Ten Infrastructure Controls Every AI Agent Needs Before Going Live

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A developer's customer-support AI agent got stuck in an overnight retry loop with a CRM tool, generating a $4,200 OpenAI bill without completing any useful work due to the absence of a circuit breaker. The incident highlights a broader pattern: roughly 95% of enterprise generative-AI pilots in 2025 yielded no measurable return, with failures tied to missing operational safeguards rather than model quality. Unlike read-only chatbots, deployed agents write to databases, issue refunds, and call APIs, making unchecked failures far more consequential. Key recommended controls include hard retry caps, deny-by-default tool allowlists, human confirmation gates for irreversible actions, and infrastructure-enforced cost ceilings — all implemented in code outside the model's reach. Research cited in the article found that action-level privilege enforcement reduced AI agent attack success rates from 70.3% to 7.3%, underscoring that safety infrastructure, not prompt engineering, is the critical line of defence.

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