ReAct (Reason + Act)
ReAct is an agent execution pattern in which a model alternates between reasoning about a task and taking an action, such as firing a query or calling a tool, repeating the cycle until it decides it has an answer.
Also known as: reason and act, reasoning and acting
In a ReAct loop, an agent doesn’t plan its full approach up front; it reasons about what to do next, takes one action, observes the result, and reasons again. This makes agents adaptive, but it also means an agent with incomplete context can get stuck repeatedly firing queries against data it doesn’t actually have access to, unable to reason its way to ‘I can’t answer this.’
The pattern is one driver behind the surge in query volume data platforms have seen as agents come online — agents in a reason-act loop can generate far more requests, far faster, than a human ever would, including unbounded or wasted queries when they lack the context to recognize a dead end.
