How I Think
I think in patterns and forces.
I grew up in a culture where effort explains everything: if something didn’t work, you didn’t want it enough. I respect the ethic. It isn’t true. Effort is a weak predictor of outcomes. The strong predictor is whether you are aligned with the underlying forces — or fighting them. The swimmer’s stroke matters less than the current. Most lives, most companies, most fortunes are explained by currents that no one inside them bothered to map.
Most thinking is reasoning by analogy — copying what already exists with the serial numbers filed off. Analogy is cheap and usually adequate, which is exactly why it’s worthless: anything it can see, everyone can see, and it is already priced in. Seeing clearly requires reasoning from first principles — stripping a problem down to what is physically and structurally undeniable, then building back up while ignoring what everyone else assumes. Physics keeps discovering counterintuitive things because it refuses to argue from consensus. I try to hold businesses and systems to the same standard.
The laws of nature work bottom-up. They decide how matter behaves, how bodies work, how brains work, how two people negotiate, how markets clear, how empires drift. Convention, consensus, received wisdom — these are recommendations, not rules. The only rules are the ones dictated by the structure of things. Everything else is negotiable, and most of it is wrong.
So the best returns — in capital, in ideas, in life — come from understanding systems, not predicting events. I map the forces that drive them. And I think in decades, because decades are where forces do their work. A force that moves something two percent a year is invisible in a quarter and undeniable in twenty years. Nearly everyone is paid to watch the quarter. The opportunity is the twenty years.
These are the forces I keep returning to — in markets, in businesses, in the systems I study. Each one is a lens. Together, they form a way of seeing.
Most people understand compounding arithmetically. Few understand it intuitively. The systems that matter — capital, knowledge, trust, code — all compound. The question is never “how big is this today” but “what is the rate, and what disrupts it?”
Almost everything returns to base rates. Margins revert. Growth rates revert. Sentiment reverts. The few things that escape this gravity — network effects, regulatory capture, genuine intellectual property — are where durable value lives. Identifying what actually escapes, versus what merely appears to, is the central problem of investing.
Stories move capital before fundamentals do. A compelling narrative creates its own momentum — capital flows in, talent follows, outcomes improve, and the narrative appears validated. The skill is distinguishing narratives that are pulling reality toward them from narratives that are merely running ahead of it.
Every organization, market, and system is constrained by the cost of getting people to act together. Businesses that structurally reduce coordination costs — through software, through standards, through design — win in ways that are difficult to reverse. This is the real moat: not what you own, but what you make effortless.
Incentive structures predict behavior more reliably than intentions, strategies, or stated values. When I study a company, I study what its people are paid to do. When I study a market, I study what its structure rewards. Show me the incentives, and I will show you the outcome.
Systems survive by adapting. But adaptation has a tempo — too slow and the environment moves past you, too fast and you lose coherence. The best businesses operate at the right tempo: fast enough to respond, slow enough to accumulate. Understanding this rhythm is understanding durability.
People are extraordinary at limbo. No matter where you set the bar, they will bend to get just under it. This is not laziness — it’s a deep feature of how humans allocate effort. We anchor to whatever target exists and unconsciously optimize toward it. Set a pessimistic scope and people will fill the time. Set an optimistic one and they’ll compress their work to meet it. The bar doesn’t measure performance. It shapes it.
This means that expectations are not neutral. They are causal. The four-minute mile was “impossible” until one person ran it, after which dozens did within months. The constraint wasn’t physical. It was the expectation itself, acting as a ceiling on what anyone attempted. Marathon finish times cluster at round numbers — 3:00, 3:30, 4:00 — not because those are natural breakpoints but because runners anchor to them and adapt their effort accordingly. The goal warps the distribution of outcomes toward itself.
