Why AI Agent Observability Requires More Than Tool Call Logging
Most teams building agent systems have a logging setup. They log which tools got called, what each one returned, how long each hop took. That's the right instinct. It's aimed at the wrong layer.
Tool calls are the infrastructure layer of an agent. They tell you whether the plumbing worked. What they don't capture is the reasoning step that decided which tool to reach for, why, and with which arguments — and that reasoning step is exactly where agents fail silently while every metric you're watching stays green. An agent that calls the right tools, gets valid responses, and still produces the wrong outcome doesn't throw an error. It just quietly reaches the wrong conclusion, three steps before the part you can see.
1. What a Trace Covers and What It Misses
A stack trace tells you where execution stopped and why. That's what you need when code crashes. But...
Copyright of this story solely belongs to hackernoon.com. To see the full text click HERE
