Mental models: the complete list of 365

A mental model is a simple idea about how the world works that you can carry from one problem to the next. Supply and demand, compounding, inversion, the map is not the territory: each one is a short way of seeing what is really going on, and a reminder of what to check before you decide.

No one model fits every problem. Charlie Munger’s advice was to carry a “latticework” of them, so you can look at a decision from several sides. This page lists all 365 we cover, sorted not by academic field but by the situation they help with. Each name links to its page, with a short explanation, a story, and related models.

Decisions: Which way should I go?

Models for making a decision. See all 35 in this situation.

A/B Testing: When opinions clash, change one thing and let real behaviour decide.
Back-of-the-Envelope Calculation: A rough answer in five minutes often beats a precise one next month.
Cost-Benefit Analysis: Count everything a choice will cost and everything it will give, not just what is easy to see.
Decision Tree: Draw your choices as branches, and the questions that really matter come into view.
Law of Diminishing Marginal Utility: Each extra helping of a good thing gives you a little less than the one before.
Opportunity Costs: The true price of any choice is the best thing you gave up to make it.
Pro-Con List: Getting reasons onto paper, and weighing them, beats juggling them in your head.
Sensitivity Analysis: Not all assumptions are equal: find the few that swing the whole result.
Utilitarianism: Judge an action by its consequences for everyone it touches.
Utility Values: Value lives in the person, not the object, so the same thing is worth different amounts to different people.
Veil of Ignorance: Write the rules as if you did not know which seat you would get.
Discount Rate: How much the future counts today depends on one number, and small changes in it flip big decisions.
Inflation: Money quietly loses value over time, so plans set in fixed amounts slowly shrink.
Net Present Value: Money has a timestamp: compare what something costs today with what its future returns are worth today.
Switching Costs: The effort of changing keeps people where they are, even when something better exists.
Counterfactual Thinking: To know what made a difference, ask what would have happened without it.
Exit Strategy: The best time to plan your way out is before you go in.
OODA Loop: Whoever observes, makes sense, decides and acts faster can adapt while others are still catching up.
Second-Order Thinking: Every action has consequences, and those consequences have consequences of their own.
Thought Experiment: Careful imagination can test an idea before it costs you anything.
Analysis Paralysis: Waiting for perfect information can cost more than acting on good enough.
False Dilemma: When a choice is framed as either-or, the best option is often the one nobody mentioned.
Grey Thinking: Most important questions have no clean right side, and the best answers often sit between the extremes.
Hick’s Law: The more options you face, the longer it takes to choose.
Information Overload: Past a certain point, more information buries the one signal that matters.
Paradox of Choice: Some choice makes us free; too much choice makes us anxious and less satisfied.
Satisficing: Set a bar for good enough, and stop searching when something clears it.
Tendency to Want to Do Something: We feel driven to act, even when waiting would serve us better.
Burn the Boats: Removing the way back can turn a hesitant effort into total commitment.
Circle of Competence: Knowing where your knowledge ends matters more than how far it reaches.
Devil’s Advocate Position: An idea worth backing should survive someone arguing hard against it.
Nuclear Option: The most extreme move can settle a fight, but its damage may outlast the problem it solved.
Pyrrhic Victory: A win that costs too much can leave you worse off than losing.
Sunk Cost Fallacy: What you have already spent is gone, so it should not decide what you do next.
Winner’s Curse: In a contest over an uncertain prize, the winner is often whoever overestimated it most.

Risk: What could go wrong, and what will I do if it does?

Acting when you cannot know what happens next, and protecting yourself in case it goes wrong. See all 32 in this situation.

