“AI agent” gets used loosely enough that it is worth being precise. A chatbot answers questions. An agent takes actions, and decides what steps to take to get there.
The practical difference
A chatbot given a question about an order status looks up the answer and replies. An agent given a goal, “get this customer their refund,” can check the order, verify the return policy applies, issue the refund through your systems, and send a confirmation, deciding the sequence of steps itself rather than following a fixed script.
Why this requires more than a better prompt
Agents need access to tools, actual functions that can query a database, call an API, or take an action, and a way to decide which tool to use and when to stop. That is meaningfully more engineering than a chat interface: you are building a system that takes real actions in real systems, which means real guardrails around what it is allowed to do without a human checking first.
Where agents are actually worth building
Agents earn their complexity on workflows that are genuinely multi-step and repetitive, lead qualification, ticket triage and routing, data entry across systems, not on simple FAQ-style questions where a well-built chatbot already does the job for a fraction of the engineering cost.
Have a project taking shape?
Tell us what you are trying to build, and we will tell you plainly what it takes.