How 3 Java Champions are using GitHub Copilot for increased productivity

AI coding tools can generate code quickly, but speed alone does not solve the hardest software engineering problems. Developers still need to provide context, validate results, protect maintainability, and remain accountable for what ships. To learn how experienced developers strike that balance, we spoke with three Java Champions, all with over a decade of experience in using Java. They shared concrete examples of using GitHub Copilot in production and open source, along with the practices they use to turn AI-generated output into reliable software. Here are the tips they shared with us. How has GitHub Copilot helped you recently? I’ve been using it to analyze, design, and implement various features in both Hypersistence Utils and Hypersistence Optimizer. For example, I’ve been wanting for a long time to develop a web application that provides Optimizer event history so we can see how performance improvement efforts are materializing in application performance. Before AI, I kept postponing this task because it would have taken me weeks to develop. But using Copilot is like having a new team member, so I used it to create an app that will ship in the next version of Hypersistence Optimizer. Instead of weeks, this task took just…