What is Reasoning Loop / ReAct?
The pattern where an AI agent alternates between thinking and acting until it solves the task — its way of 'thinking out loud'.
// Explanation
ReAct (Reason + Act) is the fundamental pattern of AI agents: the model reasons about what to do (Reason), executes an action like searching the web or reading a file (Act), observes the result, and repeats the cycle until the goal is complete. It's literally how an agent 'thinks'. Popular variants include Chain-of-Thought (reasoning step by step in a straight line), Tree-of-Thought (exploring multiple reasoning paths like branches of a tree), and Reflexion (the agent evaluates its own mistakes to improve).
// Example
You ask the agent 'find cheap flights to Madrid for June'. The agent thinks: 'I need to search for flights' → searches the web → thinks: 'these prices are high, let me try flexible dates' → searches again → presents you with options. Each think→act cycle is a ReAct loop.