Choose a task with reviewable output
Drafting a response, summarising a long enquiry, or suggesting a category can be reasonable experiments because someone can inspect the result. Begin with a narrow task and examples of acceptable output. Avoid assuming that a fluent answer is an accurate one. Identify which facts must come from your own records and how a reviewer can check them.
Decide what information can be used
Before connecting a model to a business system, list the data it will receive and why each field is necessary. Remove information that is not relevant to the task. Check the provider and deployment settings with the person responsible for your organisation’s data handling. Keep secrets and credentials out of prompts, and avoid treating incoming documents as trusted instructions.
Keep approval at consequential steps
A suggested reply is different from sending that reply to a customer. A draft record is different from changing a live account. Make those boundaries visible in the interface and decide who can approve an action. Give reviewers the original source alongside the suggestion so they can assess it without switching between several tools.
Test failure as well as usefulness
Try incomplete, contradictory, and unfamiliar examples during a pilot. Record where the system produces an unsupported answer or fails to recognise uncertainty. Provide a manual route when a result is unsuitable. Evaluate the review effort alongside any time saved; if checking the output takes longer than doing the task, the workflow may need a different approach.
