How to Generate Code that Works with Claude Code /goal Feature

Heather Brooks

In this video, you’ll see a practical demonstration of how to combine AI coding tools with executable specifications to build software more reliably. Instead of generating code first and hoping it works, you’ll learn how to define end-to-end tests in plain English before implementation, review them as the source of truth, and then use AI to generate code until every test passes.

The demo walks through updating a real application by improving a user sign-up flow, showing how testRigor enables stable, implementation-independent tests that don’t rely on XPath, CSS selectors, or other fragile locators. You’ll also see how AI can generate and refine both tests and code while keeping the business requirements at the center of the development process.

If you’re interested in AI-assisted software development, Acceptance Test-Driven Development (ATDD), or building reliable enterprise applications faster, this video demonstrates a practical workflow that improves quality while reducing manual effort and rework.

“We spent so much time on maintenance when using Selenium, and we spend nearly zero time with maintenance using testRigor.”

Keith Powe VP Of Engineering - IDT