What Everyone Missed In Leo’s Blow-Up👇 Leopold Aschenbrenner lost $30 billion (~67%) in a month. The consensus post-mortem, from the Wall Street Journal to the replies on X, is that a young man used 4-to-1 leverage on concentrated positions and got carried out. While that is true, it does not convey any useful information. Leverage is certainly the reason Leopold lost so much, so quickly. But it is not the reason he lost. Leverage is merely a magnifying glass. It doesn’t pass judgement. The reason the reason his fund was doomed was because he’s wrong. And no one, anywhere, has explained why. On the morning of Thursday, July 30, before the opening bell, Situational Awareness LP sold its entire public stock portfolio — the long side and the short side together, roughly $16 billion of it — to Citadel in a single block trade. Millennium Management and Jane Street bid for the assets. Ken Griffin and Citadel won. That night, Aschenbrenner wrote to his limited partners. Net performance for the month, unaudited: down 67%. Net performance for the year: still up 80%. "We let you down this month," he wrote. "We came closer to permanent capital impairment than is acceptable to us." Six days earlier, on July 24, he had written a different letter. That one reported a 439% net return for the first half of 2026, described the selloff in artificial intelligence stocks as one of the best buying opportunities since early 2025, and invited his investors to wire more money starting August 1. It closed with a postscript: "At times we call out opportunities that seem like a particularly good time to add funds, if you have been waiting for one." Assets that stood near $45 billion at the start of July finished the month around $10 billion, and roughly half of what remains is a single illiquid private stake in Anthropic. Leopold is 25 years old. He graduated from Columbia at 19, as valedictorian. He worked at the FTX Future Fund from February to November of 2022, then joined OpenAI's Superalignment team, then was fired in April 2024. Two months after the firing he published a 165-page essay called "Situational Awareness: The Decade Ahead," raised $225 million from Patrick and John Collison, Nat Friedman and Daniel Gross, and started a hedge fund. He had never managed money before. Situational Awareness was constructed to express only two ideas. The first conviction: the physical build-out of artificial intelligence — the chips, the memory, the power, the data centers, the neoclouds — was the trade of the decade. The fund's disclosed long positions read like an inventory of the second derivative of the AI boom. Bloom Energy Corporation (NYSE: BE), fuel cells for data centers. Sandisk Corporation (NASDAQ: SNDK) and Micron Technology, Inc. (NASDAQ: MU), memory. CoreWeave, Inc. (NASDAQ: CRWV) and Nebius Group N.V. (NASDAQ: NBIS), rented compute. IREN Limited, Core Scientific, Applied Digital, Riot Platforms, CleanSpark, Bitfarms, Bitdeer — bitcoin miners converting their substations into AI compute. The second conviction: application software was going to be destroyed by A.I. Not disrupted. Obliterated. Leo explained why on Dwarkesh Patel's podcast, in June 2024: "I'm so bearish on the wrapper companies because they're betting on stagnation. They're betting that you have these intermediate models and it takes so much schlep to integrate them. I'm really bearish because we're just going to sonic boom you. We're going to get the unhobblings. We're going to get the drop-in remote worker. Your stuff is not going to matter." That was the whole thesis. Buy the compute. Short the stuff that runs on the compute. By CNBC's reporting, the short leg included Adobe Inc. (NASDAQ: ADBE). A 13F does not disclose short stock. It does not disclose swaps. We only know about Adobe because reporters were told… but you can look at the tape and, when you do, it’s clear that Leo was short software in a major way. Between the June 30 close and the July 29 close — the last session before the block trade cleared his shorts — the two sides of his portfolio did this. The longs: · Sandisk: down 55.32% · Nebius: down 46.33% · Bloom Energy: down 45.90% · CoreWeave: down 38.90% · Micron: down 35.98% · IREN: down 35.91% The shorts, over the same 20 sessions: · Workday, Inc. (NASDAQ: WDAY): up 37.24% · Adobe: up 28.49% · Intuit Inc. (NASDAQ: INTU): up 27.64% · Salesforce, Inc. (NYSE: CRM): up 20.25% · Veeva Systems Inc. (NYSE: VEEV): up 17.15% Over that same window the Invesco QQQ Trust fell 10.14% and the SPDR S&P 500 ETF Trust fell 2.32%. Nvidia — the supposed epicenter of the AI trade — fell 5.04%, and finished the full month of July up 0.33%. This was not an AI crash. The S&P 500 stayed near its record throughout. This was a violent rotation out of the leveraged, capital-hungry, second-derivative end of the AI complex and into the profitable, cash-generating, asset-light end of it. Which is to say: the market rotated out of exactly what he owned and into exactly what he was short. Then there is Microsoft. Microsoft Corporation (NASDAQ: MSFT) closed at $390.54 on Wednesday, July 29. It closed at $451.10 on Thursday, July 30. That is a gain of 15.51% in a single session on 110.2 million shares, against a July average of 37.1 million. Yes, Microsoft reported its fiscal fourth quarter after the close on July 29. But the results were nothing out of the ordinary. Revenue came in at $90.007 billion against a $87.62 billion consensus. That is a 2.7% beat. Earnings were $4.74 per share against $4.21. It was a good quarter. Not a historic one. A 2.7% revenue beat does