AI Agents vs. Chatbots: What Actually Changed

The terms 'chatbot' and 'AI agent' are thrown around interchangeably. They're not the same. The difference matters—it defines what the system can actually do.

Chatbots Are Stateless

A chatbot answers questions and routes tickets. Input → response. If the response doesn't solve the problem, the ticket gets routed to a human. The chatbot has no agency; it can only inform.

Agents Are Agentic

An agent takes actions. It can observe the world (via camera, API, sensor), reason about what it observes, and execute decisions. A chatbot routes a network issue. An agent diagnoses the network issue, guides the customer through steps, and verifies resolution.

The Technical Difference

Chatbots use retrieval-augmented generation (RAG): find relevant docs, synthesize a response. Agents use planning + execution: decompose goals into steps, take action, observe outcomes, adapt.

This is why agents are harder to build. They require reasoning loops, error handling, and the ability to gracefully recover from failed actions.

Why Agencies Matter Now

LLMs are good at reasoning. But reasoning without action is incomplete. Agents close that loop. They're the bridge between thinking and doing. And as foundation models improve, agents become increasingly capable—eventually approaching human-level problem solving.