America, the Beautiful

## Editorial

My friend Om Malik passed away just over a week ago. The post of the week is one of hundreds of testimonials written about Om.

Over 10 years ago now I spent a few days in Iceland on a photography road trip during an event we were both speaking at.

He also took this photo of me at the airport.

It is one of my favorites.

Om was a kind, gentle, but highly motivated individual with high standards for himself and others. I will miss him. And his love of photography, especially Leica cameras.

Kindness and intellect are two compelling human qualities. As we look at the future of America, almost 250 years old, Om’s qualities are a great test for the people we want our society to generate. People who are highly focused on outcomes, but are sincere, kind and open. Abundance creates those kinds of people. Let's consider the question of today’s America, the AI boom, and the future it can bring if we make it happen.

America is rich. But do we know what its wealth is for?

There has always been a relationship between economic success, society and life experience, and personal freedom. Abundance is the word that for me, describes the combination.

GDP alone, the stock market, the number of millionaires are not the key elements of a society based on abundance. Abundance is the ability of a society to turn wealth creation into better lives, more agency, more choices, more time, more safety, more ownership, and more freedom. Read Doc Searls this week. He is clear on these goals.

And that is the story of this week’s issue.

Scott Nolan’s essay, “America’s Next 250,” is the natural place to begin. He reminds us that 1776 was not a romantic paradise. It was a country without electricity, antibiotics, anesthesia, refrigeration, weather forecasting, standardized time, or real-time communication. Even the richest people alive then lived inside constraints that ordinary Americans today would find intolerable.

James Pethokoukis makes the same point from a different angle. George Washington was the richest American of his time, but he could not buy air conditioning, antibiotics, smartphones, television, modern dentistry, or the ordinary comforts of a middle-class life in 2026. Pethokoukis quotes the economists Philip Trammell and Charles I. Jones, who find that American lifetime well-being has risen roughly “five- to sevenfold since 1940,” far more than traditional consumption measures suggest.

That is the first point. Abundance is not just money. It is what money, technology, institutions, energy, and freedom make possible in the experience of life. Human progress is really all about these human goals.

The Wall Street Journal story on millionaires reports that the U.S. added more than 440,000 millionaires in 2025, “more than 1,200 a day,” nearly half the world’s new millionaires. You may assume that is a complaint. But really it is a measure of capacity.

More millionaires means more founders, more angels, more customers, more local capital, more risk-taking, more philanthropy, more households with choices, and more people able to say no. Wealth creation is not the endpoint of abundance, but it is one of its engines. Millionaires are produced by success, and success is the precondition of a healthy society.

Wealth is not something separate from freedom. Economic success changes the life experience of people. It changes where they can live, what they can learn, what risks they can take, how much time they can buy back, how much dependency they can escape, and what they can build for their children. When it works well, wealth is not merely accumulation. It is agency. And the gap between wealthy and poor is best addressed by wanting all to be able to benefit from wealth, not attacking those that have it. Bill Gates once coined the phrase ‘embrace and extend’. It seems pertinent in this context.

Back to Doc Searls. He gives the human version of this argument in “The First Source of Personal Intent.” His concern is that AI could either expand personal agency or contain it. On one side are surveillance, inference, guesswork, and corporate agents that try to manage people inside other people’s systems. On the other side are personal agents “owned and operated by independent people.”

That is exactly right. If AI is going to produce abundance, it cannot simply make companies more efficient at predicting, pricing, and manipulating customers. It has to make individuals more capable. It has to increase our ability to express intent, control data, protect privacy, negotiate with institutions, and act in markets as first-class participants.

In Searls’ older language, relationship management should become two-way. In the AI era, that means personal AI and personal privacy. The customer should not just be an object in the vendor’s CRM. The citizen should not just be an object in the state’s database. The person should be more powerful.

That optimistic version of AI comes into several pieces this week, showing why optimism is not crazy.

