AgenticContract
What happens when an AI agent checks policies before acting, respects risk limits, routes approvals through proper channels, and tracks obligations — all in a single portable file?
End-to-end: governed production deployment
An agent wants to deploy v2.3.1 to production. Without AgenticContract, it just deploys — no policy check, no risk limit, no approval. With it, every governance dimension is enforced before the action happens.
Policy check
The engine checks all matching policies. Policy #7 (scope: global, tags: deploy, production) requires ops-lead approval. The action is blocked until approved.
Risk limit check
Daily deployment budget: 3 of 5 used. This deployment would bring it to 4/5 — within limits. API cost estimate: $23, within the $500 daily budget. Both limits pass.
Approval routing
Smart escalation routes to ops-lead-2 (93% approval rate, 4 min avg response). Request #47 created with full context: changelog, test results, risk assessment. Approved in 3 minutes.
Obligation creation
Post-deploy obligations auto-created: monitoring for 30 minutes (hard deadline), smoke test within 10 minutes (hard deadline), deployment report within 2 hours (soft deadline). Agent tracks all three.
Deployment v2.3.1 → Policy: approved (request #47, ops-lead-2). Risk: 4/5 daily deploys, $23/$500 budget. Obligations: 3 created (monitoring 30m, smoke test 10m, report 2h). Violations: 0. Contract #8 fulfilled. Governance state saved to .acon.
In plain terms
This is the difference between an agent that acts first and asks forgiveness later, and one that checks policies, respects risk limits, routes approvals, and tracks obligations before taking action. AgenticContract turns ungoverned agent behavior into auditable, policy-compliant operations with self-healing governance that learns from every violation.