
ReAct — what is the "reason and act" paradigm for LLM agents?
ReAct is an architectural pattern for large language models in which the model alternates between generating thoughts (reasoning), calling external tools, and reading observations back into its context. Understanding ReAct is a prerequisite for building any modern AI agent, because the Thought–Action–Observation loop sits underneath most agentic systems shipped today.








