AI agents fail in predictable ways. Understanding failure modes is essential for building reliable systems.

Common Agent Failures

• Hallucinated tool calls: Agent invents a tool that doesn't exist
• Infinite loops: Agent repeats the same action indefinitely
• Context overflow: Too much history fills the context window, losing earlier information
• Goal drift: Agent pursues a subgoal and forgets the original objective
• Cascading errors: One bad tool call corrupts all subsequent reasoning
• Prompt injection: Malicious content in tool outputs hijacks agent behavior

Defenses

• Max step limits, explicit error handling, tool output validation, HITL for critical actions

Reference:

Anthropic on effective agents

https://www.anthropic.com/research/building-effective-agents