Earlier this year, the prevailing tone emanating from the AI industry was one of patronizing triumphalism. Anxiety about a bubble had been hushed by the rapid adoption of AI coding tools in the tech world. The industry was excited about IPOs again. AI executives returned to the oracular mode that had gone out of fashion during the industry’s brief flirtation with retrenchment at the end of 2025. “As we move toward superintelligence, incremental policy updates won’t be enough,” began an OpenAI publication called “Industrial Policy for the Intelligence Age.” (Anthropic went with “Policy on the AI Exponential.”) Tech CEOs, seeing glimpses of a fully automated workforce in their Claude Code windows, started doing preemptive AI layoffs and writing manifestos. AI leaders were once again in charge of their own story.

So if you had entered, say, a monthslong episode of AI-induced psychosis back then and just snapped out of it today, you might find the following roundup from The Wall Street Journal sort of surprising:

In late May, OpenAI Chief Executive Sam Altman — who has long predicted that AI will lead to seismic shifts in the workforce — said during a conference, “We’ve been roughly right on technological predictions and pretty wrong on the social and economic implications.” Soon after, he told CNBC, “Our industry underestimated how much we’re going to be able to keep people at the center of everything.”

In late May, OpenAI Chief Executive Sam Altman — who has long predicted that AI will lead to seismic shifts in the workforce — said during a conference, “We’ve been roughly right on technological predictions and pretty wrong on the social and economic implications.” Soon after, he told CNBC, “Our industry underestimated how much we’re going to be able to keep people at the center of everything.”

You might also be interested in some other news items. Like the one about how xAI recently sold excess compute to Anthropic, leaving investors to wonder if its AI business was downgrading to an infrastructure provider right before its parent company’s IPO (which did not, in fact, send SpaceX’s stock price to Mars). Or how Mark Zuckerberg admitted to employees — who had just months ago lost colleagues to AI-inspired layoffs — that the “trajectory of the agentic development over at least the last four months hasn’t really accelerated in the way that we expected.”

Companies are worried about overspending on AI and are turning to cheap but functional Chinese models, which remain just a few months behind. Meanwhile, data-center backlash has taken hold, Anthropic is now downplaying the danger of Mythos, and Nvidia stock is slumping. And as much as industry executives linger on the possibilities of sudden white-collar disemployment, the impact of AI hasn’t yet shown up in clear or profound ways in the economic data, particularly around labor. A new study by Ramp teased the possibility that aggressive AI adoption can result in increased hiring at tech firms. Suddenly, tech leaders seem to be speaking a bit more carefully about their products. “Big tech has suddenly flipped on the AI jobs wipeout scenario,” The Journal argues. In other words, yet another vibe shift.

I don’t want to litigate the meaning of this particular shift. For each item above, there are available counterarguments and mitigating factors, and the basic story has remained true for a while now: Models are continuing to improve and expand capabilities, albeit in lumpy and unpredictable ways and by sometimes expected means. Meanwhile, deployment has been even less predictable, but usage, both personal and business, has been expanding spikily in various directions. Overall, this remains a story of growth.

What I do want to emphasize is that these extraordinary internal shifts in........

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