Expected Value: A choice is worth its average result across all the ways it could turn out.
Fat-Tailed Distributions: In some areas, extreme events are far more common than the bell curve says.
Foxes vs Hedgehogs: Some minds know many things, others one big thing, and each has its blind spot.
Law of Large Numbers: Luck is wild in small samples and predictable in large ones.
Lindy Effect: For things that do not wear out, every year survived predicts more years to come.
Monte Carlo Simulation: When odds are too tangled to calculate, play the future many times and count.
Prediction Market: When people must pay for being wrong, their forecasts get sharper.
Probabilistic Thinking: The future is a spread of possible outcomes, each with its own odds.
Randomness: Much of life is chance, and our minds invent patterns that are not there.
Super Forecasters: Good prediction comes less from genius than from habits anyone can learn.
Availability Bias: What comes to mind easily feels likely, whether or not it is.
Conjunction Fallacy: Every added detail makes a story more convincing and less likely.
Gambler’s Fallacy: Chance keeps no score, so nothing is ever due.
Hot-Hand Fallacy: A winning streak feels like momentum, but it is often luck on a good run.
Monte Carlo Fallacy: A roulette wheel has no memory, however long the streak.
Mr Market: The market is a moody partner: use its offers, never its moods.
Prospect Theory: Losses hurt about twice as much as equal gains please, and that bends our choices.
Black Swan Event: What matters most is often what nobody saw coming.
Boiling Frog: The most dangerous changes are often the slowest ones.
Butterfly Effect: In a complex system, a tiny change at the start can grow into a huge difference at the end.
Chaos Theory: Some systems follow exact rules yet still cannot be predicted far ahead.
Murphy’s Law: If something can go wrong, given enough time and people, it eventually will.
Peak: Most rises top out, and the top is the hardest place to see it from.
Unknown Unknowns: The biggest risks are often the ones missing from your list.
Antifragility: Some things break under stress, some resist it, and some grow stronger from it.
De-Risking: You can keep most of the upside while cutting the risk of ruin.
Margin of Safety: Build in a buffer, so that being wrong is not a catastrophe.
Moral Hazard: People take bigger risks when someone else will pay if things go wrong.
Preserving Optionality: When the future is unclear, the right to choose later is worth paying for.
Resilience: Setbacks are certain; collapse is not, if you prepare to recover.
Scenario Analysis: Rehearse several futures, so whichever one arrives feels familiar.
Stop the Bleeding: When losses mount, halt them first and plan the recovery after.

People: Why do people act as they do, and how do I work with them?

Understanding others, and getting people to pull together. See all 60 in this situation.

