Connecting a model to a system is often the most visible part of an enterprise AI project, and therefore the part most easily mistaken for the whole job.
An FDE actually faces a workflow: who makes a judgment and when, where information comes from, who receives the result, and how exceptions are handled. Only after understanding those questions can we decide where AI belongs and what must remain a human responsibility.
A demo can prove that a capability exists. It cannot prove that the capability fits daily work. The model needs reliable context before it and actionable output after it, while permissions, feedback, deployment, and changing requirements surround both.
The real deliverable, then, is not a model call. It is a workflow that has improved and can continue to operate. Code matters, but moving technology and the business forward in the same iteration is what makes the role distinctive.