What happens when an agent fails — retry, fallback, escalate, or graceful degradation.
--- name: failure-recovery description: What happens when an agent fails — retry, fallback, escalate, or graceful degradation. --- # Failure Recovery Agents fail. Networks time out, models hallucinate, tools error, and edge cases surprise. Failure recovery design determines whether a failure becomes a dead end or a graceful detour. ## Failure Types in Multi-Agent Systems - **Agent failure**: A single agent crashes, times out, or produces invalid output - **Handoff failure**: Context is lost or corrupted during transfer between agents - **Coordination failure**: Agents conflict, deadlock, or produce inconsistent results - **Resource failure**: External tools, APIs, or data sources are unavailable - **Cascading failure**: One agent's failure causes downstream agents to fail ## Recovery Strategies - **Retry**: Try the same operation again. Works for transient errors (network timeouts, rate limits). Set a retry limit to avoid infinite loops. - **Fallback**: Switch to an alternative approach. A different agent, a simpler method, or a cached result. - **Escalation**: Pass the problem to a more capable agent or to a human. Used when the failure is beyond the current agent's ability to resolve. - **Graceful degradation**: Deliver a partial result rather than nothing. Tell the user what worked and what didn't. - **Compensation**: Undo the effects of a partially completed workflow before retrying or escalating. ## Designing Recovery Paths For each point in the workflow where failure is possible: - **What could fail?** List the failure modes - **What's the first recovery strategy?** Usually retry for transient errors - **What's the fallback?** If retry fails, what's the alternative? - **When do you escalate?** After how many retries or what type of failure? - **What does the user see?** Transparent about the failure or silently recovered? - **What's the worst case?** If all recovery fails, what's the graceful degradation? ## User Experience of Failures - **Invisible recovery**: The system retries or falls back without the user noticing. Best for minor, quickly resolved failures. - **Transparent recovery**: The system tells the user something went wrong and how it's handling it. "This is taking longer than usual — trying an alternative approach." - **Participatory recovery**: The system asks the user to help. "I couldn't access your calendar. Can you check the connection?" - **Honest failure**: The system tells the user it can't complete the task and explains why. Offers alternatives. ## Design Artefacts - Failure mode inventory per agent and per handoff - Recovery strategy specifications (retry limits, fallback paths, escalation triggers) - Cascading failure analysis - User experience specifications for each failure scenario - Recovery testing protocols--- name: failure-recovery description: What happens when an agent fails — retry, fallback, escalate, or graceful degradation. --- # Failure Recovery Agents fail. Networks time out, models hallucinate, tools error, and edge cases surprise. Failure recovery design determines whether a failure becomes a dead end or a graceful detour. ## Failure Types in Multi-Agent Systems - **Agent failure**: A single agent crashes, times out, or produces invalid output - **Handoff failure**: Context is lost or corrupted during transfer between agents - **Coordination failure**: Agents conflict, deadlock, or produce inconsistent results - **Resource failure**: External tools, APIs, or data sources are unavailable - **Cascading failure**: One agent's failure causes downstream agents to fail ## Recovery Strategies - **Retry**: Try the same operation again. Works for transient errors (network timeouts, rate limits). Set a retry limit to avoid infinite loops. - **Fallback**: Switch to an alternative approach. A different agent, a simpler method, or a cached result. - **Escalation**: Pass the problem to a more capable agent or to a human. Used when the failure is beyond the current agent's ability to resolve. - **Graceful degradation**: Deliver a partial result rather than nothing. Tell the user what worked and what didn't. - **Compensation**: Undo the effects of a partially completed workflow before retrying or escalating. ## Designing Recovery Paths For each point in the workflow where failure is possible: - **What could fail?** List the failure modes - **What's the first recovery strategy?** Usually retry for transient errors - **What's the fallback?** If retry fails, what's the alternative? - **When do you escalate?** After how many retries or what type of failure? - **What does the user see?** Transparent about the failure or silently recovered? - **What's the worst case?** If all recovery fails, what's the graceful degradation? ## User Experience of Failures - **Invisible recovery**: The system retries or falls back without the user noticing. Best for minor, quickly resolved failures. - **Transparent recovery**: The system tells the user something went wrong and how it's handling it. "This is taking longer than usual — trying an alternative approach." - **Participatory recovery**: The system asks the user to help. "I couldn't access your calendar. Can you check the connection?" - **Honest failure**: The system tells the user it can't complete the task and explains why. Offers alternatives. ## Design Artefacts - Failure mode inventory per agent and per handoff - Recovery strategy specifications (retry limits, fallback paths, escalation triggers) - Cascading failure analysis - User experience specifications for each failure scenario - Recovery testing protocols
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