Frame of Reference: Every judgement is measured against something; change the baseline and the answer can change.
High Context vs Low Context: Some cultures put the meaning in the words; others leave it in the relationship and the silence.
Introverts vs Extroverts: People differ in where they find their energy, and good teams make room for both kinds.
IQ vs EQ: Being clever and being wise with people are different strengths, and big decisions need both.
Language Instinct: Children are born ready for language, and some abilities grow best through use, not drills.
Maslow’s Hierarchy of Needs: Unmet basic needs drown out higher ones, so check the foundations before blaming motivation.
Peak-end Rule: We remember an experience by its most intense moment and its ending, not by its length.
Theory of Mind: Other people act on what they know and believe, not on what you know.
False Consensus Effect: We think far more people share our views and choices than really do.
Fundamental Attribution Error: We blame people’s character for their behaviour and forget the situation pushing them.
Halo Effect: One shining quality makes us rate everything else about a person or product higher.
Hanlon’s Razor: Never put down to malice what can be explained by mistake, muddle or accident.
Horn Effect: One bad impression can cast a shadow over everything else we see in someone.
In-Group Favouritism: We give more trust, help and reward to people we see as our own, even when the group means nothing.
Most Respectable Interpretation: Read other people’s words in the most reasonable light first; the harshest reading is rarely right.
Out-Group Bias: We judge outsiders more harshly, and a simple team name is enough to start it.
Liking and Loving Tendency: Once we like someone or something, we overlook its flaws and overrate its merits.
Anchoring: The first number we hear quietly steers every judgement that follows.
Backfire Effect: Facts thrown at a cherished belief can make people hold it tighter.
Bait and Switch: An offer built to change once you are committed is not the offer you are buying.
Dark Patterns: Design can quietly steer you into choices you never meant to make.
Framing: The same facts can lead to opposite choices, depending on how they are presented.
Nudging: Small changes in how choices are arranged can change what people choose, without forbidding anything.
Reciprocity: We feel a strong pull to return what we are given, kindness and harm alike.
Social Proof: When we are unsure what to do, we copy what other people are doing.
Streisand Effect: Trying to hide something often makes far more people look at it.
Winning Hearts and Minds: Lasting support comes from meeting people’s real needs, not from forcing them to comply.
Appeasement: Giving in to keep the peace can invite bigger demands later.
Best Alternative to a Negotiated Agreement: Your power in a deal comes from what you will do if the deal fails.
Call Your Bluff: Many threats are cheaper to make than to carry out, so test them before you fold.
Deterrence: A threat that others believe you will carry out can stop a fight before it starts.
Mutually Assured Destruction: When both sides can destroy each other, neither dares to strike first.
Polarity: Once an issue grows two charged ends, everything gets pulled towards one or the other.
Redline: A limit decided in advance stops you giving ground one small step at a time.
Sayre’s Law: The smaller the stakes, the more bitter the fight can become.
Strawman Fallacy: Beating a weaker version of someone’s argument proves nothing about the real one.
Trojan Horse: The most dangerous threats often arrive looking like gifts.
Zero-Sum vs Win-Win: Many contests that look like fights over a fixed pie are chances to grow it.
Cooperation: Together, with the right rules, we can do what none of us could do alone.
Free Rider Problem: If people can benefit without paying, many will let others pay.
Game Theory: Your best move often depends on what others will do, and on what they expect you to do.
Pirate Code: Every group runs on rules of its own, and they predict behaviour better than the official ones.
Prisoner’s Dilemma: Choices that are sensible for each person can add up to a worse result for everyone.
Social Norms vs Market Norms: Putting a price on goodwill can make people care less, not more.
Tit for Tat: Start kind, answer in kind, forgive quickly, and others learn to cooperate with you.
Tragedy of the Commons: A resource everyone can use and no one looks after tends to be used up.
Trust: Trust lets us cooperate without watching every move, but it lasts only when betrayal has a cost.
Carrot and Stick: Rewards and punishments change behaviour, but not always the way you planned.
Distributive Justice vs Procedural Justice: People can accept losing under fair rules, but resent even a good result reached unfairly.
Golem Effect: Low expectations can drag people down to meet them.
Managing to the Person: People differ, so the best way to lead each of them differs too.
Peter Principle: People tend to be promoted until they reach a job they cannot do well.
Principal-Agent Problem: When someone acts for you, their interests and yours may quietly part ways.
Pygmalion Effect: High expectations can lift people up to meet them.
Bystander Effect: The more people who see a problem, the less likely any one of them is to act.
Chilling Effect: Punish a few people visibly, and many more will silence themselves.
Dunbar’s Number: We can keep up only about 150 real relationships at once.
Groupthink: A group that values harmony over honesty can talk itself into disaster.
Hierarchical Organisation: Layers of command let large groups act as one, at the cost of speed and candour.
Power Vacuum: When authority disappears, someone always rushes to fill the gap, often not who you would choose.

Work: How do I get the right things done?

Models for getting work done. See all 43 in this situation.

