Three-week on-site audit at OpenAI reveals major gaps in AI safety monitoring

Two researchers from METR and Redwood Research spent three weeks on-site at OpenAI, auditing the company's internal monitoring system for rogue AI behavior. From July 21 to August 11, they had access to OpenAI's codebase and internal documents and interviewed about a dozen employees. The team found numerous weaknesses. An estimated 6 to 25 percent of internal agentic Responses API traffic from models at the GPT-5.5 class and above wasn't covered by monitoring at all during the audit period, though METR says the uncertainty around that estimate is significant in both directions. Ad For internal Codex traffic that was supposed to be monitored, METR estimates roughly 10 percent went untracked between May and July because of a gap in how the system handled compaction events, which are context summaries.