AI can generate code in seconds. We can create features, tests, and pull requests faster than ever. But if writing the code is getting easier, what is the real bottleneck?

I’ve seen the challenge shift from generating code to knowing whether that code is actually good. Does it solve the right problem? Does it fit the architecture? Can we trust it in production? As AI helps teams produce more code, testing, review, clear constraints, and human judgment become even more important.

In this session, we will look at how teams can shift their focus from generation to validation. I will share practical ways to check AI-generated work throughout the development process, catch problems earlier, and decide when the code is actually ready for production.