Your first version is rarely your last. AI will get most of the way there, but something will be off: a button that does nothing, an error in the console, or a feature that broke when you added another. This module teaches you how to keep moving forward when that happens.
It covers iterating in small steps, reading error messages, and giving the AI the right context (the error, the file, and what you expected) so it can fix the real problem instead of guessing. You will also learn what to do when the AI gets stuck in a loop: roll back, start a fresh chat, or change your approach.
Watch the lessons in order, then continue on to Reading & Reviewing AI Code.
A beginner walkthrough that covers using Git checkpoints to undo changes, and debugging by giving the AI the console error and context.
A hands-on look at debugging AI-built apps in Cursor with Sentry, so the AI sees real errors instead of guessing.
Wes and Scott on making AI coding more reliable with deterministic tools like ESLint, knip and Sentry that catch problems automatically.
Why AI-written code is hard to trust, and the practices that make iterating on it more dependable.