{
  "dataset": "glossary",
  "record": {
    "id": "react-pattern",
    "term": "ReAct",
    "category": "core",
    "short_def": "An agent pattern that interleaves reasoning and acting: the model thinks, takes a tool action, observes the result, and reasons again — looping to a goal.",
    "long_def": "ReAct (Reason + Act) combines chain-of-thought with tool use so an agent alternates 'thought' and 'action' steps: it reasons about what to do, calls a tool, reads the observation, and updates its plan. It is the canonical loop most tool-using agents implement.",
    "see_also": [
      "agentic-loop",
      "tool-use",
      "chain-of-thought"
    ],
    "etymology_origin": {
      "value": null,
      "verify_status": "verify-against-primary-at-build",
      "source_hint": "https://arxiv.org/abs/2210.03629 — 'ReAct' introduced by Yao et al., 2022 (Princeton / Google)"
    },
    "related_to": [
      "agentic-loop",
      "tool-use",
      "chain-of-thought",
      "ai-agent"
    ],
    "contrast_with": "Unlike plain chain-of-thought, which only reasons, ReAct also acts between reasoning steps — grounding each thought in a real observation from a tool.",
    "example": "A ReAct agent answering a live question reasons ('I need current data'), calls a search tool, reads the result, then reasons again before answering.",
    "source": "https://arxiv.org/abs/2210.03629",
    "status": "active",
    "why_it_matters": "ReAct is the loop the agentic web is built to serve: every markdown twin, JSON API and callable tool is an 'action' an agent takes between reasoning steps.",
    "sameAs": [
      "https://arxiv.org/abs/2210.03629"
    ],
    "bridge_entity": "agentic-loop",
    "last_verified": "2026-07-06",
    "md_twin": "/glossary/react-pattern.md"
  }
}