An agent is not a smarter chatbot, it is a loop: it asks the model, performs an action, reads the result back, and starts again, until the job is done or the budget runs out. The model itself is unchanged — the agent is the framework built around it.
That loop turns out to be surprisingly little code. The entire control flow of a production agent scoring above 74% on a benchmark is roughly a hundred lines. What is a lot is everything else around it: the permissions, the error handling, the logging, and the point where it stops for human approval.
The limit shows up as the number of steps grows. Measurements put models close to flawless on human tasks shorter than four minutes, and below ten percent on tasks longer than four hours — which is not about the model being "stupid", but about errors piling up step by step.
What a real run looks like step by step, and where it goes off the rails, is shown by What an Agent Actually Does, Step by Step in full. Directly related terms: agent loop, tool use and human in the loop.