not add roughly $450 billion of market value to the most widely owned company on earth in six and a half hours. Something else was in that tape. And the answer is extremely important. Leo blew up quickly because of leverage. But he failed because he is simply wrong. Aschenbrenner's software thesis rests on a single premise: that a company selling enterprise software is selling the work the software performs. If a model can perform that work, the company is worth nothing. That premise is what a very smart 25-year-old engineer believes. It is not what anyone who has ever run a business believes. Nobody buys Microsoft because Microsoft writes the best code. They buy Microsoft because Microsoft is the rail everything else runs on. Active Directory is where your employee identities live. Excel is where your board deck's numbers come from. Teams is where the compliance-recorded conversation happened. Azure holds a FedRAMP High authorization and Department of Defense Impact Level 5 clearance, which means a defense contractor cannot casually swap it out for something cheaper without re-clearing the entire stack with the government. Veeva runs the customer relationship management and regulatory document systems of the pharmaceutical industry. Nineteen of the top 20 biopharmaceutical companies use Veeva's regulatory information management platform. Those systems are validated under GxP — the good-practice quality regulations that govern anything touching a drug — and 21 CFR Part 11, the Food and Drug Administration's rule for electronic records and signatures. Every major release is formally qualified. When an FDA inspector arrives, the audit trail in that system is the company's defense. You cannot replace that with a model that is very good at writing code. You would have to re-validate a decade of regulated records, in front of a regulator, on a system with no track record, to save a fee that rounds to nothing in terms of the cost of building a new drug. How small a fee? Veeva's licensing runs somewhere between roughly $1,800 and $6,600 per sales representative per year. A fully loaded pharmaceutical sales rep costs the employer between $134,000 and $219,000 a year. The software is 1% to 5% of the cost of the person using it. Microsoft raised the price of a Microsoft 365 E3 seat from $36 to $39 per user per month on July 1 of this year, and E5 from $57 to $60. Add Copilot at $30 and a fully loaded E5 seat costs $1,080 a year. Against a knowledge worker costing $75,000 to $120,000 all-in, that is roughly 1% of the employee. This is the part the compute maximalists cannot see. These companies are not selling labor. They are selling the rails on which labor runs, at a price so far below the value created that the buyer never bothers to negotiate hard, and with switching costs so high that the buyer could not leave even if he wanted to. Do people try to leave? Constantly. And they almost always fail. (Ask me how I know!) Panorama Consulting Group's tracked studies of enterprise resource planning replacements put average cost overruns at 189% across industries. Gartner projects that by 2027, more than 70% of recently implemented ERP initiatives will fail to fully meet their original business goals. Ripping out a core enterprise system is one of the most reliably disastrous things a large company can attempt, and it was true before anyone had heard of a transformer model. The incumbents are not being disintermediated by artificial intelligence. They are selling it! Microsoft passed 30 million paid Copilot seats in the June quarter, up from 15 million in January. Tech wizards like Leo hate copilot. Just like they hated Windows ’97. And everything else Microsoft has ever built. So what? Accenture alone bought 740,000 of them. Bayer, Johnson & Johnson, Mercedes-Benz and Roche have each deployed more than 90,000. Microsoft's commercial remaining performance obligation — contracted revenue not yet recognized, which is the closest thing software has to a railroad's signed freight contracts — stands at $678 billion, up 84% year over year! Adobe's AI-first annual recurring revenue passed $500 million in the quarter ended May 2026 and tripled year over year. Salesforce's Agentforce went from $800 million of annual recurring revenue in the January quarter to $1.2 billion by April, up 205%. Veeva is giving its AI agents away free inside Vault CRM through 2030, which is the single most revealing data point in the set: Veeva does not need to monetize AI, because Veeva's moat is the validated record, not the intelligence applied to it. Aschenbrenner thought AI would eat the applications. Instead the applications are selling AI as an upsell on top of a subscription the customer cannot afford to cancel – because it costs nothing compared to the value it delivers. These software companies are computing toll booths: they’re what enterprises pay to implement compute. And, as compute gets cheaper, they will generate vastly more revenue, not less. The proof is sitting there in their earnings and cash flows: they’re riding on lower and lower cost of compute, which makes their business more and more efficient. · Adobe: 36.6% operating margin, 35.6% return on invested capital, capital expenditure of $179 million on $23.8 billion of revenue — 0.75% — and $9.85 billion of free cash flow. · Veeva: 28.7% operating margin, 68.5% return on invested capital, a 44.3% free cash flow margin, and effectively no capital expenditure at all. · Salesforce: $41.5 billion of revenue, roughly $14.4 billion of free cash flow, capital expenditure of about 