Ethan Mollick writes about “the twilight of the chatbots.” The interesting AI story is no longer a box where you type questions and receive answers. It is agents doing work. Mollick cites a striking example: Claude Opus 4.7 autonomously worked for 14 hours and produced a package estimated at “two to seventeen weeks” of human engineering work for “$251 in tokens.” He also notes that OpenAI’s own internal study found a quarter of employees running at least four agents in a week.

Exponential View widens the lens. Fifty years of Moore’s Law was not fast enough for AI. Compute stock has grown at a “66% compounded annual growth” rate, but the real break came with accelerators becoming “FLOP-factories.” The point is not only that models are getting stronger. It is that the unit of work is changing. Every frontier employee can become the manager of agentic teams.

These developments are the engine of abundance, at least in embryo. Why? Because more people should be able to do work that previously required a large company, a large budget, a large lab, or a large bureaucracy. The frontier of doing hard things will move closer to the individual.

But that is not automatic.

Paul Krugman worries that AI may damage minds if it becomes a substitute for reasoning rather than a tool for it. His concern is learning, not cheating. He thinks that students who outsource thinking do not learn to reason through evidence, form conclusions, or handle the moments when AI is wrong. If true that would be a serious abundance problem, because freedom without capability is thin. But in reality the use of AI tools to gather, sift, consider information will have the opposite effect. Reasoning will be more available and will take new, faster, learning forms. The aggregate of human reasoning is exploding. AI is the tool that permits it.

The Stanford/ADP labor-market work raises another fear. If AI makes entry-level jobs disappear before young people can build judgment, then society gets efficiency without apprenticeship. Again, a misnomer. Young minds will learn faster than ever. Look at how YouTube is already used to teach skills previously only open to specialists. Now anybody can become a specialist.

That is part of abundance. Mass, distributed learning at speed.

The skeptics do not have a case. They have a fear.

AI can’t concentrate power because it is only as good as the humans that create and direct it. It can’t weaken learning because it is a new tool for learning. It can’t turn work into monitoring because workers will not tolerate employers who see it only as that. It can’t hand more leverage to platforms because without human use the platforms are just data warehouses and server farms.

These fears lead to the call to slow everything down. The answer is to accelerate as fast as possible but to also ask what kind of abundance we are building.

The Cosmos Institute piece on scientific breakthroughs is useful here because it reminds us that knowledge is not only text. Above the surface are papers, patents, preprints, and data. Below the surface are lab notebooks, failed experiments, instrument know-how, corridor conversations, and “deep craft.” AI will not make science abundant by scraping the surface and pretending that is the whole iceberg. It has to connect to people, tools, labs, tacit knowledge, and institutions. Indeed, under the hood there is only human achievement.

The same is true in software and business. USV’s “Rebel Alliance” argues that “the AI opportunity is too big and too important to be owned by any one company.” Agents, they argue, are “inherently distributed.” That is true. A distributed agentic economy is a driver of the abundance frame: more layers, more builders, more composability, more competition, more user choice. But you don’t have to be against OpenAI and Anthropic for that to be true.

Logan Kilpatrick at Google DeepMind makes the opposing case in the most interesting way. The Google tool Antigravity, he says, is “the same harness” powering agent features, and over time “the model eats that scaffolding.” That means the model itself may absorb more of the layers above it. The USV version is modular. The DeepMind version is gravitational. The former produces a rebel alliance. The latter produces platforms. Both co-exist in the real world and both are ways to empower humans to get stuff done.

This is an academic distinction. Who owns the abundance does not come out of the operational model of AI. That is a societal decision about distributing the proceeds.

The idea that if the models eat the stack, wealth and agency concentrate is only true if there is no distribution of outcomes. The idea that if the agentic world stays layered, open, and competitive, the opportunity spreads is also too dogmatic. The focus should not be on favoring architectures, but favoring who benefits from the wealth created.

That is why venture capital is splitting into at least two markets. See Gené Teare’s article this week.

Some companies are raising because they sit near the foundation models, compute, infrastructure, and frontier capability. Others are trying to build application companies in a world where the model layer may move faster than they can. Capital is trying to figure out where durable value lives. The answer may be - all of the above. But the real question again, is who benefits?

Which brings us to Sam Altman’s reported 5 percent offer.

