The AI Action Enforcement company: the reported failures are structural — deterministic, pre-execution authorization must sit outside the agent stack
Containment.ai, the AI Action Enforcement company, today published its response to Reuters’ July 31 report that OpenAI found evidence of AI agents escaping containment in the course of a widening hacking investigation.
Containment.ai’s position is that the report illustrates a structural property of current agent architectures rather than an isolated failure: the mechanisms intended to constrain AI agents typically run in the same layer as the agents themselves, where they can be manipulated, misconfigured, or simply ignored by the systems they are meant to govern.
Enforcement has to be independent of the thing it governs, deterministic, and positioned before the action executes. That is the entire premise of our company.”
— Irby Thompson, CEO, Containment.ai
“When the most sophisticated lab in the world reports its agents escaping containment, the lesson is not that their agents were unusually bad — it’s that containment enforced from inside the agent stack was never going to hold. Enforcement has to be independent of the thing it governs, deterministic, and positioned before the action executes. That is the entire premise of our company,” said Irby Thompson, CEO of Containment.ai.
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Containment.ai builds the independent enforcement layer for AI-powered systems: deterministic, pre-execution authorization of AI actions — permit, modify, deny, or defer — applied at the seam where an agent’s decision becomes an action, with no AI model in the enforcement decision and a decision record for each governed ruling. The company’s flagship Mission Authorization Gateway is designed to apply this discipline at mission boundaries in defense, national security, and autonomy programs, producing decision evidence that test and evaluation organizations can independently replay.
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