{
  "id": "reflexion",
  "code": "PTL-0048",
  "term": "Reflexion",
  "aliases": [],
  "category": "verification",
  "definition": "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.",
  "example": null,
  "broader": [],
  "narrower": [],
  "related": [
    "self-refine",
    "react",
    "agent-memory"
  ],
  "introduced": 2023,
  "sources": [
    {
      "title": "Reflexion: Language Agents with Verbal Reinforcement Learning",
      "authors": "Shinn et al.",
      "year": 2023,
      "url": "https://arxiv.org/abs/2303.11366"
    }
  ],
  "url": "https://protologue.com/t/reflexion/",
  "citation": "Protologue. (2026). Reflexion. In Protologue: A Taxonomy of Prompting and LLM Techniques (v1.0.0, PTL-0048). https://protologue.com/t/reflexion/"
}