What is the End Game?
Politics Needs to be About Defining the Future.
### Editorial
### What is the End Game?
#### Politics Needs to be About Defining the Future.
AI is getting more capable in helping humans achieve goals. Agents are becoming a core part of much work. And politics is entering the room, especially this week. Money is moving, campaigns are forming, think tanks are sharpening their positions, regulators are arguing, and the companies building the systems are trying to shape the terrain before it shapes them.
Before politics becomes the center of gravity, there is an overriding question for us all to focus on: what are we building?
I do not mean that as a product question. I mean it as a societal question. If we do not answer that now, then any policy is likely to be impossible to judge. We need an end game to be aiming for, and then, and only then, a path to getting there.
AI is no longer only a technology story. It is becoming a story about work, wealth, power, access, infrastructure, and institutional competence. If cheap intelligence becomes a general-purpose input into the economy, then the important argument is not simply how to monitor the technology. The important argument is how to benefit from it, and that means all of us.
That is where I think too much of the political intervention into the AI discussion is wrong.
The worst of politics is showing up. The reaction to fear, the short-term focus on popularity, just when the best of politics is required. The defensive version wants to monitor, slow, posture, moralize, litigate, and fundraise from fear. The better version would ask how AI can lift everyone, and everything, up.
That is the conversation we are not having loudly enough.
This issue has several threads, but they all point at the same answer. Build first. The future needs to be built. It will not simply arise, or at least not a good one.
But building is not neutral. Every agent, every data center, every model release, every campaign dollar, every think-tank memo, every new fund, every energy deal, and every product decision is part of the same social construction project.
The builders should build. Free from anything that introduces unnecessary friction.
Politicians should not pretend they can inspect every model into safety.
But politics does belong here because the future of society now relies on the future of AI. The right political question is to ask how to make sure the future, once built, is a step forward for civilization broadly defined.
The week starts with the companies themselves. The New York Times reports that the AI policy fight has moved into super PACs, with one side saying, in the headline, “This Is a War.” That is a useful sentence, not because I want AI policy to become a war, but because it reveals what has already happened. The argument is no longer academic. It is electoral. The companies and their allies are buying political terrain.
The Wall Street Journal’s Anthropic story pushes from the other direction. Anthropic is warning about “self-improvement” risk and urging a global pause under certain conditions. That is not a trivial concern. If AI helps build better AI, then the development cycle compresses. Good things happen faster.
Governance gets harder. Verification gets harder. The international problem gets harder. But beware the instinct to slow things down. No good outcome down that road.
Of course risk exists. The question is whether our politics are capable of responding to risk without turning abundance into permissioned scarcity.
That is why I am more interested in distribution than monitoring.
If agents make companies more productive, who owns the productivity gain? If cheap intelligence lets small teams do the work of much larger ones, who gets the leverage? If AI increases returns to capital, compute, data, energy, and distribution, how do workers, students, small businesses, cities, and public institutions participate?
This is not anti-builder. It is the only pro-builder politics that can last. Builders have to be embraced by everybody if they are to succeed. For that to happen, their work needs to be for everybody.
The AI section this week makes the operating change concrete. Tomasz Tunguz asks, “how much intelligence do you get per dollar?” That is the new economics. Jason Lemkin’s OpenRouter piece says agents have passed humans in token usage. The cost model of AI is shifting from people typing into chat boxes to agents burning context, tools, retries, and workflows. Microsoft is building evaluation and control standards for agents. Production-agent teams are building operating loops. Forward deployed engineers are becoming the field unit of the AI company.
In other words, the model is not the product. It is infrastructure. The product is work, or automated work. The social outcome of that is also the product.
Social outcomes create institutions. Ted Chiang’s Atlantic essay is useful here because it cuts through the mysticism. AI may be economically important and socially disruptive without being conscious. The moral subject is still us. We have to decide what we want. Then organize to get it.
That makes the policy question clearer, not easier. We should not build a politics around pretending the machine is a person. We should build a politics around the human systems that deploy it.
Bernie Sanders argued for imposing a one-time 50 percent tax on the stock of leading AI companies, such as OpenAI and Anthropic, to establish a “sovereign wealth fund.” This would give the government a large ownership stake and board representation, ensuring AI development benefits all of humanity. If he had given actual families those shares, and if it was closer to 80 percent, it may be the start of a good idea.
Last week Elizabeth Warren argued for high taxation. She proposed an overhaul of the tax code that includes an excise tax on the heavy energy used by AI data centers. The goal is to recoup economic gains for working families and offset tax incentives that currently encourage companies to replace human workers with AI.
