The interface is the last mile
It is easy to make a chat interface look convincing. It is harder to make the answer dependable when a customer, operator, or warehouse coordinator needs it.
A strong retrieval-augmented generation product starts by defining which questions it should answer. That boundary determines the content you need, the way you prepare it, and the standard an answer must meet.
Start with a question set
Collect real questions from the workflow. Include routine requests, ambiguous wording, missing information, and cases that should be handed to a person. This becomes a practical evaluation set rather than a demo script.
Then inspect the source material. Current procedures, clear ownership, useful metadata, and consistent terminology usually improve the product more than another layer of prompt instructions.
Evidence creates trust
The answer should make it easy to see where the information came from. Citations, document dates, and short source excerpts let a user verify the guidance without restarting the search from zero.
The best RAG experiences do not ask people to trust the model. They help people trust their own next decision.