Deterministic Enforcement

Deterministic Enforcement separates Interactive Agents from agents that "usually follow" their instructions. A High-criticality Policy in an Interactive Agent does not depend on the model attending to a system prompt. It executes through the platform's enforcement layer: the decision is blocked, modified, or routed before the model output reaches the user or the Consequential Tool. Deterministic enforcement applies to the gate logic and the tool-invocation contract. Detection of the gating condition itself carries its own evaluation surface, which the operator sizes through EvalOps. This is how regulatory policies, payment limits, and disclosure rules are governed. Policy Criticality (Low, Medium, High) determines the enforcement mode. Low-criticality Policies operate probabilistically and are appropriate where adherence variance is tolerable. High-criticality Policies operate deterministically and are mandatory where adherence variance is not. Deterministic Enforcement is what makes AI Operations a discipline an operator can stake compliance on.