Why a new report on Anthropic automating AI development is alarming researchers

AI is dramatically speeding up Anthropic’s research, even as the company calls for slowing down AI development.

AI is dramatically speeding up Anthropic’s research, even as the company calls for slowing down AI development.

by Robert HartNov 7, 2026, 12:30 PM UTC Robert Hart is a London-based reporter at The Verge covering all things AI and a Senior Tarbell Fellow. Previously, he wrote about health, science and tech for Forbes.

Anthropic is using AI to build more powerful AI. And it appears to be working remarkably well, with the company’s models improving roughly twice as quickly as a year ago, with little indication of slowing down.

That’s according to a new report published Thursday by the AI safety research organization METR, following an 11-week investigation inside the company, as part of a report evaluating its AI research and development. The probe is separate from a program offering safety researchers “employee-like” access to systems in the wake of high-profile hacking incidents over the summer.

The findings offer some of the clearest evidence yet of AI accelerating its own development, raising questions about how quickly the technology could advance toward a future in which AI systems can improve themselves with little or no human involvement. They also come at a pivotal time for Anthropic, which is preparing to go public even as its CEO, Dario Amodei, has publicly called for labs to pump the brakes on AI development.

But while the report offers a rare glimpse into the inner workings of the world’s leading AI labs, what it leaves out is just as revealing. Anthropic was permitted to redact portions of the final report as part of its agreement with METR, and it appears to have exercised that power liberally, raising questions about how much the public really knows about the pace — and risks — of frontier AI development.

Here are some of the biggest takeaways.

AI is dramatically accelerating Anthropic’s research and development

One of METR’s most noteworthy findings is that Anthropic’s AI models are improving roughly twice as quickly as they were a year ago, with benchmark scores suggesting “that Anthropic has made roughly two years of historical progress over the last year.” Crucially, METR’s researchers said they “are confident” that the acceleration was not simply due to scaling up the computing power used to train the models, which historically has been a major driver of AI progress.

Instead, the researchers said that the majority of the acceleration as of October “is due to AI,” with its contribution growing over time. That finding was supported by informal Slack polls and interviews with Anthropic employees, which pointed to sizable productivity gains. METR wrote that employees using Anthropic’s most capable internal model on average self-reported being around 12 times as productive at their respective work as they would have been without AI assistance, around double what staff had reported just a few months earlier while using Mythos 5.

For now, much of that acceleration appears to be coming from AI assisting human researchers, rather than AI working independently, though METR warned that “there are some signs that fully autonomous contributions will play a larger role soon.” Notably, the researchers said they found no clear signs of diminishing returns or observable bottlenecks that could prevent “even faster acceleration.”

Three of Anthropic’s newest AI models remain under wraps

Anthropic’s researchers are using more advanced AI models than the rest of us, with a lot of the acceleration and productivity gains described by METR attributable to unreleased internal models.

Over the past six months, Anthropic has finished training three models it has yet to release, according to METR. The pace of development is swift, with the models — codenamed Model 2, Model 3, and Model 4 — completing training in July, August-September, and September-October, respectively. METR also identified an unreleased model dating back to 2022, called Unreleased 2022. “These are the codenames shared with us; we understand they have different internal codenames,” the researchers wrote.

Anthropic is keeping key information secret

Anthropic gave METR access to a host of non-public information, including confidential research, model performance data, and employee interviews as part of the research process. It had no obligation to do so and by METR’s own admission, the AI lab “shared more information than was initially scoped for this project, surpassing our expectations.” This is commendable, but it is worth noting that Anthropic did not grant researchers unrestricted access, nor the kind of “employee-like” access it has promised other METR safety researchers as part of a separate program announced last month. It is an important distinction, given the reputational benefits companies can gain from independent assessments, even when they come with significant restrictions.

And there were significant restrictions. Anthropic had the power to redact information from METR’s final report — and it used that power extensively. “We submitted a ~100-page full report on our assessment to Anthropic. For the public version, Anthropic redacted a majority of the evidence we found most informative,” METR wrote on X.

METR reiterated those concerns throughout the report, highlighting other limitations on its access. “Our pipeline of information was relatively narrow, and a small number of our requests for data were denied.”

METR repeatedly stressed the impact Anthropic’s redaction decisions had on its ability to communicate its findings and for others to assess what’s going on at the company. It noted that much of the redacted evidence could have “multiple plausible interpretations,” making it difficult for the public to assess its findings, understand the uncertainties surrounding them, and judge the evidence themselve

Source: www.theverge.com — article syndicated from the publisher’s feed; all rights remain with the original publisher.