1.4% of revenue, and $72.4 billion of contracted backlog. · Intuit: $18.8 billion of revenue, roughly $6.1 billion of free cash flow, $124 million of capital expenditure. Veeva earns 68 cents a year on the dollar. And invests nothing it growing its business. Adobe currently trades at about 11 times trailing earnings. Salesforce at about 13. Intuit at about 14. These are the multiples of a dying industry, applied to businesses converting a third to nearly half of every revenue dollar into free cash. This enormous mispricing was manufactured by people who like Aschenbrenner, believed these businesses were doomed. But they aren’t. And that’s not all. Aschenbrenner assumed that because a technology is transformative, the capital that builds it will earn its cost. There is no relationship between those two things. In fact, it’s more likely not to be true. Leo’s own essay contains the tell: "Over the past year, the talk of the town has shifted from $10 billion compute clusters to $100 billion clusters to trillion-dollar clusters. Every six months another zero is added to the boardroom plans." He wrote that as a bull case. But it isn’t. That is a recipe for a financial disaster. Inc. (NASDAQ: AMZN) spent $131.8 billion of capital expenditure in 2025 against $139.5 billion of operating cash flow. That is 94.5% of everything the business generated, poured back into the ground, in a single year. Its 2026 cap ex guidance is $220 billion. Alphabet Inc. (NASDAQ: GOOGL) spent $91.4 billion in 2025, 55.5% of operating cash flow, and guides to $195 billion to $205 billion this year. Meta Platforms, Inc. (NASDAQ: META) spent $72.2 billion, 62.4% of operating cash flow, and guides to $125 billion to $145 billion. Microsoft spent $115.9 billion in the fiscal year that just ended, against $182.9 billion of operating cash flow. Capital expenditure was 34.9% of revenue, up from 18.1% two years earlier. Free cash flow fell to $67.0 billion from $74.1 billion in fiscal 2024, on revenue that grew by more than a third over the same span. Microsoft is running harder and generating less cash. That is what a huge capital cycle does even to the best business in the world. Moody's projects hyperscaler capital expenditure of $785 billion in 2026 and close to $1 trillion in 2027, funded in part by roughly $175 billion of debt issuance this year. Where will the money come from…? Oracle: fiscal 2026 capital expenditure of $55.7 billion, free cash flow of negative $23.7 billion, capital expenditure at 82.6% of revenue, long-term debt up from $76.3 billion to $124.7 billion, and $248 billion of future data-center lease obligations not yet on the balance sheet. CoreWeave: $5.13 billion of 2025 revenue, $14.9 billion of capital expenditure, negative $7.25 billion of free cash flow, net debt at 8.1 times EBITDA, term loans at 11% to 15%, a weighted-average short-term borrowing rate of 12.3%, and a $1 billion private placement in April 2026 at 9.75%. Meta's Hyperion campus in Louisiana is financed through a special purpose vehicle in which Blue Owl Capital holds 80% and Meta holds 20%, funded by $27.294 billion of senior secured notes at a 6.581% coupon maturing in 2049. The noteholders have no pledge on the physical data center. Their credit is Meta's promise to pay rent starting in 2029, plus a residual value guarantee. Twenty-seven billion dollars of debt, secured by a lease, sitting off the balance sheet. And… like the EU’s finance minister explained two decades ago… “when it gets serious, you have to lie.” Microsoft extended server useful lives from three years to four, then to six, adding about $3.7 billion to fiscal 2023 operating income. Alphabet did the same, adding about $3.0 billion. Amazon added about $2.5 billion in 2024. Meta added $2.59 billion in 2025. Oracle added $573 million. Every one of those is a non-cash increase in reported profit produced by an assumption about how long a chip stays useful. It’s a lie. But not everyone is lying. Effective January 1, 2025, Amazon shortened the useful life of a subset of its servers and networking equipment from six years back to five, citing, in its own 10-K, "the increased pace of technology development, particularly in the area of artificial intelligence and machine learning." That cost it $1.4 billion of additional depreciation and $1.0 billion of net income. Amazon is the operator with the longest and hardest-won experience running data centers at scale, and Amazon is the one telling you the hardware wears out faster than the schedules assume. How could all of this spending possibly pay off? Bain & Company's global technology report puts it at roughly $2 trillion of annual artificial intelligence revenue by 2030, and calculates that even if every dollar of on-premise IT budget shifted to the cloud and every dollar of AI productivity savings were reinvested, the industry would still be about $800 billion short. Sequoia Capital's David Cahn, who has been running the same arithmetic since 2023, has escalated his estimate from $200 billion to $600 billion to roughly $840 billion. Against that: OpenAI's audited 2025 revenue was $13.07 billion, with an operating loss of $20.92 billion. Anthropic's 2025 revenue was $10 billion. Combined, $23 billion. And of every dollar spent on Nvidia systems, roughly 72 to 75 cents is Nvidia's gross profit. Data center is now 88% of Nvidia's revenue. The margin is not in the build-out. The margin is in selling to the build-out. What’s about to happen is obvious, because it has happened before. Between 1865 and 1873 the United States built the most