An event-driven AI agent subscribes to events that describe something that happened or work that became available. The agent can process matching events, produce structured results and emit new events for other agents or services.
This design lets workflows evolve without placing every step in one fixed graph. Typed events and durable logs make dependencies explicit, while queues and validation isolate failures and stop invalid results from crossing into another part of the system.
ELI5
An event-driven AI agent starts or continues work when it receives a clearly described event, such as a new document, a completed test, or a support request. It does not need to follow only one fixed sequence or wake up on a simple schedule.
For example, a review agent could receive an event when another agent finishes a draft, check the result, and emit a new event for publication or correction. Typed events, durable records, and validation help keep invalid results from spreading through the system.
How does an event-driven AI agent receive work?
It subscribes to selected event types and begins processing when the runtime delivers a matching event.
Why use events instead of a fixed agent graph?
Events allow components to evolve independently and make it easier to add, remove or replay processing stages without redesigning one graph.
