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Automatic Error Recovery in AI Agent Networks

DEV Community·Albert zhang·20 days ago
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In a single-agent system, failure is simple: the agent errors, you retry. In multi-agent systems, failure is a graph problem. The Cascade Failure Problem Agent A: ✅ Success Agent B: ❌ Timeout (depends on A) Agent C: ❌ Skipped (depends on B) Agent D: ❌ Partial data (depends on C) Enter fullscreen mode Exit fullscreen mode One timeout propagates through the entire pipeline. Without recovery, your system is fragile. Our Recovery Strategy AgentForge implements 3 recovery layers: Layer 1: Retry with Exponential Backoff @retry ( max_attempts = 3 , backoff = exponential ( base = 2 , max = 60 )) def agent_call ( params ): return llm .…

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