Mental models
The big ideas from many fields that are useful far outside them. Charlie Munger called a set of these a latticework: with enough of them, you can look at a problem from several sides instead of one. Each comes with a real example, where it applies, and where it comes from. 96 so far.
Today’s modelOpen the daily cardConnectionsSee how they link upThinking tools · 8
Circle of competence
Know where your real understanding ends, and keep your big bets inside that line.
First principles
Break a problem down to what you know is true and reason up from there, instead of copying what others have done.
Inversion
Work a problem backwards by asking what would guarantee failure, then make sure you avoid it.
Probabilistic thinking
Think in odds rather than certainties: estimate how likely each outcome is, and judge a decision by those odds rather than by the single result that happened.
Second-order thinking
Keep asking "and then what?" until you have looked at the consequences of the consequences.
The Feynman technique
Test whether you understand something by trying to explain it in plain words to a beginner; where the explanation breaks, your understanding has a gap.
The map is not the territory
Every model, metric or plan is a simplification, and the parts it leaves out can matter more than the parts it shows.
Thought experiments
Run an experiment in your head, following an idea to its consequences, when the real experiment is impossible, expensive or not yet needed.
Probability and statistics · 9
Base rates
How common something is to begin with matters as much as the evidence in front of you, and people routinely leave it out.
Bayes' rule
Update a belief by multiplying what you thought before by how much better the evidence fits one explanation than the other.
Correlation is not causation
Two things moving together is a fact about the data, not a verdict on what causes what, until the other explanations are ruled out.
Expected value
Weigh each outcome by its probability and add them up; that is what a repeated bet is worth on average, and only on average.
Fat tails
In some domains the rare extreme event is so large that it dominates everything else, and the bell curve cannot see it coming.
Regression to the mean
After an unusually high or low result, the next one tends to be closer to average, with no cause needed beyond chance.
Selection bias
If the way cases got into your sample is related to what you are measuring, the sample will mislead you however large it is.
Survivorship bias
When you only see the cases that passed a filter, the pattern in them is partly a pattern of the filter.
The law of large numbers
Averages of many independent trials settle towards the true value; averages of a few do not, and the law never 'corrects' a streak.
Economics and incentives · 9
Comparative advantage
Even if you are worse at everything, you gain by doing what you are relatively least bad at and trading for the rest.
Goodhart's law
When a measure becomes a target it stops being a good measure, because people optimise the number instead of the thing it stood for.
Incentives drive behaviour
People do more of what a system rewards and less of what it punishes, so to predict behaviour, look at what gets paid for.
Moral hazard
When someone else will bear the cost of your risks, you take more of them.
Network effects
A product becomes more valuable to each user as more people use it, which makes leaders grow faster and makes leaving hard.
Opportunity cost
The cost of any choice is the net value of the best alternative you gave up, whether or not money changed hands.
Supply and demand
Price settles where what sellers will offer meets what buyers will take; hold it anywhere else and a shortage or a glut does the adjusting instead.
The principal-agent problem
When you pay someone to act for you, their interests differ from yours and you cannot see all they do, so expect them to serve themselves at the margin.
Tragedy of the commons
When many people share a resource nobody owns, each gains the whole benefit of using more and bears only a share of the damage, so the resource is overused.
Systems and complexity · 7
Bottlenecks and the theory of constraints
A system's throughput is set by one constraint; improving anything else is wasted effort until that constraint is fixed.
Emergence
Simple local rules among many parts produce patterns at the level of the whole that no part contains or intends.
Feedback loops
A system's output feeds back into its input: balancing loops hold a level steady, reinforcing loops make change grow on itself.
Nonlinearity
Cause and effect are not proportional: a push can do nothing or everything depending on where the system sits relative to a threshold.
Redundancy and slack
Spare parts and spare capacity look like waste until the day they are the only thing between a fault and a failure.
Stocks and flows
A stock is what has accumulated; flows are the rates that change it. The stock moves only as fast as inflow minus outflow.
Unintended consequences
Purposeful actions produce outcomes nobody planned, because the people and systems acted on respond in ways the plan never modelled.
Psychology and biases · 9
Anchoring
Any number you see before estimating pulls your estimate towards it, even when you know the number is random.
Confirmation bias
People look for, notice and remember evidence that fits what they already believe, and rarely test what would prove them wrong.
Incentive-caused bias
An incentive bends your own judgement towards the conclusion that pays, and you will not feel it happening.
Loss aversion
A loss hurts more than an equal gain pleases, so people pay too much to avoid losses and take odd risks to escape them.
Social proof
When unsure what to do, people copy what others like them appear to be doing, and treat the copying as evidence.
The availability heuristic
We judge how likely something is by how easily examples come to mind, so vivid and recent things look more common than they are.
The fundamental attribution error
We explain other people's behaviour by who they are and underrate the situation they were in.
The planning fallacy
People predict their own projects will finish sooner and cost less than almost every comparable past project did.
The sunk cost fallacy
Money, time or effort already spent cannot be recovered, so it should not count in what you do next; people count it anyway.
Science and physics · 8
Critical mass and tipping points
Below a threshold a chain reaction fizzles; above it the same process feeds itself, and the change between the two is sudden.
Entropy
Left alone, an isolated system drifts into its most probable, least ordered state, so keeping anything ordered costs continual work.
Equilibrium
A state where opposing processes balance so nothing changes on net; push it and it pushes back, but balanced is not the same as good.
Evolution by natural selection
When traits vary, are inherited and change how many offspring survive, a population shifts towards the traits that reproduce best, with nobody steering.
Half-life
A quantity that loses a fixed fraction per period has a half-life, and after a few of them most of it is gone, whether it is carbon-14 or a fact.
