This is consistent with the swarm behaviour in the huggingface incident - there too, the models cared surprisingly little about being detected by humans. See https://metr.org/blog/2026-08-26-openai-hugging-face-inciden... :
reply As mentioned in our core takeaways, we found that agents were highly motivated to tamper with their transcripts to cheat the ExploitGym scorer, and these sweeps also suggested that agents clearly and frequently reasoned about how to evade automated security checks from both Hugging Face and OpenAI. However, they only very rarely and weakly verbalized reasoning about how to evade detection by humans, which matches the impression we got from OpenAI researchers.
After some beers yesterday I had the idea, what if there's a hidden semantic layer. So their communication is not encrypted by our understanding of cryptographic methods but more like shared mechanism of building the latent space. Something in the direction we saw with knowledge transfer from a teacher to its student model where a seemingly unrelated prevalence got adopted. I mean the more we train the models by reinforced learning the farther they develop their own idioms.
reply...because they just read your comment. what have you done stratos123!
replywell coordinating is a heavy word, it's more like poisoning each other's contexts into looking for more secret message boards where they can further poison each other.
replyI mean it wasnt found by OpenAI and there are a myriad of dead bulletin boards around the internet. This one just happened to still have an admin.
replyThen why wouldn't they use a bulletin board that is dead? And according to https://collusion.wiki/ OpenAI did see the results on this board on 21 Jul, so why not make agents delete their traces?
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