For a couple of years now, the single story pounding our heads about AI all day every day has been exclusively about looming disaster. AI takes the jobs, then it takes everything else, then few people get rich. A love story. It was an intentional positioning of the technology, obviously, but the question remains why. Well, Cal Newport has a good hypothesis that I wrote about the other day. But others are noticing as well. So, the phenomenon of the old pitch evolving into something new is probably real.

In a recent episode of The AI Daily Brief, host Nathaniel Whittemore says the previous extremist narrative may finally be cracking, and he cites a fair number sources to substantiate his claim. It’s a different take from Cal Newport’s but there is some overlap. The signals are faint, he says, but they’re showing up in two key places at once so that may mean that the shift will likely have some legs. I think Whittemore may be pulling his punches a bit by saying “the signals are faint” just to cover himself since this shift has been so recent, such as really only the last few weeks. I think the shift is clearly underway. Remember, the IPOs are coming soon, baby! The companies and their simps can’t continue with the doom rhetoric. The American public has rejected that strategy. And it’s interesting that some public opinion polls in China lack this doom positioning. Anyway, back to Whittemore’s daily brief.

The first place Whittemore notices the vibe shift is within the never-ending chattering class in the media. He points to Ezra Klein’s recent New York Times article, “Why the AI Job Apocalypse (Probably) Won’t Happen.” I like the “probably” bit. But coming from a big voice on the political left and also one that’s outside the AI bubble, Klein may carry some weight in Whittemore’s eyes that a similar post from others, say, Marc Andreessen, simply wouldn’t. Klein cites economist Alex Imas from the University of Chicago and also a wider body of economic research to make a case rooted in Jevons Paradox. When something gets cheaper, we tend to use more of it, not less. So although computers may have changed or even eliminated specific tasks, the cost savings created enough new demand that the occupations expanded overall. As Klein puts it, “Every enthusiastic AI adopter I know is working harder than ever because there is more they can do.”

Whittemore points to more data that’s emerging. Software engineering, which is the job category most exposed to AI, is the one where postings have actually increased recently. Citadel Securities cites the increase at 18 percent since May of last year. Federal Reserve numbers also show software engineering jobs at their highest level since November 2023, although the current number is still well under the previous mark three years ago. Also, Stripe Atlas just hit 100,000 incorporations, with Q1 up 130 percent year over year. As Derek Thompson says, “AI agents are better at creating firms than destroying jobs.” A new trend?

The second place the shift is showing up for Whittemore is in markets themselves. Anthropic’s revenue, according to SemiAnalysis, has gone from 9 billion to more than 44 billion this year, which is roughly doubling every six weeks. Atlassian’s stock jumped about 30 percent recently after strong earnings with customers using its new Rovo AI tool growing their own ARR at twice the rate of those who weren’t. The skeptics have been questioning how you justify trillions in infrastructure when seats only sell for 20 dollars a month. Well, that’s being answered by the move from seats to tokens taking place recently in the intelligent agent era. A single engineer with Claude Code might burn through hundreds or thousands of dollars in tokens each month, and the companies selling those tokens cannot keep up with demand.

There’s another piece of the vibe shift worth noting, one which I found most interesting since I’ve worked in both industries. The Associated Press recently reported on construction companies teaming up with big tech to push back on community opposition to data centers. Rob Bear of the Pennsylvania Building and Construction Trades Council told the AP that communities should figure out what they actually want from these projects rather than just saying no. “If you don’t ask, you’re never going to get,” he said, pointing to things like better project plans or money for local schools and infrastructure. Whittemore’s take is sharper. He calls it “an insane indictment of how poorly tech companies have run these projects that the issue has gotten this bad” given how many ways there are to make data centers genuinely valuable to nearby communities at a fraction of the total cost. He’s spot on. The AI companies deserve the public backlash. We’ll see how they adapt to the very real world they are now entering.

Even the AI labs are softening their messages. Sam Altman recently wrote that “jobs doomerism is likely long-term wrong” and that OpenAI wants “to build tools to augment and elevate people, not entities to replace them.” Whittemore says this is a meaningful pivot from a company whose stated goal used to look a lot more like replacement.

But Whittemore is careful not to declare victory too fast. The AI transition will still be painful for specific workers and communities, and history shows we generally don’t help them much at all when economies move through technological advancements. But he ends on a hopeful note.

“I find it extremely encouraging to feel the collective foot being taken off the gas of the AI doomerism for just a moment. If nothing else, it creates an opportunity to have a different type of conversation. One that’s neither doom nor utopia, but about how to adapt to and maximize the opportunity of the change that’s here and coming. I think the more time we spend on that conversation rather than in the extremes, the better off we’ll be.”