When agents get stuck in loops (and how to stop them)

Agents can spin forever calling the same tool with the same input if their stop condition is fuzzy.

Some examples

• Set a max-steps limit (like 20).
• Set a max-cost limit if you're paying per call.
• Watch the first run live before walking away.

Try it!

Build any tiny agent. Set max_steps=10. Run it. Watch what happens at step 10.

Understanding "When agents get stuck in loops (and how to stop them)" in practice: AI agents don't just answer questions — they can do things, like looking things up, writing files, or talking to apps. Runaway loops eat your wallet — set hard limits before you press run — and knowing how to apply this gives you a concrete advantage.

• Design clear agent goals before adding tools
• Define permissions and scope before deploying any agent
• Build in human-approval checkpoints for high-stakes actions
• Understand when to use an agent vs. a simple chat prompt

1. 1Design an agent spec: goal, tools, permissions, stop condition
2. 2Run a simple web-search agent in a sandbox environment
3. 3Instrument an existing workflow to identify where an agent could save time