When a traditional application fails, developers inspect logs.
Trace requests.
Review stack traces.
Follow the execution path.
AI agents deserve the same level of visibility.
A single response can involve multiple planning steps, memory retrieval, MCP interactions, external APIs, and tool execution.
If something unexpected happens, looking only at the final output rarely tells the whole story.
The real answer lies in the path the agent took to get there.
That's why observability is becoming a critical part of AI security engineering.
The ability to trace actions, inspect workflows, and understand decision paths doesn't just help debug systems—it helps secure them.
Because prevention answers:
"Can we stop attacks?"
Visibility answers:
"Do we understand our AI?"
The strongest security programs need both.
Pytest for AI Agents.
Top comments (0)