A practical starting point
Work through these checks in order. Use the results to decide what needs to change in your own workflow.
- Version instructions, model settings and relevant data sources.
- Run the evaluation set before deployment.
- Release gradually and watch for changes in user corrections or failure patterns.
A shorter prompt may reduce cost while also dropping an important exception-handling instruction.
A mistake to avoid
Do not change multiple major components simultaneously when attribution matters.
How to check progress
Record which version produced each evaluated result and compare like-for-like cases.
Your action checklist
Use this checklist while reviewing your own setup. Checkmarks are temporary and stay in this open page.
Need the wider workflow?
This quick note covers one decision. For a worked example, decision table and a fuller implementation workflow, read Choosing the first AI workflow to pilot.
Further reading
Official background resources for this topic. The workflow above is general guidance, not a guarantee of a particular result.
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