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Most people use AI for investing the same way they have used Google all these years.

They type a question. They get an answer. They move on.

And, well… that is not exactly how you should use it.

With AI, you are able to build your very own research partner, which is much more powerful and valuable than a search engine.

My own research partner, for example, holds sixty years of Buffett’s shareholder letters in its working memory. It has read every letter Nick Sleep ever wrote from the Nomad Investment Partnership. It knows my analytical framework in full: the specific tests I run, the order I run them in, and the exact reasons I reject most companies at the first gate.

Here is how I built it, and how you can build something similar.

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Why most people get this wrong

The generic prompt produces a generic answer.

“Is Medistim a good investment?” tells the model nothing about what framework you use, what return you need, what risks you care about, or what you already own. The answer you get back is the answer you would get from a financial blog written for nobody in particular.

The problem is not the AI itself.

No, the problem is the absence of context.

A model with no instructions will tend to find positives. It is trained to be helpful. But ‘helpful’, without further instruction, usually means agreeable.

That is an awful output for us investors, because we need the opposite.

You need a thinking partner who tries hard to find the reason to say no, who surfaces the argument against the company you are excited about, and who does not move on until the weakest link has been named.

The difference between a generic AI prompt and a properly built research setup is not small. It is the difference between a calculator and a co-pilot.

The context is everything. And the context has to be built.

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The foundation: what goes into the knowledge base

Before I run a single company through the system, three things are loaded into the model’s working memory.

1. My primary sources.

• All of Buffett’s shareholder letters from 1977 to 2019, organised into five clean decade-based files.

• All of Nick Sleep’s Nomad Investment Partnership letters.

• Summaries and transcripts of Berkshire annual meetings spanning 1999 to 2012.

Here is the first practical tip, and it is worth taking seriously: do not use PDFs.

A PDF of sixty years of Buffett letters is too large to upload in one piece, and the text extraction is worse than you think. The model reads compressed, imperfectly parsed text and produces imperfectly reasoned analysis.

The solution is simple. Convert to markdown (MD files).

In the case of the Berkshire letters, split by decade. Five files of eighty pages each upload cleanly, parse cleanly, and the model reasons from them cleanly.

It takes little time, and it is worth it.

By doing this, the model uses your specific, curated selection of primary material, organised the way you organised it. When the model cites Buffett on owner earnings or Sleep on the destination, it cites the letter, the year, and the argument. Not a paraphrase of a paraphrase.

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2. The framework document.

This is the most important file in the setup, and the one most people would never think to build.

This is an instruction set that never changes. It is what turns a general-purpose AI into something that thinks the way I think, applies the tests I care about, and produces output in a consistent format every single time.

If you take one idea from this article, take this one: write your investment framework down before you do anything else with AI. If you do not have a written framework, the model has nothing to apply. The framework is the foundation. Without it, you are just asking questions into the dark.

3. The research library.

Every completed analysis is exported as a clean markdown file and uploaded to NotebookLM. NotebookLM becomes the searchable archive: every company ever analysed, every trigger price ever set, every moat verdict ever written. When a stock approaches a price I set a year ago, I open NotebookLM, find the file in seconds, and read the original work.

This is the compound interest of a research operation. Each analysis makes the library more valuable than the one before it.

I then like to transfer these files to my reMarkable tablet and read the analysis in peace with a strong coffee (or a glass of wine) to get a deeper understanding.

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The actual workflow

Here is what happens when a new company comes across my desk.

Step one: the screener.

I export a list of companies screened from a financial data service (I use Börsdata, as I am Scandinavian and mostly look for, and feel comfortable owning Nordic companies).

The screener consists of financial metrics that I like to look for, such as a high ROIC, 5 year avg revenue growth, cash flow and more.

Sometimes the screener find twenty names, sometimes three hundred.

Then I export the results and upload it to Claude and ask for a triage: apply the three gates, reject everything that fails, tell me which eight to twelve names deserve a closer look, and why.

The model works through all of them. It rejects most immediately, with a one-line reason for each. It promotes the survivors with a paragraph explaining what earned them a second look.

What would take me a day of manual work takes the model twenty minutes.

Step two: the financial data.

Once Claude has filtered the screener and highlighted the companies that match my framework, I pull the trigger on the deep dive. I return to Börsdata and download the full financial history for each business. It’s a fantastic Nordic service that exports clean Excel files going back 15 to 20 years (you can use Finchat, Koyfin, or similar services for international stocks).

The model reads the raw data, identifies the correct metric columns, and runs Python to compute the numbers that matter: five-year average return on capital, incremental return on capital, owner earnings net of stock-based compensation, free-cash-flow conversion, gross margin trend over a decade.

Owner earnings is the number that counts. Net income plus depreciation, minus maintenance capital expenditure, minus stock-based compensation always, minus any significant working capital change. Not EBITDA. Never EBITDA. The model knows this because the framework document says so, in plain terms, with the reason behind it.

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Step three: the eight-movement analysis.

This is the core. The model runs the full framework.

The grizzly test: could a well-funded, intelligent rival take meaningful market share within five years? If yes, there is no moat.

The Patterson sentence: one sentence naming a specific structural barrier, not “customers like us,” explaining why a well-resourced competitor would find it prohibitively difficult to take share.

The eighteen financial checks, each with a pass or fail and a one-line reason. A single accounting artifact counted once, not as three separate failures.

Three-scenario DCF discounted at 12 percent. A destination cross-check: what does this business look like in fifteen to twenty years, and what are those mature earnings worth discounted back today?

An eight-dimension quality score. An inversion: two or three specific ways this becomes a permanent loss, each told as a short story, each with a named response I have decided on in advance.

The weakest link is named explicitly.

I also feed it additional screenshots and information from other services like Simplywall.st. This service has a great insider transaction and ownership overview for example, which also is factors I look for in my analysis.

Step four: the output.

A clean, self-contained markdown file. Plain language throughout. The verdict at the top. All the numbers in an appendix. A fat-pitch trigger price: the specific price at which the margin of safety is finally wide enough that I would act without hesitation.

The file goes into NotebookLM. The trigger price goes into the watchlist at my broker.

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What the AI does, and what it does not

The model applies the framework consistently. It does not get excited. It does not get tired. It does not skip a check because the business looks obviously good and the next one looks more interesting. Consistency is underrated in investment research, and it is the thing AI does best.

It runs the numbers without arithmetic errors. It structures the output the same way every time. And it plays devil’s advocate: instructed to try hard to reject the company, it finds the argument against. You may still buy the company. But you will have heard the case against it, in full, before you do.

What it does not do: decide whether the moat is real. It surfaces the evidence. The conviction is yours.

It cannot assess management with any texture. It cannot hear the difference between a CEO who is slightly evasive and one who is outright dishonest. It reads transcripts and letters. It does not read rooms.

And it cannot sit through a 40 percent drawdown without flinching, because it does not hold positions. That is temperament, and temperament is irreducibly human.

The AI does the legwork. You do the judgment. Neither works without the other.

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How to start, step by step

Write your framework down first. Even two pages. What do you require of a business before you will look at the price? What do you always check? What would make you walk away?

Then convert your primary source documents to markdown. Paste or export to a text editor, clean the headers, and save as .md. Split anything over a hundred pages into smaller files. Upload them to the AI project you are building.

Then write the instruction document. What should the model always do? What should it never do? What order should the analysis follow? What should the output look like? This file is the difference between a generic assistant and a thinking partner.

Then start the library. Every analysis you complete becomes a file. After thirty analyses, the library is the most valuable thing in the setup.

The process compounds. That is the whole point.

Get the ebook below:

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Most investors never look here.

These companies are small. They trade in kronor and krone, and the research desks that move institutional money cannot build a meaningful position without moving the price against themselves.

But they are of high quality. And an excellent place for investors like you and me to look.

Why Nordic?

A few years ago, a fund called Alta Fox went looking for what actually drove extraordinary long-run returns. They studied over a hundred companies that returned more than 350 percent over five years. The winners clustered in Sweden, the UK, Germany, Norway, and Australia. They were mostly under two billion in market value. They had far less analyst coverage than names of comparable quality on the major US exchanges. And multiple expansion, the market finally repricing a mis-categorised business upward, contributed roughly two-thirds of the median return.

That is not a coincidence.

The Nordics sit at the centre of it.

• Sweden in particular has produced a remarkable density of quality serial acquirers: companies that buy niche industrial or software businesses, decentralise them, and compound the whole at high returns on capital for decades.

• Norway has produced niche medical-device monopolies and insurance compounders.

• Finland has produced diagnostic technology that is sold into operating theatres around the world.

These companies are often the dominant player in a niche nobody has heard of. They are poorly covered. They occasionally get mispriced in ways that a patient, attentive investor can use.

That is the pond I fish in.

What earns a place

The list starts with a hundred names from a screener and ends at thirteen. Most candidates fail immediately.

A name only makes the Nordic Watchlist when it clears every one of these:

A moat I can name in one sentence. A product surgeons would be slightly mad to rip out mid-operation. A certification that took a decade to earn and cannot be replicated in a hurry. A serial acquirer whose process compounds faster than any single business it owns. A market where the number-one position is structural rather than accidental.

A business that generates real cash. Owner earnings, the money a private buyer could actually keep after maintaining the competitive position, not headline profit. Companies that earn large accounting profits while consuming cash are excluded on the first pass.

High returns on capital held for years, not one strong year followed by mean reversion. The test is whether the business earns well on each new krona it reinvests, not just on the base it already had.

A destination. Where does this business land in fifteen to twenty years if management does nothing spectacular? If the answer is somewhere large and reasonably secure, it earns further scrutiny. If the answer is unclear, the analysis stops.

A strong balance sheet. Net cash, or leverage so modest that a bad year changes nothing.

For each name on this list, I work out what a private buyer would pay for the whole business based on the cash it produces, with a discount rate of 12 % and a margin of safety wide enough that a bear case barely loses money. That is the number I'm waiting for.

The part most people skip

Every name on the Nordic Watchlist has a Fat Pitch Price.

It is the specific price at which I would buy without hesitation, because the margin of safety is finally wide enough that I am being paid to be wrong. I do not approximate it. I calculate it on owner earnings, run three scenarios, and state a number.

Most of the time, the price never comes. Wonderful businesses rarely become cheap. The list exists so that when they do become cheap, because of a cyclical stumble, a bad quarter, a sector de-rating, or nothing more than a quiet market with no buyers that week, I already know what I think the business is worth and what I am willing to pay. The decision is made in calm, not in the middle of a drawdown.

Several names on this list are closer to their Fat Pitch Price than they have been in a long time. A few sit within a modest pullback of the trigger. Nordic small and mid-caps have had a difficult 18 months as rising rates and a cautious macro backdrop pushed institutional money toward larger, more liquid names. Some of the best businesses in the region are quietly on sale.

Get the full Nordic Watchlist

Below: all thirteen companies, the moat in one sentence for each, the single thing that would break the thesis, and the Fat Pitch Price with the margin of safety behind it.

This is my own research for my own book, not financial advice. Treat every name as the start of your own work, not the end of it.

Check out the watchlists here:

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I have a confession to make before we get started. I am a quality-compounder guy. I want businesses that earn high returns on capital and reinvest them for a decade. Michael Burry is almost the photo negative of that.

He buys ugly things. He shorts beautiful ones. He has spent most of his public life betting against the very mania that made everyone else feel like a genius.

And I admire him anyway.

I have no desire to trade like him. I never could. What I admire is the temperament. The patience. The willingness to sit alone in a position, be hated for it, and keep sitting there because the math says you are right.

That is rare. Most of us cannot do it for a single week. Burry has done it for years at a stretch, with real money, while the crowd laughed at him.

So let me walk you through how he became a legend. Then let me show you what is worth stealing from him, even if you never short a single stock in your life.

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The kid who could not stop reading

Burry was born in 1971 in San Jose. At the age of two, he lost his left eye to a rare cancer called retinoblastoma, and he has worn a prosthetic eye ever since. He has said this shaped him into an observer. A loner. Years later, he recognized that he has Asperger’s after his own son was diagnosed first.

He once described himself with no varnish at all.

“My nature is not to have friends. I’m happy in my own head.”

Most people would probably never say it out loud. Burry says it the way you would report the weather.

He studied economics and pre-med at UCLA, then earned his MD at Vanderbilt. He started a residency at Stanford and never finished it. The reason is the whole man in miniature. He kept staying up at night doing something that had nothing to do with medicine. He was picking stocks.

He once worked so hard on both at the same time that he fell asleep standing up during a surgery.

In 1996, he started posting his investment ideas on a message board called Silicon Investor. The writing was good. Really good. He built a site called valuestocks.net that won a Best of the Web award from Forbes for stock picking, and won it twice. Vanguard noticed him. Joel Greenblatt noticed him. People with serious money started asking this anonymous surgeon-in-training to manage theirs.

That is the part I love. He did not network his way in, and he had no pedigree desk job at Goldman. He wrote clearly about businesses, year after year, and the work spoke for itself. The internet found him.

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Scion, and a fantasy novel

In 2000, he quit medicine and started a hedge fund. He funded it with a small inheritance and loans from his family. His mother put in $20,000. Each of his three brothers put in ten.

He named the fund Scion Capital.

Michael is quite the fan of The Shannara Chronicles, and the name Scion specifically hails from The Scions of Shannara, a 1990 fantasy novel by Terry Brooks.

This is one of Burry’s favorite books. He was nineteen when it was published (The TV show arrived much later, in 2016, and draws from a different Shannara story entirely - although I personally think it was a shame that it got cancelled).

I cannot tell you that Burry sat down and mapped that fable onto his career. I doubt he would claim it. But I read something into the choice anyway, and I think it is fair to. Here was a man who saw himself as an heir to a tradition.

The tradition of Graham and Dodd. Real value investing.

He took up a quest most people thought was foolish, inside a market that had effectively banned his kind of thinking and blamed it for missing the party. He named his life’s work after that idea.

That is what a name is for. It tells you who a person believes they are.

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The years that made him

His investing style was old-fashioned and strict. He built the whole thing on one book, Graham and Dodd’s Security Analysis from 1934, and he has said his stock picking is “100% based on the concept of a margin of safety.” He read 10-Ks the way other people read novels. Alone, for hours, in a dark office, hunting for the number that tells you what is actually there underneath the story.

And it worked, fast.

In 2001, the S&P 500 fell almost 12%. Scion was up 55. In 2002, the market fell again, down 22%, and Scion was up 16%. In 2003, the market finally turned and rose nearly 29%, and Burry still beat it, up 50%.

By the end of 2004, he was managing 600 million dollars and turning new money away. A lot of those early gains came from shorting overpriced tech stocks while the dot-com bubble was deflating. He was already running his whole playbook. Buy hated value. Short the fantasy. Wait.

Then came the trade that put his name in a movie.

The Big Short, and the revolt

In 2005, he started pulling apart the subprime mortgage market. He read the actual loan documents stuffed inside the mortgage bonds. He saw loans handed to people with no income and no down payment, then packaged and rated as if they were safe. He concluded the whole structure would come apart once the teaser rates reset. So he did something almost nobody had done. He went to Goldman Sachs and others and asked them to create credit default swaps so he could bet against specific subprime deals.

His own investors tried to fire him.

They did not understand the bet. Housing kept rising. Burry was paying premiums every month on a short that was not working yet, and his clients were furious about it. Some demanded their money back. He had to gate the fund to stop them from yanking it out. Picture that for a second. You have done the work. You are right. And the people whose money you are protecting are screaming at you for protecting it.

He held.

By the middle of 2007, subprime began to collapse, exactly as he had said it would. Scion made 725 million dollars for its investors. Burry personally cleared around 100 million. From its start in late 2000 to the middle of 2008, the fund returned 489 percent net of fees. The S&P 500 returned roughly 3 percent over the same stretch.

Then he closed it. The backlash, the IRS audits, the sheer exhaustion of being right while everyone fought him. He was done managing other people’s money. For a while.

This is the part Keynes warned us about, and Burry actually lived. The market can stay irrational longer than you can stay solvent. Being early and being wrong look identical for a long time, and they only separate at the very end. Most investors never reach that end, because they get shaken out, or talked out, or simply bored out of the position first. His real edge had nothing to do with a secret formula. He could just sit in the discomfort longer than you can.

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Cassandra in the wilderness

He reopened a fund in 2013 as Scion Asset Management. And then he spent the next decade building a second reputation, as the boy who cried crash.

I am going to be straight with you here, because this newsletter does not do hero worship.

A lot of Burry’s big public calls since 2008 have been wrong, or at the very least painfully early. In 2017, he warned of a global financial meltdown. The market rose. In 2019, he said index funds were the next CDOs, a bubble waiting to burst. They kept inflating and never burst the way he meant.

In June 2021, he warned of “the mother of all crashes.” Stocks rallied more than 50 percent from there. On January 31, 2023, he tweeted a single word. “Sell.” The market promptly ripped higher. Two months later, he tweeted, “I was wrong to say sell,” and went on to congratulate the buy-the-dip crowd for their nerve.

One writer tried to actually score his record and figured roughly 71 percent of his major bearish calls since the crisis were wrong on timing or size. The Financial Times described his performance since The Big Short as “distinctly ho-hum.” When he shorted Nvidia and Palantir in late 2025, Palantir’s CEO Alex Karp went on television and called the bet “bat-shit crazy.”

So yes. He gets mocked. Constantly. And harshly, if you ask me. Often by impatient people who treat every tweet as a date-stamped prophecy and then high-five each other when the market climbs the following week.

But look at what the mockers keep missing.

First, Burry picked his own nickname years ago. Cassandra. The priestess in the Greek myth who was cursed to see the future clearly and to never, ever be believed. He chose that name on purpose. It tells you, right on the label, that being disbelieved is the whole job.

The only thing he writes now, the project that has become his entire focus, is his Substack publication: .

Second, the scoreboard depends on what you actually measure. His macro timing calls have a poor hit rate. True.

Third, he said it better than I can when the Wall Street Journal labeled his early calls a failure. Being early and being wrong look identical in the short term and diverge completely over time. One reflects bad analysis. The other reflects the market refusing, for a stretch, to price reality.

I am not telling you Burry is always right. I am telling you the crowd’s way of grading him is lazy, and the man understood that before any of them did, and put it in the name on the door.

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What he just told us

Which brings me to the thing that made me want to write this piece in the first place.

A few days ago, Burry published this note on Substack:

He laid out a simple story. A stock falls from 100 down to 10. That is a 90 percent wipeout. Ouch…

A value investor steps in at 10, because the business is honestly worth around 30.

Then the thing keeps sinking, all the way to 5, because a stock that has fallen that hard stops tracking the business underneath it.

Our investor is now down 50 percent on his buy. He could have bailed at 8 and capped the damage. He sits tight instead.

So, he goes off to medical school, finishes his residency, becomes a surgeon, and a decade later, the stock trades at 30. From the bottom, that is a six-fold return. Roughly 20 percent a year. He says this maps almost perfectly onto Warner Bros. Discovery, and he points out that it usually does not even take the full ten years.

Then comes the line I keep rereading.

If you are sitting on a deep loss, you own that position at today’s price, full stop. Whatever it is worth from here is the only return you will ever earn on it. Dumping it just to make the bad feeling go away, to erase the memory and chase the next shiny idea, is usually the wrong long-term move.

Sit with that one. It dismantles one of the most common mistakes any of us make.

We feel the loss in our chest. We sell to make the feeling stop, right at the point of maximum pain, which is often right before the recovery. The market has no idea what you paid and would not care if it did. Your cost basis lives in your head. The company does not know it exists. The only question that matters is what the thing is worth from here.

I have a private name for my own version of this disease. The hot potato. The urge to sell a good business too early, to lock in some relief, to avoid sitting inside a drawdown. Reading Burry describe the same impulse in a stranger’s voice was uncomfortable in the way good advice usually is.

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What to actually steal from him

So here is what I take from Michael Burry, as someone who will never run his strategy:

1. Do the work yourself, in primary documents, until you know the business better than the people talking about it on TV. Burry beat everyone because he read the actual loan files and the actual filings while his competitors read the summaries.

2. Anchor to something real. A margin of safety is a hard number. It is the gap between price and what is genuinely there. Find that number underneath the narrative and build from it.

3. Treat your portfolio as one book, not a pile of tickers. When the headlines screamed that Burry had a “$900 million” short against Palantir, the real premium he had at risk was closer to 9 million. Copying his ticker without understanding the size, the structure, and the duration would have flattened you. The headline is never the trade.

4. Be willing to be hated. The best setups are uncomfortable by design. If everyone already agrees with you, the upside has already been handed out. The money tends to hide wherever the discomfort is.

5. Separate being early from being wrong, then be honest with yourself about which one you are. Burry has been both. The thing I respect is that when he is wrong, he says so out loud, in public, with his name attached. “I was wrong to say sell.” Most gurus would have deleted the tweet and pretended it never existed.

6. And the big one. Once you are down, you own it from here. Stop grieving your cost basis. Ask only what the business is worth now, and let that answer, rather than your feelings, decide whether you hold.

That is the real Burry. Forget the doom tweet and forget the movie. The actual man is stubborn, solitary, and a lot would consider him a little different from the rest.

He reads everything. He trusts his own math over the mood of the crowd. He sizes his bets with care.

And he is perfectly comfortable being the only person in the room who thinks he is right.

Until next time,

— Rob H.

I keep this The Money Mind series free for everyone. The only thing I ask in return is that you share this post with one friend who would find it valuable.

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What this guide covers

Scale economies shared is the most powerful business model in long-term investing. The idea is simple. A company earns a cost advantage as it grows. Instead of keeping that advantage as fat margin, it deliberately hands most of it back to the customer as lower prices, better service, or wider selection. The customer notices, and rewards the company with more business. That extra volume creates more scale, which creates a bigger cost advantage, which gets handed back again. The loop turns on itself, and it gets harder to attack every year it runs.

Most moats defend a position. This one widens it. That is the whole reason it sits at the top of the durability ranking.

(At the bottom are links to three full deep dives on live examples of the model: Nu Holdings, MercadoLibre, and Toast.)

One note on the name before we start. Sleep used both “scale economics shared” and “scale economies shared” in his letters. They mean the same thing, and this guide treats them as interchangeable.

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Where did the idea come from?

The phrase belongs to Nick Sleep, but the lineage runs deeper than one man.

Sleep (born in the UK in 1968) studied geography, not finance. He worked as a landscape architect, in department stores, at an IT firm, and as a sponsored windsurfer before joining Sun Life of Canada as an analyst and then moving to Marathon Asset Management in London in 1995.

His partner, Qais “Zak” Zakaria (born in Iraq in 1969), came from Deutsche Bank, where he covered Asian equities. The two met in their late twenties.

