An agent is a system that pursues a goal by choosing its own actions in a loop, rather than executing a fixed script written by a developer. The defining property is autonomy over control flow: the model decides what happens next, and the surrounding program supplies the means to act and the results of acting.

Agent

In a conventional program the developer writes the branches; in an agent the model writes them at runtime by selecting the next tool call. This is what makes agents useful for open-ended work and also what makes them harder to test: the same input can produce different, equally valid trajectories.

Autonomy Over Control Flow

A topic of the Building AI Agents course. Planned for 1.5 hours at Easy difficulty.

University of Michigan - Ann Arbor

A category of the Building AI Agents course, covering 4 topics.

Foundations of Agentic Systems

What Makes a System an Agent

A topic of the Building AI Agents course. Planned for 2 hours at Medium difficulty.

The Perception, Reasoning and Action Loop

Agent Architectures: Reactive, Deliberative, Hybrid

Choosing a Model for an Agent

For agents, the deciding capability is rarely raw knowledge; it is whether the model reliably respects tool schemas, stop conditions and formatting contracts across dozens of turns. A model that drifts from its contract at turn fifteen cannot be deployed unsupervised.

Learn Before

Related

Learn After