What Makes an AI Agent Different From a Chatbot: The Loop Explained

An AI agent loop is a repeating cycle in which a language model decides an action, the program executes it, and the result is fed back as new context for the next decision. Unlike a chatbot, which responds once per message, an agent runs this cycle autonomously—sometimes dozens of times—until a task is complete. Every agent loop consists of three core components: state (the accumulated goal and history), action (the model's chosen next step), and a stopping condition (the rule that ends the cycle). A key distinction is that the model only selects actions; the surrounding program is responsible for executing them, tracking state, and checking when to stop. This architecture allows agents to tackle multi-step tasks that a standard chat interface can only describe, not complete.