Find a narrow, reviewable task
Summarizing an inquiry, classifying documents or drafting a response for approval can be reasonable starting tasks. Define who makes the final decision and which cases leave the automated path. Design a helper with clear inputs, outputs and acceptance criteria instead of an assistant expected to know everything. Observe the human task and its information sources first.
Separate information from instructions
An external document or customer message must not change the application’s rules. Limit tools and data access to the task. Instructions inside a customer description must not trigger transfers, deletion or access to another customer’s data. Use independent server checks and explicit human approval for high-impact actions.
Evaluate outputs using real examples
Prepare an evaluation set with correct, incomplete, ambiguous and misspelled inputs. Avoid unnecessary personal data and anonymize examples appropriately. Check source consistency and required fields, not just fluent writing. Routing uncertain cases for review is part of successful behavior.
Plan costs and a fallback path
Model access can slow down, costs can change and outputs can fail validation. Design timeouts, usage limits and a manual alternative. Measure editing time, error rates and task completion rather than simply counting generated text. The underlying workflow should continue when the helper cannot contribute.