They typically operate in a ‘continuous loop’: observe, think, act, repeat.

Said simply, they keep working towards whatever goal they’re after until they decide it’s done & ready. They do that again next time they’re triggered to do it.

First, they gather information from their environment - APIs, databases, user input, or real-time data streams. Then they process this information against their goals and constraints using AI reasoning.

Next, they choose and execute actions through connected tools and systems.

Finally, they evaluate the results and decide whether to continue, adjust course, or complete the task. Think of a customer support AI agent. They may think they gave a good response, but if the customer complains back, they just keep working on it.

The key difference from traditional software is the thinking step - agents reason about their situation rather than following predetermined logic paths.