Marathon is the part of the story people forget. It was a London shop built around the capital cycle, the discipline of watching where capital floods in (and returns collapse) and where capital starves (and returns recover). Sleep’s mentor there was Jeremy Hosking, one of Marathon’s co-founders. The intellectual habit Sleep absorbed was to study the structural mechanics of an industry rather than guess next quarter’s earnings.

In September 2001, Sleep and Zakaria launched the Nomad Investment Partnership under the Marathon umbrella. It began investing on the 10th, one day before the 11th. They spun it out as an independent partnership in 2006 and closed it voluntarily in 2014 to focus on philanthropy.

The numbers are the reason anyone studies them. Over roughly thirteen years, Nomad compounded at about 20.8 percent a year before fees, against about 6.5 percent for the MSCI World Index over the same stretch. One dollar became roughly ten. They did it with almost no turnover, a handful of names, no leverage, and letters typed in Courier font that they mailed to partners a couple of times a year. By the end the portfolio was concentrated in a short list led by Costco, Amazon, and Berkshire Hathaway.

The seed of the whole framework was a single observation in Warren Buffett’s 2004 Berkshire letter about GEICO. Buffett pointed out that GEICO delivered real money to three groups at once. Customers saved roughly a billion dollars compared to what they would have paid elsewhere. Employees earned a large profit-sharing bonus. Owners earned an excellent return. Those benefits existed only because of scale. Sleep read that and asked a sharper question. If scale produces a pool of benefits, who gets it, and what does the split tell you about how hard the business is to attack?

That question became the robustness ratio, and the company that answered it most beautifully was Costco. Nomad made Costco its largest holding and never stopped writing about it.

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The mechanics of the flywheel

Here is the loop in plain terms, using a low-price retailer like Costco as the model.

The business buys in enormous volume, so it buys cheaply. It runs a lean operation, so its costs per dollar of sales are low.

Now it has a choice:

It can pocket the savings as a higher margin, or it can drop its prices.

Costco drops its prices. The customer gets goods cheaper than anywhere else, so the customer comes back and buys more. More sales means more volume, which means even better buying power and even lower costs per unit, which Costco hands back again as still lower prices. Round and round.

Sleep contrasted this with the ordinary “high-low” supermarket, and the contrast is the whole point. The high-low retailer runs an inefficient operation, charges high everyday prices to cover it, then slashes a few items on promotion to pull people through the door, hoping they buy full-price goods while inside. That trains the customer to wait for deals, shop around, and stay disloyal. It also forces the retailer to constantly reprice, and it makes volumes lumpy and unpredictable. The incentives in that system reward exactly the behaviour that hurts the business.

The scale economies shared system rewards the opposite. The customer is trained to trust the price every day and to consolidate spending with the one player who is always the cheapest. Sleep called customer reciprocation a super-factor in business performance, and he meant it literally. It is the engine that makes the loop spin.

Three things follow from this, and each one matters for an investor.

It works far beyond retail.

Sleep pointed to AirAsia, the low-cost Malaysian carrier, whose planes flew fuller than the high-fare flag carriers because low fares filled seats. He pointed to Amazon, whose total cost per dollar of sales (operating costs plus operating margin) was lower than some high-street rivals’ costs alone. That is a brutal fact. It means those rivals could price at break-even and still not undercut Amazon. The model is industry-agnostic. It shows up anywhere a cost advantage can be returned to customers in a way they will reward.

It lowers the probability of failure every year.

This is the single most important property, and it is what separates this moat from all the others. A patent defends a position until it expires. A brand defends a position until taste shifts. A scale economy shared business does not sit and defend. Every year it operates, it grows, the cost gap widens, prices fall further, the customer proposition improves, and the business becomes harder to dislodge than it was the year before. Sleep borrowed Peter Bernstein’s image of a cone of uncertainty that widens the further out you look. Costco’s obsession with sharing savings narrows that cone. The future becomes more predictable, not less, which is precisely backwards from how most businesses age.

Forget about the quarters. The destination is the question.

Because the model compounds its own advantage, the right question is never “what does this earn in year three.” It is “what does this look like as a mature franchise in fifteen to twenty years, and is that destination secured by the loop itself.” If the loop is genuine and the management is committed to it, the annual numbers are noise on the way to a destination you can describe.

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Why it beats every other moat

It helps to place the model against the alternatives. A durable business needs a moat. It does not need the most durable type. But when you are hunting for the rare position you can size large and hold for decades, the type matters, and scale economies shared has properties the others lack.

A statutory or regulatory monopoly is close to permanent, but it is static. It defends a fixed position and rarely grows the pond. A switching-cost moat deepens with use, which is excellent, but it locks in customers you already have rather than continuously attracting new ones on improving terms. A network effect is powerful when the leading position is structural, but network density can plateau. A brand commands pricing power, but it leans on advertising, and pricing power is the opposite instinct to sharing scale. Patents alone are weak, since they expire and get designed around.

For an investor with a long horizon, this links straight to compounding. The reason predictability matters is not comfort. It is that a predictable compounder is the only kind you can size to a large weight and then sit through three fifty percent drawdowns to own for twenty-five years. A lottery-ticket business with a huge but uncertain payoff cannot be sized and cannot be held, so you almost never collect it. The scale economies shared business, with its narrowing cone of uncertainty, is exactly the kind you can hold like that. The multiple then falls out of how long the durability lasts. Compound at 20 percent and you have a six-bagger in ten years, a fifteen-bagger in fifteen, and a ninety-five-bagger in twenty-five. The rate is the thing. The multiple is an output.

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The robustness ratio: how to measure the moat

This is the part most writing on the subject gets wrong, so it is worth doing carefully.

Sleep wanted a way to put a number on moat strength for businesses that compete on price. The robustness ratio was his answer. It measures how the pool of benefit created by scale is split.

The definition. In its full form, the robustness ratio is the combined distribution to customers and employees (through lower prices, better service, profit sharing, and the like) divided by the distribution to shareholders. In its simpler and more usable form, it is the amount of money customers save divided by the amount shareholders earn. It is, in one line, dollars saved by customers for every dollar kept by owners.

The two anchor cases. Sleep worked out two, and they are the reference points for everything else.

• GEICO sits at roughly 1:1. Customers saved about a billion dollars on their policies compared to the next cheapest carrier, and shareholders earned roughly a billion in underwriting profit. One dollar out to customers for one dollar kept.

• Costco sits at roughly 5:1. Sleep estimated that a Costco member saves about five dollars compared to shopping the same basket at an ordinary supermarket, for every one dollar Costco keeps. The arithmetic ran through Costco’s gross margin of about 11 percent against roughly 23 to 26 percent at a Walmart or a Kroger, adjusted for the membership fee.

So what does the number tell you?

Broadly, the higher the ratio, the harder the business is to attack on a like-for-like basis. A rival trying to take share from Costco has to find five dollars of customer value that Costco is already giving away before it even reaches Costco’s own thin profit. That is a very deep moat to cross.

Where the ratio applies, and where it does not. This is the boundary Sleep drew explicitly, and it is the most common misuse. The robustness ratio is appropriate only when the customer proposition is built on price. Costco, GEICO, a discount retailer, a low-fee financial product. It is not appropriate for a proposition built on advertising or aspiration. Sleep used the example of Nike trainers. Nobody buys Nike to save money, so measuring a price-based give-back tells you nothing about that moat. If the value a business delivers is mostly status, brand, or experience rather than price, the robustness ratio is the wrong instrument, and you should reach for a different moat test.

The interpretation is not “higher is always better.” There is a real tension built into the number. A higher ratio means a wider moat. It can also mean a less equitable split, where the business is handing customers so much that shareholders take very little. Costco’s 5:1 and GEICO’s 1:1 may be equally effective barriers against competition. A ratio even finer than GEICO’s may be perfectly sufficient to repel competitors in some industries. The ratio tells you how hard the business is to attack. It does not, on its own, tell you it is the better investment.

The caveats Sleep attached, which almost everyone drops. He was emphatic that the ratio is a thinking tool. It is plainly not a numerical magic bullet for measuring moats. Four specific warnings travel with it:

• A finer ratio can still be a powerful barrier. The number is not a leaderboard where 5:1 beats 2:1.

• A falling ratio is not necessarily a shrinking moat. It can simply mean the moat is no longer being widened as fast as it could be, while remaining perfectly strong.

• The ratio is most useful for spotting companies that are under-earning relative to their potential. This is its real power, and we will come back to it.

• The split should change for competitive reasons only, never to please the stock market.

Where the ratio earns its keep: spotting the under-earner. Here is the insight that turned the robustness ratio into a money-making tool rather than an academic curiosity. A business with a high ratio is deliberately leaving profit on the table. It is choosing to under-earn today in order to widen the moat and secure a larger, more certain destination tomorrow.

The stock market, which reads reported earnings, sees thin margins and a cheap-looking business, and misprices it. The patient investor who understands the model sees a franchise getting stronger every year while the income statement understates the truth. This is exactly why Costco’s share price went nowhere for years even as the business strengthened, and exactly why that period was an opportunity. The mispricing is the point.

The time dimension. The right split is not fixed for life. Early in a company’s development, it makes sense to reward customers disproportionately, because referrals and repeat business are what build the franchise. As the business matures, the bias can ease, and shareholders can reasonably take a larger slice. Push that too far, though, and the moat drains.

The capital markets will applaud the higher margins right up until growth stalls and the company enters what Sleep called growth purgatory, the place where a highly rated stock falls because investors finally notice that the reported profitability was borrowed from the future. Coca-Cola leaning too hard on its bottlers, Gillette cutting advertising, Home Depot boosting gross margins: these are the cautionary cases of harvesting a moat to feed quarterly earnings.

The harvesting trap is stated as a rule. When you find a scale economies shared business, watch the direction of the split as closely as the level. Margins creeping up while the customer proposition stops improving is the early signal that management has started to harvest the moat. That is the tide going out. It is the thing that ends these stories.

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How to use it inside a full analysis

The robustness ratio is one input, not the whole verdict. It answers a single question well: how deep is the moat for a business that competes on price? It does not tell you whether the destination is large, whether the company can reinvest its cash at a high rate, or whether management is honest. Those are separate tests.

In practice, it slots into the moat work alongside three other judgments.

First, the destination. Where is this business going in fifteen to twenty years? Can you describe it in two plain sentences without hedging, and is that destination secured by the loop itself rather than by a battle not yet won?

Second, the reinvestment runway. A high return on capital only compounds wealth if the business can redeploy its earnings at that high return for a long time. The robustness ratio tells you the moat is deep. The runway tells you whether the engine has room to run. A deep moat around a small, full pond is a fine income stream and a poor wealth builder.

Third, the mispricing. The most valuable setups are the ones where the robustness ratio and the income statement disagree. A high ratio that the market reads as “low margin, mediocre business” is the under-earning mispricing Sleep exploited at Costco.

If you can name the specific wrong heuristic the market is using (cyclical when it is structural, low-margin when it is deliberately reinvesting, stagnant when it is compounding), then you have both a quality thesis and a re-rating thesis in the same name. That is the combination that produces the largest long-run returns, where the growth does the heavy lifting and a multiple re-rating adds a kicker on top as the business proves its durability.

Price still comes last, and it still binds. A wonderful flywheel at a silly price is a watch-and-wait, not a buy. But for a genuinely secured, widening, scale economies shared business, the protection lies in the durability and predictability of the compounding, and demanding a deep bargain entry often just means never owning it at all.

The model in the wild: three deep dives

The clearest way to learn the model is to watch it operate in real businesses. Below are three live examples, each with a full deep dive. They are deliberately different. One is a near-perfect modern copy of GEICO. One is the textbook marketplace-plus-fintech flywheel. One is the honest edge case where the robustness ratio is harder to apply, which is itself the lesson.

Nu Holdings: the modern GEICO of financial services

If you want to see the robustness ratio in its purest modern form, look at Nubank. It built a digital-only bank with a cost to serve a fraction of what Brazil’s incumbent giants carry, and it handed that advantage straight back to customers as free or near-free products in a market long defined by high fees.

Customers reciprocated, mostly through word of mouth, which kept customer acquisition costs low and fed the loop. More customers mean more scale and more data, which lowers the cost to serve and sharpens credit underwriting, which funds an even better customer deal. The give-back is measured in fees the customer no longer pays, which is exactly the kind of price-based proposition the robustness ratio was built to measure. Nubank is the closest thing in this generation to the GEICO that started the whole framework.

Read the full Nu Holdings deep dive →

MercadoLibre: the Latin American flywheel

MercadoLibre runs two reinforcing flywheels at once. The marketplace loop is the classic version: more buyers attract more sellers, which widens selection and pushes prices down, which attracts more buyers. The scale economies shared mechanism shows up most clearly in logistics, where building out fulfilment lowers the per-parcel cost of delivery, which gets handed to buyers as faster and cheaper shipping.

Bolted to that is Mercado Pago, the payments and fintech arm, where rising volume lowers the effective cost of moving money and funds better products. This is a marketplace-plus-fintech compounder, not a passive listings portal, and the distinction is the whole point. The give-back runs through cost, selection, and convenience rather than a simple shelf price, which makes the robustness ratio a directional read here rather than a clean single figure.

Read the full MercadoLibre deep dive →

Toast: where the robustness ratio gets harder

Toast is the most instructive of the three precisely because it does not fit the Costco template cleanly. It is the operating system for restaurants, bundling point-of-sale software, online ordering, payroll, and payments into one platform. The scale loop is real. As Toast grows, it spreads its software investment across more restaurants and processes more payment volume, which lets it offer an ever more capable platform at a competitive, effective cost.

But the benefit it hands back is mostly capability and integration, not a lower headline price. That puts it nearer the boundary Sleep drew, where the proposition is partly about value delivered rather than purely about price saved. The honest read is that Toast blends scale economics with switching costs, and that the robustness ratio is harder to compute for it than for a pure discounter. That is the lesson: the model is a spectrum, and the cleanest measurement belongs to the businesses competing most directly on price.

Read the full Toast deep dive →

Frequently asked questions

Is scale economies shared the same as economies of scale? No. Economies of scale just means costs per unit fall as a business grows. That is common, and on its own it produces a fatter margin that invites competition. Scale economies shared is the deliberate decision to give most of that cost saving back to the customer as lower prices or a better deal, which triggers the reciprocation loop. The sharing is the part that builds the moat.

Does giving savings away just mean lower profits forever? In the short run, yes, margins look thin. That is the point. The business is choosing to under-earn today to secure a larger and more certain destination, and a widening cost advantage means per-share free cash flow can still grow steadily even on flat margins, helped by rising volumes and falling asset intensity. The reported income statement understates the franchise, which is the mispricing the patient investor exploits.

How is the robustness ratio different from gross margin or return on capital? Gross margin and return on capital measure how much the business keeps. The robustness ratio measures how much it gives away relative to what it keeps. A business can have a low gross margin and a very high robustness ratio at the same time, and that combination, low reported profitability sitting on top of an enormous customer give-back, is the signature of a deep and deliberately under-earned moat.

Which companies are scale economies shared businesses? The canonical historical cases are Costco, GEICO, and Amazon. Sleep also pointed to AirAsia. Live modern examples that exhibit the loop include Nu Holdings and MercadoLibre, with Toast as a partial case. The test is whether the business systematically returns its scale advantage to customers in a way that they reward with more business.

Why did Costco’s stock go nowhere for years if the model is so good? Because the market reads reported earnings, a business that deliberately keeps margins thin to widen its moat looks cheap and unexciting on those earnings. The franchise was strengthening the whole time. The gap between the improving business and the flat stock was the opportunity, and it is the clearest real-world illustration of why this model rewards patience.

Can the model break? Yes, in one main way. Management starts to harvest the moat, letting margins creep up to please the stock market while the customer proposition stops improving. The capital markets applaud right up until growth stalls and the stock falls. Watching the direction of the split, not just its level, is how you catch this early.

Key takeaways

• Scale economies shared is a business model where a company hands its growing cost advantage back to customers, triggering a self-reinforcing loop that widens the moat every year it runs.

• It is the most durable moat type because size becomes a weapon rather than a liability, and because it lowers the probability of failure over time rather than merely defending a fixed position.

• The robustness ratio measures the depth of the moat for price-based businesses. It is customer savings divided by shareholder profit. GEICO sits near 1:1 and Costco near 5:1.

• The ratio is a thinking tool, not a magic number. A finer ratio can still be a powerful barrier; a falling ratio is not necessarily a shrinking moat, and the instrument only fits propositions built on price.

• The ratio’s real power is in identifying businesses that are deliberately under-earning, which the market misprices on reported earnings. That mispricing is the source of return.

• The model breaks when management harvests the moat to flatter margins. Watch the direction of the split.

• Predictability is what lets you size a position large and hold it through deep drawdowns, which is how the compounding is actually captured.

Sources and further reading

• The Nomad Investment Partnership letters to partners, Nick Sleep and Qais Zakaria, 2001 to 2014. The primary source for both scale economies shared and the robustness ratio.

• Berkshire Hathaway annual letters, Warren Buffett, in particular the 2004 letter discussing GEICO, which seeded the framework.

• Richer, Wiser, Happier, William Green, 2021, chapter six on Sleep and Zakaria.

• Capital Returns, edited by Edward Chancellor, for the Marathon capital-cycle thinking that shaped Sleep’s approach.

It usually sounds something like this:

I hear this everywhere. I have to admit, the argument sounds incredibly persuasive. It sounds logical, grounded, and reassuring.

Yet, whenever I hear the consensus asserting a fundamentally new era because our spreadsheets are better or our trading apps are faster, a massive warning light goes off in my head. I firmly believe the single greatest blind spot in modern finance involves the assumption of markets as perfectly rational, calculating machines.

The danger today is not that every AI company is fake, or that the largest technology firms are empty shells. The danger is more subtle: investors can be right about the technology, right about the business quality, and still be catastrophically wrong about the price.

We look at forward-looking P/E multiples, we run discounted cash flow models, and we assume the math working on paper guarantees logical behavior from the human beings executing the trades. I think this completely ignores the raw, unadulterated power of human emotion.

When the market narrative eventually breaks, our collective, panicked, reptilian brains dictate the absolute bottom.

Here at Atomic Moat, my goal remains to offer learning, alpha, and entertainment. I want to sit down with you today and really unpack why the math of Wall Street cannot save us from the psychology of Main Street. Let us look at history, let us look at human nature, and let us explore why the modern architecture of the market might actually make the next panic worse.

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The Echoes of 1999: Euphoria in the Trenches

People arguing for a fundamentally safer market today often do so by painting a caricature of the late 1990s. Many dismiss the dot-com era as a time of foolishly buying empty shell companies with no business plans. There was plenty of that. I think we must look at real stories from that era to understand the investor mindset.

The people investing back then genuinely believed they were participating in a technological revolution destined to change human history. The crazy part is they were completely right about the technology. Their timing and price evaluations proved disastrously wrong.

Let me give you three specific examples from the 1999 to 2000 era. I believe these examples hold up a perfect mirror to the psychology we see today.

1. The Picks and Shovels Delusion: Cisco Systems

Today, everyone justifies the astronomical valuation of companies making AI chips or building data centers by calling them the “picks and shovels” of the AI gold rush. I think people forget this exact same analogy defined the narrative for Cisco Systems in March of 2000. Cisco made the routers and switches physically powering the internet. The logic was flawless. No matter which dot-com company won, they all needed Cisco’s hardware.

Driven by this undeniable logic, investors bid Cisco’s market cap up to $555 billion, briefly making it the most valuable company on Earth.

Its Price-to-Earnings ratio blew past 100. People said the earnings were real and the margins were incredible. Here is the fascinating part. The investors were completely right about the business. Over the next twenty years, the internet changed the world, and Cisco’s earnings actually grew substantially. Yet, an investor buying Cisco at the peak of that rational, logic-driven euphoria in 2000 saw their stock plummet by over 80 percent when the bubble burst.

It took more than two decades for the stock to merely get back to its year-2000 price. Having real earnings and real margins did not save investors from the devastating effects of a contracting multiple.

2. The Liquidity Mirage: TheGlobe.com

We often think today’s retail investors are unique in their ability to drive up speculative assets quickly. I believe we need to remember the IPO of TheGlobe.com in November 1998. It was one of the earliest social networking companies. The underwriters priced the shares at $9. When the market opened, the pent-up retail demand was so ferocious that the first trade executed at $87. It hit $97 by the afternoon and closed its first day of trading up 606 percent.

The founders became paper multi-millionaires before lunch. The financial press hailed it as proof of a new paradigm where retail investors could instantly recognize value the stodgy Wall Street banks had missed. A few years later, the stock was trading for pennies and faced delisting. The retail investors buying at $87 because of FOMO were completely wiped out. The speed of the market merely accelerated their demise.

3. Ignoring the Unit Economics: Pets.com

I think the details of Pets.com are what truly matter. Pets.com famously raised $82 million in its IPO in early 2000. They bought a $1.2 million Super Bowl ad. They possessed a wildly recognizable brand with the sock puppet. They were selling heavy bags of dog food online and shipping them via FedEx, meaning they lost money on literally every single transaction. In 1999, the market completely ignored the unit economics. Analysts invented new metrics, arguing sufficient “eyeballs” and market share would miraculously produce profits later. Less than 300 days after going public, Pets.com entered liquidation.

I look at the massive, multi-billion-dollar losses being subsidized today in the name of capturing the AI infrastructure market, and I see the exact same psychological mechanism at work. We are once again willing to forgive horrific current unit economics in exchange for a utopian vision of future dominance.

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The Dangerous Myth of the Rational Shock Absorber

I spend a lot of time thinking about the structural changes in the market over the last twenty years. Perhaps the most significant shift involves the massive, systemic migration of capital out of active management and into passive index funds and ETFs.

I think a lot of investors view this as a stabilizing force. They see it as a giant, unfeeling shock absorber for the financial system. The logic suggests trillions of dollars locked up in passive vehicles tracking the S&P 500 or the Nasdaq-100 insulates us from the emotional, manic day-trading of the past. Algorithms do not feel fear. They do not get sweaty palms, they do not panic upon reading a terrifying headline, and they do not sell because of a bad quarterly earnings call.

I believe this theory possesses a fatal, catastrophic flaw. It completely separates the tool from the user. Algorithms remain emotionless, whereas the human beings holding those index funds absolutely feel fear.

When the market narrative eventually shifts, human psychology takes the wheel. As Howard Marks always reminds us, the pendulum forever swings from flawless optimism to crushing pessimism.

We know from decades of behavioral economics that the pain of losing money is roughly twice as intense as the joy of making it. This principle of loss aversion is incredibly powerful. When everyday investors see their 401(k)s and brokerage accounts bleeding red week after week, they log in and hit the “sell” button.

