AI coding agents can write code fast, but in real projects they still get lost, miss hidden constraints, and return confident wrong answers. This talk is about closing the engineering loop: collect requirements, change the code, validate the result, compare it with what “done” means, and repeat until it is ready for review.

I’ll show how to give agents the right context, create validation cycles with tests, logs, screenshots, UI state, and reports, and scale the workflow with running apps, parallel sessions, cloud emulators, and orchestration.

Attendees will leave with a practical workflow for using agents with less babysitting and more confidence.