Reflexion
Reflexion is an agent technique in which, after a failed attempt, the model writes a verbal reflection on what went wrong and stores it in memory to guide its next attempt.
Description
It is reinforcement through language rather than weight updates, and uses feedback signals such as unit-test results or environment rewards. Shinn et al. reported large gains on coding and sequential decision-making benchmarks.
Sources
- Shinn et al. (2023). Reflexion: Language Agents with Verbal Reinforcement Learning.
Cite this entry
Protologue. (2026). Reflexion. In Protologue: A Taxonomy of Prompting and LLM Techniques (v1.0.0, PTL-0048). https://protologue.com/t/reflexion/
BibTeX
@misc{protologue_reflexion,
title = {Reflexion},
author = {{Protologue}},
year = {2026},
howpublished = {Protologue: A Taxonomy of Prompting and LLM Techniques, v1.0.0},
note = {Entry PTL-0048},
url = {https://protologue.com/t/reflexion/}
}