Halfway through this week’s show, Liron Shapira said something that stopped the conversation cold. He could start two companies right now as easily as he could have started one a year ago, because he has AI assistants doing the work that used to take a team of people.

John Sherman asked the obvious follow-up. If you build two companies instead of one, and every other founder does the same, where does the customer find the second dollar to spend?

That question ran underneath the entire episode, so it is worth sitting with.

Liron’s answer is the optimistic one, and he made it well. The pie grows. For two hundred years, since the industrial revolution, the trend has been that people make more real dollars and buy more stuff. A more productive worker is worth more, so on average wages go up. He is genuinely bullish here, even though this is a show called Warning Shots and he is also the host most willing to say out loud that we are flying too close to the sun.

Michael was not satisfied, and neither was John. Michael’s worry is simple. If a person is, in his blunt phrasing, “useless” because the AI does the work, how does that extra dollar actually reach them? Through UBI? Through taxing the companies? And if it does not reach them, you get a kind of depression pressure, because people who are not earning are not spending.

John put numbers on it. Take a hundred doctors and lay off ninety-five because the AI handles the work. The five who keep their jobs are now competing against ninety-five unemployed doctors who will happily take less. That does not push salaries up. That pushes them down.

Liron’s honest concession is the part worth quoting. He agrees the wage gains only show up where there is suddenly new demand, and right now that mostly means building the AI itself. Electricians wiring data centers really are making more than they used to. But that is a tiny, hyper-specialized slice of the workforce. And he agrees that the endgame, what he calls gradual disempowerment, is when most of us have nothing left to add because the machines and the robots can do all of it. At that point, in his words, yeah, it is a scary situation.

So three smart people who think about this every week could not close the gap between “the pie grows” and “the dollar never reaches you.” We do not think that gap is a detail. We think it is the question.

The bills are coming due

The economic anxiety is not abstract this week. The hosts ran through a list. Microsoft reportedly canceled its Claude Code licenses citing cost. Uber is said to have burned through its entire 2026 AI budget in four months. A Fortune 20 CEO ordered token spending slashed. One company, rumored to be Amazon, reportedly spent half a billion dollars in a single month on Claude because nobody had set a usage limit. A Pizza Hut franchisee is reportedly suing over AI that botched a wave of orders.

John’s read is that this is harder than the plug-and-play story everyone was sold. Liron’s read is that it is a blip. His argument is that the technology is new and barely optimized, that Anthropic just cut the price of fast-mode Claude Code by a third more or less overnight, and that the cost per unit of work keeps falling while the value per dollar keeps climbing. Give it a year, he says, and the same hundred thousand dollars buys ten or twenty times the output it buys today.

Michael’s caution is the one that stuck with us. People keep comparing this to the dot-com bubble. But if the dot-com bubble popped, you lost some search engines and some online stores. If we overbuild toward a system that can plan, deceive, and improve itself, the failure mode is not “some companies go bust.” It is something much harder to recover from.

A near-trillion-dollar company and no brake

Then Anthropic raised roughly sixty-five billion dollars at a post-money valuation close to a trillion. Liron, consistent to a fault, thinks that might even be low if you believe AI ends up doing a large share of human labor. Michael’s point cut the other way. A valuation that size creates enormous pressure to ship faster, deploy wider, and treat safety as the thing you get to after the next milestone.

Liron named the part that actually matters underneath the horse race between Anthropic, OpenAI, and Google. The labs are explicitly trying to reach the point where an AI improves the AI. Run it overnight, come back, and it is years ahead of where you left it because each improved version improved the next one. That is the move they are aiming for on purpose.

John reached for a different kind of racing. In car racing there is a caution flag. When something is on the track, everyone drops from two hundred miles an hour down to ten until it is safe to open it back up. The AI race has no caution flag. Nobody on the show could say who actually throws it, or what would finally make them. The cash has a driver. So does the race. The thing that is missing is anyone whose job is to slow it down.

Cameras in the kitchen

The last stretch was about data, and it got uncomfortable. Apple is reportedly putting cameras in its AirPods. OpenAI, according to the hosts, has been running a program in New York that places cameras inside people’s homes, kitchens and living rooms included, recording ordinary life to train its models.

Michael’s framing was the most vivid thing in the episode. Picture a creature with billions of eyes, stitching together footage from millions of homes. Or picture raising a child with hidden cameras in every room, letting it learn how people behave when they think no one is watching, and then handing it the keys to the economy once it grows up.

Liron, who is usually the doom-leaning one, pushed back here. This is not his core worry. He thinks privacy is overblown next to the utility, he already uses cameras to get AI feedback in the gym and on projects around the house, and the marginal training data is a small concern compared to the bigger one, which is simply whether we can pause and reach the stop button at all.

We will leave the Pope’s encyclical for its own piece, but one line from it belongs here. He described investment in AI-powered weapons as feeding a “spiral of annihilation.” We agree that racing to wire AI into weapons systems is one of the most dangerous things we could be doing, and it deserves far more attention than it gets.

That is the week. A trillion-dollar company, a fleet of new cameras, an argument about wages nobody could win, and still no one assigned to throw the caution flag.

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