consequential physical network in its history and destroyed an enormous amount of capital doing it. Track mileage went from 35,085 miles in 1865 to 52,922 in 1870 to 74,096 by 1875. Construction peaked at 7,439 miles laid in 1872. Railroad capital reached roughly $4.5 billion at a time when the entire banking system's capital was $720 million and the federal debt was $2.3 billion. In January 1870, of 896,596 shares traded on the New York Stock Exchange, 781,340 — 87% — were railroad shares. From 1870 to 1874, roughly 70% of all railroad securities issued in London were American. American rail bonds paid 6.5% when British consols paid far less, and European capital came for the yield. Every argument you hear today was made then, too. The railroads will transform the country. Yep, they did compress distance and cost of transportation in a way that seemed impossible only a few years earlier. And it didn’t make any difference. On September 18, 1873, Jay Cooke & Co. failed. Cooke had contracted to place $100 million of Northern Pacific 7.3% gold bonds, but sold less than $20 million. He ended up effectively owning 75% of the railroad he was supposed to be financing. And it failed. The New York Stock Exchange closed for ten days — the first closure in its history. By 1876, 134 railroads were in default on $500 million of bonds out of roughly $2 billion outstanding. By 1877, 20% of American railroad track mileage was in receivership. European investors are estimated to have lost around $600 million between 1873 and 1879. A very large fraction of the capital that built the American rail network was lost. And where the roads survived, competition took the returns. Revenue per ton-mile fell from 1.88 cents in 1870 to 0.73 cents in 1900, a decline of about 61%. Rate wars on the New York-to-Chicago corridor drove the through rate from $1.88 down to 25 cents, then 20 cents, and no pooling agreement stabilized the worst of it until late 1885. Every additional mile of track made the network more valuable to America and less valuable to the men who had paid for it. The AI build-out will have the same problem – but it will be much, much worse. Compute will be a pure commodity. Nobody disputes that the models are transformative. The problem is, that’s true of all of them. Which of the second-derivative names Aschenbrenner owned has route control, like a monopoly railroad? Bitcoin miners with retrofitted substations? Rented compute resold at a spread? Memory, an industry that has never once earned its cost of capital through a full cycle? Those are not toll booths. Those are the Northern Pacific just before bankruptcy. The railroads made a fortune – but not for their investors. Adams Express Company was incorporated in 1854 with $1.2 million of capital. It did not own a single mile of track. It bought space on other men's trains and moved parcels, money and valuables on them. By 1866 its capital was $10 million and it was paying an 8% dividend quarterly. By 1875 its capital was $12 million. It paid an unbroken $8 per share annual dividend from 1869 forward — straight through the depression that put a fifth of American rail mileage into receivership, and straight through the next one in the 1890s. American Express Company (NYSE: AXP) declared a $6 dividend in 1869, cut it to $3 in the depression year of 1877, restored it to $6 by late 1881, and held it there for the rest of the century. An 1888 board report showed ten-year net earnings of $26.24 million. By 1890, the express companies were handling more than 115 million packages a year over 174,535 miles of railroad and steamship routes. And they didn’t own a single locomotive or a single boat. Pullman's Palace Car Company was organized in 1867 with $1 million of capital. It did not own track either. It owned the sleeping cars and leased them to the railroads. Capital grew to $36 million by the early 1890s with nearly $25 million of accumulated surplus. Dividends ran 9.5% to 12% from 1867 to 1871 and 8% annually for decades after. In 1879, with 464 cars out on lease, it earned gross revenue of $2.2 million and net profit of almost $1 million. Pullman put out $1 million of equity and earned $1 million a year on a network that cost other people billions and bankrupted a third of them. Adams Express converted itself into a closed-end investment fund in 1929 and is still listed today as Adams Diversified Equity Fund (NYSE: ADX). The company that rented space on the railroads outlived almost all of them. I’d bet a lot of money that Leo had never heard of any of these businesses. But for people who are experienced in putting capital at risk, the pattern is not subtle or hard to understand. When an economy builds an expensive new network, the capital that builds the network earns a poor return because competition, obsolescence and overbuild strip it away. The businesses that ride on the network at near-zero incremental capital cost, and that own the customer relationship, the data or the standard, keep the profit. I’ve seen this entire act before, during my career. In the five years after the Telecommunications Act of 1996, carriers poured more than $500 billion into fiber, switches and wireless networks. By the early 2000s no more than 2% of North American long-haul capacity was in use. Global Crossing raised roughly $20 billion, built 100,000 miles of undersea fiber, filed for bankruptcy in January 2002, and saw its assets change hands for about $250 million — roughly 1.25 cents on the dollar of invested capital. WorldCom filed six months later, at the time the largest