Java Developers Use GitHub Copilot to Boost Productivity

What happened

Three Java Champions, each with over a decade of Java experience, shared how they use GitHub Copilot to improve productivity. One developer, Vlad Mihalcea, used the tool to develop a web application for Hypersistence Optimizer, reducing the task time from weeks to two days.

Vlad Mihalcea also described using GitHub Copilot as an IDE plugin in IntelliJ IDEA for code assistance during debugging and feature development. He emphasized that AI should improve productivity without replacing the developer, noting that he still reviews and validates AI-generated code.

Why it matters

The use of AI tools like GitHub Copilot in production and open-source projects highlights their growing role in software development. Developers stress the importance of validation, maintainability, and accountability when using AI-generated code to ensure quality and stability.

Key details

Vlad Mihalcea created custom skills for GitHub Copilot to generate documentation that mimics his writing style based on 65 published articles. He also developed skills for AI to mimic existing code practices, focusing on maintainability and stability for existing products.

Patrick Baumgartner described how GitHub Copilot helped in building a terminal UI application with Tamboui, which initially worked in Linux under WSL but had issues in Windows environments. He also mentioned a scenario where a terminal UI application had issues with the Enter key in Windows CMD or PowerShell, highlighting the importance of testing software early.