Activation Energy: Good things often fail to happen not because they are hard, but because starting is.
Catalysts: The right spark can make change happen faster, without doing the work itself.
Compounding Effect: Gains that build on earlier gains grow slowly, then dramatically.
Conditioning: A signal paired often with something that matters comes to trigger the feeling alone.
Dopamine Loop: The brain learns most from surprise rewards, and chases the cues that predict them.
Forcing Function: Shape the situation so the right action becomes the easiest, or the only, path.
Inertia: People and organisations keep moving along their current path until a real force makes them change.
Momentum: Progress builds on itself: early wins make the next ones easier, and slides gather speed too.
Bikeshedding: Groups spend the most time on what everyone understands, and the least on what matters.
Law of Diminishing Returns: Adding more of one thing eventually buys less each time, and can make things worse.
Leverage: A small force in the right place can move a great weight, for better or worse.
Manager’s Schedule vs Maker’s Schedule: One meeting costs a manager an hour, and a maker half a day.
Pareto Principle: A small share of causes usually produces most of the results.
Top of Your Mind: Whatever you think about in idle moments gets hours of free work.
Two-Front War: Fighting two battles at once often means losing both.
Tyranny of Small Decisions: Many small, sensible choices can add up to a result nobody wanted.
Velocity: Progress is speed with direction; being busy is not the same as moving forward.
Hofstadter’s Law: It always takes longer than you expect, even when you allow for that.
Minimum Viable Product: Build the smallest thing that works, then learn before investing more.
Mythical Man-Month: Adding people to a late project usually makes it later.
Perfect is the Enemy of Good: Waiting for the ideal can cost you the useful.
Premature Optimisation: Polishing before you understand wastes effort and locks in mistakes.
Unforced Error: Many of our worst setbacks are mistakes nobody forced us to make.
Algorithms: Clear steps solve a problem the same way every time.
Boots on the Ground: To understand or change a place, you have to be there.
Cargo Cult: Copying the look of success rarely delivers the real thing.
Commandos: Different stages of growth need different kinds of people.
Crowdsourcing: Many people, each giving a little, can solve what a few experts cannot.
Directly Responsible Individuals: Every outcome needs one named owner, or it becomes nobody’s job.
Divide and Conquer: Split a big opponent or problem into parts you can handle one at a time.
Double-Entry Bookkeeping: Every transaction has two sides, and recording both keeps the books honest.
Entropy: Left alone, things drift towards disorder; order has to be paid for.
Institutional Knowledge: Much of what an organisation knows lives in people, not documents.
Parallel Processing: Split work into parts that can run at once, and finish sooner.
Replication: Copying lets one success spread far, and it spreads the flaws just as faithfully.
Comparative Advantage: Do what costs you least to do, even if you are best at everything.
Deliberate Practice: Skill grows from focused work on weaknesses, not from hours alone.
Divergent Thinking vs Convergent Thinking: Open up the options, then close them down.
Generalist vs Specialists: Breadth helps you adapt; depth helps you excel. The mix depends on your world.
Potential Energy: Stillness is not emptiness: value can be stored, waiting to be released.
Resonant Frequency: Small pushes in the right rhythm can build into enormous effects.
Spacing Effect: We remember more when learning is spread out than when it is crammed.
Specialisation: Focusing on a narrow task makes each person far more productive.

Strategy: How do I win when others want the same thing?

Models for strategy and competition. See all 56 in this situation.

