Article argues for deterministic AI agent action verification

The author argues that AI agent action verification should use fast, deterministic checks and calibrated binary decision models on the request path rather than a second large-model prompt. Relying on an uncalibrated confidence score or asking a model to grade its own terminal output wastes compute resources and worker slots. The article provides a checklist for implementing reliable tool-call guardrails and gateway hooks to halt unauthorized actions before execution. Open article →