How to Add Observability to Your OpenClaw Agent
At AI Engineer Europe 2026, developer Zechner raised an alarm that resonated across the room: engineers running AI coding agents often have zero visibility into why the agent made a particular decision. The agent acts; the engineer observes the result. The reasoning in between is a black box. This isn’t just an academic concern. When your agent does something wrong — and at scale, it will — you need to know why. Without observability, debugging an AI agent means guessing. With it, you have a traceable chain of events you can follow back to the root cause. ...