Windows AI Workflows: From Request to Reviewed Result
Plan a focused Windows AI workflow, give Rachna a clear task, and verify the result before using it.
Choose a small, measurable task
Start with one folder or repository. For example, ask for a summary of a project and a list of files relevant to a bug. Name the folder, the desired output, and the actions that need your review.
Write a request with boundaries
Try: “Read this repository and explain how the login flow works. List the relevant files and suggest a fix for the error I describe. Ask before installing dependencies or changing credentials.” Replace the repository and error with your own details.
Move from inspection to action
Review the explanation first. Then request a small change and ask the assistant to show the diff and run the relevant existing checks. Connected tools and available permissions determine which actions can be completed.
Verify the result
Read the changed files, check test output, and try the affected workflow yourself. For folder organisation, start with a copied sample and review proposed moves before applying them to the full folder.
Make the workflow repeatable
Save the successful task instructions with the inputs, expected result, and review steps. Reuse that request with fresh context rather than assuming the assistant remembers earlier files.