What ReAct (Reason + Act) means in practice
ReAct is the foundational agent design pattern, introduced in a 2022 paper and now baked into most production agent frameworks. The model is prompted to emit alternating Thought/Action/Observation triples: it reasons about the next step, takes an action (typically a tool call), observes the result, and continues. The pattern's strength is interpretability — every step in the chain is human-readable and replayable. Its weakness is verbosity and latency. Production enterprise agents typically use ReAct for the planning loop and switch to a more compact format (just tool calls with minimal reasoning) for the execution loop, balancing auditability against cost.
Related terms
Agentic AI →
Systems where an LLM acts as a planner that chooses tools, decomposes tasks, and iterates toward a goal rather than producing a single completion.
Tool use (function calling) →
An LLM capability to emit a structured call to an external function or API based on the user's request, then continue the conversation with the function's result.
Multi-agent orchestration →
An architecture where multiple specialised LLM agents coordinate on a task, typically with a planner agent decomposing the work to executor agents.
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