bankruptcy in American history. Who got the value? Google, Amazon and Netflix, which built businesses on top of bandwidth that had become nearly free because somebody else had already gone bankrupt providing it. By 2018 and 2019, Google and Facebook were funding roughly four of every five dollars of new transatlantic cable investment — buying the rails only once the rails were cheap and only once they owned the applications that made the rails worth owning. Leopold Aschenbrenner is not stupid. He is the opposite of stupid, which is part of the problem. He is a brilliant technologist who has never had to make a payroll, never had to explain to an auditor why the electronic records changed, never had to decide whether to spend eighteen months and $40 million ripping out a working system to save $200,000 a year in license fees. He looked at enterprise software and saw code. A businessman looks at enterprise software and sees the thing his company cannot operate without for a single day, priced at 1% of the employee who uses it, backed by a validated audit trail he would have to rebuild from scratch in front of a regulator, and running on a contract he signed for three years. An investor who has read a balance sheet from 1874 sees $220 billion of annual capital expenditure, an 8-times-levered reseller of rented compute borrowing at 12%, $27 billion of data-center debt hidden in a special purpose vehicle, and useful-life assumptions that the most experienced operator in the business is quietly walking back. The kid believed the technology determines the return. But it never has. It’s the capital structure that determines the returns: who controls the standards, who controls the customer, and who owns the data? Yes, the A.I. models will change everything. But that does not mean the people building the machines will be paid for it. The money will be made where it was made in 1874 and again in 2004: by the toll booths riding on top of somebody else's ruinous capital expenditure.

"Disparate Impact," the legal doctrine that stipulates outcomes between blacks and whites must be the same, was codified into law by the 1991 Civil Rights Act. That doctrine has destroyed the schools and the colleges and the police. It very nearly destroyed financial system when mortgages were awarded on the basis of racial quotas. And, as of this writing, it remains the operating doctrine of every major public American institution. It has not been repealed. It has been mildly rolled back in some domains — the Supreme Court ruling in SFFA, the state DEI rollbacks in Texas and Florida, the Trump administration’s executive orders — but it has not been uprooted. The people who believe in "equity" still staff HR departments, admissions offices, the civil-rights divisions of the federal agencies and the editorial boards of what used to be the newspapers of record. They will not go quietly. They cannot. Their entire professional identity is built on a doctrine that, if honestly examined, would be repudiated as nothing more than racial Marxism. So they will fight — inside the universities, inside the corporations, inside the courts, inside the federal bureaucracy, inside the cities they still run — for every inch of the ground the doctrine has captured. And the fight they will put up is one of the things that makes the coming Fourth Turning particularly dangerous. A Fourth Turning in which the political class is honest about what it has done — as FDR was honest about abandoning the gold standard, as Hamilton was honest about paying the state debts — can be resolved relatively quickly. A Fourth Turning in which the political class refuses to admit what caused the crisis and continues to fight for it is what leads to violence. Like during the Civil War of 1861-1865. And, sadly, I believe it will, once again, lead us into the equivalent of a race-based, low-level civil war. Why? Because there is no reform that fixes this. There is no tax increase that reverses disparate-impact jurisprudence. There is no interest-rate cut that restores public safety to Baltimore. There is no stimulus that teaches an Oregon high-school graduate to read. There is no political candidate who can, within the current legal and regulatory framework, restore the premise that individuals are to be judged as individuals and that the standards by which a society measures achievement are not themselves to be abandoned whenever they produce a disparity. The false doctrine, that individuals are not equal under the law because some people are functionally different than others, is embedded in statute. It is embedded in case law. It is embedded in the professional identity of three generations of administrators. It will not be uprooted by ordinary political means. It will be uprooted, if it is uprooted at all, by the same process that has uprooted every other entrenched false political doctrine in American history — by a Fourth Turning severe enough to make the doctrine’s defenders surrender ground they would never have surrendered in ordinary politics. And thus, you must be ready for what will come next. You cannot, by yourself, fix American public schools. But you can choose your children’s schools. You can homeschool them. You can place them in classical academies or Catholic schools or the small number of charter schools that have kept the older standards. You cannot, by yourself, fix the violence and mayhem in our cities. But you can own productive land. You can own real assets, directly, that will survive what's coming. You cannot, by yourself, fix the police. But you can