In organizations, this effect is devastating when it goes wrong. Most teams estimate how long something will take, then plan around that estimate. But the estimate becomes the target, and the target becomes the floor. The high-urgency environment — the site is down, the company might die, the deadline is now — consistently produces the fastest work, because there is no scope to anchor to. There is only the problem and the imperative to solve it. Introducing a “realistic” timeline often makes things slower than having no timeline at all.
The implication is profound and underappreciated: optimism is not a personality trait. It is a strategic instrument. If you set ambitious expectations — genuinely ambitious, not performatively ambitious — people will organize their effort around meeting them. The gap between what a pessimistic scope produces and what an optimistic scope produces, compounded across thousands of tasks over years, is the difference between an ordinary organization and an extraordinary one. Ambition shapes reality. Optimism, applied consistently, warps the distribution of outcomes in your favor.
Seeing the forces is the first step. Acting on them is the second. This is the process I follow — a sequence that matters. Most mistakes come from doing the steps out of order.
- Question every assumption. Every thesis, every model, every “obvious” conclusion should come with a name attached — the person who made the claim and the data behind it. The most dangerous assumptions come from smart people, because nobody thinks to challenge them. Challenge them anyway. Then make the assumptions less wrong.
- Delete what doesn’t matter. Eliminate noise. Most data, most analysis, most commentary doesn’t change the decision. Strip it away. If you’re not willing to cut at least a tenth of what you thought was essential, you haven’t cut enough. You can always add it back. In practice, you rarely need to.
- Simplify before you optimize. Don’t refine a model for a business you shouldn’t own. Don’t polish an analysis that shouldn’t exist. Simplification comes after deletion — never before. The common mistake is optimizing a part of the process that should have been removed entirely.
- Accelerate what remains. Once you’ve identified what actually matters, increase the tempo. Speed of learning compounds. Every cycle of observation, hypothesis, and correction makes the next cycle faster. But only accelerate after you’ve questioned, deleted, and simplified — otherwise you’re just moving faster in the wrong direction.
- Systematize last. Build checklists, models, and repeatable processes only after the thinking is right. Systematizing bad thinking doesn’t make it efficient. It makes you wrong at scale.
- Seek disconfirming evidence. The most valuable input is the kind that tells you you’re wrong. Solicit it, especially from people you respect. This sounds like simple advice. Almost nobody does it.
- Be wrong, not confidently wrong. Conviction without humility is the most expensive trait in investing. It’s fine to be wrong — you will be, often. Just don’t be wrong and certain at the same time.
- Stay hands-on. You cannot evaluate what you cannot feel. Anyone making capital allocation decisions should understand the operations at a level deeper than the dashboard. Otherwise, you’re a cavalry leader who can’t ride a horse.
- Urgency is an operating principle. Not panic. Not recklessness. A bias toward action, toward learning, toward closing the gap between what you know and what you need to know. Time is the one resource you cannot allocate more of.
- The best investments come from understanding systems, not predicting events.
- Incentive structures are more predictive than financial statements.
- Most of what looks like genius is actually good positioning — riding the right wave at the right time.
- Intelligence is becoming abundant. Judgment is not. The premium is migrating to taste — knowing what is worth wanting.
- The next decade of value creation will be determined by who controls the best training data.
- Durability is rarer and more valuable than growth.
The defining force of my lifetime is that thinking itself is becoming cheap. Intelligence — the input that was scarce for the whole of human history, the constraint behind every other constraint — is being manufactured at falling cost. Every system I study is being rewritten by that one fact, mostly by people who haven’t noticed yet. This is not a market cycle. It is a substrate change, the kind that happens a handful of times in a civilization, and almost everything downstream of it is still mispriced.
Moments like this reward a specific posture: see the forces early, position quietly, and compound without interruption — capital, knowledge, trust, taste. The people who matter across a century are rarely the ones who predicted it loudest. They are the ones who built things the forces kept pushing forward long after everyone stopped paying attention. Influence is not announced. It accumulates.
That is the game I am playing. Not the quarter. Not the cycle. The arc.