Lesson 1156 of 1570
Why AI Agents Fail (and How to Catch It Early)
Agents fail in predictable ways: looping forever, faking success, going off-topic. Knowing the patterns helps you stop them fast.
Lesson map
What this lesson covers
Learning path
The main moves in order
- 1The big idea
- 2agent failure
- 3infinite loop
- 4confabulation
Concept cluster
Terms to connect while reading
Section 1
The big idea
The classic failures: infinite loops (same action over and over), confabulation (claiming success without checking), goal drift (solving a different problem), and tool misuse (calling the wrong API). Watch for them or your agent will burn budget and ship nothing.
Some examples
- Claude Code edits the same file 8 times trying to fix one bug — that's a loop, kill it.
- An agent says 'task complete!' but never ran the test — confabulation.
- You asked for a login form and the agent built a whole auth system — goal drift.
- An agent calls the search tool with the user's password as the query — tool misuse.
Try it!
Run an agent on a task. Set a max of 10 steps. Read its action log when it finishes (or hits the limit). Spot which failure mode it's closest to.
Key terms in this lesson
End-of-lesson quiz
Check what stuck
15 questions · Score saves to your progress.
Tutor
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