Now, here’s Ian…

Last week, OpenAI announced its latest model release with slightly less fanfare than usual. Sure, the industry is excited about GPT-5.6 Sol, Terra, and Luna. But, in a twist, the new model family is launching only as a limited preview “for a small group of trusted partners” vetted by the U.S. government. According to a company blog post, the staggered rollout is a “short-term step” while OpenAI works with the Trump administration to comport with the White House’s suddenly very hands-on approach to A.I. regulation: “We don’t believe this kind of government access process should become the long-term default. It keeps the best tools from users, developers, enterprises, cyber defenders, and global partners who need them.”

It’s all somewhat head-spinning. Until recently, the administration was ostensibly gung ho about removing bureaucratic obstacles to A.I. adoption. But everything changed after Anthropic previewed Mythos, which demonstrated advanced cybersecurity capabilities. Earlier this month, the government leveraged export controls to force Anthropic to essentially shut down its most advanced models—an outcome that was surely lingering in Sam Altman’s mind when he struck this latest agreement. (On Friday, Anthropic said it was permitted to redeploy Mythos “to a set of U.S. organizations that operate and defend critical infrastructure.” Meanwhile, Fable, the publicly available version of Mythos, remains offline.)

For industry observers, the administration’s focus on GPT-5.6 signaled that its newish regulatory posture was not simply designed to punish Anthropic. On the contrary, said Arthur Tellis, a senior technology fellow at the Institute for Progress, this “improvised pseudo-regulatory regime” is clearly the result of a growing recognition of “the very real security risks posed by broad access to general intelligence”—risks, he said, that were “anticipable” a year ago or longer. Interestingly, Tellis added, “the national security enterprise now appears to be driving more of the government’s policy response,” largely by controlling access to these tools rather than trying to shape the technology itself. (OpenAI did not return a request for comment, and neither Google nor Meta commented on whether the latest moves have affected their approach to frontier model deployment.)

The volte-face has been particularly galling for former White House A.I. czar David Sacks, who had been instrumental in Trump’s original A.I. Action Plan. “A year ago, President Trump declared that America was in a global A.I. race and that the way to win it was to be pro-innovation, pro-infrastructure, pro-energy, and pro-export,” Sacks wrote on X over the weekend. “President Trump was exactly right; we deviate from that strategy at our peril.”

Others have voiced more-nuanced criticism. Anthony Aguirre, the executive director of the Future of Life Institute—which authored the famous 2023 letter calling for a six-month pause on A.I. development, signed by Elon Musk and 33,000 others—told me that the policy shift is “hugely good news” for the world. At the same time, he said, the lack of clarity surrounding A.I. governance and policy is understandably frustrating for the industry. “I’m not someone who tends to go through life having a huge amount of sympathy for the A.I. companies, but I do a little bit here,” he said. “They have no idea what they’re supposed to do. Everyone will be better off if we have a well-thought-through structure for this.”

Indeed, there’s a feeling in the industry that the government is essentially making up new rules in real time. Trump’s early June executive order had described a voluntary procedure for A.I. labs to work with the government on predeployment. Even at the time, I was cautioned by well-wired sources that the process was not, in fact, truly voluntary—which is exactly what appears to be playing out now. “We’re seeing the Anthropic action probably have one of its intended effects—of bringing the other A.I. frontier labs to heel,” Peter Harrell, a former White House economics advisor, told me.

But this state of affairs may also be temporary. As Harrell pointed out, a process in which the U.S. government essentially handpicks the customers that labs are allowed to serve will ultimately “gum up U.S. and global deployment of U.S. models in a way that even folks in the administration who are pro-regulatory would realize will only disadvantage the U.S. vis-à-vis the Chinese.” If the administration doesn’t abandon its approach in favor of a transparent legislative framework within a few weeks, Harrell predicted, thousands of potential customers in allied countries could instead turn toward Chinese models, whose developers have been laser-focused on catching up to the U.S. frontier. Chris McGuire, a senior fellow for China and emerging technology at the Council on Foreign Relations, put a finer point on it, saying: “This is how we lose.”

Of course, the administration’s customer-review process also threatens cashflow for the so-called hyperscalers, which could lose out on much-needed revenue with a constrained client base. Over the short term, Tellis said, “the flywheel is kind of sustainable” given how well-capitalized these companies are—but the fear is that the “short term eventually becomes the long run.” Michael Horowitz, a senior fellow for tech and innovation at the Council on Foreign Relations, echoed this sentiment, telling me that “there could be economic and security risks from delaying deployment for too long. This creates an obvious tension that the Trump administration will have to navigate.”

That’s not to say that controlled model releases and risk-mitigation mechanisms are incompatible with industry growth. “It just requires patience, discipline, expertise, statecraft, and adaptive institutions,” Tellis told me. “It’s not beyond our control or our capacity. But I’m not that optimistic that anyone can really rise above their atavistic urges here.”

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