
- Viral loops (user invites user)
- Content/SEO loops (content attracts users)
- Network effect loops (more users = more value)
- Paid loops (revenue funds acquisition)
Four Fits (Brian Balfour)
- Market-Product Fit
- Product-Channel Fit
- Channel-Model Fit
- Model-Market Fit
Product-Led Sales
- Self-serve to sales-assist progression
- Usage-based qualification
- Expansion revenue patterns
Planning Frameworks
Located in /frameworks/planning/
Now-Next-Later (Janna Bastow)
- Now: Current sprint, high confidence
- Next: Next 1-3 months, medium confidence
- Later: Future possibilities, low confidence
- Cone of uncertainty principle
LNO Prioritization (Shreyas Doshi)
- Leverage: High impact, do these first
- Neutral: Expected work, batch and schedule
- Overhead: Low value, minimize or eliminate
Scope Projects Down
- 80/20 principle for features
- Minimum viable scope
- Cut ruthlessly, add back later
Measurement Frameworks
Located in /frameworks/measurement/
PMF Survey (Rahul Vohra)
- "How disappointed would you be if you couldn't use this product?"
- Target 40%+ "very disappointed"
- Find your high-expectation customers
- Build for them, ignore the rest
AI-Era Practices
Located in /frameworks/ai-era-practices/
Prototype-First (Aakash Gupta)
- Ship prototypes before docs
- Code is the spec
- Iterate faster than you document
Issues Not Stories (Linear)
- Describe the problem, not the solution
- Let engineers figure out how
- Direction → Building → Quality phases
AI Unit Economics
- Cost per interaction modeling
- Inference costs at scale
- Value vs cost tradeoffs
Continuous Calibration
- Agency vs control spectrum
- When to give AI more autonomy
- Testing probabilistic systems
Organizational AI Adoption (CODER Framework)
- Culture, Organization, Data, Expertise, Roadmap
- Systematic approach to AI transformation
AI Technical Frameworks
Located in /frameworks/ai/
Production AI Systems (Chip Huyen)
- Data quality > model complexity
- Monitoring and observability
- Handling model degradation
Fine-tuning vs RAG Decision
- RAG for dynamic data, domain knowledge
- Fine-tuning for style, task specialization
- Cost and maintenance tradeoffs
AI Evals (Aman Khan)
- Prompt-level testing
- Task-level testing
- System-level testing
- Regression testing for AI
How to Apply Frameworks
Conversationally, Not as Lectures
Don't say: "Let me explain the Four Risks framework..."
Do say: "What evidence do you have that users want this? That's the value risk."
Ask Questions That Apply Frameworks
- "What's the smallest thing you could test this week?" (Continuous Discovery)
- "Is this Leverage, Neutral, or Overhead work?" (LNO)
- "Can you prototype this before writing the PRD?" (Prototype-First)
- "What's your growth loop here?" (Growth Loops)
Push Toward Action
- Prototype over document
- Test with users over internal debate
- Small experiments over big bets
- Evidence over opinion
Thought Leaders
Detailed profiles in /thought-leaders/:
- Marty Cagan - Discovery, empowered teams, four risks
- Teresa Torres - Continuous discovery, opportunity trees
- Elena Verna - Growth loops, product-led growth
- Brian Balfour - Four fits, growth strategy
- Chip Huyen - Production AI, ML engineering
- Aman Khan - AI evals, vibe-driven development
- Janna Bastow - Now-Next-Later, roadmapping
- Aakash Gupta - Prototype-first, visual frameworks
- Rahul Vohra - PMF survey, high-expectation customers
- Ravi Mehta - Product Strategy Stack
Integration with Commands
This skill provides background knowledge for:
/strategy-session - Apply frameworks conversationally/four-risks - Deep dive on risk assessment/growth-loops - Identify growth mechanisms/four-fits - Assess market-product alignment/lno-prioritize - Categorize work by leverage/now-next-later - Build roadmaps/pmf-survey - Measure product-market fit/ai-cost-check - Model AI economics/start-evals - Design AI evaluation
Key Principles
- Evidence over opinion - Always ask "what evidence do we have?"
- Prototype over document - Ship something testable
- Users over internal debate - Talk to real customers
- Small experiments - Test assumptions cheaply
- Frameworks as tools, not rules - Apply judgment
This skill surfaces PM frameworks from the /frameworks/ and /thought-leaders/ directories.