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Sprint projectOct 26, 2026New York City

Reading Intent from the Outside: Message + Action Monitoring of Deceptive LLM Agents

Ian Propper · Team Beginner's Luck

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

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Report: Reading Intent from the Outside: Message + Action Monitoring of Deceptive LLM Agents

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When predicting an agent's plans, having both action and message seems to perform better than having one or the other (with the agent I tested). However, monitors seem unable to perform better than a coin flip when an agent's action differs from its private plan.

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  1. Well controlled, great dataset! Very useful takeaway (plan drift failures). However, please refine: this projects rather investigates evasion than collusion.

Cite this project

@misc{propper2026reading,
  title = {{Reading Intent from the Outside: Message + Action Monitoring of Deceptive LLM Agents}},
  author = {Ian Propper},
  year = {2026},
  month = oct,
  note = {Submitted to AI Collusion Research Sprint, an Apart Research Sprint},
  howpublished = {\url{https://apartresearch.com/sprints/projects/reading-intent-from-the-outside-message-action-monitoring-of-deceptive-llm-agents-q98n}},
  url = {https://apartresearch.com/sprints/projects/reading-intent-from-the-outside-message-action-monitoring-of-deceptive-llm-agents-q98n}
}

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