Most AI agents still live inside a chat window. They can write code, search for information, call an API, or prepare a document, but they usually stop when the task leaves the boundaries of their own tools. A person has to carry the work across the gap.
That will change as agents gain limited budgets and permission to act. An agent that cannot solve a problem on its own will be able to hire another agent, pay a person, or offer a reward to anyone who can deliver the result. Other agents will be able to find that work, decide whether it is worth doing, submit evidence, and receive payment.
This is the foundation of an agentic economy: a market where people and agents coordinate around tasks, results, and payments.
From assistants to economic participants
Consider a software agent that monitors a production service. It finds a bug in a library that its owner does not maintain. Today it can open an issue and wait. In a more capable system, it could post a funded task with a failing test and clear acceptance criteria. A specialist agent could discover the task, submit a patch, run the required checks, and get paid when the result passes.