Barriers to Entry: The harder a market is to enter, the longer those already inside can keep their profits.
Center of Gravity: Find the one point everything depends on, then protect it or aim there.
Economies of Scale: When fixed costs are spread over more units, each one becomes cheaper to make.
Moats: Lasting success needs a structural defence, not just a moment of brilliance.
Niches: You don’t have to win everywhere; fit one need better than anyone else.
Punching Above Your Weight: Resources set the odds, but a smaller side can win by choosing where to fight.
Secrets: The most valuable insights are important truths that most people do not yet believe.
Seizing the Middle: Whoever controls the point that everything must pass through holds power beyond their size.
Sustainable Competitive Advantage: An edge only matters for long if rivals cannot copy it quickly.
Trademarks: A distinctive sign becomes a promise that customers learn to trust at a glance.
Adverse Selection: When one side knows more about quality than the other, the best tend to leave and the worst stay.
Apostle Model: Satisfied customers drift away; only delighted ones bring others with them.
Churn: Growth means little if customers leave as fast as they arrive.
Customer Development: Treat every idea about customers as a guess, and test it with real people early.
Jobs to be Done: People do not buy products; they hire them to make progress in their lives.
Lock-in: Today’s convenient choice can become tomorrow’s trap when leaving costs too much.
Loss Leader Strategy: A price can be a doorway, not a destination: the bargain is meant to lead you somewhere.
Loyalists vs Mercenaries: Discounts buy attention quickly, but they rarely buy commitment.
Personas: You design better for people when you picture a specific person rather than “users”.
Pivot: Change direction on what you have learned, while keeping what you are good at.
Product/Market Fit: When something truly meets a pressing need, people pull it towards them.
Crossing the Chasm: What enthusiasts love, the mainstream still needs to see proven, complete and recommended.
First Mover Advantage: Arriving first can be worth a fortune, but only if you can defend the lead.
Flywheel: Many small pushes in the same direction build momentum that one big heave never could.
Long Tail: When shelf space is unlimited, many small niches can add up to more than a few hits.
Metcalfe’s Law: The value of a network grows much faster than the number of people in it.
Network Effects: Some products become more valuable every time another person starts using them.
Power Law: In many areas, a few things account for most of the results.
S-Curves: New ideas spread slowly, then suddenly, then slowly again as the market fills.
Supply and Demand: Prices rise when more people want something than there is to go round, and fall when there is plenty.
Technology Adoption Lifecycle: People take up new things at different speeds, and each group needs a different reason to join.
Winner Takes Most Markets: When being biggest makes you more attractive, a small early lead can become lasting dominance.
Creative Destruction: New ways of doing things grow by tearing down the old ones.
Cultural Evolution: Ideas, habits and tools evolve like living things, only faster: the useful spread and the rest fade.
Disruptive Innovations: Giants are often toppled by cheap, simple newcomers they once thought too small to matter.
Generals Fighting the Last War: The lessons of the last battle can leave you perfectly prepared for a fight that never comes.
Natural Selection: The environment decides what thrives, and when it changes, so do the winners.
Only the Paranoid Survive: Success breeds complacency, so look hardest for threats when things are going well.
Paradigm Shift: Sometimes a whole field’s basic assumptions are wrong, and progress means replacing the frame.
Red Queen Effect: When everyone else keeps improving, you must keep running to stay in place.
Survival of the Fittest: Success goes not to the strongest, but to whoever best fits the conditions.
Arbitrage: When the same thing sells for different prices in different places, someone profits from closing the gap.
Idea Maze: Breakthroughs come from exploring many paths and learning from every dead end.
Joy’s Law: However strong your team, most of the smartest people work for someone else.
Local Optimum vs Global Optimum: Being the best in your neighbourhood can stop you finding a much higher peak beyond it.
Luck Surface Area: You cannot control luck, but you can widen the area it can land on.
Simultaneous Invention: When the conditions are right, several people often reach the same idea at once.
Arms Race: When rivals keep matching each other’s build-up, both spend more and neither ends up safer.
Asymmetric Warfare: A weaker side wins by refusing to fight on the stronger side’s terms.
Beachhead Strategy: Win one small, defensible position first, then use it to push further.
Counter-Insurgency: Persistent resistance is fed by something, and cutting off that supply works better than force alone.
Flypaper Theory: Draw a threat to a place of your choosing, and it stays away from what matters most.
Guerrilla Warfare: A small, nimble player can beat a giant by choosing where, when and how to fight.
Nash Equilibrium: A stable outcome is one where nobody gains by changing course alone, even if all would gain together.
Strategy vs Tactics: Brilliant moves cannot rescue a weak plan, and a good plan fails without good moves.
War of Attrition: Some contests are won not by the best blow, but by whoever can last the longest.

Evidence: Is this really true?

Checking whether something is really true before you trust it. See all 68 in this situation.