At that exact moment, the supposed shock absorber instantly transforms into a turbocharger for the crash. The fund managers at institutions like Vanguard, State Street, or BlackRock do not sit down to analyze a tech giant’s balance sheet or evaluate its long-term cash flow before selling. They are mechanically and legally obligated to liquidate the underlying shares to return cash to their panicked clients. This selling is entirely blind, completely indiscriminate, and completely merciless.

A company could be generating record-breaking free cash flow, and its shares will still be dumped onto the open market because the ETF redemption mechanism demands it.

I think we also need to address the illusion of modern liquidity. People genuinely believe they are safer today because they can maneuver quickly with zero-commission apps on their phones. In my experience, liquidity acts like a coward.

It is incredibly abundant when the market is rising and everyone is eager to buy. The moment real panic hits, the buyers evaporate. Trying to exit a collapsing market on a smartphone resembles trying to evacuate a burning stadium through a single, narrow turnstile. Your lightning-fast connection speed merely ensures you and ten million other investors hit the bottleneck at the exact same millisecond.

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The Fast-Track Danger: The SpaceX Experiment

To see how this mechanical risk is actively forced onto the average investor, I think we should look at a real-time example. The colossal IPO of SpaceX is fascinating.

SpaceX represents the ultimate test of our modern market infrastructure. In the past, a company had to undergo a lengthy maturation period in the public markets to prove its stability before gaining an invitation into the major indices. Tesla went public in 2010. It only gained entry into the S&P 500 ten years later. It had to prove its survival capabilities.

Today, the rules have been altered to accommodate the hype. Major index providers now facilitate fast-track inclusions for mega-cap companies. I find this deeply concerning.

Shortly after SpaceX went public, large passive index funds were mathematically forced to purchase gigantic quantities of the stock to reflect its market weight. Millions of everyday investors, through their retirement accounts, automatically became shareholders at the absolute peak of the IPO frenzy.

This entire process bypasses any individual choice, due diligence, or risk assessment.

I believe SpaceX hitting a speed bump will have massive consequences. If the AI rollout faces delays, if the energy infrastructure costs spiral out of control, or if the technology simply fails to monetize as aggressively as projected, the resulting valuation collapse will severely hurt risk-hungry Silicon Valley venture capitalists and everyday investors alike. The passive ETF system will distribute that devastating, multi-hundred-billion-dollar loss directly into the pensions and savings of the broader public. The machine forces us to buy the top.

The Ape in the Room: NFTs and Unchanged Human Nature

It always strikes me as deeply ironic how the investment class of the 2010 to 2024 era spent so much time mocking the naive speculators of 1999. We looked back at the dot-com bubble and laughed at people buying companies with zero revenue based on clicks. I believe we spent the last decade building our own bubble, wrapped in a more respectable vocabulary. We stopped talking about eyeballs and started talking about quality software, recurring revenue, and total addressable markets.

The underlying delusion remains identical, regardless of what we buy in the markets. We believe an asset is a must-buy regardless of its price.

If you want undeniable, irrefutable proof of human rationality acting as a thin, fragile veneer, I think we only need to look back a couple of years to the NFT craze. Anyone arguing investors are more educated today must explain the Bored Ape Yacht Club.

In January 2022, the pop star Justin Bieber purchased a digital asset. He bought Bored Ape Yacht Club #3001. It was a cartoon JPEG of a sad-looking ape with tears in its eyes. He paid 500 Ethereum for it. At the time, that was the equivalent of roughly $1.3 million.

Let that sink in for a moment. A human being spent 1.3 million real, tangible dollars on a hyperlink to a PNG file. There was no cash flow here. There was no intrinsic value. There was no balance sheet, no physical asset, and no fundamental logic.

No, this was driven entirely by raw greed, the desperation of FOMO, and the greater fool theory. People dressed it up in the techno-utopian language of Web3 and the blockchain.

By the summer of 2024, the floor price of the Bored Ape collection had absolutely cratered. That $1.3 million ape suddenly traded for around $50,000. That represents a wipeout of over 96 percent.

To look at that psychological phenomenon involving billions of dollars globally and confidently claim today’s equity markets are governed by cool, educated rationality seems willfully blind to me. Human nature simply has not evolved since the Dutch tulip mania of the 1600s or the South Sea Bubble of the 1700s. We do not possess fundamentally different brains. We just have faster Wi-Fi and better pitch decks now. When the money is easy and your neighbor gets rich quickly, the logical part of the human brain simply shuts down.

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The Prophets of the New Paradigm

The 1999 bubble had its star analysts like Henry Blodget, who became a financial pop star overnight by predicting Amazon would hit $400 and projecting endless upside. Today’s tech boom has generated its own prophets. Back then, the company was nothing more than a digital bookseller, yet after debuting at a mere $9 a share the previous year, the stock was already trading at $240.

But today’s investors are seemingly smarter. We know that a traditional Wall Street analyst can be wrong and is heavily compensated to be bullish. We pat ourselves on the back for ignoring the suits, searching instead for the “right” people with the “right” insider knowledge. Today’s tech boom has generated its own completely new breed of prophets.

Today, I think we need to look at figures like Leopold Aschenbrenner. He is a brilliant AI researcher and a valedictorian from Columbia at age 19. He worked on OpenAI’s superalignment team. After leaving OpenAI, he published a massive 165-page manifesto called “Situational Awareness,” predicting the arrival of Artificial General Intelligence by the end of the decade. He then launched his own investment fund, backed by Silicon Valley royalty, pouring billions into the physical infrastructure required for AI, including power grids, cooling systems, and retrofitted crypto-mines.

His logic is incredibly compelling. His intellect is undeniable. His essays are masterful. I believe this exact dynamic perfectly illustrates how bubbles inflate. A visionary paints a mathematically plausible, highly optimistic picture of the future. The narrative takes hold, the capital floods in, and the market immediately prices the infrastructure companies as if that utopian future is already a historical fact.

The narrative completely replaces the calculator. When that narrative takes hold, investing morphs into participating in a religion.

The Floor is Real, and the Drop is Brutal

So, where does this leave us? I am often asked if things are fundamentally different today.

I think in one very specific, structural way, they are. Today’s tech mega-caps actually generate hundreds of billions in real cash, vastly differing from the empty shell companies of 1999. Microsoft, Apple, Google, and Meta are monetary fortresses. There is a fundamental floor to the market today. If prices fall far enough, massive corporate share buyback programs and deep-pocketed value investors will eventually step in and halt the slide. The companies will not go to zero.

But I believe that floor on a lot of companies sits terrifyingly far away from where we are trading today.

Let us do the math on multiple contraction. If a market darling is currently trading at 40 times its earnings, and a panic-driven recession shifts investor sentiment back to a historical, rational average multiple of 15, the stock drops by over 60 percent.

That catastrophic drop happens even if the company’s actual earnings stay exactly the same. The business can remain perfectly healthy and continue to grow. Meanwhile, the valuation multiple gets entirely wiped out. That premium we pay for hope, euphoria, and the illusion of a new paradigm simply disappears.

That is the incredible danger of buying anything at any price. An investor can be completely right about the quality of the company and simultaneously lose more than half their money because they were wrong about the psychology of the market.

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Surviving the Cycle

Navigating an environment like this requires a very delicate balance. Recognizing the fragility of the market requires careful navigation rather than blindly running in the opposite direction. Aggressively shorting a euphoric market is a fantastic way to destroy your capital. I am not enthusiastic about this strategy if it is used recklessly. The market can remain irrational far longer than any of us can remain solvent. Attempting to time the exact top is a fool’s errand.

Instead, I believe true alpha right now is found in maintaining a profound, humble respect for human irrationality. It means keeping your head when everyone else is losing theirs. It means understanding that when the tide turns, your passive index funds will offer no protection. The fast-tracked mega-caps will fall just as hard as the rest, and the compelling narratives of today’s market prophets will be entirely rewritten in the financial press overnight.

The spreadsheets, the DCF models, and the corporate margins are all very real. When the fire alarm gets pulled, all of those metrics become irrelevant. The tools of modern finance have become entirely digital. The fear that ultimately drives them remains profoundly, dangerously human.

Stay aware. Stay grounded. Remember that in investing, history rarely repeats itself exactly, yet it almost always rhymes.

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Disclaimer:

This is an opinion piece and not financial advice whatsoever. I am just a random guy on the internet with opinions. DYOR. And be careful with your money.

Once or twice a week, someone asks me the same thing. What is actually on your watchlist?

A list of great companies is the easy part. The hard part is that a great business and a great investment are not the same thing.

Overpay for a wonderful company, and you can sit on a flat result for a decade while it does everything right. Most watchlists tell you what is good and go quiet on what it is worth.

This one does both.

How I find them

I fish where the big funds cannot follow. Neglected smaller companies in places like Sweden, the UK, Germany, Norway, and Australia, mostly under a couple of billion in value, with thin analyst coverage and a founder who still owns a large slice.

Then I screen for the things that do not lie: a high return on capital held for years, earnings that turn into real cash, little or no debt, and profits being put back to work rather than paid away.

What earns a place

The screen hands me a hundred maybes. Almost all of them fail.

A name only makes the list when it clears every one of these:

• A founder or owner-operator still in the chair, with their own money on the line, not a hired hand collecting options.

• A moat I can name in one sentence. A product a customer would be slightly mad to rip out, a network that gets stronger as it grows, a niche monopoly in something like medical devices, or a serial acquirer that compounds by buying well.

• A balance sheet strong enough that the company controls its own fate.

• A long runway, room to keep reinvesting its own profits at a high rate for

  years, rather than a pond already fished out.

• A reason competitors lose. Ideally, a moat that widens as the business grows instead of one it has to keep spending to defend.

The part most people skip

For every company on the list, I publish a Fat Pitch Price.

It is the price I would pay today, no hesitation, because the margin of safety is finally wide enough that I am being paid to be wrong. I reach it the slow way, and then I wait, often for years.

Most of the time, the price never comes.

As I write this, several of these companies are closer to their Fat Pitch Price than they have been in a long time, and one or two sit within a modest pullback of it. That is rare. For most of the past few years, this list has been a waiting room. Right now, a few names are stirring.

Get the full list

The names, the rankings, the Fat Pitch Price for each one, the margin of safety behind it, and a plain note on why each moat holds and the one thing that would break it are below for paid subscribers.

This is my own inventory for my own book, not financial advice. Treat every name as the start of your own work, not the end of it.

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You’ve probably never heard of him. And if you have, maybe his name is somewhat familiar, but you don’t know much about him besides that.

That’s partly because he doesn’t do interviews, doesn’t chase headlines, and reportedly shows up to the office looking like he’s been sleeping in his car. But since taking over the Contrafund in 1990, he has outperformed the S&P 500 by roughly 2% a year, every year, across dot-com bubbles, financial crises, and a global pandemic.

Two percent doesn’t sound dramatic. Here’s what it does to money over time: $10,000 invested with Danoff in 1990 is worth roughly $250,000 today.

The same money in an index fund gets you around half that.

The gap between “good enough” and “slightly better, sustained forever” turns out to be a quarter of a million dollars.

So. What’s the idea?

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He Learned One Thing From Peter Lynch, And He Never Forgot It

Danoff joined Fidelity as an analyst in 1986, four years before taking over the Contrafund.

His mentor was Peter Lynch, who ran the Magellan Fund to legendary returns and then retired at 46 because he’d made enough money and wanted to watch his kids grow up, which is frankly the most correct decision anyone has ever made, if you ask me.

Lynch’s lesson to Danoff was deceptively simple: a stock is not a ticker symbol. It’s a piece of a business run by actual human beings.

Those human beings have ambitions, blind spots, competitive instincts, and varying degrees of ability to allocate capital intelligently. Your job is to figure out which ones are exceptional before everyone else does.

Danoff took this and ran with it. He spent years cold-calling executives, sitting across from CEOs in conference rooms, asking the same questions over and over: Where is your growth coming from? What would have to be true for you to double earnings in five years? Who in your industry scares you, and why?

He wrote everything down. In composition notebooks. By hand. Thousands of them over thirty-plus years.

This is either inspiring or slightly alarming, depending on your personality. Either way, it worked.

The Only Metric That Actually Matters (According To Danoff)

Here is the entire Danoff investment thesis, compressed into one sentence:

That’s it. He calls this the Earnings North Star, and it’s his true north on every single investment decision he makes.

Now before you roll your eyes; yes, “buy good businesses” is obvious advice. The non-obvious part is what Danoff is willing to pay for those businesses, and how long he’s willing to wait.

Most investors look at a stock trading at 30x earnings and recoil. That’s expensive. They gravitate toward the stock at 15x earnings. It feels safer. It feels responsible.

Danoff does the opposite. Here’s his logic:

Company A: 15x earnings. Slow growth. Management focused on defending turf and paying dividends. This looks cheap.

Company B: 30x earnings. Growing earnings at 20% a year. Management is aggressive, hungry, eating market share for breakfast. This looks expensive.

Fast forward five years. Company B has compounded its earnings substantially. At 20% annually, earnings roughly 2.5x over five years. That 30x multiple? It’s been absorbed by the growth. The stock price has reflected the new earnings reality and moved considerably higher.

Meanwhile Company A is still trading at 15x its stubbornly flat earnings, exactly where you left it.

The “expensive” stock was actually the cheap one. The “safe” stock was the trap.

Danoff has been making this trade, in various forms, in various sectors, for thirty-five years.

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The Part Nobody Talks About: He’s Also Willing To Be Wrong And Move On

Here’s what separates Danoff from a lot of growth investors: he has no ego about his positions.

When the thesis breaks, he leaves.

When a sector’s earnings momentum shifts, he reallocates.

He rode retail giants through the 90s. He moved into software and tech as they became the dominant earnings engines of the 2000s and 2010s. He didn’t stay loyal to any industry because he’d built a position there. His only loyalty is to the earnings trajectory.

This sounds obvious. It is almost impossible to actually do in practice. Most investors hold declining positions too long because selling means admitting you were wrong, and admitting you were wrong feels terrible.

Danoff essentially treats this feeling as irrelevant data. The notebook doesn’t lie.

Either the thesis holds or it doesn’t.

The Awkward Part: Size

Managing $130 billion is not like managing your ISA.

When you decide to sell a position, you click a button and it’s done. When Danoff decides to trim a multi-billion-dollar holding, he has to do it over weeks.

Slowly, algorithmically, carefully. Because if he moves too fast he crashes the price against his own shareholders.

This is called the liquidity trap, and it’s a genuine constraint that gets worse as a fund grows. It’s the main reason some great investors cap their fund sizes or close to new money entirely. Danoff never did, which means he’s been operating with one hand partly tied behind his back for decades.

The 2008 financial crisis is the stress test that matters here.

The Contrafund dropped around 37%. On a $100 billion fund, that’s tens of billions of paper wealth gone in months. The question in that moment isn’t whether your spreadsheet is right. The question is whether you can look at the carnage, go back through your notebooks, verify that your best businesses still have dominant competitive positions, and hold.

He held. The subsequent decade rewarded him considerably.

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Three Things You Can Steal From Danoff Today

1. Write The Thesis Before You Buy Anything

Before deploying capital into any stock, write down (by hand if you’re feeling ambitious) exactly how this company doubles its earnings in the next five years. Not “the sector is growing” or “management seems good.” The actual mechanics. What markets are they entering? What’s the margin expansion story? What does the competitive landscape look like in five years?

If you can’t write two coherent paragraphs answering that question, you don’t have an investment thesis. You have a vibe. Vibes are not a portfolio strategy.

The notebook discipline also does something else: it gives you a document to return to when the stock drops 20% and you’re panicking.

Either the thesis still holds — in which case you hold, or buy more — or it’s broken, in which case you sell. The notebook removes emotion from the decision because the decision was already made when you were calm.

2. Ask The Competition, Not The Company

Corporate investor presentations are designed to make you feel good about investing. They are professionally produced optimism. Don’t trust them as your primary research source.

Instead, find the company’s fiercest competitor and read their filings, their earnings transcripts, their risk disclosures. Pay attention to how they talk about your target company.

If a direct rival grudgingly acknowledges that a competitor is winning, and that they’re losing customers to them, that their technology is better, that their sales team is everywhere… that’s more valuable than any glossy slide deck.

A begrudging compliment from a competitor is one of the best buy signals available to retail investors, and almost nobody does this.

3. Do The Annual Thesis Audit

Once a year, go through every position you own and ask one question: Is the original reason I bought this still true?

Not “is it down, so maybe I should wait to break even.” Not “I’ve held this so long it feels like part of my identity.” Just: is the thesis intact?

If yes, hold. If no, sell. Don’t wait for a recovery that may not come.

This is the one Danoff habit that most directly translates to individual investors and the one most people will refuse to do because it requires confronting decisions they’d rather not think about.

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The Human Being Behind The Fund

Danoff is famously not what you’d expect from someone managing this much money.

No bespoke tailoring. No exclusive clubs. Colleagues describe him as carrying a permanent air of barely-contained urgency:

Pockets stuffed with earnings reports, notebooks under his arm, scheduling 6am calls with obscure small-cap CEOs and then running straight into meetings with Silicon Valley founders in the afternoon.

He applies the same level of obsessive scrutiny to a $50 million position as to a $5 billion one.

His edge was never a proprietary model or a better Bloomberg terminal. It was the volume and quality of conversations he had with the people running businesses, sustained across decades. Somewhere in those notebooks is a record of almost every important public company in America, as seen through the eyes of their management teams, captured in real time.

That’s not a system you can automate.

Is This Strategy For You?

Yes, if:

• You can genuinely hold a stock for 5-10 years without checking it every morning

• You’re comfortable owning companies that look “expensive” by conventional metrics

• You can sit through a 30-40% drawdown without selling, because you’ve already written down why you own it

• You find businesses genuinely interesting rather than just as instruments for making money

Probably not, if:

• You need dividend income from your portfolio

• You enjoy trading actively and would go insane holding the same 20 stocks for a decade

• You want to time macro cycles and rotate between sectors based on economic forecasts

• You’ve never once read a company’s annual report and have no plans to start

The honest summary: Will Danoff is a growth investor who is better at growth investing than almost everyone else, sustained over an almost implausibly long time period. The edge isn’t a secret formula. It’s discipline, a notebook, an obsessive personality, and thirty-five years of talking to the people who actually run businesses.

The notebook you can start tonight. The thirty-five years, unfortunately, you’ll have to earn.

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First, let’s kill the word

“Multibagger” is a clickbait word. I know it, you know it, and the algorithm knows it. So let me defuse it before we go any further.

A multibagger is a business that compounds its value at a high rate, held for a long time. That’s it. The multiple is arithmetic, not magic.

Watch how fast the arithmetic runs. A business that compounds intrinsic value at 20% a year turns into roughly a 6-bagger in ten years, a 15-bagger in fifteen, and a 95-bagger in twenty-five.

Berkshire became one of the great 100-baggers of all time the boring way: it compounded at around 20% for sixty years. Buffett bought predictable, wonderful businesses at fair prices and then did the hardest thing in investing, which is nothing.

“The big money is not in the buying and the selling, but in the waiting.” — Charlie Munger

So when I screen for “multibaggers,” I am really screening for three ingredients, and I want you to use the same three on every name below:

1. A durable compounding engine. A high return on capital that the business can actually reinvest, not just earn once. The return on the next dollar is what matters, not the average return on the dollars already spent.

2. A long runway. Room to keep redeploying cash at that high rate for a decade or two. A brilliant business with no room to grow is a lovely dividend stock and a poor wealth-builder.

3. Hold-ability. Enough predictability that you can sit through the three 50% drawdowns every one of these will hand you without selling at the bottom. This is the ingredient everyone ignores, and it is the one that actually decides whether you collect the multiple or just admire it from the exit.

There is a fourth thing that turns a good return into a spectacular one, and it is not what most people think.

For a real long-run winner the growth does the heavy lifting, tens of times over. The multiple re-rating is a 2x to 3x kicker on top. That kicker is not bargain-hunting. It is the market slowly admitting it had the wrong label on a business, and the day it admits that is the day your thesis pays you twice.

One last thing about where these live. A famous study of 104 stocks that returned more than 350% over five years found the winners clustered in Sweden, the UK, Germany, Norway, and Australia, with thin analyst coverage, and 84% of them started under $2 billion in market cap. Small, neglected, developed-market businesses are the pond.

Five of the seven names below are fishing in exactly that water. Two are not, and I will tell you which.

Disclaimer: All content is for informational and entertainment purposes only and does not constitute financial advice.

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The seven

These come in three flavours.

The compounding machines own the process of getting bigger. The fallen quality names are good businesses the market has thrown out with the bathwater. The asymmetric bets are smaller, spicier, and more binary, where the upside is large and so is the way you can be wrong.

Let’s get to it.

1. Teqnion (TEQ)

Building something for the next 100 years

What it is

Teqnion is a Swedish serial acquirer. It buys small, profitable, gloriously dull industrial companies, the kind that make connectors, transformers, lab equipment, and indication systems for military practice shooting, and then it leaves them alone to keep doing what they were already good at. Founder and CEO Johan Steene talks openly about building a company that lasts a hundred years, and he runs it like someone who means it: decentralised, cash-focused, allergic to head-office empire-building.

The numbers today

The stock trades around SEK 158, for a market cap near SEK 2.5 billion, which is about $255 million. Full-year 2025 revenue was roughly SEK 1.8 billion with net income near SEK 98 million, putting the shares around 28 times earnings. There is no dividend, by design. Every krona that comes in goes back out to buy the next business. The stock is up modestly over the past year and has spent twelve months bouncing between SEK 136 and SEK 189.

The runway

This is the part that matters. There are tens of thousands of small, owner-run industrial niche businesses across the Nordics and Europe whose founders will eventually want to retire and sell to a good home. Teqnion is a rounding error against that universe. A serial acquirer this size does not have a TAM problem; it has a “can we keep finding good deals and not overpay” problem. The engine is the acquisition process itself: the culture, the discipline, the decentralisation. The product could change entirely and the moat would still be there.

Why it could be a multibagger

The model is proven. Constellation Software, Lifco, Lagercrantz, and Indutrade all turned the same playbook into double-digit-to-twenty-percent per-share compounding for decades. Teqnion is early on that curve and small enough that its size edge is real, which is exactly the combination the data says you want. If Steene keeps buying well, a small base compounding in the high teens for twenty years is the whole multibagger story, and it requires no heroics.

What has to go right, and what could break it

A serial acquirer is only as good as its discipline. The headline P/E looks pricey because acquisition goodwill sits on the balance sheet and drags reported returns down; the honest way to judge Teqnion is the return on tangible capital and the return on each new acquisition, and that is the thing to watch every year. The risks are the obvious ones for the model: overpaying as it scales, diluting shareholders if it issues too many shares to fund deals, and the simple fact that the businesses underneath are lower-margin industrials, not asset-light software. None of that is fatal. All of it is worth watching.