choose where you live, you can choose whom you associate with, and you can prepare your family to defend itself and to help defend your neighbors. And you cannot, by yourself, fix the disparate-impact doctrine. But you can see it for what it is. You can teach your children to see it. You can refuse to participate in its rituals. You can decline to sign its loyalty oaths. You can, and this is perhaps the most important thing, tell the truth about it in public, in your own voice. How? By using the words it refuses to accept. “Marxism” is one of those words. “Per capita” is another – some groups are prone to violence, prone to ignorance, prone to abandoning their families. Pointing this out isn’t “racist.” It is identifying serious social problems that must be addressed and that cannot fixed by waving the magic wand of "disparate impact" or by an HR rule. "Responsibility” is a third. The entire racist agenda today is based on the idea that people can’t be responsible for their own lives because of racial oppression that ended more than three generations ago. The antidote to these lies is speaking the truth. Use these words. Do not flinch when the doctrine’s defenders accuse you of racism or bigotry. They are not interested in your character. They are interested in your silence. The doctrine has only ever had one real enemy, and it is not a political party or a candidate or a court. Its enemy is the plain speech of a free people. When free people describe what the doctrine has done — when they name it, in the ordinary language of their communities — the doctrine loses its power. Because its power was never in its arguments. Its power was in its capacity to intimidate people out of naming it. So, name it. That is the first political act of a Fourth Turning. Everything else that the country needs to do to get through the next decade — the monetary reset, the fiscal consolidation, the restoration of discipline in the schools, the re-policing of the cities, the rebuilding of standards across the institutions — depends on millions of ordinary Americans recovering the courage to call the thing by its true name. The true name is Marxism. The American form of it is disparate impact. Its consequence, measurable in the statistics of forty years, is the ruin of American institutions. The doctrine can be defeated. It has been defeated once before — in the Soviet Union, which built a more ambitious form of it at greater cost and collapsed under the weight of the contradictions it could not resolve. Ours is smaller and more refined and better camouflaged, but it is the same doctrine, and in the end it will collapse because of the same contradictions. The only question — the only question that matters, now — is whether we can name the doctrine and defeat it at the ballot box and in the courts and in the schools, or whether we will have to suffer a violent collapse of society. However it resolves, you must survive. The rest of this book is dedicated to helping you and your family survive whatever comes next.

Across 26 years, Berkshire Hathaway has invested $11.3 billion of capital directly into Berkshire Hathaway Energy, by acquiring MidAmerican Energy, Northern Natural Gas, Kern River Gas Transmission, PacifiCorp, and NV Energy. It has also continued to re-invest all of BHE's earnings back into the business -- that's another $50+ billion. These investments have produced have produced zero cash dividends for Berkshire. Not a nickel. And, in 2024, the value of these assets were written down by more than $40 billion when the estate of Walter Scott sold its interests. Today the entire remaining carrying value of the subsidiary is gravely at risk from a potential $50 billion wildfire liability. But, that's not the biggest risk. The biggest risk is the company's enormous (~$40 billion) investment into wind generation. Buffett and Munger believed in Peak Oil. They committed a massive amount of Berkshire’s capital over the past quarter-century to a strategy that was rational only if Peak Oil was correct. The strategy emphasized wind and solar generation, transmission build-out across western timber and rangeland states, and the gradual replacement of hydrocarbon-fired generation in service territories where customers would, the thesis assumed, increasingly pay premium rates for non-hydrocarbon electricity in a world of structurally rising oil and gas prices. But the Peak Oil was bunk, as any rational economist could have predicted it would be. Since 2005, U.S. liquid hydrocarbon production has increased 4x. The structural oil and gas price level fell, on a real basis, by approximately 50% over the period of the strategy’s implementation. The customer base that was supposed to pay premium rates for renewable electricity in a hydrocarbon-scarce world is, instead, demanding lower rates in a hydrocarbon-abundant one, and the regulators who set those rates have responded. Munger died in November 2023 still on the record believing oil and gas was “absolutely certain to be incredibly short and very high priced.” His Peak Oil thesis had been falsified, by an order of magnitude, in real time, in his own country, for a decade. The financial press, which has spent fifteen years celebrating Buffett’s late-life evolution into a clean-energy visionary (cue the Kumbaya music), has not, to my knowledge, published a single feature article questioning why BHE's carrying value was marked down by $40+ billion -- the largest capital loss in Buffett's entire career. The story is sitting in the open. I do not know why nobody else is telling it.

