OpenAI is releasing its latest advanced LLM, Sol, for wide public access. Sol is considered to be at least on par with Anthropic’s Fable, a model whose capabilities (or ownership) so stressed the White House that it was briefly banned from public access.

So how did these models get the go-ahead for release? Short answer: no one is quite sure.

“Frankly, I don’t have visibility into those exact processes, so yeah, I don’t feel like I have enough information to say whether they’re adequate or not,” Mina Narayanan, senior research analyst at Georgetown’s Center for Security and Emerging Technology, told TechCrunch. “Anthropic said that they were in talks with the government and that they developed a classifier to detect jailbreak attempts, and that they implemented defense-in-depth strategies to prevent future jailbreaks, but it is not clear exactly what that dialogue between the government, Anthropic and OpenAI went like.”

Dean W. Ball, a former Trump policy adviser who now works for OpenAI, wrote in his newsletter last month that “no one knows what the requirements are for getting a license.”

Andy Konwinski, a computer scientist who co-founded Databricks, Perplexity and the Laude Institute, said he has never spoken to anyone who understands the process, not even frontier lab employees. “It’s an existential problem,” he tells TechCrunch. “Security or not, it’s about who has the power to make decisions: who controls and decides on permits?”

Eighteen months into the Trump administration, there is still little clarity about how to move forward, despite (or, some critics allege, because of) the industry figures setting policy. Last month, after weeks of infighting, an executive order was released laying out a roadmap for evaluating frontier models, but the details have yet to be finalized, other than what won’t exist. “There will not be an FDA for AI,” Sriram Krishnan, a former partner at Andreessen Horowitz who served as a senior AI adviser at the White House until last month, told the Financial Times.

In particular, there is still no agreement on what types of models require government scrutiny, or which agency or agencies should conduct those evaluations. For now, the Commerce Department’s AI Standards and Innovation Center appears to be taking the lead, but the executive order directs six Cabinet agencies to determine a final process by early August. What has emerged in the meantime is, at best, ad hoc.

OpenAI CEO Sam Altman said on CNBC that the process involved conversations with officials such as Commerce Secretary Howard Lutnick, Treasury Secretary Scott Bessent and US National Cyber ​​Director Sean Cairncross, but it’s unclear who the experts tested the models or how they did it. OpenAI declined to share details about the government’s process with TechCrunch, but pointed to the results of several external assessments by organizations such as UK AISI, SecureBio, and Irregular on the latest model’s security card.

As with Anthropic’s Fable release, OpenAI previewed the model to the government and selected users before a broader release, but we don’t know who all those users were or how they were chosen. In a late June blog post, the company said that “we don’t believe this type of government access process should become the standard in the long term,” stating that it would work with the government to develop a different path forward.

However, the backdrop to those conversations includes Altman reportedly offering up to 5% of OpenAI’s equity for the administration’s so-called “Trump Accounts,” and OpenAI President Greg Brockman’s role as the largest publicly known donor to Trump’s mid-term political operation. It’s difficult for outside observers to separate those activities from the government’s seemingly lighter approach to regulating the Sun.

Anthropic’s Fable, on the other hand, was briefly removed from wider access when the US government banned its use by foreign citizens, partly due to real concerns that users would break the model to access hacking capabilities and partly due to personality clashes between Anthropic and the Trump administration. The threat of an export ban may also have led OpenAI to cooperate more with (unknown) government requests.

From the industry’s perspective, a hands-off approach to regulation might be good, but one that relies on personal connections with administration officials creates uncertainty and bad incentives.

Konwinski told TechCrunch that he is concerned that the real experts in this technology (“security researchers, alignment researchers, interpretability researchers, but also data people and people across the board”) are not playing a sufficient role in the model release process.

Konwinski argues that an “open commons” is the best way to truly balance security and innovation. He points to models such as the FDA, the NIH or national laboratories, which convene researchers, government officials and private companies to reach a consensus on safety issues.

Part of that comes down to the incentives of capitalism that have motivated AI researchers for more than a decade and that played out in the courtroom during Elon Musk’s lawsuit that challenged OpenAI’s corporate structure. Ball notes that the nature of the AI ​​business requires companies to recoup much of their training costs soon after launching their models and get further ahead of the competition.

“Even if your intentions are good, there are very clear legal obligations and fiduciary responsibility that are built right into operating procedures,” Konwinski says.

Ball, in his post, argued that the path forward will depend on third-party, government-authorized auditing organizations that will evaluate the security approach of border labs. Konwinski is also optimistic about new institutional formats, such as focused research organizations that could help more disinterested experts from academia and the nonprofit world access and evaluate frontier models.

For now, the secrecy around AI development isn’t going away, but it will also create political challenges for an industry that Americans increasingly view with skepticism. “There’s no sense that responsible people are driving these changes,” Remzi Arpaci-Dusseau, a computer science professor at the University of Wisconsin-Madison, said last week at the Open Frontier conference.

At the same event, David Siegel, the computer scientist who founded Two Sigma, one of the most successful quantitative hedge funds, asked attendees to “imagine a situation that I think would be very bad.” [where] a small number of companies control the technology; the government, in its secret laboratories, is evaluating whether or not the technology is suitable for use; and the general public and the scientific community don’t really have any access to any of that.”

It seems we don’t need to imagine it.