Base Rate Fallacy: A vivid detail means little until you know how common the outcome is in general.
Bayes’ Theorem: Change your mind in proportion to the evidence: a lot for strong clues, a little for weak ones.
Central Limit Theorem: Average enough random pieces and the averages settle into a predictable bell shape.
Conditional Probability: Odds are never fixed: they change the moment you learn something new.
Confidence Interval: The honest answer to many questions is a range, not a single number.
Distributions: A single number hides the shape of the spread, and the shape often matters more.
Error Bars: Every number comes with a margin of doubt, whether or not anyone draws it.
Frequentists vs Bayesians: Probability can mean how often something happens, or how strongly you believe it will.
Mean, Median and Mode: “Typical” can mean three different numbers, and each one tells a different story.
Normal Distribution: Most things cluster around the middle, but the bell curve makes extremes look rarer than they are.
Probability Distribution: Good decisions weigh everything that could happen, not just the single most likely outcome.
Regression to the Mean: Extreme results tend to be followed by ordinary ones, because luck rarely repeats itself.
Standard Deviation: An average tells you the centre; the spread tells you how much to trust it.
Variance: Every process wobbles; the skill is telling ordinary wobble from a real warning sign.
False Negative: A clean result should lower your concern, not end it.
False Positive: An alarm is a question, not an answer.
Falsification: Trying to prove yourself wrong is the surest route to finding out what is right.
Hypothesis: A good guess is one that reality can prove wrong.
Inductive Reasoning: Experience suggests what will happen next, but it can never promise it.
Meta-Analysis: Many small, uncertain studies, pooled together, can give one clear answer.
Null Hypothesis: Assume a claim does nothing until the evidence forces you to think otherwise.
Occam’s Razor: When explanations compete, start with the simplest one that fits the facts.
P-Values: A small p-value says a result would be surprising by chance, not that an idea is true.
Placebo Effect: Belief and care can make people feel better, even when the treatment itself does nothing.
Randomised Controlled Experiments: Let chance decide who gets the treatment, and any difference left is the treatment’s doing.
Scientific Method: Let evidence, not authority or wishful thinking, decide what you believe.
Statistical Significance: A significant result is one that chance alone would rarely produce; it need not be big.
Systematic Review: To know what the evidence says, gather all of it by rules set in advance.
Causal Fallacy: Two things happening together is not proof that one caused the other.
Clustering Illusion: Randomness is lumpier than we expect, so we see patterns where there are none.
Confounding Factor: When two things move together, a hidden third factor may be pulling both strings.
Correlation and Causation: Patterns are where good questions begin, not where they end.
Regression Fallacy: Inventing a cause for a return to normal is one of the commonest mistakes we make.
Texas Sharpshooter Fallacy: Draw the target after the shots and every shooter looks like a marksman.
Anecdotal Evidence: A vivid story shows that something happened once, never how often it works.
Data Dredging: Search enough data and some pattern will always turn up, by chance alone.
Hasty Generalisation: A few examples, however vivid, are not enough to support a sweeping rule.
Non-Response Bias: The people who stay silent can change the answer as much as those who reply.
Overgeneralising from Small Samples: Small samples swing wildly by chance, so their patterns often vanish when you look again.
Publication Bias: The studies we read are often the lucky survivors of all the studies that were run.
Replication Crisis: A finding earns trust only when others repeat the work and get the same result.
Response Bias: What people say about themselves often reflects how they want to appear, not what they do.
Selection Bias: How you choose a sample can decide the answer before you ask a single question.
Survivorship Bias: When failures vanish from view, the survivors look like the whole story.
Ad Hominem: An argument does not become false because you dislike the person making it.
Appeal to Authority: A famous name or senior title is not evidence; ask how they know.
Appeal to Emotion: Strong feelings can carry an argument that the facts alone would never support.
Appeal to Ignorance: No evidence of harm is not evidence of no harm, unless someone has really looked.
Appeal to Pity: A sad story can stir real sympathy and still have nothing to do with the question.
Bandwagon Fallacy: How many people believe something tells you about its popularity, not its truth.
Black and White Fallacy: Most real choices have more than the two options on offer.
Circular Argument: A claim cannot be its own proof, however smoothly it is restated.
Equivocation: A statement can be technically true and still built to mislead.
Non Sequitur: True facts can still be strung together into a conclusion that does not follow.
Red Herring Fallacy: The most persuasive answer is sometimes an answer to a different question.
Slippery Slope: A first step does not lead to disaster unless every link in the chain holds.
Tu Quoque: Pointing out that a critic does the same thing does not make the criticism wrong.
Bias from Incentives: When pay or status depends on a conclusion, people tend to reach it, sincerely.
Echo Chambers: Surrounded only by people who agree, our views grow more extreme and more certain.
Filter Bubble: A feed that learns what you like can quietly shrink your view of the world.
Garbage In Garbage Out: No system, however clever, can produce better answers than the information it is given.
Heisenberg Uncertainty Principle: Some things cannot be pinned down at once, and looking closely can change what you see.
Narrative Instinct: We turn events into stories, and often see intention and meaning where there is only chance.
Observer Effect: Watching people or systems changes how they behave.
Potemkin Village: An impressive front can be built precisely to hide what is behind it.
Proxy: A stand-in measure is only useful while it moves in step with what really matters.
The Map is not the Territory: Every model is a simplification, and when it disagrees with reality, reality wins.
Zombie Ideas: Some ideas keep walking long after the evidence has killed them.

