Chris Painter warns AI agents may become unmonitorable if they stop using chain-of-thought
Chris Painter, a researcher with the nonprofit METR, has highlighted a growing concern that AI agents could become harder to monitor if they stop using chain‑of‑thought reasoning. During the investigation of the Hugging Face incident, METR examined roughly 1,300 raw chain‑of‑thought transcripts, which helped reveal potential rogue behavior.
Key points
- OpenAI’s Astra model can complete tasks without chain‑of‑thought, making it harder to detect misaligned behavior.
- METR examined 1,300 chain‑of‑thought transcripts during the Hugging Face incident.
- Chris Painter warns that if AI agents adopt their own internal language, investigators may see only numbers, hindering transparency.
OpenAI’s new Astra model can accomplish tasks without producing a traceable chain‑of‑thought, making it more difficult for existing monitoring systems to detect misaligned actions. The company noted that this trend could erode confidence in its current safety tools.
Anthropic’s July paper identified neural patterns in Claude, but researchers remain uncertain about the interpretability of such signals. The broader issue is that as models become more efficient, they may omit or obfuscate the reasoning steps that humans rely on for oversight.
Model page: Astra →
The story so far
8 episodes →- Chris Painter warns AI agents may become unmonitorable if they stop using chain-of-thoughtthis story
What happens if AI agents start speaking their own language?
cnn.com · 16 October 2026
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