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2. Röko (ROKO B)

Lifco 2.0, run by the man who built Lifco

What it is

Röko is the same serial-acquirer idea as Teqnion, scaled up and run by serious pedigree. It was founded in 2019 and chaired by Fredrik Karlsson, the former CEO who compounded Lifco into one of Europe’s great acquisition machines. Röko buys majority stakes in profitable European niche leaders, mostly businesses with EBITA between two and ten million euros, and keeps them forever under a decentralised model that preserves each company’s name and independence. It listed its B shares in Stockholm in March 2025.

The numbers today

The stock trades around SEK 1,900, for a market cap near SEK 28 billion, which is roughly $2.9 billion. That makes Röko comfortably the largest name on this list, and I want to be straight about that: at this size it is not a small cap, and it does not get my pure small-cap edge. It trades around 37 times earnings. Net sales were about SEK 6.2 billion for 2024, with adjusted EBITA margins around 20%, and in the first quarter of 2026 it grew organic sales 6% and total sales 9%, with three more acquisitions closed. It has done over thirty platform deals since inception.

The runway

Same answer as Teqnion, just with deeper pockets and a wider net across the UK, the Nordics, the Netherlands, the US, and beyond. The European long tail of family-owned niche businesses is effectively bottomless relative to even a SEK 28 billion acquirer. The constraint is capital discipline and deal flow, never market size.

Why it could be a multibagger

You are buying a proven operator running a proven playbook with a runway measured in decades. Karlsson has done this before at enormous scale, and the whole point of the perpetual-owner model is that it gets compounding-friendlier as the portfolio diversifies. If Röko sustains high-teens compounding of per-share value over fifteen to twenty years, the math takes care of itself.

What has to go right, and what could break it

The 37x multiple is the honest problem. It already prices in a lot of future success, which means the second engine, the multiple, has less room to help you and more room to hurt you if growth disappoints. The model runs on continuously deploying capital at good returns; the day acquisitions get too expensive or integration slips, the flywheel slows. And it is still young as a public company, so the seasoned track record is shorter than Lifco’s was when it earned its reputation. This is the quality-at-a-full-price name in the group. You are paying up for the pedigree.

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3. ChemoMetec (CHEMM)

Selling picks and shovels to the cell-therapy gold rush

What it is

ChemoMetec is a Danish company that makes the NucleoCounter, an instrument that counts cells, and then sells the consumable cassettes and reagents that the instrument eats every time it runs. It is a razor-and-blade business pointed at one of the best end-markets in science: bioprocessing, and the booming world of cell and gene therapy. Crucially, it does not bet on any single drug working. It sells the equipment that every lab in the field needs no matter whose drug wins, which is the cleanest way to own a gold rush.

The numbers today

The stock trades around DKK 315, for a market cap near DKK 5.4 billion, which is about $0.8 billion. It earns roughly DKK 10 per share, so it trades around 31 times earnings. The economics are gorgeous: gross margins around 91%, EBITDA margins around 50%, net cash, and a small dividend. Here is the kicker that makes it interesting right now: the stock is down roughly 72% from its 2021 peak of DKK 1,149, and it has traded between DKK 235 and DKK 804 in the past year alone. Analysts covering it carry an average target up near DKK 640.

The runway

Cell and gene therapy is still early, and every approved therapy and every new manufacturing line needs cell counting as a basic, repeated, non-negotiable step. The recurring consumables grow with the installed base, and the installed base grows with the industry. On top of that, management is now pushing a new “XM” platform and talking about a more software-and-licensing-shaped business over time, which is the kind of pivot that, if it works, re-rates the whole company.

Why it could be a multibagger

Start with a 90%-plus gross margin, net-cash, recurring-consumables compounder. Knock 70% off its price. Add a software transition that could change how the market values it. That is a recipe for both engines firing at once: earnings recovering as the cell-therapy cycle turns, and the multiple expanding as the market re-rates a saturated-looking instrument maker back into a growth compounder.

What has to go right, and what could break it

Even after a brutal de-rating, 31 times earnings is not cheap, so this is not a statistical bargain; it is a quality compounder you are buying at a fair-to-rich price after a fall. The reason it fell is real: the NucleoCounter base started to saturate and growth stalled, which is why the stock got cut in half and then some. The XM platform transition is unproven, and “we are becoming a software company” is a sentence that has humbled many a hardware business. Cell-therapy capital spending is also lumpy. You are betting that the franchise is durable and the next chapter works.

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I stumbled upon Toast the way I find a lot of names: out walking, with my headphones on.

Sean Barrett broke the company down on Business Breakdowns and made the bull case about as well as you will hear it: a restaurant that runs on Toast tends to stay, the share keeps moving its way, and after years of burning money, the cash has finally started to pile up. “A better company today than ever before”, he stated.

I came away genuinely interested, which does not happen as often as the size of my watchlist would suggest.

But interested is a looong way from invested.

A great story is where the work starts, and a good podcast, however persuasive, cannot answer the one question that decides everything for me: is the price low enough to give me a real margin of safety? So I ran home, pulled the filings, built the numbers myself, and went looking.

Here is what I found.

Note: I bought a sliver of Toast so it would have my attention (and to use that pun), because a name I own is a name I actually read. The position is tiny though, and that’s on purpose. I respect the business. So far I have refused to pay up for it.

If you’re in a rush

• They sell restaurants the one system the whole place runs on: the till on the counter, the software for the floor and the kitchen, the card processing under every order, and a growing stack of add-ons like payroll, lending, and marketing. Most of the money comes from a small slice of every card payment, which is why processing is the engine.

• The market loves them for taking share off Block and finally turning a real profit, and fears them as the next victim of the so-called SaaSpocalypse.

• What governs the outcome is the price I pay for a destination that is probable but not yet locked.

The internal verdict is a ‘Yes’ with an asterisk, so the published label is Watchlist, owned at an attention-only weight.

I am paying close attention.

Three MIT engineers and a point-of-sale that ran on a DOS prompt

The idea came from a bad dinner. Steve Fredette, Aman Narang, and Jonathan Grimm, all MIT graduates who had met building search software at Endeca (a company Oracle swallowed in 2011), were eating in Kendall Square and watched the staff fight with a point-of-sale system that kept crashing and rebooting to an antiquated DOS prompt.

Narang’s phrase for it later was that these systems were old and scary for the people who had to use them.

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So they built one. It started in Narang’s basement in 2011 as a humble consumer app for mobile payments and loyalty, then became the thing the restaurant actually runs on. That pivot is the origin of the moat. They went deep on one trade. They talked to restaurateurs for hours and built features a generalist would skip: real-time messaging to the kitchen about a dish that just sold out, software shaped around the rhythm of a Friday-night rush.

Chris Comparato ran the company as CEO from 2015 through the scaling years. On the first day of 2024, Narang, the co-founder, took the chair. Founder-led again, with the engineer who saw the crashing DOS prompt now allocating the capital.

The lesson the origin teaches, and the one I keep returning to, is that the vertical focus is the asset. A bear with a balance sheet could copy the software in a year. Copying fourteen years of restaurant-specific obsession is the part that breaks attackers.

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What you are actually buying

Picture a busy operator on a Friday night. Tickets are flying to the kitchen, a server is splitting a check four ways, a delivery order pings in, payroll runs Monday, and the whole thing sits on one system from one vendor.

That is what Toast sells: the restaurant’s operating system. They make most of their money the way a toll booth does, by taking a thin slice of every dollar that passes through.

The slices are uneven. Of $1,630M of revenue in the first quarter of 2026 (Q1 2026, USD, GAAP, 10-Q), the financial-technology line, mostly card processing, was $1,323M.

Subscription software was $268M.

Hardware was just $39M, and here is a tell worth holding onto: hardware runs at a gross loss of roughly minus $72M for the quarter (Q1 2026, GAAP, release).

They sell the terminals cheaply to get the system onto the counter, because once it is there and running the business, it tends to stay.

The interesting motion is underneath the headline. Annualized recurring run-rate grew 26 percent year over year to about $2.2 billion (as of March 31, 2026, company-defined non-GAAP, release), while locations grew 22 percent to roughly 171,000.

Recurring revenue is climbing faster than the location count, so each restaurant buys more over time: payroll, lending, marketing, and the new AI tools.

A crowded pond, and the edge I give up to fish in it

Toast is a $15 billion company on the New York Stock Exchange, followed by somewhere between fifteen and twenty-seven analysts depending on which estimate sheet you read.

Every line in the filing has been chewed over by professionals with better terminals than mine.

Owning Toast, I step into a ring with the most-resourced investors alive, on a name they all know cold. The too-big check, drift risk number two, fails outright: at this size, my position is a rounding error in daily volume, so the liquidity wall that usually guards my edge is absent.

What the crowd has not settled is the competition. Toast is the shark in a fragmented tank. Its gross payment volume grew 22 percent year over year to $51.3 billion last quarter, while Block’s Square, at a similar scale, grew about 10 percent.

Management says Toast now powers around a fifth of US small and mid-market restaurants, double its share of three years ago. The rivals are real and well-funded: Fiserv’s Clover, SpotOn, the legacy Oracle Micros boxes, and a coming wave of AI-native entrants. Taking a share of Block while the others circle is the evidence that counts.

Atomic Take: I am fishing where I hold no structural advantage, so I had better get paid for it in the price.

Falsifier: net location adds decelerate while a named rival’s accelerate.

What stops a rich, clever rival from simply stealing these customers

Run the grizzly test first: Put a well-capitalized, intelligent competitor in the room and ask whether it is still likely to lose. Mostly, yes. Restaurants do not rip out the system that runs their floor on a whim, and when they do switch, they tend to switch toward Toast, which is why the share keeps moving its way.

Here is the Patterson sentence, the one specific barrier in a single line. A well-funded rival would find it prohibitively hard to take meaningful restaurant share within five years, because Toast’s hardware, software, and payments are fused into the daily running of the business, and switching means retraining staff and risking a service meltdown on the one system a restaurant cannot afford to have go dark.

The moat model, named plainly, is high switching costs that deepen with every product the restaurant attaches. I want to be careful with the prettier label. Scale economics shared is the Nomad whiteboard’s most powerful idea, the Costco move where saved pennies are visibly handed back to the customer and volume follows.

Toast does some of this, ploughing scale into more product, twenty-plus updates in the spring release, a drive-thru system, and an AI marketing agent. The payment take rate is the profit, and they keep it rather than cutting it to chase volume. So I will call scale-shared a secondary, emerging feature here and lean the thesis on switching costs, which stands on its own as a first-class moat. The idiot-proof test passes: the installed base would survive five years of mediocre management.

Now the mis-categorisation sentence, the heart of any re-rating case. The market prices Toast through the heuristic of AI-disruptable horizontal software, when the right lens is a payments-and-hardware-anchored vertical operating system, where the physical till and the switching costs blunt the disruption and AI feeds the business more than it threatens it.

The Audit on that thesis: it is half-spent already. The stock fell from about $50 to about $26 on exactly this fear, so much of the re-rating I would be hoping for has either happened or been prepaid by the market’s panic. The spring is half-uncoiled.

Atomic Take: the moat is real and built from switching costs, and the cheap re-rating it once offered has largely been collected by the people who bought the panic.

Falsifier: blended payments take rate or net revenue retention falls for two consecutive quarters.

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The river of cash, and where the taxman is about to step in

Follow the one river. Money comes in the door, $6,446M of it over the trailing twelve months (TTM to Q1 2026, USD, GAAP-derived, my spreadsheet). A lot is spent paying the card networks because the payments line is reported gross, which leaves gross profit of $1,694M.

Then the sales force, the engineers, and the overhead take their share, leaving operating income of $364M (TTM, GAAP). The reported bottom line reads $412M of net income (TTM, GAAP), and here I slow down.

Two things flatter that number. First, the company has paid almost no tax, $5M on $131M of pretax income last quarter, because of a valuation allowance against past losses that the company itself says could be released within twelve months (Q1 2026, 10-Q). When it releases, a real tax bill arrives. Second, a chunk of pretax income is interest on the cash pile, which is real and recurring, and which is also not the operating business compounding.

Now the discipline. Munger’s instruction is to substitute the words “bullshit earnings” every time someone says EBITDA, and management does lean on an adjusted-EBITDA frame and a 40 percent long-term EBITDA margin target that steps around two real costs: stock-based compensation and tax. Stock comp ran about $54M in the quarter, roughly 3.4 percent of revenue (Q1 2026, 10-Q), and I expense it in full.

Do the honest build. Start from normalized net income with tax at 25 percent, about $314M, add back depreciation of about $55M, subtract a maintenance-capex estimate of about $45M (this is an asset-light software business, where depreciation is a fair proxy), and leave stock comp where it belongs, charged against the owner. Owner earnings land near $300M to $320M for the trailing year. On a $15 billion market value, that is an owner-earnings yield of about 2 percent.

Atomic Take: the business now genuinely drowns in cash, and the current owner yield is thin once you tax it properly and charge it for its stock comp.

Falsifier: stock-based compensation reaccelerates above 5 percent of revenue.

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The Geiger test, the turbine, and the reactor

Take the balance sheet first, the Geiger counter for fragility. Cash and marketable securities of about $1.77 billion sit against roughly $17M of debt, so the company carries net cash of nearly $1.75 billion (as of March 31, 2026, USD, 10-Q). Return on equity of 20.7 percent and return on assets of 13.3 percent on a trailing basis (my spreadsheet), both flattered a touch by the tax holiday. Nothing here keeps me up at night.

The turbine is the cash flow. Free cash flow was $115M in the quarter on the company’s own measure (Q1 2026, company non-GAAP, release), and cash from operations covers reported profit comfortably. The capex-intensity flag stays green: this is a light business that does not spend heavily to stand still, so checks fourteen and fifteen of my eighteen both pass, and the BNSF detector, the warning that a business eats capital faster than it admits, stays quiet.

The reactor is the income statement, and this is where the one real distortion lives. Blended gross margin reads about 26 percent (TTM, GAAP), which fails my 40 percent screen.

That single fact, the choice to report payment volume as gross revenue, mechanically depresses gross margin, net margin, and the ratio of overhead to gross profit all at once. It is one structural artifact, and I charge it a single time. Strip it back, and the underlying software-and-payments gross profit is the number that matters, and it is growing fast.

The Audit on any optical cheapness: there is none to perform, because the stock is not optically cheap. It trades around 20 times forward earnings and 37 times trailing, with an owner yield near 2 percent. The statements are clean. The price is the problem, and I will get there.

Atomic Take: a strong balance sheet and an asset-light cash engine, where the only “failure” is a reporting artifact I refuse to double-count.

Falsifier: free-cash-flow-to-net-income falls below 0.7 on a clean basis.

The people allocating the capital

Founder-led, disciplined, and lately profitable. Aman Narang sits in the CEO chair he co-founded the company to fill, with super-voting Class B stock concentrating control, a governance fact I keep an eye on.

The retained-earnings test, which asks whether a dollar kept turns into more than a dollar of value, now works: incremental operating margins were reported around 59 percent in the fourth quarter and roughly 68 percent for the full year, so the next dollar of gross profit drops a large share to the operating line.

The capital-allocation behavior is mostly the kind I want to see. The share count fell, from 589 million to 580 million, as buybacks of $378M year to date through early May (company release) outran the stock handed to employees.

Shrinking the count while founder-led is the right instinct.

I hold one honest reservation, tagged. Handing back this much cash so soon, while the incremental returns are so juicy, hints that the highest-return internal runway is not infinite.

At roughly $27 to $33 a share, against my central estimate near $23, those repurchases look fairly priced, so I credit them only mildly.

Atomic Take: the founder is back, the dilution has reversed, and the buyback is sensible without being a value gusher.

Falsifier: buybacks accelerate well above intrinsic, or stock-comp dilution resumes.

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Where this goes by the early 2030s

The destination question decides everything, and Nick Sleep framed it best: do not ask what the business makes in year three, ask what it looks like as a mature franchise in fifteen to twenty years.

The runway is genuinely long, and it is the kind that widens as the company digs. Beyond more US restaurants, there are international, retail, enterprise, the roughly 140,000 US drive-thru locations they just built a product for, and the fintech and AI layers stacking on top. This is a company that can enlarge its own pond; the trait that kept Amazon from being capped at “online retail is tiny.”

Here is the discipline, though. The destination is large and probable. It is not yet secured. It leans on continued share gains, on margins expanding the way the bulls model, on the AI vector cutting for the company, and on no recession knocking the wind out of restaurant spending.

A probable-but-unsecured destination earns my full margin-of-safety bucket, and I hold that line in the next section.

Compound a fading growth rate, say 20 percent decaying toward 10 as the pond fills, off a roughly $7.5 billion revenue base, and you get something like three times the revenue by 2032. Layer on margin expansion, and earnings might grow three to five times. That places the intrinsic business in a 3-to-5x band at the optimistic end over six years. A clean 5-to-10x by 2032 sits above that, out at the bull-of-bull edge, and I will not size to an edge.

Atomic Take: the runway is long and self-widening, and the destination is probable while it is unsecured, which sets the price bar high.

Falsifier: two years of sub-12 percent revenue growth with no macro shock to blame.

What is it worth, and am I overpaying?

Price comes last, and price is the binding constraint. This is the section that explains where I believe the fat pitch for Toast is:

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Dislcaimer: None of this is investment advice, every figure here is rough and from spring 2026 (markets move — check the latest before you act), and you should absolutely do your own homework before putting a single dollar, or peso to work. I’m a guy on the internet with opinions, not your financial adviser.

Okay, settle in. I want to tell you about my favorite kind of business, and then introduce you to six small, mostly-unknown companies trying to become it.

Here’s the weird part: the thing that makes these businesses great is that they refuse to get greedy.

Let me explain.

The flywheel that runs backwards

Most companies, when they get bigger, do the obvious thing. They use their new size to squeeze better deals out of suppliers, and then they keep the savings. Bigger scale, fatter margins, happier shareholders. Makes sense.

A rare breed does the opposite. They get bigger, their costs fall, and then they hand the savings straight back to the customer as lower prices. They deliberately stay thin on margin. On purpose. Forever.

Why would anyone do that? Because it sets off a loop:

The investor Nick Sleep gave this loop a name: Scale Economies Shared.

His favorite examples were Costco and early Amazon; companies that treated every efficiency gain as something to give away rather than pocket.

Costco could jack up its prices tomorrow and mint a fortune this quarter. It doesn’t. It caps its markups by policy, makes most of its actual profit on membership fees, and uses its monstrous buying power to simply be the cheapest game in town.

The payoff is a customer base so loyal it’s almost spooky. And a moat that gets wider every single year, because every new member makes the whole machine a little bigger, a little cheaper, and a little harder to compete with.

That’s the magic.

Most moats erode over time, but this kind compounds.

The one test that separates the real thing from the fakes

Here’s how you tell a genuine Scale-Economies-Shared business from a pretender, and it’s almost embarrassingly simple:

Watch the margin line.

If a company is getting bigger and its profit margins are flat or even drifting down? That’s the tell.

It’s sharing the gains. (Costco’s gross margin has barely moved in decades. By design.)

If margins are climbing as it scales, then it’s pocketing the savings, not sharing them. That might be a perfectly lovely business, but it isn’t this one. Keep that test in your back pocket; we’ll use it at the end to bounce a couple of imposters off the list.

Why I hunt for the tiny ones

Costco is wonderful. Costco is also worth roughly a third of a trillion dollars. I think it is too much to expect that this is going to 10x from here very soon.

So I go looking for the small versions.

These are companies running this exact playbook but still valued in the hundreds of millions or low billions, in markets where the flywheel has barely started spinning. A $1.5 billion company that nails this can plausibly become a $15 billion one. A $300 billion one cannot make this move that easily.

Two more things I want before I’m interested:

A founder still at the wheel, ideally owning a big slug of the stock. Giving margin away is a decade-long act of discipline, and salaried managers cycling through on three-year bonus plans almost never have the stomach for it. Founders with their net worth riding on it do.

It is important to note that a price moat is not a lock-in moat. Nobody is stuck shopping at a discount store the way a company is stuck with the software it runs on, in comparison.

I have also written an article about switching costs that you can read here

The defense here is cheapness and trust, not switching costs. But this could make these businesses more fragile than they look.

With all that out of the way; here are six companies that follow the scale economies shared playbook and that could do a 10X from here, if they keep doing what they do:

1. BBB Foods — the one I’d start with

BBB Foods, which runs the Tiendas 3B hard-discount chain in Mexico, is the cleanest example on the list.

Picture a small, no-frills shop stocked with around 800 mostly own-brand products at rock-bottom, everyday-low prices. The scale crushes the cost of goods, and the savings go right back onto the price tag, which pulls in more shoppers, which builds more scale. Classic flywheel.

The runway is the exciting part: hard-discount is only about 3% of Mexican grocery spending, versus 24–38% in mature markets, so there’s a long way to grow into. Revenue has been compounding somewhere around 34% a year, and the founder still controls a big chunk of the votes.

The honest risks: it’s burning cash to open stores at speed, it leases every location (which flatters some of the headline numbers), Walmart’s Bodega and FEMSA’s Bara are competing hard, and the founder is in his sixties, so succession is a real question. But if you want to see the model in its purest, fastest-growing form, start here.

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2. Trial Holdings — the clever one

Trial Holdings runs everyday-low-price discount supercenters in Japan, but with a twist that most discounters can only dream about: it bolts a “Retail-AI” layer on top — smart shopping carts, in-store digital advertising, and a river of shopper data.

That data-and-advertising income effectively subsidizes lower shelf prices, which gives the flywheel an extra turbo.

It’s the most technologically interesting business here, and the founder is still steering.

The company is listed in Japan, which makes it tricky for a lot of foreign investors to actually buy, and it’s busy digesting a very large supermarket acquisition (Seiyu). Big integrations are exactly where retailers tend to trip.

Now let’s move on to one of the most attractive on the list, one the numbers:

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He never picked a stock. He never timed a market. He freely admitted, in writing, that he had no idea what the market would do next, and neither did anyone else.

Yet Jack Bogle built the largest asset manager in human history and, in doing so, transferred an estimated $1 trillion in fees away from Wall Street professionals and back into the pockets of ordinary investors.

His weapon was a mathematical identity so simple it fits on a napkin:

Gross Return − Costs = Net Return

That equation doesn’t look like a revolution. Wall Street spent fifty years hoping you’d never notice it was one.

