AI Can Write Code. Who Checks That It Works?

AI can produce working code while the customer still gets a broken outcome. Follow a checkout retry to see what a passing test can miss—and how to verify the fix. We build a small local example: an order is accepted, its response is discarded, and a retry creates a duplicate. Then we define acceptance criteria and use a stable operation key to make the illustrated retry safe. You will learn the difference between function behavior and user outcomes, why a timeout is uncertain, what idempotency keys do, and how function, integration and user-journey tests support different claims. This is a constructed in-memory Python demonstration, not a model benchmark, real payment system or browser end-to-end test. Production systems also need concurrency, persistence and failure-handling design. Subscribe to InfraLensreal for visual explanations of AI engineering, DevOps and infrastructure. Which failure case would you test first? CHAPTERS 00:00 The green test and the failed purchase 01:06 The response disappears 02:15 Start with the outcome 03:28 Make retries safe 04:44 Verify more than the happy path 05:54 The skill that matters References: https://docs.stripe.com/api/idempoten... https://playwright.dev/docs/best-prac... #SoftwareTesting #AIEngineering #QualityAssurance