An agent is a structure that decides for itself which tool to call and when in order to reach a given goal. That flexibility is both its power and its real enterprise risk.
01. How It Differs from a Chain
In a chain you set the order of steps and the outcome is predictable. In an agent the model sets the order. The same input can take two different paths. That fundamentally changes debugging and testing.
02. Three Components
An agent has three parts: a goal, the tools it may use, and a stopping condition. The third is the most neglected; an agent without a clear stopping condition loops forever and generates an invoice.
03. Where It's Valuable
Where input structure is uncertain and the number of steps isn't known in advance. Investigating a support ticket by gathering information from several systems, or comparing multiple sources into a report.
04. Where It's Overkill
In processes with defined steps and fixed rules an agent is unnecessary complexity. Issuing invoices, updating stock and routing approvals run cheaper and more reliably as deterministic flows.
05. The Production Reality
The general picture across the industry isn't optimistic: the large majority of pilots stall before reaching full production. The causes are less technical than governance gaps, missing identity management, absent rollback plans and weak observability.
06. The Starting Rule
Build your first agent on reversible work. A read-heavy scenario whose output passes human approval both demonstrates value and bounds risk.