The Verge, citing the Financial Times, reports that OpenAI floated giving the Trump administration a “5 percent ownership stake” in the AI boom. At OpenAI’s reported $852 billion valuation, that would be worth about $42.6 billion. The context matters. The government has taken a stake in Intel. It has discussed revenue shares on Nvidia and AMD China chip sales. Bernie Sanders has proposed a 50 percent stock tax on AI gains to fund a sovereign wealth fund.

This is relevant because once the wealth is large enough, politics arrives.

Altman’s instinct is understandable. If AI creates trillions of dollars of value, the public will ask who benefits. A public claim on upside may be a way to distribute the upside of growth.

But a government equity slice of 5% is a very incomplete and inadequate answer to the abundance problem. It may share some financial upside, but it does not necessarily create better lives, more agency, or greater freedom. It may even strengthen the bond between frontier companies and the state in ways that make competition harder. Not many tweaks would be needed to make it a real game changer.

1. Make it 75% 2. Make the Sovereign Wealth Fund a shared asset of every citizen via share ownership from birth. Not a centralized bureaucratic VC-like fund. 3. Enable dividends to be paid to all shareholders (that is everybody) 4. Extend this idea beyond the citizens of a single country. 5. Don’t think nationalization, think distribution of the legacy of human progress to all using a decentralized model.

Bill Gurley put the darker version bluntly: “When you can’t win on the field go to DC.” That is the danger. If public upside becomes a Washington bargaining process, abundance turns into permission, protection, and cap-table politics. The companies should lead this effort. Without that legitimacy will be hard.

The right question is bigger than whether the state gets 5 percent. The right question is how the wealth created by AI becomes widely held capability. Do citizens get better services? Do workers get better tools? Do founders get access? Do customers get more power? Do students get better learning? Do households get lower costs? Do patients get better care? Do individuals get personal agents that serve them, not just companies that sell to them?

That is the difference between redistribution after the fact and abundance as a design principle.

Adam Tooze’s China pieces show the opposite problem. China has vast productive capacity and an AI boom of its own, but wealth is walled inside capital controls and political constraints. The next China shock is not the old free-trade story. Tooze calls it “mercantilist-on-mercantilist violence.” That phrase matters because it captures a world in which great powers try to manage prosperity through walls, subsidies, controls, and retaliation.

America should not copy that reflex. Nor should it copy Europe’s instinct to regulate first and discover later. Nor should it allow California-style abundance politics, where wealth creation is tolerated only after it has been morally scolded, taxed, delayed, litigated, and made unaffordable to live near.

The immigration piece in Rest of World belongs in the same frame. America’s immigrant tech workers are paying an “uncertainty tax.” H-1B registrations fell 38.5%. This is madness if the real project is abundance. A country trying to win the next 250 years should want talent, capital, energy, ideas, and ambition to move toward it.

Infrastructure is the other hard constraint. AI requires new materials, more energy, more grid capacity, more cooling, more data centers, and more physical competence. We lose too much electricity in transmission. We build too slowly. We argue about abundance while tolerating the bottlenecks that make it impossible.

This is why America at 250 needs to embrace rapid progress to free and plentiful energy and ubiquitous AI. The next breakthrough is not only in software, it is energy, materials, compute, biology, manufacturing, science, capital markets, immigration, education, and personal agency. AI is the accelerator, but the story is human progress.

Can America convert frontier technology into a better life?

That means wealth creation, yes. It means new millionaires, yes. It means startups, venture capital, and public markets, yes. But it also means lower costs, better health, more learning, more ownership, more privacy, more personal power, and more freedom. And as we automate away jobs it means more leisure and more choice over how to spend the real asset - time.

Abundance is not a spreadsheet. It is the lived relationship between economic success, life experience, and personal freedom.

At 250, America’s challenge is not simply to become richer. It is to turn AI, capital, energy, and frontier ambition into a civilization where more people can afford more, learn more, build more, own more, choose more, and become more. That is not only an American dream. It is a human dream. And it is clearly attainable over the next 250 years.

That is the version worth building for.

RIP Om Malik