We all think we’re rational.
Most of the time, most of the people are just apes with phones making pattern-matching errors at scale. If you aren’t sure, just look around.
Shane Parrish’s The Great Mental Models, is a antidote — a toolkit for thinking clearly and making fewer stupid decisions. Hopefully.
Btw, I wrote about it in the past as I ‘took’ ideas from the great Charlie Munger:
Below are nine models I keep coming back to, rephrased for the real world (and with fewer academic eyebrows raised).
1. The Map Is Not the Territory
Your model of the world is not the world.
It’s a cartoon version that leaves out 99% of reality.
That’s fine — as long as you don’t confuse the drawing for the thing itself.
In tech, we do this all the time. Dashboards, metrics, and AI reports — they’re maps, not the territory.
A subway map helps you navigate, but it won’t tell you about the weather, traffic, or that guy with the saxophone in the station.
Stay humble.
When your “map” doesn’t match reality, don’t double down — update the map.
2. Circle of Competence
Know what you actually understand versus what you think you understand.
If you’re a backend engineer giving strong opinions on human psychology, you’re probably outside your circle.
That’s fine — just admit it.
You can always expand your circle through learning, but pretending you already know everything is how you crash expensive experiments.
Buffett said it best:
“The size of your circle doesn’t matter — knowing its boundaries does.”
Or in startup terms: if you’re going to BS, at least label it as speculative fiction.
3. First Principles Thinking
Instead of reasoning by analogy (“This is like that”), strip the problem down to its basics.
Ask:
What do I know for sure? What are the fundamental truths here?
Elon Musk didn’t think, “How do other companies build rockets?”
He asked, “What’s actually required to get something into orbit?” That’s first-principles thinking.
It’s slower, harder, and occasionally painful — but it’s how breakthroughs happen.
Think of it as refactoring your brain’s codebase.
Less copy-paste, more understanding.
4. Thought Experiments
Run mental simulations before you spend money, time, or reputation.
Ask:
What if this goes terribly?
What if it goes too well?
What if my assumptions are wrong?
Thought experiments are like wind tunnels for ideas — you can test how they behave in extreme conditions without wrecking anything.
Scientists use them (see Schrödinger’s Cat), but product people, founders, and managers should use them too.
It’s free R&D for your brain.
5. Second-Order Thinking
First-order thinking asks: “What happens if I do this?”
Second-order thinking asks: “And then what?”
Example: you offer unlimited PTO.
Everyone cheers.
Six months later, nobody takes time off because they don’t know what’s “too much.”
Burnout follows.
You just reinvented guilt leave.
First-order thinking makes you look smart today.
Second-order thinking makes you stay smart tomorrow.
6. Probabilistic Thinking
Reality isn’t binary.
It’s shades of probability.
Stop thinking in yes/no. Start thinking in likelihoods.
“This feature has a 70% chance of working.”
“There’s a 30% chance our users ignore this.”
Combine that with expected value — what’s the payoff if it works versus the cost if it doesn’t?
Update your beliefs as new evidence appears (that’s Bayesian thinking).
If you never change your mind, you’re not thinking — you’re running stale code.
7. Inversion
Instead of asking “How can I succeed?”, ask “What would guarantee failure?” and then avoid doing that.
Want a healthy startup? Don’t ignore users, burn cash, and pivot every Tuesday.
Want a healthy life? Don’t sleep four hours, eat like a raccoon, and skip exercise.
Inversion is debugging for decisions.
Sometimes it’s easier to find the stupid than the smart — and just not be stupid.
8. Occam’s Razor
When you have competing explanations, the simplest one is usually right.
Your app probably isn’t crashing because of “quantum interference in AWS.” Someone just missed a semicolon.
Start with the simple hypothesis; add complexity only when evidence forces you to. Simplicity isn’t naive — it’s efficient. Complexity should be earned.
9. Hanlon’s Razor
“Never attribute to malice what can be explained by stupidity.”
When a teammate breaks production, they’re probably not out to get you — they just missed a detail. Most chaos is caused by carelessness, not evil.
This mindset saves energy and relationships. Assume ignorance first, verify later. But don’t be naive: some people really are snakes — just fewer than your paranoia thinks.
The Latticework Effect
Each model helps you see part of reality. Together, they form a latticework — a mental grid that catches your blind spots.
Use multiple lenses at once:
- The map isn’t the territory — question your data.
- Circle of competence — know your limits.
- First principles — strip it down.
- Second-order — trace the ripple effects.
- Probabilistic — think in odds.
- Inversion — debug your plan.
The world won’t get simpler.
But your decisions can get sharper, more robust, and slightly less foolish.
TL;DR
The goal isn’t to be perfect — it’s to be less wrong than yesterday.
That’s how wisdom compounds.
Or as a friend once said:
“Better thinking is the best growth hack.”
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