Error Handling in Production AI Agents
Production agents encounter errors constantly. How they handle errors determines whether they degrade gracefully or fail catastrophically.
The Error Handling Imperative
Every production agent will encounter errors: systems that are temporarily unavailable, inputs that don't match expected formats, permissions that have changed, data that doesn't exist. Agents that aren't designed to handle these situations fail in ways that damage user trust and are difficult to debug.
Error Categories for Agents
- Tool/Skill errors — the Skill returned an error. The agent must decide: retry, try an alternative, or escalate.
- User input errors — the user's request is ambiguous, incomplete, or outside scope. The agent should ask for clarification rather than guessing.
- System availability errors — a target system is unavailable. The agent should inform the user, provide an ETA if known, and offer to retry later.
- Permission errors — the agent doesn't have permission to perform the requested action. Escalate to a human with appropriate access.
Graceful Degradation
Design your agent to degrade gracefully: when it can't complete the primary path, it should offer an alternative. "I wasn't able to retrieve your account data from Salesforce — it appears to be unavailable. Would you like me to check again in 15 minutes, or can I help you with something else?"
Never Let Agents Fail Silently
The worst failure mode: the agent encounters an error and either tells the user everything is fine (incorrect) or drops the conversation (confusing). Every error the agent encounters should result in an explicit, honest communication to the user about what happened and what the agent can do about it.