Lesson 2095 of 2116
AI Agent Self-Reflection: Critique Loops That Actually Improve Output
When and how reflection loops genuinely improve AI agent performance.
Lesson map
What this lesson covers
Learning path
The main moves in order
- 1The premise
- 2self-critique
- 3reflection
- 4iterative refinement
Concept cluster
Terms to connect while reading
Section 1
The premise
AI self-reflection loops (generate, critique, revise) improve some tasks substantially and degrade others — the difference depends on whether errors are recognizable post-hoc.
What AI does well here
- Critiquing its own output against an explicit rubric
- Producing substantively revised drafts after critique
- Identifying surface-level errors in code and prose
- Adopting feedback when the rubric is concrete
What AI cannot do
- Catch errors of the same type it made on the first pass
- Improve indefinitely with more reflection rounds
Key terms in this lesson
End-of-lesson quiz
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