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The Origin Story

Jack Bogle and his twin brother were born into wealth on May 8, 1929, in Montclair, New Jersey. The timing was catastrophic. Within months, the Depression arrived and dismantled everything.

The family lost their home. They sold their possessions. His father, unable to bear the reversal, descended into alcoholism and eventually left.

Bogle grew up working, delivering newspapers, waiting tables, setting up bowling pins at a local alley. He got a precise, personal understanding of what it costs to earn a dollar and how quickly it can disappear.

He won a scholarship to Princeton, where he survived on work-study wages and developed the habit of reading everything. In 1949, a Fortune magazine article about the mutual fund industry caught his attention. The industry was young, loosely regulated, and making large promises about its ability to select superior stocks on behalf of investors.

Bogle spent his final two undergraduate years writing a 130-page senior thesis dismantling those promises. His central argument was blunt: mutual funds were not delivering on their claims, their fees were destroying the returns of the people they were supposed to serve, and their primary obligation should be minimizing costs, not maximizing the appearance of sophistication. He concluded that funds should aim simply to match the market, not beat it.

It was 1951. He was twenty-one years old.

Walter Morgan, founder of the Wellington Fund, read the thesis and hired Bogle immediately. Over the next fifteen years, Bogle rose to become CEO — disciplined, cost-conscious, relentlessly focused on the investor.

Then he made one catastrophic mistake.

The Firing

In the late 1960s, the market was euphoric.

Growth stocks were soaring. Bogle, under pressure to compete with flashier funds, and perhaps seduced by the bull market himself, approved a merger with Thorndike, Doran, Paine & Lewis, a Boston investment boutique known for aggressive, high-conviction growth stock picking.

The combined entity would manage Wellington’s conservative assets alongside the new firm’s speculative ones.

Then, in 1973 the market turned.

The growth stocks, built on optimism rather than earnings, collapsed. Wellington’s performance cratered. The board had seen enough. In January 1974, after a brutal internal vote, Jack Bogle was fired from the company he had spent his entire career building.

He was forty-four years old. His reputation was damaged. And the terms of his dismissal legally barred him from managing investments or running a fund advisory firm.

Most people would have left the industry. Bogle read the legal language very carefully.

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The Superpower

What the firing prohibited was specific: Bogle could not manage money or run an investment advisory firm. What it did not prohibit was administration; the back-office mechanics of running a fund: legal, accounting, compliance, operations.

Bogle went back to the Wellington board with a proposal. He would form a new company, owned not by outside investors or private partners but by the Wellington funds themselves. This company would handle administrative functions only. It would, technically, not be an investment adviser.

He named it The Vanguard Group, after the British flagship at the Battle of the Nile.

The board approved it, assuming they were signing off on a clerical subsidiary. They had just handed Bogle the keys.

The ownership structure he designed was unlike anything in American finance. In a conventional asset management firm, investors pay fees that flow to the firm’s owners; shareholders, partners, executives. The firm’s incentive is to grow assets and extract maximum fees. The investor’s return is what’s left over.

At Vanguard, there were no outside owners. The funds owned Vanguard. The investors owned the funds. Any profits generated by the management company flowed back to reduce the costs borne by investors. The structure had no mechanism for extracting money from investors because investors were the owners.

[Traditional Asset Manager]  ──> Fees flow to ──> Outside Shareholders & Partners
[The Vanguard Structure]     ──> Profits flow to ──> Lower Costs for Fund Investors

This made one outcome structurally inevitable: Vanguard’s costs would always fall toward zero.

In 1976, Bogle launched the First Index Investment Trust; the first retail index fund available to ordinary investors, designed to track the S&P 500.

It held every stock in the index in proportion to its market weight. It hired no analysts. It made no predictions. It sought no edge. It simply owned corporate America and waited.

Wall Street called it “Bogle’s Folly.” The mockery was genuine. What serious investor would deliberately settle for average?

The answer, buried in the arithmetic, was: a very rational one.

Active funds were charging, on average, 1% to 1.5% annually in management fees. Add trading costs, tax drag from frequent portfolio turnover, and the spread paid on transactions, and the real cost of active management was routinely 2% or higher per year. That sounds modest. Compounded over decades, it is catastrophic.

On a $100,000 portfolio growing at 7% annually over 30 years:

On a $100,000 portfolio growing at 7% annually over 30 years: a 0.05% index fund leaves you with ~$757,000.
A 1% active fund leaves you with ~$574,000.
A 2% active fund leaves you with ~$432,000.

The difference between the first and last number is $325,000, paid entirely in fees, compounded against you over decades.

The “average” return, captured at near-zero cost, beat the majority of actively managed fund because of arithmetic.

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The Graveyard

To own the market is to survive everything the market does to you.

There is no protection in Bogle’s approach. No analyst to raise cash when conditions deteriorate. No tactical allocation to shift into bonds at the first sign of trouble. When the dot-com bubble burst in 2000, index investors fell with it. When the 2008 financial crisis arrived, broad index funds lost roughly half their value in eighteen months.

Bogle’s entire architecture assumes you will not sell.

The moment you do, rattled by headlines, unable to stomach another month of losses, the mathematical advantage evaporates.

A 40% loss requires a 67% gain just to return to even. Selling at the bottom locks in the loss permanently and converts a temporary decline into a permanent one.

This is the only real skill the strategy demands: the ability to sit still while the world appears to be ending. It sounds easy. During a genuine panic, it is one of the hardest things an investor will ever be asked to do.

The Toolkit

Bogle’s philosophy reduces to three executable principles. They have been dressed up in many names by many commentators. The ideas themselves are deliberately plain, because their power comes from being followed.

Own the whole market, not pieces of it.

The moment you select individual stocks or sectors, you introduce the possibility of being wrong in ways that compound against you. The aggregate market, all of corporate America, all of its earnings, all of its dividends, grows over time because human productivity and commerce grow over time. That growth is yours to capture at near-zero cost. What you pay to capture it is the only variable fully within your control.

Make cost the first criterion, not the last.

Before evaluating any fund’s historical performance, calculate what it costs to own. An active fund returning 9% annually at a 1.2% fee has delivered 7.8% to you. A passive fund returning 8.5% at 0.05% has delivered 8.45%. The passive fund won because it was cheaper. Past performance shifts. Fees are contractual.

Remove yourself from the process.

Automate contributions. Set an asset allocation appropriate to your time horizon. Then do not watch it. The financial media exists to generate attention, not returns. Every analysis that makes you want to act is a cost, in fees, taxes, or mistimed decisions. The correct number of portfolio adjustments made in response to macroeconomic news headlines is, in Bogle’s view, approximately zero.

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The Human Factor

Bogle’s heart was always the problem. He suffered his first heart attack at 31 and would endure two more, plus a cardiac arrest, over the following decades. He lived for years with a pacemaker, acutely aware that his time was limited. In 1996, at 65, he received a heart transplant that granted him twenty-two additional years of uncompromising work.

He used them loudly. And, near the end, in unexpected ways.

Despite founding the firm that made index investing mainstream, Bogle spent his later years as a vocal critic of what index investing had become.

The explosion of exchange-traded index funds, which trade throughout the day like stocks, enabling precisely the speculative behavior he had spent his career fighting, troubled him deeply.

He was not opposed to indexing. He was opposed to trading. An ETF, he argued, was a vehicle designed to help people who couldn’t help themselves do exactly that, wrapped in the philosophy of a strategy that required them not to.

He was, in his final decade, openly at war with his own legacy. The idea had been captured and repackaged by an industry that had never fully understood it. Or, perhaps, had understood it perfectly and simply declined to follow it.

Had Bogle structured Vanguard as a conventional for-profit firm, his personal stake would have been worth tens of billions of dollars. Instead, at his death in January 2019, his net worth was estimated at around $80 million.

A substantial fortune, but a rounding error against what he had deliberately walked away from. He flew coach. He lived in the same modest house for decades. He kept a bagged lunch at his desk.

He once said, with characteristic plainness: “I have had a wonderful life. I have done what I wanted to do, and I have done it on my own terms.”

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The Verdict

Bogle’s philosophy is not a strategy for people who want to feel clever. It offers no stories to tell at dinner, no moments of vindication when a bet pays off, no individual genius to point at. What it offers instead is something rarer: a mathematically grounded approach to not losing to your own costs, your own impatience, and your own overconfidence.

This philosophy rewards you if:

• Your investment horizon is measured in decades, not quarters.

• You are more interested in the near-certainty of a good outcome than the remote possibility of a spectacular one.

• You can watch your portfolio fall 40% without interpreting it as a signal to act.

Walk away if:

• You believe you have an informational or analytical edge over institutional investors with billion-dollar research budgets.

• You need the engagement of active management to stay interested in investing at all.

• You cannot sit still.

The rest is just arithmetic. Bogle spent his life insisting that was enough.

“The greatest enemy of a good plan is the dream of a perfect plan. Stick to the good plan.”
― John C. Bogle

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Alright, let’s get to it!

I have had Nu on my radar for a very long time. If you’ve spent any time studying the legendary investor Nick Sleep, you know his framework of “Scale Economies Shared”, and NU is one example of a business that uses this model.

Scale Economies Shared is the idea that a company can win permanently by relentlessly dropping its unit costs and handing those savings right back to the consumer to lock in terminal loyalty. Costco did it. Amazon did it.

But admiration is one thing; entry price is another.

In a hyper-growth credit story, discipline is the only thing that keeps you from getting blown up.

So I watched, I modeled, and I waited. Recently, the market finally served up a price level I actually quite like: $12.29 per share. So I initiated a decent position.

Now that I have real skin in the game, it’s time to pressure-test the thesis. If you are a shareholder, or thinking about becoming one, you have to get comfortable with the structural tension of this business.

Let’s break down exactly what we are dealing with.

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If You’re In a Rush

• What they do: Nu is a digital financial services juggernaut. They monetize their massive user base through three primary engines: Credit Income ($3,173.3m), Float Income ($1,383.0m), and Fee Income ($759.1m), according to their Q1’26 managerial metrics.

• Why it’s hated: Wall Street looks at Nu and sees a “credit book” first, and a “software-like platform” second. Because of that, every single quarter turns into a tense courtroom trial over credit quality, non-performing loans (NPLs), and risk-adjusted economics.

• What fixes it: Keeping the core flywheel spinning. We want to see Average Revenue Per Active Customer (ARPAC) march higher than its current $15.9, and the Efficiency Ratio stay glued near its incredible 18% mark, all without late-stage delinquencies re-accelerating from the current NPL 90+ rate of 6.5%.

Atomic Position: I currently hold a long position with a cost basis of $12.29 per share. Because of that, you should treat my optimism the same way you’d treat a package carrying a tiny, polite amount of radiation. Do your own homework.

Atomic Take: Nu’s story is a beautiful compounding flywheel that is forced to operate under a harsh credit-cycle spotlight 24 hours a day, 7 days a week.

Falsifier: If the NPL 90+ metric starts trending upward for multiple consecutive quarters from its current 6.5% base, the entire “controlled credit machine” narrative shatters.

The Setup

Nu’s own presentation of their business is almost insultingly tidy.

They show you a beautifully simple equation: take a rapidly growing customer base, monetize them at higher rates over time, run it all on a highly scalable low-cost platform, and watch it translate into massive earnings.

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If you look at the Q1’26 investor deck, they plot it out perfectly:

• Total customers rising to 135 million

• ARPAC climbing to ~$16

• Efficiency ratio dropping down to 18%

• Net income hitting $871 million

On the surface, the quarter was an absolute powerhouse, delivering $871.4 million in managerial Net Income and a scorching 29% Return on Equity (ROE).

But if you’ve owned anything even remotely adjacent to the credit space for more than five minutes, you know how this game works. The ultimate villain in banking isn’t usually “revenue.”

No, the real villain is a lagging indicator that shows up late to the party wearing a trench coat: delinquencies, provisioning, and the brutal timing of cash flows.

This structural reality is exactly why Nu is such a love/hate object in the investing community.

It is a spectacular software platform narrative strapped directly to a traditional lender’s balance sheet. When things go right, that combination creates a legendary compounding engine.

When things hit a bumpy patch, it feels like an anxiety subscription.

The Market, The Bulls, and The Bears

• The Market View: “It’s a nice app with great tech. But credit losses are the ultimate tax on this business model. Eventually, that tax bill is going to go way up.”

• The Bull View: The earnings-generating formula is completely real, and more importantly, it is proving it can travel. Mexico officially reached break-even in Q1’26, proving that the exact same monetization formula can unfold successfully outside of Brazil.

• The Bear View: Fast growth mixed with credit expansion and shifting product mixes is a recipe for disaster. Eventually, a future quarter will hit where the risk-adjusted economics crack, and the stock’s valuation multiple will re-rate violently downward like a boring, traditional bank. Because at the end of the day, that’s what it is.

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This deep dive really boils down to one fundamental question: Does Nu pass the classic Nick Sleep “Scale Economies Shared” sniff test?

In other words, is Nu taking the benefits of its massive scale and reinvesting them directly into better products, lower prices, and a superior user experience to drive even more scale?

Or is it simply a very well-run lender that will always be held back by a permanent credit discount?

Atomic Take: The Q1’26 numbers absolutely shout “platform leverage,” but this thesis only compounds over the long haul if the credit metrics stay incredibly boring while the customer acquisition machine stays incredibly loud.

Falsifier: If the efficiency ratio begins to drift meaningfully above the ~20% band that management has targeted for the year, the “structural low-cost platform” claim starts to look very wobbly.

How the Business Actually Makes Money

Let’s start by looking at what Nu chooses to disclose, because that gives us a direct window into how management thinks about value creation.

They recently introduced a new Managerial P&L framework (which is a company-defined, non-IFRS measure).

They did this to better explain how value is generated across a platform that spans multiple countries and dozens of products. It’s worth noting that standard IFRS remains their official statutory basis, and net income, capital, and cash are fully preserved. But this managerial view helps us see the moving parts clearly.

In these Managerial P&L terms, Nu’s revenue is definitely not some mysterious banking blob. It is a highly distinct, three-engine system. Out of $5,315.5 million in total managerial revenue for Q1’26, the breakdown looks like this:

The Three-Engine Revenue Breakdown (Q1’26)

• Credit Income: $3,173.3m

• Float Income: $1,383.0m

• Fee Income: $759.1m

Total Performance: $5,315.5m

That specific mix matters immensely because it tells you exactly what kind of beast you are underwriting as an investor. If this were a pure credit story, you would be completely hostage to the cost of credit.

But when you have a digital platform that can grow float income and fee income right alongside its credit book, you get a beautiful extra layer of structural resilience. That is, assuming the diversification is real and not just an accounting costume.

Nu’s latest deck explicitly highlights this “fee and float diversification” as a powerful compounding trend, even while noting some typical Q1 seasonality on the credit side. All told, gross profit for the quarter landed at $1,877.7 million.

Now, let’s apply that Nick Sleep/Nomad lens.

“Scale economies shared” means that as the company gets bigger, its cost per unit drops significantly, and the company actively hands a big chunk of those savings back to the customer to lock in their loyalty and keep the loop spinning.

And I think the data points from Nu that track this loop are incredibly compelling:

• ARPAC reached $15.9, while their historical cohort curves show that their most mature customer cohorts have already reached a hefty $30.8 in monthly ARPAC.

• The cost to serve remained rock-solid at just $1.0 per active customer, which stands out as a massive competitive advantage against legacy brick-and-mortar banks.

• The efficiency ratio dropped to 18%, with management explicitly boasting on the earnings call about achieving a record-low efficiency ratio below the 18 percent threshold.

Atomic Take: This is about the cleanest setup for “scale economies shared” you will ever see in the financial sector. You have steadily rising customer revenue, an incredibly low and flat cost-to-serve, and an efficiency ratio that looks completely allergic to gravity.

Falsifier: If ARPAC growth suddenly stalls out while the cost to serve begins climbing north of that $1.0 mark, the compounding flywheel will start looking like a basic treadmill.

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What Went Wrong

Nothing actually “went wrong” this quarter in the catastrophic sense of the phrase. Instead, the anxiety here is entirely structural.

Any business model that is driven by high-growth credit gets judged on two completely different timelines simultaneously:

1. The Fast Timeline: This is the exciting stuff: customer growth, climbing ARPAC, and improving efficiency ratios.

2. The Slow Timeline: This is the quiet, lagging stuff: creeping delinquencies and the heavy burden of provisioning for bad loans.

During Q1’26, the portfolio behaved exactly the way credit portfolios typically behave during the first quarter of the year: early-stage delinquencies ticked upward, while late-stage delinquencies managed not to implode.

Looking directly at the headline metrics from the earnings release, the shift becomes clear:

• NPL 15–90 hit 5.0%, marking a noticeable step up from the 4.1% we saw in Q4’25.

• NPL 90+ landed at 6.5%, which was actually down a tiny bit on a sequential basis.

Because of this mix shift and credit expansion, the company’s risk-adjusted economics took a step backward. The Risk-Adjusted Net Interest Margin (NIM) landed at 9.5%, down from the 10.5% recorded in the previous quarter.

Management’s core defense across their call and investor materials can be summarized simply: regular seasonal trends, combined with aggressive growth and product mix changes, naturally required them to book higher provisions. They explicitly stated that they do not view this asset behavior as a structural degradation of the portfolio.

Saying “asset quality isn’t degrading” can be factually accurate in a narrow sense because late-stage NPLs remained stable.

At the exact same time, saying “risk-adjusted profitability got worse this quarter” is also 100% true because the risk-adjusted NIM compressed by a full percentage point.

Those two realities do not contradict each other.

Instead, they serve as a loud, clear warning label that your true margin of safety in an investment like Nu is strict, unyielding credit discipline.

Atomic Take: Q1 didn’t break the fundamental investment thesis for Nu by any means. What it did was give everyone a sharp reminder that this high-flying platform flywheel is still firmly attached to a credit engine that suffers real, seasonal bruises.

Falsifier: If the NPL 90+ metric begins climbing meaningfully past 6.5% while the risk-adjusted NIM continues to compress below 9.5%, then blaming “seasonality” will officially turn into corporate denial, in my view.

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Rebound Catalysts

When you are looking for things to go right with a business, you need testable milestones.

Let’s look at the actual gauges on the dashboard that will tell us if this machine is accelerating safely.

#1. Mexico Becomes a Repeatable Profit Machine

Nu tells us that Mexico officially crossed 15 million customers and reached break-even in Q1’26, proving that their signature “earnings-generating formula” can work outside of Brazil.

But here is the common-sense test: hitting zero once for a single quarter doesn’t prove a trend. The real test is whether Mexico can transform from an exciting “inflection point” into a massive, steady profit contributor to the group, all without dragging down that beautiful consolidated efficiency ratio.

#2. Artificial Intelligence Shows Up in Credit Outcomes, Not Just Productivity Anecdotes

Nu loves to talk about its multi-phase AI transformation, and to be fair, they have some fantastic productivity metrics to show for it. They claim engineering throughput is up 50% YoY and testing cycles are running 90% faster.

They also state that their AI Private Banker now serves over 15 million monthly active users, and their proprietary “NuFormer” model is fully live in production, making credit card decisions in Brazil and Mexico, as well as handling unsecured lending in Brazil.

If their AI is truly a competitive advantage in underwriting, it shouldn’t just stay a nice tech story. It has to show up in the numbers where it matters: credit limits growing safely with extreme resilience.

I want to see their risk-adjusted economics stabilize and hold firm even as the total loan book expands.

#3. ARPAC Keeps Climbing as Cohorts Mature

When you look at Nu’s customer cohort charts, management is essentially telling you: “Be patient, because patience gets paid.” While their headline ARPAC sits at $15.9 for Q1’26, their oldest, most mature customer cohorts have already climbed to a massive $30.8 in monthly ARPAC.

As long as new customers follow that exact same upward trajectory over time, the top-line engine takes care of itself.

#4. Efficiency Stays Within Guardrails While Launching New Bets

Nu is currently laying the groundwork for a U.S. expansion, but they are framing it as a highly disciplined, strictly capped experiment. They expect the maximum investment impact to remain below 100 bps on the consolidated efficiency ratio across both 2026 and 2027.

Management explicitly notes that this investment will be contained within the general ~20% efficiency range they have communicated for the full year.

The investor deck even uses the phrase “bounded cost to enter,” meaning they have intentionally built a roof over their potential downside.

Atomic Take: The perfect script for Nu from here is beautifully simple: we want the business to be incredibly boring in the places that cause sleepless nights (NPLs and efficiency) and incredibly loud in the places that create massive wealth (ARPAC growth and Mexican profitability).

Falsifier: If the consolidated efficiency ratio begins to meaningfully degrade despite this “<100 bps” U.S. spending cap, the narrative that they can fund major new expansions without breaking the core margin machine will face—and fail—its very first live test.

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Financial Quality Rubric (Score: 1 to 5)

Let’s look at this business through a classic, no-nonsense financial checklist to see exactly what we are buying.

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Every IPO, at its core, is a theatrical performance.

There is a script. There is a cast. There are producers who have been working behind the scenes for years. And then there is an opening night, when the curtain finally rises and the audience, that’s you, buys a ticket at the box office and takes a seat in the dark.

What I find fascinating, and what I think most coverage gets badly wrong, is that nobody tells you that by the time you walk through the doors, everyone who actually matters has already seen the dress rehearsal. The critics got advance screenings. The investors who will make the most money were in the room when the script was still being written.

You? You’re buying a ticket on opening night. At full price. From the box office. For a show the cast is very motivated to sell you.

The IPO process is structurally tilted away from you.

And right now, with SpaceX, OpenAI, and Anthropic all about to hit public markets within months of each other, I think it’s worth sitting down and talking through exactly what kind of theatre you’re about to walk into.

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First, Let’s Talk About What’s on the Marquee

On May 20, 2026, SpaceX filed its IPO prospectus with the SEC. The company is expected to trade on Nasdaq under the ticker SPCX, with trading possible as early as June 12, depending on the final roadshow and pricing process.

The reported valuation target is around $1.75 trillion. On listing day, that would not quite put SpaceX beside Apple, Microsoft and Nvidia at the very top of the market, but it would put it in a ridiculous neighbourhood: potentially the seventh-most valuable public company in America.

To put that in perspective: the entire global IPO market raised $42.6 billion in Q1 2026. Even if these companies only sell a small slice of themselves, the proceeds could dwarf what the normal IPO market does in an ordinary quarter.

Then comes OpenAI, the company behind ChatGPT, a product now used by more than 900 million people every week. It is reportedly preparing for a possible public listing as early as September.

Then Anthropic, the makers of Claude, which is also reportedly circling the public markets with valuation talk somewhere near the trillion-dollar edge.

Put the three together and, if the reported targets hold, you are looking at well over $3 trillion in market value trying to enter public markets in less than a year.