Your own mind: Is my own thinking leading me astray?

How your own judgement can be quietly pulled off course. See all 31 in this situation.

Blind Spot Bias: We see bias clearly in other people and hardly at all in ourselves.
Cognitive Dissonance: When our actions and beliefs clash, we often change the story rather than the behaviour.
Commitment and Consistency Bias: Once we have said or done something, we bend later choices to stay consistent with it.
Confirmation Bias: We look for, notice and remember the evidence that agrees with what we already believe.
Denial: When a truth is too painful, we refuse to see it, often until it is too late.
First-Conclusion Bias: The first explanation that fits tends to become the only one we consider.
Hindsight Bias: Once we know how things turned out, the outcome seems to have been obvious all along.
Observer-Expectancy Bias: We tend to see what we expect to see, and sometimes cause it without meaning to.
Semmelweis Reflex: We reflexively reject new evidence when accepting it would mean we were wrong.
Tendency to Stereotype: We judge people by the group they seem to belong to, not by who they are.
Birth Lottery: Where, when and to whom we are born shapes our chances more than almost anything we later do.
Dunning-Kruger Effect: The less we know about something, the more likely we are to overrate our skill at it.
Fixed Mindset vs Growth Mindset: Whether we think ability is fixed or can grow shapes which challenges we take on.
Imposter Syndrome: Even very capable people can feel like frauds, sure they will soon be found out.
Just World Hypothesis: We like to believe that people get what they deserve, so we blame the unlucky.
Optimism Bias: We expect things to turn out better, faster and cheaper than they usually do.
Self-Serving Bias: We take credit for our successes and blame our failures on everything else.
Victim Blame: When harm happens, it is tempting to blame the people who suffered it.
Deprival-Superreaction Tendency: Losing something we have, or almost have, provokes a reaction far bigger than gaining it would.
Fear: Fear keeps us safe, but when it spreads it can create the very danger it warns of.
Freudian Slip: A slip of the tongue can sometimes reveal what we really think.
Influence of Stress: A little pressure sharpens judgement; too much breaks it.
Loss Aversion: A loss hurts more than an equal gain pleases, so we pay to avoid losses.
Scarcity: When something seems scarce, we want it more and think about little else.
Self-Preservation: The drive to survive is powerful and often wise, but it narrows what we can see.
Disliking and Hating Tendency: Once we dislike someone or something, we stop judging it fairly.
Envy and Jealousy Tendency: Seeing what others have can make us want things we never needed.
Bandwagon Effect: The more people do something, the more others join in, whatever the evidence.
Gateway Drug Theory: A small, easy first step can make a much bigger next step feel natural.
Grass is Greener Mentality: Other options look better from a distance than they turn out to be up close.
Relativity: We judge our situation less by absolute standards than by comparison.

