# Mental Models > Apply a Munger-style latticework of mental models from multiple disciplines to analyze a problem. Use when the user needs multi-disciplinary perspective, wants to avoid single-framework bias, or needs to triangulate insights from physics, biology, psychology, economics, math, and history simultaneously. - Skill: `dvcrn/mental-models` (Agent Skill) - Install (CLI): `npx skillmds@latest add dvcrn/mental-models` - Raw SKILL.md: https://api.skillmd.com/api/skills/dvcrn/mental-models/raw - Safety review: pending (external: skill-scanner PASS, skillspector PASS) - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: dvcrn (https://skillmd.com/u/dvcrn) - Updated: 2026-09-08 - Page: https://skillmd.com/skills/dvcrn/mental-models --- # Mental Models (Munger-Style Latticework) **Mental models** are simplified representations of how the world works, drawn from multiple disciplines. Charlie Munger's key insight: you need a **latticework of mental models** from many fields — not just one hammer looking for nails. By viewing a problem through multiple disciplinary lenses simultaneously, you get triangulated wisdom that no single perspective can provide. The goal is to have ~100 models and know when each applies. --- Analyze the current topic or problem under discussion through the **latticework of mental models**. Apply models from at least 6 different disciplines. Cross-reference and triangulate. Apply this framework to whatever the user is currently working on or asking about. --- ## Discipline 1: Physics & Engineering Apply relevant models: - **Leverage** — Where is the point of maximum leverage? Small input, large output? - **Friction** — What friction exists in the system? What would reducing friction enable? - **Critical mass** — Is there a threshold that, once crossed, triggers self-sustaining change? - **Entropy** — Is this system tending toward disorder? What energy is needed to maintain order? - **Feedback loops** — Positive (amplifying) or negative (stabilizing) feedback? - **Redundancy & margin of safety** — Where are the single points of failure? - **Resonance** — Is there a frequency/timing that amplifies the effect? Which physics/engineering model is most illuminating here, and what does it reveal? ## Discipline 2: Biology & Evolution - **Natural selection** — What is being selected for? What traits survive in this environment? - **Adaptation vs. extinction** — Is the subject adapting fast enough to environmental change? - **Ecosystem dynamics** — What is the ecosystem? Who are the predators, prey, symbiotes, parasites? - **Red Queen effect** — Do you have to keep running just to stay in place? - **Niche construction** — Is the subject changing its environment, not just adapting to it? - **Immune system** — What are the defense mechanisms? What gets past them? - **Punctuated equilibrium** — Long stability interrupted by sudden change? Which biological model fits best, and what does it predict? ## Discipline 3: Psychology & Behavioral Science - **Incentives** — What behaviors are being rewarded? (Munger: "Show me the incentive and I'll show you the outcome.") - **Loss aversion** — Are people weighing losses ~2x more than equivalent gains? - **Social proof** — Is behavior driven by what others are doing rather than independent analysis? - **Commitment & consistency bias** — Are people doubling down because they've already committed? - **Availability heuristic** — Are recent/vivid events distorting probability estimates? - **Narrative fallacy** — Are we constructing a story that feels right but doesn't match the data? - **Pavlovian association** — What conditioned responses are at play? - **Dunning-Kruger** — Who is overconfident? Who is underconfident? Which psychological model explains the most about the human behavior in this situation? ## Discipline 4: Economics & Business - **Supply and demand** — What shifts the curves? Where is equilibrium moving? - **Comparative advantage** — What can be done here that can't be done better elsewhere? - **Opportunity cost** — What is being given up? Is it worth it? - **Marginal thinking** — What does one more unit cost/produce? (Not average — marginal.) - **Moats** — What creates durable competitive advantage? How wide and deep is the moat? - **Principal-agent problem** — Whose interests are misaligned? Who's playing with other people's money? - **Tragedy of the commons** — Are shared resources being depleted because individual incentives diverge from collective interest? - **Creative destruction** — Is something new destroying something old? Is that good or bad? Which economic model is most relevant, and what does it prescribe? ## Discipline 5: Mathematics & Statistics - **Power laws vs. normal distributions** — Is this a domain of averages or extremes? - **Compounding** — What is growing exponentially that looks flat now? - **Regression to the mean** — Is current performance sustainable, or will it revert? - **Bayes' theorem** — What should the prior be? How much should this evidence update it? - **Order of magnitude** — Are we arguing about 10% differences when there's a 10x factor we're ignoring? - **Combinatorics** — How many possible configurations exist? Are we exploring enough of the space? - **Asymmetry of outcomes** — Is the upside/downside symmetric, or heavily skewed? Which mathematical model provides the clearest insight? ## Discipline 6: History & Philosophy - **Chesterton's Fence** — Before removing something, understand why it was put there. - **Lindy effect** — Things that have survived a long time are likely to survive longer. - **Ozymandias effect** — All empires fall. What's the half-life of this? - **Hegelian dialectic** — What is the thesis, antithesis, and potential synthesis? - **Via negativa** — What should be *removed* rather than added? - **Skin in the game** — Who bears the consequences of the decision? (Taleb) - **Historical analogy** — What historical parallel illuminates this situation? Which historical/philosophical model offers the deepest wisdom? ## Cross-Disciplinary Triangulation Now synthesize across all six lenses: - **Convergence**: Where do multiple models from different disciplines **agree**? (High confidence) - **Divergence**: Where do they **disagree**? (Needs deeper investigation) - **Blind spots**: Which models are **missing** from the analysis? What discipline hasn't been consulted? - **Dominant model**: Which single model provides the most explanatory power for this specific problem? - **Ensemble insight**: What understanding emerges from combining the models that **no single model alone** could produce? ## Actionable Output - What is the **recommended course of action** based on the multi-model analysis? - What are the **key risks** identified by the models? - What **mental model** should the decision-maker keep at the forefront? - What would **Charlie Munger** probably say about this situation? --- "To the man with only a hammer, every problem looks like a nail." The cure is a toolbox full of mental models from every discipline. Use them all, trust no single one, and pay attention when they disagree.