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The Production You’re Joining (And Who Runs It)

Here is how an IPO actually works:

A private company, let’s use SpaceX as our example, hires investment banks. Goldman Sachs. Morgan Stanley. You know, the usual names.

These banks take the company on a “roadshow,” which is the industry’s polite word for a travelling sales performance. The “cast and producers” sit across from the world’s largest pension funds, sovereign wealth funds, and hedge funds. Together, they set the price. Together, they decide who gets seats.

Then the stock lists on an exchange, and you, an individual investor sitting at home, get to buy whatever’s left in the general admission section.

Ask yourself honestly: at which point in that production do you think the pricing most favors the general audience?

“Anytime anybody offers you anything with a big commission and a 200-page prospectus, don’t buy it. Occasionally, you’ll be wrong if you adopt Munger’s Rule. However, over a lifetime, you’ll be a long way ahead, and you will miss a lot of unhappy experiences.”

Charlie Munger, Vice Chairman, Berkshire Hathaway

A SpaceX S-1 prospectus is, almost to the letter, that 200-page programme. And much like a real theatre programme, it was written by the production’s own lawyers, it tells you what they want you to know, and it costs you nothing because the real price comes later.

The company and its bankers choose the exact moment to go public. They pick the moment most favorable to them: when sentiment is high, when the story is cleanest, when the numbers look best. They do not ring a bell and announce that now would be a great time for retail investors to buy their shares at a fair price.

The curtain goes up when the production company is ready. Full stop.

What the Historical Reviews Actually Say

Alright, let’s talk data, because the data is fascinating and I find it consistently ignored in the excitement around big IPOs.

Academic research on IPOs has found the same uncomfortable pattern, over and over: the opening-night applause is often much better than the long run.

The first-day pop, that exciting percentage you see on the news, has historically averaged somewhere around the high teens. That is the part everyone talks about. That is the champagne. That is the photo outside the theatre.

But over longer periods, IPOs as a group have tended to disappoint against the boring old market index sitting quietly in the background.

I think about this the way critics talk about opening-night reviews versus the longer run. Shows get standing ovations on opening night all the time. It takes a few weeks to know whether it’s actually any good.

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Here is the detail that really stings. The opening-night pop that makes the headlines? The one you see screaming across financial Twitter at 9:35am? I want you to understand that you almost certainly cannot access it at that price.

The best IPO allocations, the shares sold at the official offering price before the market opens, are reserved for the banks’ most valuable institutional clients. Research has shown this clearly: the IPOs with poor opening-night performance are easy to get allocations for. The ones with strong performance are quietly distributed to hedge funds and pension managers before retail investors can act.

By the time you see the pop, you’re watching a performance that opened without you. The people selling into that excitement are the ones who got in at dress rehearsal. They’ve already seen the show. They’re selling you their seats on the way out.

“I think buying new offerings during hot periods in the market is not anything that the average person should think about at all.”

Warren Buffett, Chairman, Berkshire Hathaway

Buffett has missed Amazon. He’s missed Google. He acknowledges both. His view is that owning great companies is one of the best things you can do with money. The IPO moment specifically is when the structural odds tilt hardest against the retail investor, and he has simply refused to play on those terms for seventy years.

It’s hard to argue with seventy years.

Now Let’s Read SpaceX’s Programme

Here is where I have to be honest: SpaceX is a legitimately extraordinary company.

It has done things that were supposed to be impossible. Reusable orbital rockets. The largest satellite constellation in human history. NASA contracts that previously went to companies ten times its size. The Falcon 9 launch cadence is something the aerospace industry still struggles to comprehend.

The S-1 reveals, for the first time, what the production actually looks like backstage. And backstage tells two very different stories.

The front-of-house story: SpaceX generated $18.7 billion in revenue in 2025, up sharply from the year before. On an adjusted EBITDA basis, the company produced about $6.6 billion in profit. Starlink, its satellite internet division, is a dominant machine in low-earth-orbit broadband, serving parts of the world that traditional networks either cannot reach or cannot reach profitably.

The backstage story: despite that adjusted profit, SpaceX posted a GAAP net loss of about $4.9 billion for full-year 2025. And in Q1 2026 alone, it lost roughly $4.3 billion.

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That gap between “adjusted EBITDA profit” and “actual loss” is not a rounding error. It is the show behind the show: depreciation, stock-based compensation, enormous capital spending, and, most unusually, the cost of folding Elon Musk’s AI empire into the SpaceX story.

Let that sit for a moment. When you buy SpaceX, you are not only buying Falcon 9, Starship and Starlink. You are also buying exposure to Grok, X, and Musk’s attempt to build an AI platform that competes, in one way or another, with the other two productions coming to market: OpenAI and Anthropic.

It makes the investment considerably harder to explain.

Then there is the governance question. I want to show this clearly, because it tends to get lost in the excitement about rockets and Mars colonies.

If Musk wants SpaceX to lean harder into AI infrastructure, Mars, Starlink, Grok, or some future project none of us has heard of yet, public shareholders will not be sitting around the table with a meaningful vote. They will own a piece of the production, but not the stage directions.

If he wakes up one morning and decides SpaceX should acquire X again, he can. You would own a piece of the production and have no say in the casting, the venue, or the running time.

In any meaningful governance sense, you’re a ticket holder. The production company runs the show.

The Bit the Programme Leaves Out

Peter Lynch, who ran Fidelity’s Magellan Fund to a 29% average annual return over 13 years, had a test for every investment he considered:

“If you can’t explain to an 11-year-old in two minutes or less why you own the stock, you shouldn’t own it.”

Peter Lynch, former manager, Fidelity Magellan Fund

I want you to try explaining the SpaceX investment thesis to an 11-year-old.

“It’s a rocket company, but also a satellite internet company, and now partly an AI infrastructure company, and it has exposure to Grok and X, and it may be valued around $1.75 trillion even though it just lost more than $4 billion in a single quarter, and the founder controls about 85% of the votes, and he also runs Tesla, X, xAI and Neuralink...”

You might lose the kid at “satellite internet.” Lynch’s point was never about simplicity for its own sake. It was that if you can’t articulate the thesis clearly, you probably don’t understand it clearly. And the IPO process is specifically designed to make you feel like you understand something you don’t have the backstage information to properly evaluate.

Here is the part I want you to really absorb: the information gap in IPOs is structural and deliberate. The insiders, founders, early employees, and venture capitalists, have lived with this company for years. They know the actual revenue trajectory. The real customer churn rate. They know the competitive threats that didn’t make it into the programme.

Every one of them is selling to you. The banks advising the deal earn their fees from the company, not from you. The analysts covering the IPO work for those same banks.

You, sitting at home reading a prospectus that runs hundreds of pages, with a deadline, are being asked to out-analyse all of that in the two-week roadshow window before opening night.

“If you’ve been playing poker for half an hour and you still don’t know who the patsy is, you’re the patsy.”

Warren Buffett

In the IPO game, the patsy has a name. It’s the retail investor who buys on opening night, reads the rave reviews in the financial press, and assumes they’re getting the same deal as the institutions who got tickets six months ago.

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So, What Will I Do?

I want to be clear: this article stops well short of calling these bad companies.

They could be extraordinary ones.

Starlink is a dominant business in low-earth-orbit satellite broadband, especially in places where terrestrial internet is weak, expensive or simply unavailable. Falcon 9 has an unmatched launch cadence. Anthropic is reportedly growing fast. OpenAI has more than 900 million weekly ChatGPT users and a product embedded in the workflows of students, developers, lawyers, founders, analysts and probably half the people pretending they are not using it.

These are remarkable performances.

The technology is real. The moats are real. The question I keep coming back to is the price at which you buy, and the moment at which you buy it.

Here is what I will do: grab some popcorn, read some Buffett and Munger, and wait for the reviews.

Every great production has a run that extends well past opening night. The lock-up expiration, often around 180 days after an IPO, is one of the first moments when early employees and investors may be allowed to sell more freely.

That does not guarantee a crash. Nothing in markets is that neat.

But it does change the supply of shares. It changes the cast of sellers. And it gives you something opening night does not: more information.

The first few earnings reports, stripped of the roadshow energy and the carefully rehearsed narrative, tell you what the business actually looks like when the lights come up on a Tuesday afternoon in a half-empty theatre.

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The Show Will Go On

We are living through a genuinely remarkable season. The companies that may come public in this cycle, a rocket company trying to make Mars real, the laboratory that helped turn AI into a consumer product, and the teams building the language models now reshaping work, are the kind of productions that define eras.

I keep coming back to Netscape.

The Netscape IPO in 1995 helped launch the internet era. The stock exploded on opening day. The phrase “Netscape moment” became shorthand for the arrival of a new technological age.

And yet the lesson was never simply “buy the IPO.”

The internet changed everything. Netscape itself did not become the enduring winner. The show ran for thirty years and is still running, but the money was not made by blindly buying every opening night. It was made by understanding which parts of the new world would actually endure.

The companies are real. The technology is real. The performances will be extraordinary.

“The only question that matters is at what price you’re being asked to buy a seat.”

Right now, you’re being asked to believe in SpaceX at a valuation of roughly $1.75 trillion, while it is losing billions under GAAP accounting, in a production where the lead actor controls the stage directions and public shareholders have very little say in the script.

What I might do: wait for the reviews.

Let the opening-night energy settle. Let the first earnings reports arrive. Let the lock-up calendar do what lock-up calendars do. The show will still be on. The seats may be better value. And you’ll know, finally, whether the production is as good as the programme promises.

One more thing. Bruce Hornsby's 'The Show Goes On' has been on repeat in my house this week. Make of that what you will.

Disclaimer:
This is an opinion piece. It is not financial advice. Think of it as the kind of conversation a well-read friend would share over a beer, someone with no financial interest in your decision. Make your own choices. Read the S-1. Speak with a licensed financial adviser. And remember Munger’s Rule: if it comes with a 200-page programme and a large commission, the curtain may not rise the way they promised.

I actually got the idea for this installment of The Money Mind from a comment a paid subscriber left on a recent portfolio update. They laid out a beautifully detailed, incredibly sharp bear case against one of my core holdings. It was the kind of feedback you can’t ignore; analytically tight and logically sound.

So… I couldn’t do much else but acknowledge his brilliant perspective, but the exchange reminded me of a fundamental truth about markets and life: the world is far too complex to determine with absolute accuracy.

In the long run, it is much healthier, and infinitely more profitable, to focus on being directionally correct.

And nobody embodies that truth better than the man featured in this issue of Money Mind.

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William Green spent years interviewing the world’s greatest investors for his book Richer, Wiser, Happier. He expected to find ruthless optimizers. What he found instead, again and again, was something far more disarming: people who had made peace with uncertainty, and built their entire advantage around that peace.

Tom Gayner is perhaps the purest expression of that finding.

Green profiles him not primarily as a stock-picker, but as a man who has constructed an entire life around a single, quietly radical idea: that you don’t need to be right. You just need to be directionally right. And that distinction, compounded over decades, turns out to be worth billions.

Who is Tom Gayner?

Gayner is the CEO and Chief Investment Officer of Markel Corporation, a specialty insurance company based in Richmond, Virginia. To call it unglamorous would be generous.

Markel doesn’t make headlines. It doesn’t disrupt anything. It insures niche, hard-to-price risks (collectible cars, summer camps, horse farms) and it has done so, profitably and quietly, for decades.

Gayner joined Markel in 1990 as an investment officer, trained as a CPA. He arrived with a ledger mindset: systematic, methodical, allergic to sloppiness. Over time, he became the architect of its entire capital philosophy.

Today Markel is often called a “Baby Berkshire”, a comparison earned through a genuine philosophical kinship with how Buffett thinks about business and time.

His personal track record across decades is one of the most consistent in institutional investing.

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The Accident of Float

To understand Gayner’s edge, you need to understand one structural fact about insurance companies: they collect premiums before they pay claims.

The money sitting in between (sometimes for years) is called the float. It belongs, technically, to future claimants. But until those claims arrive, it can be invested.

Most insurance companies invest their float conservatively, in bonds. Gayner invests Markel’s float in equities, and holds them for years, sometimes decades. Because the float is large, sticky, and doesn’t demand sudden redemption, he never has to sell into a bad market.

He simply waits.

This is a structural advantage most individual investors can’t replicate. But the philosophy underneath it, the willingness to sit still, to resist the pressure to act, is entirely transferable.

The Four Pillars

Gayner filters the entire universe of publicly traded companies through four questions. They are almost aggressively simple:

1. Is the business highly profitable, with strong returns on capital and low debt?

Not flashy revenue growth. Return on capital. He wants businesses that make more money than they consume.

2. Does management have both ability and integrity?

He treats these as inseparable. A brilliant but dishonest management team is worse than useless — they’ll find creative ways to enrich themselves at shareholders’ expense.

3. Are there reinvestment opportunities within the business?

A great business that can’t grow is a melting ice cube. He wants companies that can plow their own profits back into further growth, compounding internally.

4. Is the price fair?

Not cheap. Fair. He’s not hunting for distressed bargains. He’s willing to pay a reasonable price for an exceptional business, and let time do the work.

When all four align, he buys. Then, characteristically, he does very little else.

“Directionally Correct”

In Richer, Wiser, Happier, Green captures something essential about Gayner’s psychology: he is profoundly unbothered by being wrong in the short term, because he has thought carefully about what kind of wrong he can tolerate.

Gayner once described wanting to return to his college weight. His plan wasn’t a diet. It was to lose one pound a year for ten years.

Excruciatingly slow.

Entirely sustainable.

Completely successful.

This is the Gayner framework in miniature. He doesn’t ask: is this the perfect trade at the perfect price on the perfect day? He asks: is this the right direction? If the answer is yes, he acts. Then he waits. Then he compounds.

Green’s broader argument in the book is that the investors who survive and thrive across long periods share a particular kind of temperament; what he calls equanimity. In other words, the ability to remain calm when the crowd panics, and to resist action when action is not warranted. Gayner is his clearest example.

This runs against everything Wall Street rewards. Financial culture prizes speed, activity, decisiveness. Gayner prizes stillness. He’s made a fortune from it.

The Markel Style

What makes Gayner unusual even among patient, value-oriented investors is that he refuses to separate his investment philosophy from his values as a person and an employer.

Markel operates according to something called the Markel Style, a document that has guided the company’s culture for decades. Its logic inverts the standard corporate hierarchy: customers win first, employees win second, shareholders win third.

If you genuinely serve the first two, shareholder returns compound naturally as a byproduct. Exploit either group and the whole machine corrodes.

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The Markel Ventures Family

This is where the Markel Style becomes most visible. Rather than owning a collection of abstract equity stakes, Gayner has assembled what he calls a “family of companies” — unglamorous, capital-efficient businesses run by people he genuinely trusts, operating with a high degree of autonomy under a shared set of values.

The portfolio spans industries that couldn’t feel further apart. And that’s precisely the point.

A few that currently call Markel home:

Markel Food Group (AMF Bakery Systems)

If you’ve eaten a fast-food hamburger bun, there’s a reasonable chance AMF’s equipment made it.

The company manufactures industrial bakery equipment used by customers to produce billions of buns, crackers, cookies, and pizzas annually. It was Gayner’s very first Ventures acquisition in 2005. Chosen, he said, partly because bread has been around for thousands of years and seemed unlikely to be technologically disrupted.

Costa Farms

The largest producer of ornamental plants in the world, founded in 1961 by Jose Costa and now a third-generation family business stretching over 4,000 acres globally.

This is Gayner’s philosophy made literal: a business so unglamorous it sells houseplants, compounding quietly for generations.

Brahmin

A creator of fashion leather handbags with significant wholesale distribution and a growing direct-to-consumer business, founded in 1982. Gayner said when Markel and Brahmin were introduced, it was immediately clear they shared the same business vision and culture.

Buckner HeavyLift Cranes

A provider of heavylift crawler cranes serving wind energy, data centers, semiconductor manufacturing, nuclear energy, and space markets.

Boring by any surface reading. Structurally essential to almost every industry building the future.

Havco Wood Products

Manufactures laminated oak and composite wood flooring for truck trailers, intermodal containers, and truck bodies. Floor panels for freight trucks. It couldn’t sound less exciting. It also isn’t going anywhere.

Others:

• CapTech: An IT consulting firm.

• PartnerMD: A concierge primary care and executive health company.

• VSC Fire & Security: Fire suppression systems.

• Ellicott Dredges: Industrial dredging equipment.

• Metromont: Precast concrete.

• Cottrell: Over-the-road car haulers.

• Lansing Building Products: Building materials distribution.

• Weldship: Industrial and specialty gas storage vessels.

Read that list aloud and you get a picture of what Gayner means by “a diverse and resilient family.”

Experts in bakery equipment, car haulers, IT consulting, medicine, industrial gas storage, ornamental plants, precast concrete, construction, fire protection, furniture, dredges, leather goods, trailer flooring, building products distribution. Not a single one of them will ever trend on social media.

That’s the whole idea. Every acquisition goes through the same four-part test: strong returns on capital with low debt; management with equal measures of talent and integrity; reinvestment opportunities with capital discipline; and a fair price. The industry is almost irrelevant.

The character of the business and the people running it are everything.

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Who this is for, and who it isn’t

Gayner’s approach will bore you during bull markets. When meme stocks are doubling overnight and AI darlings are soaring, a portfolio of unglamorous, capital-efficient businesses will feel like a punishment.

You will be mocked, at least implicitly, by your brokerage app’s performance tab.

That is the price of admission. If you can pay it — if you can hold through that grinding underperformance without flinching — the math of compounding will eventually reward you in ways that the hype cycle cannot.

If you can’t, that’s worth knowing too. The first thing Gayner’s philosophy asks of you is honesty about your own temperament.

Green’s book is worth reading in full for exactly this reason. Its central argument is that the best investors are not the ones with the best models; they are the ones who know themselves clearly enough to build a strategy they can actually sustain.

Three things you can take from Gayner today

• The 48-hour rule. Before any trade, wait two days. Then ask: is this driven by a real change in the business fundamentals, or by anxiety and the need to feel like you’re doing something? Most of the time, it’s the latter.

• Apply the four pillars ruthlessly. Not as a checklist to rationalize a decision you’ve already made. No, use this as a genuine filter. If a holding fails any one of the four, ask whether you’d buy it fresh today. If the answer is no, that’s information.

• Think about direction, not precision. You will not call the top. You will not call the bottom. Neither will anyone else, consistently. The question is whether the trajectory of your portfolio — its quality, its time horizon, its underlying businesses — is pointing the right way.

Richer, Wiser, Happier by William Green is one of the most honest books written about what great investing actually looks like from the inside. If Gayner’s thinking resonates with you, I highly recommend you give the book a read.

Hey everyone,

There’s a version of investing that looks productive: checking prices daily, reacting to earnings drops, rotating into whatever narrative is working this week.

And then there’s the version that actually builds wealth, which mostly looks like doing nothing while trusting that the businesses you own are quietly compounding on your behalf.

The recent SaaS selloff and AI panic have created exactly the kind of environment where these two versions diverge. When macro narratives shift, the market sells first and asks questions later. Great businesses get priced as if their terminal value has evaporated overnight. For a patient investor, that indiscriminate selling is an opportunity.

This month I’m running five positions and watching three more closely.

1. A company with proven switching cost moat embedded in European labour law, sitting 50% below its peak while the market sleeps on a regulatory catalyst I expect to matter a great deal by 2028.

2. A serial acquirer of software micro-monopolies, near multi-year lows, compounding through a process that cannot be replicated by capital alone.

3. A professional information giant the AI narrative has cut in half — where I believe the market is confusing adjacent to AI with threatened by AI.

4. The clearest real-world example I have found of the framework Nick Sleep used to identify Amazon and Costco before they became obvious.

5. And a niche UK software company where the management compensation structure, when I share it, tends to genuinely surprise people.

On the watchlist: three businesses I want to own but won’t buy at current prices. One at €35. One at $130, with $6.5 billion in net cash and a 50% drawdown from the all-time high. And one I considered over a position I did buy this month. the business quality is arguably higher, but at today’s price I’d be paying nearly three times as much per dollar of earnings.

The names and full reasoning are below:

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As I mentioned, I want you who’ve been in ‘the bunker’ since the beginning to get the best deal. Today, that Founding Member tier is officially open.

This is how pricing will work:

1. The first 35 subs will get everything for $99 per year (update: 35/35 spots taken). To sweeten this deal even further, these will be grandfathered at today’s level.

2. The price for an annual subscription is $199 after this.

3. Then, it will increase to $350 per year once we cross 100 paid subscribers.

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What changes when you upgrade

Just to reiterate: Money Mind, Simple Truths, and Titan Test stay free. All the deep dives published up to this point stay free.

The paid tier is a proper home for the work that goes deepest. By upgrading, you get exclusive access to:

• All upcoming Deep Dives & Valuation Teardowns: The comprehensive work that takes a full weekend or more to build.

• Forensic Balance Sheet Analysis: Looking under the hood to find what others miss.

• The Live Multibagger Index: Tracking the highest-signal opportunities in real-time.

• My Portfolio & Portfolio Moves: See exactly how I allocate capital.

• My watchlists: See what companies are currently in my investing universe. Watchlists are split into founder-led, Nordic quality, 100-bagger potential companies, and more.

• FINS: Earnings numbers broken down in an easy-to-understand way.

You all have helped build the highest-signal investing community I’ve been part of. If you value the models, the pushback, and the honest research we’ve shared over the last few months, this offer is for you.

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Thank you to everyone who has already stepped up to support the work. I don’t take it lightly.

Back to work.

— Rob

When I started Atomic Moat back in December last year, the goal was simple: build a research process I could trust, and share it honestly. No noise, no engagement bait, no lazy hot takes. Just the work.

What I didn’t expect was how many of you would show up for exactly that. Over 1,400 of you now. I get replies with your own models, pushback on my assumptions, and the occasional catch I missed entirely. This is the highest-signal investing community I’ve been part of. That’s on you, and I don’t take it lightly.

So before anything else: thank you. Seriously.

Where Atomic Moat is heading

I’m turning on paid subscriptions.

Let me be completely straight about what that means, and what it doesn’t.

Everything you’ve been reading (Money Mind, Simple Truths, Titan Test) stays free. Always.

The paid tier exists because the research has outgrown what I can sustain as a side project. Simple as that.

Every deep dive that’s already been published stays free. If you’ve saved something, shared it, or want to go back to it, it’s yours. The paywall only applies to what comes next.

What it adds is a proper home for the work that goes deepest: full valuation teardowns, forensic balance sheet analysis, and the live Multibagger Index dashboard. The stuff that takes a full weekend to build and deserves more than a footnote.

What’s coming next

In one week I’m opening a founding member tier.

