Lesson 1324 of 1455
When agents get stuck in loops (and how to stop them)
Runaway loops eat your wallet — set hard limits before you press run.
Builders · Agentic AI · ~4 min read
The big idea
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
- 1Design an agent spec: goal, tools, permissions, stop condition
- 2Run a simple web-search agent in a sandbox environment
- 3Instrument an existing workflow to identify where an agent could save time
End-of-lesson quiz
Check what stuck
8 questions · Score saves to your progress.
Lesson help
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