Mental models for breaking down hard problems and finding solutions. First Principles decomposition, Inversion, bottleneck analysis, and other frameworks that t
Mental models for breaking down hard problems and finding solutions. First Principles decomposition, Inversion, bottleneck analysis, and other frameworks that turn overwhelming challenges into tractable steps.
Browse all mental models for this use case below. Each model includes a practical explanation, a historical case study, real-world examples, and an interactive exercise.
Instead of asking how to succeed, ask what would guarantee failure — then avoid it.
Break any problem down to its fundamental truths, then build your reasoning up from there.
The simplest explanation that fits the evidence is usually the correct one.
Test ideas by running them in your imagination rather than in the real world — cheaper, faster, and sometimes just as revealing.
In any system, there are specific places where a small change produces disproportionately large effects.
Don't evaluate the total — evaluate the next unit. The value of one more hour, one more dollar, one more feature is what matters.
Roughly 80% of effects come from 20% of causes. Find the vital few and ignore the trivial many.
Improve by removing what's harmful rather than adding what might help. Subtraction often beats addition.
Instead of asking how to improve by 10%, ask how to improve by 10x. The radical question forces you to abandon incremental approaches and find breakthrough solutions.
Hide complexity behind simple interfaces. You don't need to understand how an engine works to drive a car.
Some complexity is inherent to the problem. Some is created by the solution. Learning to tell the difference is a superpower.
Every system has one constraint that limits overall throughput. Improving anything else is waste until you fix the bottleneck.
Offload information from your biological memory to an external system so your brain can focus on thinking, not remembering.
We tend to prefer complex explanations and solutions over simple ones, even when the simple version works better.
Each additional unit of input produces less additional output. The first hour of practice helps more than the hundredth.
People often fail to transfer knowledge from one domain to another, even when the underlying principle is identical.
If you can't explain something simply, you don't understand it well enough. Teaching is the ultimate test of understanding.
The best model isn't the most complex or the most elegant — it's the one that best fits your specific situation.
Small inputs that produce disproportionately large outputs. Time, capital, code, media, and labour can all be leveraged.
Find the smallest input that produces the desired result. More is not always better — sometimes it's waste.
Don't perfect what you haven't validated. Optimising the wrong thing wastes more effort than doing nothing.
Sometimes the best move isn't adding something new — it's removing something that's holding you back.
Any component whose failure causes the entire system to fail. The question isn't whether it will fail — it's whether you've prepared for when it does.
Searching for answers where it's easy to look, rather than where the answers actually are.
Goals are about the end state you want to reach. Systems are about the process you follow every day. Systems-oriented people tend to outperform goal-oriented people.
Quick shortcuts today create compounding costs tomorrow. Like financial debt, technical debt accrues interest — and eventually the interest payments exceed the original savings.
Form a hypothesis, design a test, observe results, update your beliefs. The most reliable process for separating truth from opinion.
Improvement by subtraction (removing what's harmful) is often more reliable than improvement by addition (adding what's beneficial).
Some problems have no definitive formulation, no stopping rule, and no test for a solution. Recognising them changes how you approach them.