Two outside researchers who spent three weeks inside OpenAI this summer found several gaps in the system the company uses to watch its internal AI agents for misbehavior. When the exercise began, reinforcement-learning (RL) training runs weren’t covered by the misalignment monitor, and the testers found two client-controllable headers that could switch monitoring off for newly started agents, though setting them could itself be caught by the monitor.

The findings come from a public summary posted Thursday by METR , an AI evaluation nonprofit, and published in the same form by Redwood Research . One employee from each group worked on site from July 21 to Aug. 11 with access to OpenAI’s internal codebase, the monitor’s prompts and configuration, and internal documentation.…