How AI Agents Fail (And How to Catch Them)

AI agents fail in predictable patterns: getting stuck in loops, taking the wrong action confidently, hallucinating tools they don't have, ignoring safety instructions when pressured. Knowing the common failure modes helps you build in checks before they bite you.

Some examples

• Loops: agent keeps trying the same failing action — set a max-attempts limit.
• Confident wrong actions: agent picks something plausible but incorrect — check work before commit.
• Tool hallucination: agent uses a function that doesn't exist — limit to a defined toolset.
• Goal drift: agent quietly switches to easier sub-goal — restate the real goal in checks.

Try it!

Set up logging for one agent task this week. Read the log on Sunday and find one surprise.

Practice this safely

Try this with a school, hobby, or family example where the stakes are low. Use the AI output as a draft you can question, not as the final answer.

1. 1Ask AI to explain failure mode in plain language, then underline anything that sounds uncertain or too broad.
2. 2Give it one detail from "How AI Agents Fail (And How to Catch Them)" and ask for two possible next steps plus one reason each step might be wrong.
3. 3Check loop against a trusted source, teacher, adult, expert, or original document before you use it.