pm-frameworks
Expert knowledge of proven product management frameworks for discovery, growth, measurement, planning, and AI-era practices.
What this skill does
# 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 1. **Evidence over opinion** - Always ask "what evidence do we have?" 2. **Prototype over document** - Ship something testable 3. **Users over internal debate** - Talk to real customers 4. **Small experiments** - Test assumptions cheaply 5. **Frameworks as tools, not rules** - Apply judgment --- *This skill surfaces PM frameworks from the `/frameworks/` and `/thought-leaders/` directories.*
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