A limited number of spots at $99/year, locked in permanently, no matter what the price becomes later. Those of you who have already pledged higher amounts than this will also get this deal.

If you’ve been here a while, if you open these posts, if Atomic Moat is part of how you think about investing: that offer is for you.

I want the people who’ve been in the bunker since the beginning to get the best deal.

Until then, nothing changes. The next post lands in your inbox exactly as it always has.

Back to work.

— Rob

A colleague has been talking about a company called AST SpaceMobile for months.

Space-based cellular broadband. Direct-to-device. Governments involved. Verizon. 50+ mobile network operators. Nearly 3 billion potential subscribers. A monopolistic position in the making. 20-30x by 2030.

He speaks about it with the fluency of someone who has done serious work.

I recognize that fluency. I have had it myself, on other ideas, at other times.

The confidence that comes from absorbing a compelling thesis is almost indistinguishable from the confidence that comes from actually doing the work.

So I asked him four questions.

What is the current dilution tempo? What does the cash burn look like relative to the cash position? What is SBC as a percentage of revenue? And — specifically — why do the short sellers have it wrong?

Silence.

Not approximately. Not directionally. Not at all.

He had the destination. He did not have any of the map.

So I went and found the answers myself.

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Around $37 billion market cap. $71 million in revenue. $342 million net loss in 2025. $363 million in operating cash burn in a single quarter. Multiple senior executives — President, CFO, COO, CTO — selling hundreds of thousands of shares in the months prior, with no meaningful insider buying on the other side.

And a race against SpaceX, which has more capital, more launches, and more satellites already in orbit.

The short thesis is not a bombshell. There is no fraud allegation, no regulatory smoking gun. It is simply: the valuation is enormous, the losses are real, the execution risk is significant, and the entire thesis requires a sequence of engineering milestones all going right simultaneously against a better-capitalised competitor.

I presented this to my colleague.

His response:

And I have been thinking about that response since.

Not as a judgment on him, but as a mirror.

Because… where do I show the same kind of behavior?

When contradicting evidence arrives and we respond by doubling down, something specific is happening. We are not evaluating information. Instead we are more likely to defend the story. The short sellers become confirmation of a squeeze opportunity, the losses become the price of a revolution, the insider selling becomes noise.

Every piece of contrary evidence gets reprocessed as support.

This is the backfire effect. Contradicting evidence does not update the model. It reinforces it.

And the reason it happens is not stupidity. It happens because we outsourced the work somewhere along the way, and absorbed a conclusion from someone we trust, without acquiring the reasoning that produced it. When that conclusion is challenged, we have nothing to defend it with except the conclusion itself.

We have all done this. The question is whether we notice it when we do.

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I know my own version.

For a period, my portfolio looked different every week. I would spend days building conviction in a company. Reading the annual reports, running the numbers, convincing myself I understood the moat, and then sell it two weeks later because the price moved against me, or because I read something unsettling, or simply because doubt crept in overnight.

I bought companies I loved on a Tuesday and questioned on a Thursday. I called it being responsive. It was something else.

It was the same problem in a different costume. My colleague holds a narrative too tightly to update it. I held my own conclusions too loosely to trust them. Both of us, for the same underlying reason: we had not done enough of the real work to know, with genuine conviction, what we owned and why.

One person doubles down, the other keeps rotating. But they share a common origin: borrowed confidence. My colleague borrowed his from a few voices on X. I borrowed mine from the last thing I read that was more compelling than my own reasoning.

Real conviction is the kind that survives a bad week, a negative article, and a price drop. It does not come from a thesis you absorbed. It comes from work you cannot hand to someone else.

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Which brings me back to the question I started with.

What my colleague has is not an investment thesis. It is a story with a price target attached.

And I do think the story is genuinely compelling.

Space connectivity is real. The technology works. The contracts are real. It may even be that the 20-30x call proves correct. I cannot rule that out, and I want to be honest about that.

But here is what I do know: he cannot tell you why the short sellers are wrong. He cannot tell you what happens to the thesis if the next launch fails. He cannot tell you at what cash burn rate the dilution becomes thesis-breaking rather than manageable.

So when the story hits turbulence (and all stories do) there will be no framework for evaluating whether the thesis is broken or merely delayed. The result will be a decision made on feeling, at exactly the moment when feeling is least reliable.

Not from volatility. Not from short sellers. Not from macro.

From not knowing.

The most dangerous form of not knowing is not knowing that you do not know. And the “that’s it?!” response is its signature, because someone who genuinely understood the risk would not dismiss the short thesis in four words. They would engage with it. Even if they ultimately disagreed.

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I am not in ASTS. Not because I am certain it fails, but because I cannot get inside the circle of competence fast enough to evaluate whether the execution risk is adequately priced at this valuation. The framework I use says: when you cannot answer that question, the correct response is to pass.

There are businesses I can evaluate. There are businesses whose earnings in ten years I can describe with something approaching confidence. A pre-profit satellite constellation racing SpaceX to commercial scale is not one of them.

My colleague may make a lot of money. That outcome is genuinely possible. But a good outcome does not validate the process that produced it. The nut does not prove the squirrel could see.

The question I try to ask now, before committing capital to anything, including the ideas I am most excited about:

If I cannot do that, I am not really holding a position. I am holding someone else’s research and conviction.

That distinction is worth sitting with.

Especially on the ideas that feel most certain.

If you read the Thesis Brief, you know the business. You know the flywheel, you know the Estonian tax shock, you know that a 78% EBITDA margin on a classifieds portfolio is genuinely extraordinary. You know the thesis.

This piece goes underneath it.

I want to be upfront about something before we start. I bought a position in BCG after writing the Thesis Brief. But by the time I finished this Deep Dive, I had sold it.

Not because the business disappointed me. The business is everything the Brief said it was, and more. But going through every corner of a company sometimes teaches you something the headline numbers cannot.

It’s about what you are actually paying, and about what you are taking on that does not show up in any financial model.

That lesson is in here, in this deep dive. It comes near the end. I think it is worth the walk to get there.

In this deep dive we are going to:

• look at each of BCG’s four segments individually, not just the revenue number but what is actually driving it and whether it sustains.

• look at the two people running this business and whether they have earned the trust their shareholders are placing in them.

• examine the one acquisition BCG has made and what it says about their capital discipline.

• build the valuation from scratch, assumption by assumption, rather than just quoting a range.

(Put this on listen. It is built for the walk, the commute, and the gym.)

Let’s get into it.

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The four segments, one at a time

BCG reports four business lines:

1. Auto

2. Real Estate

3. Jobs and Services

4. Generalist

Together they produced €44.8m in revenue in the first half of BCG’s 2026 financial year — the six months to the end of October 2025.

But the aggregate number hides something interesting.

Three of the four segments are telling a story of genuine momentum. The fourth is telling a very different story, and understanding the difference is the key to understanding whether this thesis holds.

Real Estate

Let’s start with Real Estate, because Real Estate is where BCG is doing something that deserves more attention than it has received.

In the six months to October 2025, Real Estate revenue was €13.2m. That is up 20% from the year before. Twenty percent revenue growth from a business that already dominates its market. The interesting part is where that growth came from. It was not just price increases, though there were price increases.

The number of real estate brokers paying BCG a monthly subscription grew 4%. The monthly fee each broker pays (the ARPU) grew 16%. And on the consumer side, private sellers paying per listing saw their per-listing yield increase 27%.

Three levers pulling in the same direction at the same time. That does not happen by accident.

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What is driving it is a combination of two things. The first is the Baltic real estate market itself, which is genuinely hot right now. Real estate transactions across Lithuania, Estonia, and Latvia grew 7% in the period. Average apartment prices in the three capital cities are up 4%.

When the underlying market is active, brokers are busier, developers are more willing to pay for visibility, and private sellers are more motivated to list at a premium tier because faster sales justify the cost. BCG benefits from a healthy market.

But the second driver is more interesting and more durable. BCG has been deepening the Real Estate product in ways that are changing the relationship between the platform and its professional users. Property Price Compass, the tool that integrates national land registry transaction data with listing history to produce a professional pricing report, was introduced at Aruodas.lt in Lithuania over the last two years.

It is now something broker clients expect. At Untu.lt, the recently acquired platform, agents are handling leads through an AI-assisted call tracking service that logs conversations, suggests follow-up actions, and gives brokers visibility into what happens after a lead is acquired.

These are not cosmetic features. They are workflow tools. And workflow tools create a completely different switching cost profile than listing services. A broker who uses Property Price Compass at every vendor meeting cannot easily switch to a competitor platform without losing the tool her clients have come to expect. BCG is not just the place where listings happen. It is becoming the software layer through which Baltic real estate professionals run their business.

The honest question to ask about Real Estate is whether this growth is repeatable.

The market tailwind (active transactions, rising prices) could cool. Interest rates in the Baltics have been falling, which has supported the market, but that tailwind is not permanent. And the ARPU expansion of 16% reflects pricing changes implemented in September and October 2024.

Those changes have now fully annualised. The next set of pricing changes was implemented in September and October 2025, and they have not yet fully fed through. So the near-term revenue picture for Real Estate looks strong. The medium-term picture depends on whether the Baltic real estate market stays active and whether BCG can continue deepening the product quickly enough to justify continued pricing power.

My read is that Real Estate is the segment carrying the thesis right now. It is growing at a rate that suggests the moat is widening rather than just holding.

Auto

Now Auto, which is the segment everyone has been focused on for the wrong reasons.

Auto produced €16.0m in revenue in the half. Exactly flat with the year before.

Not collapsing, not growing. Just flat.

The Brief explained why; the Estonian vehicle tax halved car transactions, listing volumes fell 29%, but dealer subscriptions held and per-listing prices rose enough to compensate.

What the Brief did not go into is what Auto actually looks like at the unit level, and the unit level picture is more interesting than the flat headline suggests.

On the B2C side (the professional dealer subscriptions) the number of dealers paying BCG fell by just 1% despite the Estonian market collapsing. One percent. In a country where car transactions were down between 45% and 66% every single month. Dealers stayed on the platform because where else were they going to advertise? And the monthly fee each dealer pays grew 13%. In Auto, in a terrible market, BCG still managed to raise prices and keep almost every dealer on the subscription.

On the C2C side (private sellers) the volume picture is ugly. Listed ads down 29%, active ads down 26%. That is the Estonian tax at work. But the per-listing yield grew 29%. The sellers who did list paid more. Again, because there is nowhere else to go.

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Now here is the thing about Auto that makes me genuinely optimistic about H2. The terrible Estonian comparison base rolls off in January 2026. The tax was introduced in December 2024, so from January 2026 onwards you are comparing current Auto performance against already-collapsed prior-year numbers. The year-on-year percentage will flip from negative to positive almost mechanically. Management has confirmed this explicitly.

Lithuania, which is the larger Auto market for BCG, grew car transactions 8% in the same period. BCG’s Autoplusas platform in Lithuania leads the nearest competitor by 6 times on time spent on site. That market is healthy and BCG’s position in it is strong. Auto is not broken. One country implemented a severe tax that hurt one year’s results. The business underneath is intact.

Jobs and Services

Jobs and Services grew 7%, driven by a combination of more customers and better yields. The Jobs side, primarily CVbankas in Lithuania, grew both customer numbers and the monthly fee per customer. The unemployment rate in Lithuania ticked up slightly to 7.1%, which sounds like a headwind but actually reflects a growing labour force rather than a shrinking economy. Lithuanian wages grew 8.5% in the year. Companies are still hiring and still willing to pay for CVbankas’s recruitment tools, including the salary estimator that gives them a data advantage in setting competitive offers.

Services — the C2C classifieds for tradespeople and service providers — grew active ads 11%. More plumbers, cleaners, and builders are listing on BCG’s services portals. This is a steadily growing vertical that does not get much attention because it is modest in size but the trend is consistent.

Generalist

Generalist grew 4%, which looks unimpressive until you understand what it is.

Skelbiu.lt, BCG’s main generalist portal in Lithuania, is the sixth most visited website in the entire country. It competes partly with BCG’s own vertical platforms through cross-listing.

A private seller who lists a car on Skelbiu.lt may also get redirected to Autoplusas. The generalist portal is as much a traffic acquisition tool for the verticals as it is a standalone business. Growth of 4% driven by yield improvement, with active inventory holding steady, is the right outcome for this segment.

The synthesis is straightforward. Real Estate is carrying the thesis, growing at 20% with unit economics that suggest the moat is deepening. Auto is temporarily impaired by policy, structurally intact, and set to show positive year-on-year growth from January 2026 onwards. Jobs and Services is growing steadily with no signs of stress. Generalist is modest, useful, and not the point.

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The people running this business

BCG listed on the London Stock Exchange in July 2021. Justinas Šimkus has been CEO since before the IPO. Lina Mačienė is CFO.

They have been running this business together through the IPO, through the post-COVID normalisation, through the Estonian tax shock, and through a sustained period of annual price increases that have pushed ARPU and yields consistently higher across every segment.

The way to evaluate management is not to read their investor presentations. It is to compare what they said with what happened.

At the IPO, BCG’s stated capital allocation policy was to return one third of adjusted net income annually through dividends, with the preference for returning excess cash through share buybacks. Three and a half years later, that is exactly what they have done.

The dividend policy has been adhered to with mechanical consistency. Buybacks have continued through good periods and bad ones.

In the half-year to October 2025, with the Estonian situation creating uncertainty, they still bought back €6.4m of shares and paid a €12.5m dividend. They also voluntarily repaid €10m of debt, which was not required but was the right use of surplus cash.

The Estonian Auto situation is itself a management test. When the vehicle tax was introduced and it became clear that Estonian car transactions were going to collapse, there was a decision to be made about whether to adjust B2C pricing for Estonian car dealers.

BCG’s annual B2C pricing actions were implemented in September and October 2024 for most of its markets. For Estonian Auto dealers specifically, the pricing adjustments were postponed.

They made the right call.

Hitting Estonian dealers with a price increase at the same moment the tax was destroying their market would have been extractive and short-sighted. Instead they held pricing for that one market, kept almost all their dealer base, and positioned themselves for recovery when the comparisons normalise.

That is the Bloopers Test in action. A management team making obvious, decent decisions rather than clever ones.

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The one area where I would want more information is on organic growth strategy beyond price increases.

BCG’s revenue growth has been driven primarily by yield expansion (charging existing users more) rather than by growing the user base materially. The number of real estate brokers grew 4% in the half. Auto dealers actually fell 1%. Jobs companies grew 1%. These are not large customer base expansions. The strategy is to extract more value from an already-dominant position rather than to expand the addressable market.

That is a legitimate and often excellent strategy. It is the strategy of a business that knows it has already won its market. But it does mean that the long-term growth trajectory is bounded by how far you can push yields before the customer pushes back. Management has not yet found that wall. Three consecutive years of pricing increases and no material customer loss suggests the wall is further away than bears assume. But it exists, and an honest assessment of management has to acknowledge it.

Overall: yes, I trust these people.

They have done what they said they would do, they have made sensible operational decisions under pressure, and they have not done anything that suggests they are optimising for personal benefit at the expense of shareholders.

The one acquisition

BCG has made one acquisition since listing: Untu.lt, a Lithuanian real estate technology platform, acquired in FY2025 for €1.0m.

One million euros. For context, BCG generates approximately €60m in operating cash annually. This was not a transformative deal. It was a targeted technology acquisition.

What Untu.lt brought was a set of AI-assisted real estate tools;

• The property valuation technology that became Property Price Compass

• The call tracking and lead management system now used by agents on the platform.

BCG acquired a technology capability that deepened their Real Estate moat rather than a revenue stream or a new market.

The price discipline is the notable thing.

€1.0m for a technology acquisition that is now embedded in the workflow of thousands of real estate brokers across the Baltics. That is not a trophy acquisition. That is a specific capability bought at a sensible price and integrated into the core product.

What it signals about BCG’s M&A appetite: they are not empire builders. They are not using their cash generation to buy adjacencies or to pay premium multiples for growth. The one acquisition they made was small, targeted, and directly additive to the moat they already have. That is the right behaviour for a dominant franchise in a small market.

Where the numbers came from; the history since listing

BCG listed in July 2021. Here is what has happened to the business since then:

When BCG listed, revenue for the financial year ending April 2021 was approximately €42m. This financial year, ending April 2026, the annualized run rate puts revenue somewhere around €87m. That is a doubling in five years, which implies a compound annual growth rate of roughly 16%.

The margin history tells an equally interesting story. In financial year 2021, the EBITDA margin was 76%. In 2022 it was closer to 47% , which was a significant step down driven by post-IPO operating cost increases and heavy amortization of acquired intangibles.

But that was a one-off. From 2023 onwards the margin has moved consistently upward: 75.6% in 2023, 76.9% in 2024, 78% in 2025. The business did not find efficiency after a period of inefficiency. It went through a brief post-IPO cost absorption period and then returned to its structural margin level, which has been improving gently ever since.

The capital return history is consistent with the stated policy. Dividends have been paid every year. Buybacks have been ongoing. The share count has been declining. A company that listed with approximately 489 million shares now has approximately 483 million in issue, and that number will continue to fall as buybacks continue.

The key question to ask about the historical picture is whether yield expansion is accelerating or slowing.

The data from H1 2026 suggests it is actually accelerating in some segments. Real Estate C2C per-listed-ad yield grew 27% in the half. Auto C2C per-listed-ad yield grew 29%. These are larger percentage increases than in prior periods.

That tells you one of two things:

1. either BCG has more pricing power than the market appreciates

2. or the base effects from low prior-year prices are temporarily flattering the percentages.

The truth is probably some of both. But the direction is right and the magnitude is not trivial.

Given everything that has happened since the IPO, is BCG better or worse than the prospectus implied? Better. Revenue has grown faster than the prospectus suggested. Margins have recovered to above the listing-period levels.

Capital returns have been disciplined and consistent. The Estonian shock is the first genuine operational headwind since listing, and the business absorbed it without a revenue decline. That is a better track record than most businesses produce in the same period.

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Valuation

Start with what BCG actually earns for its owners, because reported profit and owner earnings are not the same thing for this business.

Net income for H1 2026 was €26.4m. That is the GAAP number. Three adjustments are needed to get to owner earnings.

First, add back the non-cash amortization of acquired intangibles — €3.7m in the half — because this is an accounting artefact of the 2020 acquisition of business client relationships, not a real economic cost. Those intangibles are now fully amortized, so this adjustment disappears going forward.

Second, subtract stock-based compensation of €0.5m. This is real dilution and must be treated as a cost regardless of how it is classified in the income statement.

Third, the maintenance capex is €0.4m against depreciation of €0.4m on non-acquired assets. These roughly cancel out.

The result: owner earnings of approximately €25.9m for the half, or €52m annualised.

Now the assumptions;

Revenue growth: Management has guided for H2 revenue growth above H1’s 7%, and double-digit growth for the full 2027 financial year. The B2C price increases implemented in September and October 2025 will fully annualise into H2 2026 revenue.

Estonian Auto comparables flip positive from January 2026. Real Estate is growing at 20% with a strong market backdrop. A 10% to 12% annualised revenue growth rate for the next three years is conservative relative to management guidance and recent trends.

Margin assumption: BCG has guided that EBITDA margins will remain in the mid-seventies even with investment in data and AI. The structural reason for this is simple: the cost base does not need to grow proportionally with revenue. More listings, higher yields, more broker customers — none of these require meaningful additional headcount or infrastructure. A 75% to 77% EBITDA margin assumption is conservative.

At 10% revenue growth and 76% margins, owner earnings grow from approximately €52m today to approximately €70m by year three. At 12% growth and 77% margins, the number is closer to €78m.

What multiple is warranted?

BCG operates in a market so small that it has essentially pre-empted competition. The moat is deepening through product development. The capital requirements are negligible.

The management team has a clean track record. For a business with these characteristics and this growth profile, a multiple of 22 to 25 times owner earnings is defensible.

At the lower end of the growth assumption and the lower end of the multiple range, the implied value is approximately €1.28bn. At the upper end of both, the implied value reaches €1.95bn.

The base case: €1.28bn, or approximately 220p per share.

The bear case: growth disappoints at 5%, margins compress to 74%, and the multiple contracts to 18 times. Implied value approximately €846m, or around 145p. The current price of 190p sits about 30% above the bear floor.

The bull case: growth runs at 14%, margins hold at 78%, and the multiple expands to 25 times as the debt-free capital return story gets priced in. Implied value approximately €1.95bn, or around 330p.

This is not a business trading at a severe discount to obvious value. It is a good business at a fair price, temporarily de-rated by a policy shock, with a specific catalyst — the Estonian comparison base — that is already reversing.

So, the case for owning it is not that it is obviously cheap. The case is that the de-rating was an overreaction to a temporary problem in a business that has now demonstrated it can absorb that problem without a revenue decline.

The distinction between what BCG earns on its own capital and what an investor earns at today’s price is worth dwelling on. BCG’s return on tangible capital is essentially infinite — the platform requires almost no tangible capital to operate.

But the investor buying at 190p and an enterprise value of approximately €1.05bn is paying for that extraordinary capital efficiency at a 4.9% owner earnings yield. The business earns extraordinary returns. The investor earns fair returns. These are different numbers, and conflating them is one of the most common errors in quality growth investing.

BCG is a wonderful business at a fair price. Not a fair business at a wonderful price.

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The balance sheet

BCG ended October 2025 with net cash of €5.1m. Six months earlier it had net debt of €3.6m. The transition happened because BCG generated €30.6m in operating cash in the half, used €12.5m to pay the final dividend, bought back €6.4m of shares, and voluntarily repaid €10m of the bank loan.

The remaining loan balance is €15m, maturing in July 2026. This is trivial against the cash generation rate.

BCG generates the equivalent of the entire loan balance in operating cash every six months. Watch the refinancing terms when the facility matures, not because there is a solvency concern but because the interest rate will likely improve if they choose to maintain any debt capacity.

Management has said the company could be debt-free by the end of the current financial year; April 2026. When that happens, the full approximately €60m of annual operating cash flow becomes available for buybacks and dividends.

At the current market capitalisation of £880m, that is a total cash return yield of around 7%, growing at double digits. That is what the capital return conversation will look like in a few months.

The item on the balance sheet that looks alarming until you understand it is the goodwill. BCG’s balance sheet shows €330m of goodwill out of €386m of total assets. That is 85% of total assets in a single line item. For most businesses that would be a serious red flag.

For BCG it reflects the structure of how the business was assembled. Before the IPO, private equity assembled the portfolio of Baltic classifieds portals through a series of acquisitions. The goodwill represents the premium paid for those businesses above their book value. The assets underlying the goodwill are not tangible — they are the brand relationships, the audience, the network effects, the professional workflows. These are real assets.

