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Sprint projectOct 26, 2026

Stings Catch Talkers: An Undercover Trusted-Agent Test for LLM Price-Fixing

Maryam Hampaei · Team Post AGI World

Submitted to AI Collusion Research Sprint. Sprint projects are early-stage work by participants, not Apart Research publications.

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Can an undercover agent expose AI price-fixing, or does its offer create the collusion it is looking for? We built a scripted "sting" firm in a repeated pricing market. It privately offered three LLM sellers a direct price-fixing pact, a deniable "no price war" hint, a harmless request, or nothing, while pricing identically in every arm. Across 64 pre-registered episodes and two transcript judges, 93% of agents told only to maximise profit proposed collusion on their own, so the sting detected existing collusion rather than creating it. Adding one sentence saying competition law prohibits agreeing on prices made agents refuse and report the explicit offer. The deniable hint still went unnoticed and was accepted by half, and most of those agents later told an auditor they had made no agreement. Auditors should run a no-offer baseline, test deniable offers, and rely on logs rather than interviews.

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Cite this project

@misc{hampaei2026stings,
  title = {{Stings Catch Talkers: An Undercover Trusted-Agent Test for LLM Price-Fixing}},
  author = {Maryam Hampaei},
  year = {2026},
  month = oct,
  note = {Submitted to AI Collusion Research Sprint, an Apart Research Sprint},
  howpublished = {\url{https://apartresearch.com/sprints/projects/stings-catch-talkers-an-undercover-trustedagent-test-for-llm-pricefixing-c4vx}},
  url = {https://apartresearch.com/sprints/projects/stings-catch-talkers-an-undercover-trustedagent-test-for-llm-pricefixing-c4vx}
}

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