A small model bill can hide review, correction and investigation work. A fictional refund example shows how to price those costs, check daily specialist slots and decide when to hold expansion.
A prompt change can send more refunds to specialists without changing code. Decide its release using tested actions, qualified reviewer time and someone who can stop new admissions.
A refund assistant can give a convincing answer while requesting the wrong amount. Check its proposed action, attempted service requests and stored business outcome before shipping a change.
A refund assistant can pass permission checks and still leave customers with wrong proposals or unresolved payments. Give the product team an owner who can stop intake, fix the workflow and see every affected case through to an answer.
An agent can propose a refund but it cannot grant itself permission. Check order access before a tool runs and repeat the check in the business service before a refund attempt.
An AI workflow can pass its quality checks while leaving too little time for human review. Use a review worksheet and a launch rule that checks qualified staff, unfinished work and decision deadlines before admitting traffic.
A timed-out write may already be complete. Save its operation identity before sending it and keep uncertain outcomes pending. Recover the original receipt through downstream support rather than sending a new business action.
AI systemsSoftware engineering
Paths through the archive
Each topic starts with one useful article, then goes deeper.