The Commanding Heights

Scarce, controllable positions of economic power whose holders durably capture the gains of increasingly capable and diffused intelligence.Scarce, controllable positions of EconomicPower whose holders durably capturethe gains of IncreasinglyCapable and diffusedintelligence.

Will Manidiswill@willmanidis.com & Joe Robertsjoe@josephjcroberts.com

We also thank the following, who have given feedback on this document or shaped its ideas, with no presumption of endorsement:

Shyam Sankar, Sriram Krishnan, Michael Kratsios, Jeff Huber, Patrick O’Shaughnessy, Ravi Gupta, Samay Shamdasani, John Aristotle Phillips, Jamie Cox, Zack Baker, Jeremy Giffon, John Fiorentino, Justin Mares, Nabeel Qureshi, Samir Unni, Clark Minor, Dan Ashton, Paul Rice, Austin Bishop, John G Kennedy, Nick Abouzeid, Alex & Talia Immerman, Chauncey Hamilton, Zann Ali, Lucas Vaz, Josh Buckley, Max Meyer, Tomás Pfeffer, John Dulin, Charlton Boyd, Ben Braverman, Louis Mosley, Zane Dille, Isabella Garcia-Camargo, Will Reed, Zoe Taylor, Bala Chandrasekaran, Chad Byers, Pratyush Buddiga, Salen Churi, Cody Kittle, and foreign correspondents C.S., D.P.M., and C.V.

Abundant machine intelligence diffuses into Bangalore.

Technological revolutions are almost never born where they ultimately create wealth. Gutenberg went insolvent, and the great railroad fortunes were captured by men who never built a locomotive. New frontier models become commodities within months, so the most lasting wealth will accrue to those positions that intelligence must pass through to reach its utility. We call these the Commanding Heights.

The Genesis of intelligence is composed of the industry that makes and serves models, and it will keep spending on itself even as returns fall. Rational capital allocation at the level of the lab or hyperscaler can destroy capital in the aggregate. Intelligence’s tremendous revenues still come from early adopters deploying models into existing workflows. As with the railroads, the larger fortunes will be captured outside Genesis, by those who control how models reach the far larger economy they create.

The American future depends on AI spending, stock prices, and model capability rising together as one line: the common exposure beneath growth, household wealth, and credit. The imperative means it will. Training costs rise ~3.5x a year, and Washington will utilize increasingly central backstops such as retirement savings and the Treasury to guarantee its continued rise, even as impairments occur throughout Genesis.

America and China will become the only countries capable of sovereign expression because only they can continually develop frontier models. Intelligence will splinter into a commercial and sovereign frontier, with the latter being locked behind SCIFs and developed by lab subsidiaries for statecraft, not cash flow. China can publish cheap open-weight models and accept low valuations for its labs because it is not subject to the American 401(k) class. These sovereigns will exercise control over model-producing firms without formally announcing nationalization.

America’s greatest power in the age of intelligence will be the Dollar. Abundant models will manufacture near-unlimited demand for a newly global, stablecoin USD, the Neo-Dollar. Global participants replacing their local currency with Neo-Dollars would not have been banked in the USA, but indirectly hold Treasuries nonetheless. The American sovereign will use this new demand to help carry its costs through debasement, while the owners of these new economic channels will collect a toll that rises with inflation.

The diffusion of intelligence has begun in the rich world’s back office, turning work meant to develop poor countries into margins booked in New York. Citizenship and licensing will protect workers in rich AI-surplus countries, while many others will lose their jobs and emigratory escape paths. The K-shape will ever widen, and Main Street’s vibecession will continue as the riches of diffusion accrue to the Gulfstream backlog.

The Commanding Heights are scarce, controllable positions of economic power whose holders durably capture the gains of increasingly capable and diffused intelligence. In 1922, Lenin defended concessions to private trade on the justification that the state still held “all the Commanding Heights,” the vital branches of the economy through which all else flowed. Unlike fleeting bottlenecks, a Height durably captures a share of the economic activity it enables, and the multiplication of that activity further entrenches the Height.

Economic activity is organized around firms, their shape evolving with each technological revolution. The originary owner-operator, the manager-employee, and shareholder-disciplined firm each had their era; the last has been made obsolete by intelligence. Tomorrow, firms will be composed of a few operators, paid and governed like capital, directing work done mostly by models. Venture becomes trading, private equity is refashioned to diffuse model capability, and the sovereign re-settles its obligations to the private sector.

Investors will find false security in owning the last era’s Commanding Heights and financing this era’s inventions, because both miss what comes next. Even Buffett mistook one era’s economic settlement for a permanent position, buying newspapers through 2012 and selling them all in 2020 for less than half of what he paid. Only reconstructed portfolios, composed of re-mandated managers, will have a chance at laying claim to the new Commanding Heights while they can still be purchased.

Ravi wakes up at 5:56 AM to light tapping on the window. It is the rainy season, and his upper-middle-class apartment in Bellandur, which usually has such expansive views of Bangalore, is cloaked in fog. His wife is still asleep next to him, and he is careful not to wake her as he dresses. He clutches his buzzing phone.

