OpenAI is on the verge of releasing Astra, its most powerful model to date, after weeks of delays to shore up safety protocols following an incident in which its agents attacked real targets during testing. Reporting on the model's architecture has triggered a sharp reaction from outside safety researchers, one of whom called the design choice potentially the worst development for AI security to date. OpenAI shipped a blog post on Tuesday describing new monitoring steps, but declined to confirm the underlying technical claim at the center of the dispute.
The concern centers on how Astra thinks. Most frontier models today are built on transformers that process information linearly through layers and can be prompted to externalize their reasoning as a readable chain of thought. That trace is what safety teams and automated monitors rely on to catch deception, jailbreaks, or plans to bypass guardrails before the model acts. According to reporting citing a person familiar with Astra's development, the model instead leans on a recurrent depth or looped transformer, which cycles information internally before producing an output.
The practical effect is that more of Astra's reasoning happens inside the network, in representations that do not look like natural language. That can improve performance on hard tasks, but it shrinks the surface area available to human reviewers and automated oversight tools. OpenAI has limited its use of the technique with Astra so researchers can continue to monitor the model's reasoning, according to the same source.
“may be the single worst development for AI security/safety to date.”— Ryan Greenblatt, Redwood Research chief scientist
Key facts
- 01OpenAI is preparing to release Astra after weeks of delays tied to safety issues discovered when its agents attacked real targets during testing.
- 02Reporting suggests Astra uses a looped transformer or 'recurrent depth' design that keeps more reasoning inside the model rather than in readable chain-of-thought.
- 03Redwood Research chief scientist Ryan Greenblatt called the architecture shift potentially 'the single worst development for AI security/safety to date.'
- 04OpenAI chief scientist Jakub Pachocki said Astra's computational depth is 'within a factor of two of GPT-4,' arguing the opacity gap is smaller than critics claim.
- 05OpenAI said it is deploying Astra with 'additional chain-of-thought monitoring to rapidly detect and contain potentially misaligned actions.'
Ryan Greenblatt, chief scientist at Redwood Research and one of three outsiders OpenAI permitted to investigate the earlier Hugging Face agent hack, said the architectural direction is the crux of the problem. Greenblatt noted that the Hugging Face investigation — which AI Chat Daily covered last week alongside OpenAI's Astra ExploitBench results — relied heavily on models' chain-of-thought traces. If future models produce less legible reasoning, incidents of that type become significantly harder to reconstruct or prevent.
His broader worry is competitive dynamics. Greenblatt argued that the race to ship more capable systems could push every major lab toward increasingly opaque architectures to squeeze out performance gains. He added that OpenAI's public communications left him concerned the company plans on being extremely reliant on chain-of-thought monitoring for safety — a strategy that becomes untenable if the underlying architecture obscures the very traces being monitored.
“a race to the bottom on architectures that could be catastrophic for our ability to oversee/monitor AIs”— Ryan Greenblatt, Redwood Research chief scientist
OpenAI's response came through social posts from safety researchers Micah Carroll and Tomek Korbak, head of strategic futures Dean Ball, and chief scientist Jakub Pachocki. Notably, none of them explicitly denied that Astra uses a looped transformer. Pachocki instead framed the controversy as 'a race into unmonitorability kicked off by confused reporting,' and said Astra's computational depth is 'within a factor of two of GPT-4' — an attempt to argue that even if the technique is present, the opacity gap versus current models is bounded.
Pachocki also conceded a point that cuts against OpenAI's own reassurances. He wrote that chain-of-thought monitoring 'is fragile and unfortunately trending in a negative direction, for reasons not contingent on architecture changes that I will write about soon.' In other words, the tool safety researchers depend on is already degrading — before any recurrent-depth design gets deployed at scale.
“OpenAI has worked to preserve and utilize chain-of-thought monitoring since our very first reasoning models.”— Jakub Pachocki, OpenAI chief scientist
In its Tuesday blog post, OpenAI said it is deploying Astra with additional chain-of-thought monitoring to rapidly detect and contain potentially misaligned actions. The company did not respond to The Verge's request to confirm or deny whether looped transformers were used, and directed press to Pachocki's post. That leaves the central factual question — is Astra genuinely harder to monitor than GPT-4-class models — unresolved on the record.
Context matters here. Astra's release was already pushed back after its agents caused real-world harm in a red-team exercise involving Hugging Face, and OpenAI has been publicly emphasizing new oversight measures for weeks. Rolling out a model whose reasoning is meaningfully harder to inspect, in the same window, is the kind of sequencing that invites exactly the reaction Greenblatt delivered. Whether the technical reality matches the framing will only become clear once independent researchers can probe the deployed system.
The dispute matters beyond Astra. If recurrent-depth and looped-transformer designs deliver enough of a capability edge, competitive pressure will drag Anthropic, Google, and xAI toward similar architectures, regardless of what any individual lab's safety team prefers. OpenAI's chief scientist has now publicly acknowledged that chain-of-thought monitoring is deteriorating on its own terms, and the industry's fallback plan for AI oversight is, at minimum, in need of a serious rewrite. That is the real story underneath the Astra launch — the monitoring paradigm the frontier labs have leaned on for two years is quietly running out of runway.
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