Berkshire Hathaway underperformed the S&P 500 by more than 30-percentage points over the last year! Berkshire's only annual performance that was worse was in 1999 -- during the Internet mania. Today, though, Berkshire owns Apple and Google, unlike in 1999 when it didn't own any tech stocks. So, what else could explain the company's declining performance? More than a decade ago, researchers at AQR ran a series of regression studies across 30 years of Berkshire's public stock investments to discover which factors drove Buffett's outstanding investment results. They discovered -- to no one's surprise -- that Buffett buys ultra-high quality, large-cap, low-volatility stocks that are extremely cheap. But that's not all they discovered. They also disaggregated Buffett’s portfolio into two distinct sleeves and then ran the same the regression studies on each separately. The public sleeve is the portfolio of publicly traded stocks held inside Berkshire’s insurance subsidiaries — disclosed quarterly in SEC Form 13F filings. This is what most financial press coverage focuses on. The Coca-Cola, the American Express, the Apple, the Bank of America. Over the full sample it averaged about 35% of Berkshire’s total capital. The private sleeve is the portfolio of wholly-owned operating businesses — See’s Candies, Nebraska Furniture Mart, GEICO after the 1995 full acquisition, BNSF after 2010, Berkshire Hathaway Energy, Dairy Queen, NetJets, Precision Castparts, the whole roster of consolidated subsidiaries. Over the full sample the private portion grew from under 20% of Berkshire to more than 78% today. Berkshire was once an insurance company with an equity portfolio. Today it’s an insurance company owned by a conglomerate. And here's why that matters. The public sleeve — the portfolio of stocks Buffett bought fractionally and held — earned an average excess return of 12.0% per year at 16.2% volatility. Sharpe ratio: 0.74. The private sleeve — the portfolio of whole companies Buffett bought outright — earned an average excess return of 9.3% per year at 20.6% volatility. Sharpe ratio: 0.45. The publicly traded pieces of companies Buffett owned delivered materially better returns, especially when compared against the risk taken. The private sleeve’s Sharpe ratio of 0.45 is, remarkably, lower (worse) than the broad market’s 0.49 over the same period. In other words, when Buffett bought pieces of great public companies, he outperformed. When Buffett bought whole private companies, he did not. The private sleeve’s drag on Berkshire’s overall performance is meaningful. That drag was smaller in the early years, when the private portfolio was only 20% of the business. As the private sleeve has grown to 78% of Berkshire’s capital, the drag has grown proportionally. The declining Sharpe ratio of Berkshire over time — which every long-term shareholder has felt, even if they could not name it — comes primarily from the growing share of capital trapped inside whole-company acquisitions that underperform the public-market alternatives Buffett could have bought instead. Learn more about Warren's Mistakes and how to learn these lessons to improve your own investing in my new book.

Here's the #1# thing most people don't know about Warren Buffett: There is nothing special about Buffett’s stock picking. That doesn’t mean that Buffett wasn’t a great investor. He was! Buffett was, by far, the greatest investor in history, by a huge margin. Over 486 months between October 1976 and March 2017 –— 41 years –— Berkshire Hathaway’s Class A stock earned an average excess return of 18.6% per year above U.S. Tbills. Annualized volatility was 23.5%. Sharpe ratio: 0.79. Berkshire’s Sharpe ratio of (0.79) is roughly 1.6x times the broad U.S. stock market’s Sharpe ratio of 0.49 over the same period. Among all large-cap U.S. stocks and mutual funds with 30-plus-year continuous track records, those are unmatched numbers. A dollar invested in Berkshire on October 31, 1976, was worth more than $3,685 by March 31, 2017. A dollar invested in the S&P 500 with dividends reinvested over the same period was worth approximately $76. Buffett beat a passive index by a multiple of 48. But he didn’t do it with stock picking! Three researchers at AQR Capital Management –— Andrea Frazzini, David Kabiller, and Lasse Heje Pedersen –— dissected Berkshire’s 50 years of investments through 2013. They expanded and republished their findings in 2018 in the Financial Analysts Journal, which is the most highly respected industry financial journal. Their work won the Graham and Dodd Award for the best published paper of the year. The paper is called Buffett’s Alpha. They found, after accounting for cheap leverage (from the insurance float) and exposure to a handful of publicly documented factor premiums, Buffett’s investment skill –— the portion of his returns that cannot be explained by any mechanical strategy –— is 0.3% per year. That's statistically indistinguishable from zero. In other words, the alpha that Berkshire enjoyed for 50 years (as it compounded capital at 24% a year!) wasn’t due to Buffett’s stock picking. So, how did he do it? He did it by gaining access to a huge amount of investment capital that he did not own, for free. Buffett’s track record was built on leverage. That’s a dirty word for most investors, but it's the secret behind Berkshire. The AQR researchers had access to something most Buffett commentators do not: 40 years of Berkshire’s audited financial statements and the full quarterly history of the public 13F stock portfolio. The researchers asked a specific question: If I take Berkshire’s monthly stock returns from October 1976 through March 2017, and I run a linear regression