Representative Greg Casar, a Democrat from Texas, proposed an AI “token tax,” using a unit of measurement for AI processing data. The revenue generated from this tax would directly fund a New Deal-era style federal jobs program for Americans displaced by automation.
All of these suggestions have the right spirit: use the benefits to uplift us all. But all are centralized, asking government to seize ownership in one way or another.
What is required is a decentralized mechanism, giving everybody their share of the upside of AI. Robert Heinlein’s “Human Heritage” check in “For Us, The Living” comes to mind. This is not about welfare, or charity, or benefits. It is about using AI to elevate civilization.
I favor government leaving technology to figure out its path. I also favor politics embracing growth to create widespread abundance.
The venture stories show who is already moving. The State of Venture says May was not a broad reopening. It was a narrowing. $22.2 billion went into 482 disclosed rounds, and the top 10 captured 54 percent of the capital. Benchmark raising a $1.25 billion late-stage fund tells the same story from the investor side. Even firms built around the old early-stage model are adapting to an AI market where the winners stay private longer, absorb more money, and may require larger ownership checks. Venture placing bets on winners does make sense. And if the returns to pension funds and endowments come, then it is a great example of ownership benefiting us all.
Om Malik’s Anthropic piece asks whether investors can even see the numbers they are pricing. That is a fair question. Liaquat Ahamed’s historical warning, via Andrew Keen, is even better: “be optimistic about the boom, but do not buy the stock.”
I like that line because it separates technological optimism from financial credulity. The railroads were real. Electricity was real. The internet was real. AI is real in the same way. But real technologies can still produce bad securities, fragile politics, concentrated ownership, and long hangovers. Pricing is an art, not a science. Giving citizens shares is one thing. Asking them to buy them is another.
So what are we building? A new productivity base? Or another enclosure?
John Battelle’s Google piece makes the enclosure problem visible. For years, the web’s bargain was simple enough: publishers let Google crawl, and Google sent traffic back. AI search changes that. Google can answer, summarize, and act inside its own surface. The open web may remain technically open while the economics move into a closed answer engine. Google’s new controls for website owners sound like choice, but the choice is brutal: participate in AI-mediated discovery or risk disappearing from where users now look.
The infrastructure section removes any remaining illusion that this is just software. AI wants power. Politico calls it “speed to power.” Google is building the Meitner Energy Center in Texas. Google is also working with Voltus to unlock 100 megawatts of flexible capacity in PJM. SemiAnalysis is asking whether space data centers can ever make economic sense. Stratechery’s Google Capital Company frame points at the same reality: AI is pushing Big Tech toward capital-company economics. And the scale of the investment means that this is a societal decision. Most of the money being invested via funds belongs ultimately to pensioners.
The future is not floating in the cloud. It is sitting on land, water, power, chips, fiber, permitting, ratepayer politics, debt, equity, and local communities.
So again: what are we building?
If we are building a future where a handful of model companies, cloud providers, and distribution platforms control, and meter, cheap intelligence, then politics will arrive as resentment. If we are building a future where every school, worker, founder, city, and small business gets access to AI leverage, then politics can become leadership.
That is the political conversation I want. Not a priesthood of model monitors. Not a culture war over whether the machine is alive. Not a defensive scramble to slow the future because incumbents and politicians arrived late.
I want campaigns and think tanks asking better questions. What does broad AI access look like? What public goods should AI wealth fund? How do we tax extraordinary AI rents without killing the builders? How do workers share in productivity gains? How do we make every student and small business AI-capable? How do we build energy, compute, and open standards as public infrastructure? How do we keep markets competitive when the returns to scale are so large?
That is not anti-market. It is the market’s legitimacy problem, seen early enough to do something about it.
USV Analyst 2.0 is the right Post of the Week because it captures the constructive version. USV tried agent analysts. It did not conclude that humans are obsolete. It concluded that the analyst job should move away from repeatable tasks and toward founder networks, taste, judgment, original points of view, and convening. The machine takes the repeatable load. The human moves closer to trust and judgment.
That is the future I want to build toward. AI that expands human capability. AI that makes work more meaningful, not merely cheaper. AI that gives small teams leverage without giving all the power to the largest platforms. AI that creates wealth and then forces us to answer, politically and morally, how that wealth lifts us all.
We should be angry with politicians when they fail to lead that conversation. Not because politics is unwelcome here. Politics is absolutely welcome here. The future of society relies on the future of AI. But the job of politics is not to make fear sound responsible. The job is to lead society toward a future worth building.
Build first.
Then share the future.
Enjoy.
*