Before you automate.
Five checks before an AI workflow becomes part of someone’s job.
Start with one job
Pick a process with a clear owner, a repeatable input, and a useful output. Write down how long it takes today. That gives you something concrete to compare against.
Test on work you actually see
Use a small, representative set of requests, including awkward ones. Decide what counts as a good result before running the test. Have the people who do the work review the outputs.
Set the budget before the big run
Measure a small batch, cap the total spend, and verify that the cost alert reaches someone. Count retries and repeated context, not just the price of one model call.
Decide when a person must approve
Name the actions that need review, such as sending a message, changing a customer record, or committing money. Give the system only the access the task requires.
Try the failure path and the finished result
Test a timeout, a missing tool, and a bad response. Make it possible to stop or resume the work. Then try the deployed workflow as a user; a successful build is only one part of the check.