Pattern · intermediate
Reflection and Self-Critique Pattern
Reflection patterns add a critique step so agents can check work, catch errors, and improve outputs before finalizing.
Reflection (self-critique) inserts a review step: generate → critique against criteria → revise.
When to use
- High-stakes writing or analysis
- Coding agents after tests fail
- Any time a cheap verifier exists
Variants
| Variant | How it works |
|---|---|
| Self-reflection | Same agent critiques itself |
| Dual-model | Stronger/cheaper critic model |
| Tool-verified | Tests, schemas, compilers as critics |
| Human critique | HITL review |
Prefer tool-verified reflection when possible—it is less circular than pure LLM self-talk.
Cost warning
Reflection multiplies calls. Gate it:
- Only on low confidence
- Only on high-risk actions
- Only when automated checks fail
Evaluation
Measure lift in success rate vs added cost. Drop reflection if it does not move outcomes.
FAQ
Frequently asked questions
What is reflection in AI agents?
Reflection is a deliberate critique step where the agent (or a second model) reviews intermediate work against criteria and revises before producing a final result.