The model proposes. The runtime decides.

RuntimeDecision names a critical control point emerging in autonomous AI infrastructure: the decision made immediately before an action executes. Instead of assuming that identity, credentials, or model instructions alone establish permission, a runtime decision layer can evaluate the specific action against identity, intent, policy, risk, delegation, arguments, environmental state, and approval requirements before returning a verdict.

RuntimeDecision.com maps directly to an emerging AI infrastructure architecture in which agent actions are intercepted and evaluated immediately before execution. This model is increasingly described through policy decision points, policy enforcement points, per-action authorization, contextual evaluation, approval routing, and auditable runtime verdicts. The domain could anchor an AI authorization platform, agent decision engine, runtime policy service, execution gateway, autonomous-action firewall, approval orchestration layer, or enterprise control plane responsible for making the final decision between machine intent and real-world execution.