How do I handle AI agent failures gracefully?

Graceful AI agent failure means converting unpredictable agent breakdowns into predictable, typed errors that your application can handle programmatically — instead of letting the agent fail silently, retry infinitely, or corrupt state.

Most agent failures are silent. The agent hallucinates a parameter, the API returns unexpected data, the agent retries with the same bad input — and no one knows until the damage surfaces hours or days later.

Exogram makes failures loud and structured:

• Typed error responses: Every blocked action returns a specific error code (SCHEMA_MISMATCH, POLICY_VIOLATION, CONFLICT_DETECTED) that your application can handle
• Circuit breaking: If an agent retries the same failing action 4 times, Exogram kills the loop and returns LOOP_KILL — saving thousands of wasted tokens
• State preservation: When an action is blocked, the pre-action state is preserved via SHA-256 hash — no partial commits, no state corruption
• Human-in-the-loop escalation: Blocked actions can trigger alerts to human operators for review and manual approval
• Deterministic fallback: Your application receives the exact same error format every time, enabling automated recovery workflows

The key insight: a blocked action is better than a bad action. Exogram converts unpredictable AI agent failures into predictable, recoverable events.