against a set of well-documented risk factors –— market beta, size, value, momentum, and two newer factors called Betting-Against-Beta and Quality-Minus-Junk (detailed below) –— how much of Buffett’s performance can the factors explain? And after the factors have been stripped out, how much excess return remains? The data show clearly there are a few qualities that drove Berkshire’s results. First, Buffett has always preferred large-cap stocks, contrary to the popular image of him as a small-cap value investor. He buys elephants. Second, no surprise, Buffett buys cheap. Berkshire is almost six standard deviations away from neutral on the value axis. So far the picture is ordinary. Every large- cap value manager in America loads positively on size and on value. Buffett’s genius lies in the last two factors. These last two factors are a little complicated, but please stick with me. There’s a new factor, that, like value and size, characterizes Buffett’s strategy. It’s called Betting-Against-Beta (“BAB”). What it means is intentionally investing in stocks with very low volatility. The BAB factor captures the excess return that accrues to investors who own low-beta stocks. Low-beta stocks have historically earned higher risk-adjusted returns than high-beta stocks. Financial theory teaches that higher beta (higher risk) should mean higher return. But it doesn’t. The opposite occurs, in fact. And Buffett was one of the very first people to figure this out. Why does this factor persist? In an efficient market, once that factor is known to investors, then they should bid the price up on low- beta stocks until it no longer provides an edge. The explanation, per the theory of AQR’s Frazzini and Pedersen’s theory, is that because ordinary investors do not use leverage and seek high returns, they create persistent excess demand for more volatile stocks. (Having worked with retail investors for 30 years, I can assure you that is true.) But, an investor with access to cheap leverage –— Warren Buffett, for instance –— can exploit the mispricing by owning the low-beta names and levering them up to produce market-beating returns. And the last factor that matters to Buffett is quality. Buffett buys companies with high returns on invested capital. Quality-Minus-Junk (“QMJ”) is a factor described by Cliff Asness, also at AQR with Frazzini, and Pedersen, in a 2019 paper in Review of Accounting Studies. The QMJ factor captures the return to owning stocks of high-quality companies –— profitable, growing, safe, with high payout ratios –— against stocks lacking those characteristics. QMJ has been positive and statistically significant in every major developed equity market for which it has been measured. Berkshire’s loading is 0.37, with a t-statistic of 4.6. –– meaning it is highly significant to Berkshire’s results. In plain English: Buffett only buys large, high- quality, low-volatility stocks of the highest quality. But, Berkshire’s results were not, in any way, unusual. Any investor buying these same kinds of stocks would have earned those same returns –– about 16% a year over time. So how did Berkshire compound at 23% a year? To figure that out, AQR’s researchers built a Berkshire replica. They constructed a simple, rules-based, publicly investable portfolio that mechanically tilts toward large-cap, cheap, low-beta, high-quality stocks, and levers it 1.6- to- 1 to match Berkshire’s insurance float leverage. The correlation between their replica’s returns and Berkshire’s were virtually identical. The authors’ conclusion is unambiguous. “In summary, we find that Buffett has developed a unique access to leverage that he has invested in safe, high-quality, cheap stocks and that these key characteristics can largely explain his impressive performance.” Berkshire’s cost of insurance float has averaged almost three percentage points below the Treasury bill rate across 50fifty years of data. In roughly two-thirds of all years, Berkshire has been paid to hold other people’s money. That is not an investment strategy. That is a financing miracle. It is also the living, breathing heart of Berkshire Hathaway. It’s what Buffett built, starting in 1967 when he paid $8.6 million for National Indemnity’s $19.4 million of float. And it is the factor every retail investor admiring Berkshire’s returns has never paid any attention to. The 1.6-to-1 leverage that AQR measured over the full period, financed at this negative cost, explains the dollar magnitude of Berkshire’s returns. How do we know? An unleveraged version of the same stock portfolio –— which you can approximate by looking at the 13F holdings alone –— has earned an average excess return of 12% percent per year. It’s Berkshire’s leverage that magnifies this excess return to 18.6 %percent. How does this square with Berkshire’s reported gains? Berkshire’s 18.6% excess return, plus the T-bill rate that averaged roughly 4.7% over 1976–2017, gives you a total nominal return of roughly 23% per year, which is the figure you usually see quoted for Berkshire’s historical performance. The 23% tells you what Berkshire returned. The 18.6% tells you how much of that return was compensation for taking investment risk, as opposed to the baseline yield every lender to the U.S. government was earning anyway. With both of Berkshire’s “edges” –— systematic factor exposures to cheap, high-quality, low-volatility stocks and roughly 1.6-to-1 leverage delivered with insurance float –— you get Berkshire Hathaway’s 23% annual gains over 60 years. It’s the structure that’s genius, not the stock picking. And that's very important because it means the original Berkshire formula can work for any investor. I show you exactly how, in my new book.