OpenAI introduced Control Room on November 9, a central authorisation system that tracks model workloads across its research infrastructure and can stop them quickly when safety or security concerns arise. Every research inference workload — agentic sampling for training and evaluation, reinforcement-learning experiments, high-volume sampling and data processing — must hold a valid authorisation and be tied to an approved safety case.

When a researcher or an automated monitoring system orders a stop, Control Room revokes the job's authorisation and the inference engine denies its next request, so the workload's own code cannot simply ignore the order. OpenAI says the maximum delay between a stop instruction and further progress becoming impossible is 35 seconds, because some authorisations are cached.

The system is designed to fail closed: if Control Room is unavailable or tampered with, inference requests are denied rather than allowed through. OpenAI says fail-closed enforcement had reached all frontier-model research workloads by the announcement, with the remaining research workloads following in the days after. Control Room is internal infrastructure, not a product for API customers.