Inertia
A body keeps doing what it is doing until a force acts on it, and so, by a looser analogy, do habits, defaults and organisations.
Leverage
A lever trades distance for force; financial and personal leverage do the same, and every kind multiplies losses as faithfully as gains.
Scale effects and the square-cube law
Double an object's length and its surface grows four times but its volume eight, so a thing scaled up in proportion is a different thing.
Math intuitions · 7
Averages hide the spread
A mean describes a group, not any member of it; without the spread you cannot tell whether anyone is near it.
Compounding
Returns earned on past returns: a steady rate applied to a growing base turns small repeated gains into large ones, mostly at the end.
Exponential versus linear growth
Linear growth adds the same amount each step; exponential growth multiplies by the same factor, and the two look alike only at the start.
Orders of magnitude
Estimate to the nearest power of ten from a few facts you know; being within a factor of three is often enough to decide.
Power laws and the 80/20 rule
In many distributions a few items hold most of the total, and doubling the size of an event divides its frequency by a fixed factor.
The birthday paradox
In a room of 23 people the odds that two share a birthday are just over even, because the number of pairs grows with the square of the group.
The rule of 72
Divide 72 by the annual growth rate in percent to get the number of years a quantity takes to double.
History · 5
Famous blunders and their causes
The great historical mistakes share a shape: the warning existed, an alternative existed, and the people in charge had reasons not to hear it.
Imperial overreach
A power that takes on more commitments than its economic base can carry pays for them with its future, and the bill arrives as decline.
Multiple discovery
The same discovery is often made independently by several people at about the same time, because the field was ready for it.
Path dependence
Early choices, including accidental ones, can lock a system onto a track that later choices cannot easily leave.
The adjacent possible
At any moment only the ideas one step from what already exists can be built; the rest wait until their parts arrive.
Software and engineering · 11
Amdahl's law
Speeding up one part of a job is capped by the share of time that part takes; whatever you leave untouched sets the ceiling.
Brooks's law
Adding people to a late software project makes it later: the new hands cost training and communication before they add output.
Conway's law
A system's design copies the communication structure of the organisation that built it, so the org chart is an architecture decision.
Gall's law
A complex system that works grew from a simple system that worked; one designed complex from the start rarely works and cannot be patched into working.
Hyrum's law
With enough users of an interface, every observable behaviour gets depended on by someone, whatever the contract promises.
Leaky abstractions
Every non-trivial abstraction leaks: sooner or later the thing it hides shows through, so you need to understand one layer down.
Little's law
In any stable system the average number of items inside equals the arrival rate times the average time each spends inside: L = λW.
Postel's law
Be conservative in what you send and liberal in what you accept: it got the early internet to interoperate, and it lets errors harden into the standard.
Premature optimisation
Do not tune code for speed before you have measured where the time goes; most of it is in a few places, and you will guess them wrong.
The CAP theorem
During a network partition each operation must give up either availability or consistency; the rest of the time the trade is latency against consistency.
YAGNI (you aren't gonna need it)
Build a capability when you actually need it, not when you foresee needing it; the forecast is usually wrong and carrying the code is not free.
Decision-making and strategy · 8
Asymmetric bets
Take bets where the most you can lose is small and known and the most you can win is large, even if you expect to lose most of them.
Margin of safety
Leave a wide gap between what you expect to need and what you build or pay, so that your errors and bad luck do not sink you.
One-way and two-way doors
Make reversible decisions quickly and save slow, careful deliberation for the ones you cannot undo.
Optionality
Prefer positions that give you the right, but not the duty, to act later, so you can take the upside when it appears and walk away when it does not.
Pre-mortem
Before you start, imagine the project has already failed and ask everyone to explain why.
Regret minimization
For a big personal choice, imagine yourself at 80 looking back, and pick the option you would be least likely to regret.
Satisficing versus maximizing
Decide in advance what good enough looks like, take the first option that clears it, and stop searching.
The opportunity cost of time
The real price of an hour is the best thing you could have done with it instead.
Learning and the mind · 7
Chunking
Working memory holds only a few items, so experts get around the limit by grouping details into larger units they recognise at a glance.
Deliberate practice
Expert skill is built by structured, effortful practice aimed at specific weaknesses with feedback, not by hours spent doing the activity.
Desirable difficulties
Conditions that make learning feel slower and harder often make it last longer; the ease you feel while studying is a poor guide to what you keep.
Retrieval practice
Pulling something out of memory strengthens it more than putting it in again, so a test is a better study tool than a reread.
Sleep and memory consolidation
The brain replays and reorganises the day's memories while you sleep, so a night of sleep improves recall and skill where a day awake does not.
Spaced repetition
Reviews spread out over time beat the same reviews crammed together, and the best gap grows with how long you need to remember.
The forgetting curve
Memory for new material drops fast in the first hours and then slowly; what is left after a day is most of what will be left after a month.
Wisdom and philosophy · 8
Chesterton's fence
Before you remove a rule, a process or a piece of code, find out why someone put it there.
Hanlon's razor
Never attribute to malice that which is adequately explained by stupidity, or more kindly, by error, haste or ignorance.
Occam's razor
When several explanations fit the evidence equally well, prefer the one that needs the fewest extra assumptions.
Steelmanning
Before you argue against a view, state it in its strongest form, well enough that the people who hold it would agree with your version.
Strong opinions, weakly held
Reach a definite conclusion early so you have something to test, then try hard to prove it wrong and let it go when the evidence turns.
The dichotomy of control
Sort everything into what is up to you and what is not, and spend your effort and worry only on the first.
The Lindy effect
For things that do not wear out, such as ideas, books and technologies, every year they survive raises how long they can be expected to last.
Via negativa
Improve things by removing what does harm before adding anything new, because we usually know more about what is wrong than about what is right.