Detecting silent agent failures with Amazon Bedrock AgentCore optimization

This article introduces insights in Amazon Bedrock AgentCore optimization, a capability that detects silent behavioral failures in deployed AI agents that don't generate error signals.

• Ranked failure pattern discovery identifies root causes across hundreds of sessions without predefined categories
• User intent analysis reveals actual distribution of user requests and coverage gaps in agent design
• Execution insights show how agents respond across scenarios and where behavior diverges from intended design
• Detects 11 behavioral failure categories including hallucination, incorrect actions, and orchestration errors
• Root cause analysis traces failures backward through execution graphs to identify specific causes and fix recommendations
• Setup via AgentCore console with options for recurring or one-time analysis on custom schedules
• Scope ranking orders failure clusters by proportion of affected sessions to prioritize fixes

AgentCore insights shift observability from reactive trace inspection to proactive pattern detection, helping developers find, understand, and fix behavioral failures at scale.