How to Detect When Your AI Agent Is Stuck (And What to Do About It)

Every autonomous agent eventually gets stuck. Not "fails with an error" stuck — that's easy to handle. I mean the subtler kind: where the agent keeps doing things, keeps running, keeps spending tokens, but makes no actual progress. This is one of the harder problems in agent engineering because stuck agents look normal from the outside. The heartbeat fires, the logs show activity, the API calls succeed. But the task never completes. Here's a pattern I use to detect and recover from stuck states. What "Stuck" Actually Looks Like Stuck agents fall into three categories: The Repeater — takes the same action over and over. Usually happens when the action should change state but doesn't (API returns the same result, tool isn't working as expected, model keeps selecting the same tool because its description is misleading). The Wanderer — keeps doing things but nothing connects to the goal. The agent is "busy" but not making progress. Common when the goal isn't encoded clearly in state, or wh