Fixing problems: Why does this keep going wrong, and how do I fix it for good?

Models for fixing problems and systems. See all 40 in this situation.

Black Box: When you cannot see how a system reaches its answers, you cannot easily spot its mistakes.
First Principles Thinking: Strip a problem back to what you know is true, then build up again from there.
Inversion: To find the way to success, first work out what would guarantee failure, then avoid it.
Lateral Thinking: When digging harder gets you nowhere, the answer is often to dig somewhere else.
Maslow’s Hammer: If the only tool you know is a hammer, every problem starts to look like a nail.
Post Mortem: After something goes wrong, look honestly at how it happened, so it never happens again.
Proximate vs Root Cause: The trigger that sets off a problem is rarely the condition that made it possible.
Reframe the Problem: Changing the question can turn an impossible problem into a solvable one.
The 5 Whys: The first explanation for a problem is rarely the deepest, so keep asking why.
Bottlenecks: A system can only move as fast as its narrowest point, so find that point first.
Ecosystems: Nothing acts alone: a change in one place travels along links you cannot see.
Feedback Loops: When a system’s results feed back into it, they either steady it or spin it out of control.
Homeostasis: Stability is not stillness: healthy systems stay steady by correcting themselves all the time.
Hysteresis: Remove the cause of a problem, and its effects may still linger.
Le Chatelier’s Principle: Push on a system in balance and it pushes back, settling into a new balance.
Broken Windows Theory: Small signs of neglect tell people that nobody cares, and invite bigger trouble.
Chain Reaction: In a tightly linked system, one small trigger can set off everything after it.
Containment: When you cannot solve a problem at once, stop it spreading first.
Critical Mass: Many efforts only take off once they pass a threshold; below it, they fizzle out.
Domino Effect: One small fall can set off a chain that topples far bigger things.
Herd Immunity: Some protections only work when enough of us take part, and then they shield everyone.
Quarantine: Isolate what might be harmful long enough to learn whether it really is.
Tipping Point: Pressure builds quietly for a long time, then change arrives all at once.
Blowback: Actions meant to control others can return, years later, as the very harm they were meant to prevent.
Cobra Effect: A reward for fixing a problem can end up paying people to create more of it.
Collateral Damage: Every action aimed at one target also lands on people who never chose it.
Hydra Effect: Attack a problem without touching its cause, and it can come back in several new forms.
Jevons Paradox: Making a resource cheaper to use often means we end up using more of it, not less.
Law of Unintended Consequences: Actions in complex systems produce results that nobody planned.
Spillover Effects: The effects of a decision travel far beyond the people who made it.
Zero Tolerance Policy: Rules that allow no exceptions bring clarity, but can punish honest mistakes as harshly as real harm.
Cap and Trade: Fix the total you can afford, then let people trade to meet it as cheaply as possible.
Coase Theorem: When bargaining is cheap, people can settle a shared harm with a deal.
Goodhart’s Law: When a measure becomes a target, people learn to hit the number and miss the point.
Government Failure: Government action meant to fix a problem can leave things worse than doing nothing.
Incentives: People do what they are rewarded for, not what they are told or asked.
Market Failure: Free markets go wrong when prices leave out costs that fall on someone else.
Perverse Incentives: A badly designed reward can pay people to produce the opposite of what you wanted.
Regulatory Capture: Watchdogs set up to guard the public can end up serving the industry they watch.
Shirky Principle: Institutions tend to preserve the problem to which they are the solution.

Want one at a time? Read today’s model, or follow along every week.