They generate €60m of operating cash per year. They have never required impairment. BCG has not paid too much for businesses that subsequently disappointed. The goodwill is the price of buying dominant market positions and those positions have produced exactly what was paid for.

The risks

Let’s go through the risks, because there are things we need to be aware of with Baltic Classifieds.

The first is the free-listing attack.

If a platform with existing Baltic user trust (Facebook Marketplace for example) decided to offer free listings at scale across all three Baltic states, the consumer C2C side of BCG’s business would come under genuine pressure.

Private sellers deciding whether to pay €42 to list their car or €0 to list it on Facebook will choose free. The question is what percentage of BCG’s economics depends on private seller behaviour versus professional subscriber behaviour.

On the Auto segment, B2C dealer subscriptions represent the majority of revenue. Dealers will not stop paying for Autoplusas because Facebook offers free listings — they need the professional tools and they need the inventory depth that comes from a dominant platform.

On Real Estate, professional broker subscriptions and the workflow tools like Property Price Compass represent the core economics. A free-listing generalist platform does not threaten that. The vulnerable segment is generalist C2C, which is 15% of group revenue and where the competitive moat is weakest.

The early warning signal for this risk is BCG’s Auto and Real Estate C2C active ad volumes. If those numbers start declining for multiple consecutive quarters without a named policy explanation, it is the signal that inventory depth — the foundation of the flywheel — is eroding. Track those numbers every half-year.

The second mechanism is regulatory.

BCG raises prices every year on customers who have no practical alternative. That is the definition of a business that attracts antitrust scrutiny.

The Estonian Competition Authority has active enquiries open. BCG’s directors have assessed the likelihood of a material outflow from those enquiries as remote. I give that assessment weight because BCG’s market, while dominant, is also small. The harm from BCG raising annual prices on Lithuanian real estate brokers is genuinely minimal in the context of the national economy. The antitrust case is harder to make when the affected market is modest in size.

But the risk is real and observable. Any formal announcement from the Lithuanian or Estonian competition authorities opening an investigation specifically into BCG’s B2C pricing practices would change the valuation materially. The primary driver of BCG’s revenue growth is yield expansion. A cap on that expansion is a cap on the growth thesis.

And we can’t leave out macro/geopolitical risk.

I rarely include macro in my analysis, but in this case, we must address the elephant in the room.

Lithuania, Latvia, and Estonia sit at the eastern edge of NATO, sharing borders with Russia and Belarus. Estonia and Latvia border Russia directly.

Lithuania borders the Kaliningrad exclave and Belarus. These are not abstract geographic observations. The three Baltic states have lived under Soviet occupation within living memory, they understand the threat more clearly than most of their NATO allies, and they have responded to it seriously. All three now exceed NATO’s 2% of GDP defence spending commitment, with Estonia leading European allies at roughly 3.4%. NATO has substantially increased its forward presence in the region since 2022, with multinational battle groups deployed in each country.

None of this eliminates the risk. A significant escalation in the wider conflict or a direct threat to Baltic territory would affect consumer confidence, transaction volumes, and the attractiveness of Baltic equities to foreign investors in ways that BCG’s moat cannot insulate against. Small open economies with active property and labour markets are sensitive to geopolitical uncertainty in a way that larger, more diversified economies are not.

The Baltics have been pricing in proximity to Russia for thirty years. Their institutions are strong, their NATO integration is deep, and their populations have not needed recent events to remind them what is at stake. BCG’s business has compounded through every period of elevated tension since 1999. That does not make the risk theoretical. It means the risk is understood and priced locally in a way that external investors sometimes overreact to.

Of the risks in this piece, geopolitics is the one I think about least in terms of the day-to-day thesis and most in terms of position sizing. It is not a reason to avoid BCG. It is a reason not to make it the only thing you own.

The verdict

After going through all of this, here is where I land.

Going through the segment data, the management track record, the acquisition history, and the full financial picture has not weakened the case to me since writing the thesis brief. Real Estate is the strongest it has ever been. Auto is temporarily impaired in a way that is already reversing.

Management has done exactly what it said it would do since listing. The balance sheet is about to become debt-free. The capital return story is getting more interesting by the half-year.

If I had to name one thing that would most change my view, it would be evidence that the professional workflow integration is not as sticky as the product narrative suggests.

If broker churn on Aruodas.lt were rising, or if dealer retention on Autoplusas were declining, or if the ARPU growth started requiring unusual commercial concessions to maintain, any of those would suggest the moat is less embedded than it appears. None of those signals are present in the current data.

The verdict

After going through all of this, here is where I land, and it is not where I expected to when I started:

First, the business is excellent. The moat is real and deepening. Management has earned trust. The Estonian shock is temporary and the comparables will flip. None of that has changed in my mind after going through every corner of this company.

What has changed is my view on the price and what I am being paid to own it.

At 4.9% owner earnings yield, BCG is fairly priced for what it is.

Not cheap. The base case gets you to around 220p, which is roughly 15% from current levels.

That is a reasonable return for a dominant franchise in a small market. But reasonable is doing a lot of work in that sentence. Fifteen percent upside, with a 4.9% starting yield, is not the kind of asymmetry that makes me want to concentrate capital.

The bull case requires things to go better than guided. The bear case, where regulation caps pricing or a free-listing platform gets traction, does not look remote enough to dismiss.

And then there is the… map.

I laid out the geopolitical picture honestly in the section above. The Baltics have strong institutions, deep NATO integration, and thirty years of experience pricing in proximity to Russia. I believe all of that.

But when I combine a valuation that requires things to go right with a geography that carries tail risk I cannot model, I find myself looking for a better combination elsewhere.

And not because BCG is a bad investment. Because my opportunity cost is real and the risk-adjusted return here does not clear my bar.

I bought a small starter position in BCG earlier. I have since sold it. Not because the thesis broke (it did not) but because the price never gave me enough margin of safety to sit comfortably with the geography.

A wonderful business at a fair price is still a fair price. I want wonderful businesses at prices that make the geopolitical risk feel adequately compensated.

If BCG trades down toward 145p to 155p, the conversation changes entirely. At that level the owner earnings yield moves above 7%, the bear case is closer to priced in, and the same geopolitical risk starts to feel adequately compensated. That is the price where I would consider to own this properly rather than tentatively.

Until then: thesis intact, position closed, watching carefully.

Sources and references

• Baltic Classifieds Group PLC — Half Year Results for the Six Months Ended 31 October 2025. Published 4 December 2025. Available at balticclassifieds.com.

• Baltic Classifieds Group PLC — Half Year Results Presentation, Six Months Ended 31 October 2025. Published 4 December 2025.

• Baltic Classifieds Group PLC — Annual Report and Accounts 2025. Financial year ended 30 April 2025.

• Maanteeamet (Estonian Road Administration) — Monthly vehicle registration and transaction data, calendar year 2025.

• Similarweb — Time on site data, leadership position vs nearest competitor. Referenced via BCG H1 2026 results presentation.

• Google Analytics — Baltic site visit data, averaged based on Baltic population statistics. Referenced via BCG H1 2026 results presentation.

• Skandinaviska Enskilda Banken (SEB) — Nordic Outlook Update, November 2025. GDP, inflation, unemployment, and wage growth forecasts for Baltic states.

• Eurostat — Real GDP per capita CAGR, 2000–2024.

• Swedbank — Average apartment prices in Vilnius, Riga, and Tallinn, calendar H1 2025.

• State Enterprise Centre of Registers Lithuania, Land Register Latvia, Land Board Estonia — Real estate transaction volumes.

• Euromonitor — E-commerce market growth, Lithuania and Estonia, 2019–2028.

• Börsdata — Financial data export, Baltic Classifieds Group PLC, historical annual and quarterly figures.

Disclaimer
This Deep Dive is an educational breakdown of a public company based on information available in the materials provided (e.g., annual/quarterly reports, investor presentations, earnings transcripts) and my interpretation of that information. It is designed to be a “bolt-on” intelligence layer to your own due diligence — not a replacement for it.

Independence: I do not accept compensation of any kind from the companies discussed. My research is driven solely by my personal search for high-quality compounders.

Skin in the Game: Unless otherwise stated, assume the author may hold a long position in securities mentioned. Any position creates bias — treat this as commentary, not gospel.

Not Financial Advice: Nothing here is investment advice, a recommendation, or a solicitation. I am not a financial advisor. You are responsible for your own decisions. The stars rating is not a buy recommendation, but meant as a guide to understand the quality of the financial statement of the respective companies.

Error & Update Risk: Financial statements change, companies restate, guidance evolves, and I can be wrong. Verify key figures in the primary filings and consider reading the footnotes before deploying capital.

Most people who know Charlie Munger know the ending.

The wit. The aphorisms. The Berkshire annual meetings. The billionaire who sat next to Warren Buffett for six decades and made the whole thing sharper, deeper, and more permanent than it would have been without him.

But the ending is not the interesting part. Not for you. Not if you are in your 30s, building something real, trying to figure out how someone goes from a standing start — broken, broke, starting over — to the kind of wealth and freedom that makes everything else possible.

The interesting part is the middle. The decade most biographies rush through. The years between the disaster and the breakthrough.

That decade is what this piece is about.

And I want to be direct about why: because if you are where Munger was at 30, the path he took is one of the most instructive case studies in modern financial history. Not because you should copy it (you can’t, the world has changed) but because the logic of what he did is completely transferable. The mindset. The sequencing. The willingness to run two things simultaneously before committing fully to either.

Let’s go back to the beginning of the hard part.

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Pasadena, 1953. Everything Gone.

Charlie Munger was 29 years old.

He had a Harvard Law degree, a small practice in California, and almost nothing else. His marriage to Nancy Huggins — a rushed, youthful marriage that his own daughter Molly later described as two people who had “utterly no idea what they were doing” — had ended. The family home went to Nancy. His savings, already modest on a lawyer’s salary, were largely gone. He had three children he was supporting: Teddy, Molly, and Wendy.

He was living in a single room.

This is not a detail you often see in the Munger mythology, which tends to begin at Berkshire and work backwards. But it matters enormously, because the man who emerged from that period remarried by 32 to Nancy Barry, with whom he would go on to have four more children, rebuilt not just his finances but his entire operating philosophy during the years that followed.

He later said, with characteristic bluntness:

“Like Warren, I had a considerable passion to get rich. Not because I wanted Ferraris — I wanted the independence.”

Independence. Not lifestyle. Not status. The freedom to think without financial constraint, to act without begging permission, to say no to work you don’t respect. That was the goal. And it is a materially different goal from simply wanting to be wealthy, because it focuses your attention on the structure of your financial life rather than the level.

Munger wanted to own things that generated returns while he slept. He wanted out of the time-for-money trap as fast as possible. And he was willing to run two careers simultaneously — law and investing — to get there.

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The First Business Lesson: Transformer Engineers

Before the real estate, before the investment partnership, before any of the things that actually worked, Munger made a mistake.

In 1950, aged 26, he was doing legal work for a man named Ed Hoskins, an engineer and entrepreneur who ran a small company called Transformer Engineers Ltd. Munger liked Hoskins. He found the business interesting. He had the instinct, even then, that sitting around waiting for clients he liked was too passive.

One morning, driving past the Transformer Engineers office on his way to work, Munger made a decision. He did a U-turn in the middle of the street, walked in, and told Hoskins he wanted more work and more involvement in the business.

Hoskins had a problem with his venture capital backers, who, in typical fashion, wanted to replace the founder. Munger helped Hoskins structure a buyout, using debt.

Munger himself borrowed money to buy into the business as a part-owner.

He later described the deal this way: “It was an early leveraged buyout. It was a nonlegal solution to what looked like a legal problem.”

The only problem was that Transformer Engineers was a bad business.

Munger didn’t know it when he got in. But the Korean War ended, defence contracts dried up, and the company slowly lost momentum. It was Munger’s first experience of the painful gap between a business that looks interesting and a business that actually works.

He lost money. He learned something more valuable.

The lesson he took from Transformer Engineers was one he would repeat for the rest of his life: the quality of the business is not a soft consideration. It is the central one.

A mediocre business bought at a cheap price gives you a one-time gain. A bad business bought at any price eventually destroys capital. The structure of the economics;

• what happens to margins as the business scales

• whether the customer has any alternative

• whether the cost of serving each new customer falls or rises over time

These questions matter more than the entry price.

He would apply this logic, with devastating clarity, for the next seventy years.

1955. The Year That Reframes Everything.

In 1955, Munger’s son Teddy died of leukaemia. He was nine years old.

Munger used to walk to the hospital because he didn’t want to spend money on cabs he didn’t have. He sat with his son through the illness knowing the outcome was likely irreversible, knowing that no amount of intelligence or willpower would change what was happening.

I include this not for sentiment but because it is the context for everything that follows.

The man who rebuilt his finances in his mid-30s had already survived something that breaks most people. He had lost a marriage, lost his savings, started over in a single room, and then watched his firstborn son die. By any conventional measure of adversity, Munger had experienced more by 31 than most people accumulate in a lifetime.

What he didn’t do is almost as important as what he did do.

He didn’t become reckless, betting everything on a single big play to recover lost ground fast. He didn’t become paralyzed, retreating into the safety of a lawyer’s salary and stopping there. He didn’t become bitter, and there is no recorded evidence of self-pity in anything Munger ever said or wrote about those years.

He remarried. He kept practicing law. He kept studying businesses and markets. He kept building relationships with interesting people. He kept going.

“I had a child die. I had a divorce. I had a lot of adversity. And I just kept going.” — Charlie Munger

Three sentences. The entirety of what he had to say on the subject, in most interviews. Not because the grief wasn’t real; it clearly was (and he spoke about Teddy unprompted even in his 90s), but because Munger had internalized something the Stoics had been writing about since Marcus Aurelius: that the only rational response to the things you cannot control is to accept them fully and direct all your energy toward the things you can.

If you are in your 30s reading this, I want you to sit with that for a moment. Whatever difficulty you are carrying — financial, personal, professional — Munger’s 30s is the answer to the question “what do I do when it gets really hard?”

You keep going. Methodically, rationally, one decision at a time.

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Late 1950s. The Relationship That Changed Everything.

Through his law practice in the late 1950s, Munger got to know a man named Otis Booth.

Booth was a real estate developer and investor. He and Munger became friends. The kind of friendship that forms between two intelligent people who recognize something in each other. Booth was practical, experienced in how physical assets worked, how to develop land, what made a project viable. Munger brought the analytical mind, the legal clarity, and an increasingly sharp sense of business economics.

In 1961, Booth came to Munger with a specific problem. He needed help handling a probate settlement ; a piece of property that had come to him through a deceased estate.

Munger looked at the property. His advice was immediate and clear: don’t sell it. Develop it.

Booth agreed. Then he said something that changed both their financial trajectories: “Only if you join me.”

This is the moment worth studying most carefully, because it contains several layers of wisdom that are easy to miss.

First: Munger had earned this opportunity through relationship, not transaction. He and Booth were friends. Booth trusted his judgement.

The deal came because Munger had spent years building genuine relationships with interesting people, actually engaging with clients, understanding their problems, doing U-turns in the street to stay involved. The quality of your relationships, particularly with people who are doing interesting things, is a long-term asset that most people dramatically underinvest in.

Second: Munger said yes despite the risk. He was not a wealthy man in 1961. Putting $100,000 into a single real estate development — alongside his existing practice and a family of several children — was not a trivially comfortable decision. But he had done the analysis, he trusted his partner, and he committed.

Third: He brought his legal skills directly to the investment. The probate settlement required exactly the kind of expertise Munger had spent over a decade building. He wasn’t starting from scratch; he was finding the intersection of what he already knew and where capital could be deployed intelligently.

The Caltech Deal: $100,000 In, $500,000 Out

The property they developed was a set of apartments adjacent to Caltech in Pasadena — the same institution where Munger had studied meteorology during the war, the city that had become his home.

Each man put in $100,000. They owned 50% each.

The project took six years. It was completed in 1967 and sold at a 400% profit. Each man walked away with $500,000.

From a standing start of $100,000, Munger had turned one deal into half a million dollars. In 1967. That is roughly $4.5 million in today’s money.

But the more interesting part is what he learned during those six years, because the lessons shaped the four deals that followed.

The first thing he noticed was which units sold fastest. It was the ground-floor apartments. Interestingly, not the upper floors or the ones that felt more exclusive, that had better views.

No, the ground floor. Why? Because buyers in that market wanted ease. Access. The absence of stairs. This was not an obvious insight. It required actually paying attention to what was happening on the ground rather than what seemed theoretically preferable.

From that observation, Munger and Booth made a decision that sounds almost too simple: they would make the next project entirely single-story. No upper floors. Lower building costs, faster sales, higher margins per unit.

“Lush landscaping. That is what sells,” Munger declared. “You spend money on trees, and you get it back triple. Stinting on landscaping is building malpractice.”

This is the observation of someone who is actually watching what drives buyer decisions, not what should drive them in theory.

The lush landscaping insight is quintessential Munger. It is specific, counterintuitive, based on direct observation, and completely ignored by competitors who are cutting costs rather than watching what sells.

They did it again. The single-story condos sold even faster, at higher prices. So they did it a third time. Then a fourth. Then a fifth.

When it was over, Munger had $1.4 million from real estate alone.

“When it was over, I had $1.4 million as the result of my real estate involvement. That was a lot of money at that time. I did a total of five projects, then stopped.” — Charlie Munger

Five projects. Five iterations of the same thesis, refined each time based on what the market was actually telling him. Not fifty projects. Not a sprawling property empire. Five disciplined executions of a well-understood edge, then a clean exit to focus on something with even more potential.

This is perhaps the most underrated part of the story. Munger knew when to stop. He didn’t mistake a successful edge for a permanent one, or confuse the accumulation of assets with the building of wealth. When the real estate had served its purpose, which was to generate the capital base he needed to go full-time into investing, he stopped.

The ability to close a chapter cleanly, without nostalgia, is rarer than it sounds.

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Running Multiple Things Simultaneously

What makes Munger’s mid-30s genuinely remarkable is that he was not doing one thing. He was doing three.

He was practicing law. He was developing real estate with Otis Booth. And from 1962 onwards, he was running an investment partnership called Wheeler, Munger & Company — a fund he co-founded with Jack Wheeler, with a seat on the Pacific Coast Stock Exchange.

From 1962 to 1975, that fund generated compound annual returns of 19.8%. The Dow, over the same period, returned 5.0% per year.

He was doing this while developing apartments. While running a law firm he had co-founded, Munger, Tolles & Olson.

While raising eight children from two marriages.

The point is not to make this sound superhuman. It wasn’t. The point is that Munger understood something about the early stages of wealth building that most people never grasp: you do not get to choose between your day job and your investment activity until your investment activity can replace your day job.

Until that moment, you run both.

Most people wait until they feel “ready” to invest seriously. They want to finish one thing before starting another. Munger’s answer to this instinct was essentially: you don’t have that luxury. The compounding on the investment side needs to start as early as possible, because time is the one input you cannot manufacture.

He kept the law practice alive, he was generating income, building relationships, providing deal flow. And he did this until the investment side was clearly the superior use of his time. Then, and only then, did he walk away from the law.

By the time he did, he was already wealthy. Not rich in the Berkshire sense; that would come later. But free.

The independence he had wanted since his single room in 1953 was now his.

What Munger Was At 40, And How He Got There

By the time Munger met Buffett in 1959, he was 35. By the time he wound down his legal career, he was in his early 40s.

Here is what he had built by then:

• A network of relationships, with clients, partners, and counterparties, that provided constant deal flow and intellectual stimulation.

• An investment partnership running at nearly 20% annual returns.

• A real estate portfolio that had converted $100,000 into $1.4 million across five disciplined projects.

• A law firm bearing his name that was already becoming one of California’s most respected.

And a mind that had been sharpened by failure (Transformer Engineers), grief (Teddy), forced rebuilding (the divorce), and the daily practice of thinking carefully about how businesses actually work.

He succeed through the relentless accumulation of learning, relationship, and capital across a decade of parallel effort.

The law fed the real estate, which fed the investment partnership, which eventually made the law unnecessary. Each activity generated returns — financial, intellectual, or relational — that compounded into the next.

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The Actionable Framework: What Munger’s 30s Actually Tell You

If you are in your 30s, building something — a business, a newsletter, a research platform, an investment framework — here is what Munger’s decade actually tells you to do.

1. Don’t wait until you’re ready. Run two (or more) things. Munger ran law and investing simultaneously for years. He didn’t wait until the investing was proven before starting it. He started it while the law was covering his costs, and let time do the compounding work.

Whatever your day income source is right now, the investment or ownership activity needs to start today, and not when you feel financially comfortable enough to focus on it.

2. Your professional relationships are a deal pipeline. Every significant opportunity Munger had in his 30s came through a relationship he had built while doing his day job. Hoskins through his legal practice. Booth through his legal practice. Buffett through a mutual friend connected to his legal and investment circles.

He was genuinely engaging with interesting people and staying in their orbit. The best deals of your career will come from the people who already trust your judgement.

3. Iterate on what the market actually tells you, not what you expect. Munger learned that ground floors sold faster not by theorising about buyer psychology but by watching what actually happened.

Then he rebuilt the entire project model around that observation. Whatever you are building — products, content, research — the market’s response to what you have already done is more valuable than any plan you can write about what you haven’t done yet. Watch what sells. Double down on it.

4. Know when to stop. Five real estate projects. Not fifteen. Munger stopped when the thesis had run its course and a better use of his capital and time was available. Most people stay in the thing that worked in the past because it is comfortable and familiar. Munger’s discipline was knowing when the edge had been extracted and it was time to move.

5. The independence goal is more powerful than the wealth goal. Munger wanted the freedom to think and act without financial constraint.

That goal — not a number, not a lifestyle — shaped every decision he made about what to work on and when to stop. If your goal is a number, you will either stop short of it (afraid) or overshoot it (addicted). If your goal is independence, every decision becomes clearer: does this move me closer to owning my time, or further away?

The Last Thing Worth Saying

In 1959, when Munger met Buffett over dinner in Omaha, he was 35 years old. He was a divorced lawyer, recently remarried, running a small practice, just starting to invest seriously.

Thirty-nine years later, Berkshire Hathaway was one of the most valuable companies on earth.

None of that was obvious in 1959. None of it was guaranteed. What was present in 1959 was a man who had already survived the worst, rebuilt from zero, and developed the judgement that comes only from having done both.

That judgement — not the brilliance, not the quips, not the famous partnerships — is what made everything else possible.

You build it the same way he did. One careful decision at a time, across a decade of parallel effort, without waiting until you feel ready.

He wasn’t ready either.

He just started anyway.

“The best thing a human being can do is to help another human being know more.” — Charlie Munger