How do you debug an autonomous AI agent that went completely off-script in production?

We’ve all seen the dazzling demos of multi-agent systems executing complex workflows. But as developers start deploying these agents into deep production with direct API access, a terrifying reality sets in: debugging non-deterministic behavior.

When an agent hallucinates a tool call parameter, enters an infinite reasoning loop, or gets subtly manipulated by an indirect prompt injection, tracing why it happened at runtime is a nightmare. Traditional logs just show a wall of async LLM requests.

While building Aegisora, we realized that observability and security for agents can't be treated like traditional web apps—you need real-time runtime inspection and deterministic guardrails.

I’m curious to hear from builders here: What is your current strategy for monitoring and debugging autonomous agents when they misbehave in production? How do you catch runtime anomalies before they hit your external APIs?

Let's discuss in the comments! 👇