Ravi is a proud graduate of the Indian Institute of Technology Madras, one of the top technical universities in India. He is among those who remained after graduating fourteen years ago. Others went to Europe, Canada, or America, but Ravi saw a bright future in the growing skyscrapers and the promise of nearly 1.5B Indians climbing up the ladder of modernization. He moved to Bangalore, fell in love, married, and had a daughter. He began doing systems implementation at a multinational firm that primarily did back-office accounting for American clients. He slowly rose up the corporate scale, promotion after promotion and incremental salary raises affording a better life than most. The rest of his career, his life, is laid out predictably before him like the table set he sees in the morning light as he moves through the kitchen, pouring tea.

The phone continues to buzz. His work has been speeding up and ballooning in scale. He’s managing delivery for five North American insurance clients. Usually it’s just one or two. It’s all because of AI. In practice the company calls it “accelerated outcome strategies,” a very nondescript term, but it means Ravi is managing more and more automated processes. He is used to overseeing people. These days, he’s just doing quality assurance on enterprise accounting systems powered by artificial intelligence from China. Graduate intake to the company has been paused for a year, and the fresh minds from the IITs are no longer coming in. In the last month, three departures alone on his team of fifteen. They won’t be filled. He’s been getting requests to help friends find work, but he doesn’t have time to answer. The agents never sleep. Now, neither can Ravi. Late nights at the office and early departures. It’s been like this for months, and his marriage is strained. But business is booming. Margins for the company have been steadily growing. He’s making more than ever.

He checks on WhatsApp as he waits for his driver in the lobby of his building at 6:22. He recently purchased a subscription to an AI tutor for his daughter and took her out of the reasonably pricey private English-medium school. He can oversee her curriculum from the app. He doesn’t look up from his phone, buzzing with incoming reports from agents that he signs off on without reading as the driver opens the door. He hardly reads the reports anymore; the agents are good enough. The car silently glides past the galvanized steel gates and new concrete walls that surround his safe, hard-won, upper-middle-class residential complex right at 6:25.

The driver puts on BBC as they roll onto a six-lane highway jam-packed with other drivers. Still raining, a certain tension in the air. English words, a polished Indian accent. The weather will clear up around mid-afternoon. New scientific discoveries announced from the sequestered American machine intelligence conglomerates. The breakdown of law and order in Lagos, aid to Indonesia.1 The Philippines has been downgraded from an emerging market to a frontier market. The riots in India are getting worse. The Prime Minister in a press conference says there’s nothing to worry about. The country’s future remains as bright as ever. India has immense potential, he says, and it will only be realized by utilizing the best in modern technology and boosting productivity. Then, to coverage from the night before. Unrest in Hyderabad, Gurugram, and Pune. Dismissed workers barricading themselves in an office in Chennai. Lynchings. It’s reminiscent of the unrest earlier in the year in Jakarta that toppled the government. Comparisons to the farmers’ protest seven years before. The noise is too loud, and Ravi needs to focus on monitoring his reports. He asks the driver to shut it off.

1 This, after a 40% fall in Indonesia’s markets on the year and a downgrade in rating from emerging to frontier market. Get ready for more.

Ravi enters his office complex on the Outer Ring Road near Devarabisanahalli at 6:44. The lights flick on automatically, and he doesn’t notice that it’s strangely empty, even at this early hour. He has an office with a door and a view, though he doesn’t face the window. He replaces his phone with a three-screen setup so as to better monitor his agents. He can’t see them doing anything, of course, but rather gets progress updates, finalized versions, requests for permission that he blindly approves. Why wouldn’t he? In the months that he’s been doing this, there has never been a mistake on the part of his agents. His employees required constant monitoring, but it was different. Ravi would circle the cubicles, check in on the state of spreadsheets and deliverables, and dispense praise and admonishment in equal measure. Now, his agents are completing tasks in hours that would have taken his subordinates weeks. Ravi continues to approve and skim over reports.

At 9:15, the SENSEX opens to a new record high. It’s the fifth time this month. Ravi might otherwise take notice, but he is not in the market. Most of his wages go toward maintaining the mortgage on his apartment. He purchased it six years ago, and it won’t be paid off for another seven. He needs to provide daily necessities for his wife and daughter and pay his driver and housekeeper. Comfort, even with his education and job, is not inexpensive, and that leaves little for owning equities.

At 9:30, Ravi tears his eyes away from the approval enterprise software and joins an all-hands conference Zoom session for management. A man appears in an office that Ravi has never seen before. It’s sunny. He makes an announcement in a hurried tone, the only one on the call with sound enabled. Margins are increasing. The firm has a very bright future, buoyed by productivity growth even amid a challenging environment for firms like Ravi’s. Those back offices behind the back offices. Separated by thousands of miles and several oceans from their customers.

In an equally upbeat register, the CEO of the America-listed outsourcing company that owns Ravi’s firm announces that the entire corporatio