Policy Operations

Q1: How do we detect "Runaway Agent" behavior?

Detect runaway behavior by monitoring for abnormal patterns relative to the agent’s expected intent and baseline. Strong signals include: sudden spikes in tool calls, repeated failures/retries, widening resource access, attempts to escalate privileges, accessing new tenants/resources, and rapid sequences of write actions.

Use rate limits, circuit breakers, and anomaly thresholds: if triggered, automatically downgrade to read-only, revoke elevated tokens, or quarantine the agent session. Also log intent-to-action mismatches: if the agent claims one intent but performs unrelated operations, treat it as a policy violation.

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Q2: Can we support "Dry-Run" modes for agent actions?

Absolutely. Dry-run mode lets an agent simulate actions and produce an execution plan without changing systems. It’s ideal for high-risk operations (config changes, provisioning, access updates).

Architecturally, dry-run can be enforced at the policy layer (deny writes, allow reads) and at the tool layer (tools expose “validate/preview” endpoints). Require agents to produce structured outputs: the proposed change set, impacted resources, and rollback steps. Dry-run becomes a governance tool when it’s logged and reviewed before “apply.”

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Q3: How do we test agent policies in CI/CD?

Treat policies like code: version them, lint them, and run automated tests before deployment. Build a policy test suite with golden scenarios (expected allows/denies) across tenants, environments, intents, and risk contexts. Include negative tests for common failure modes:

privilege escalation,

cross-tenant access,

missing approvals, and

policy bypass attempts.

Add regression tests whenever a policy changes or a new tool is added. The key is determinism: policies should be testable with mock context inputs so changes don’t introduce unexpected access.

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Q4: How do we do "Canary Releases" for policy changes?

Roll out policy changes gradually to reduce blast radius. Start with a small slice: a subset of tenants, a specific agent fleet, or a percentage of requests. Run the new policy first in shadow/observe mode (log decisions without enforcing) to measure expected impact. Then enforce for the canary group while monitoring deny rates, error rates, incident tickets, and any spike in privilege requests.

Keep instant rollback ready: policy version pinning and fast revert. Canary releases are especially valuable for agentic systems because small policy shifts can change behavior at scale.

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