Over the past year, millions of developers have started using AI tools like GitHub Copilot to help them write code. But most are only scratching the surface of what these tools can do. Copilot is more than just pressing TAB to autocomplete snippets. It can support you through the entire development cycle.

In this session, we'll explore how to use Copilot across the entire development lifecycle. A big part of this is context engineering: teaching the AI about your domain, your codebase, and your goals so its suggestions are more accurate and valuable. We'll show you how to set up instruction files and create custom agents that specialize in different development tasks. You'll see how Copilot can help with creating backlog items, designing implementation plans, writing real code, generating tests, reviewing pull requests, and producing documentation.

Through a live demo, we'll show you how to implement a production-ready feature using AI at every stage. You'll learn how to assign entire issues directly to Copilot and let it work autonomously in the background, creating pull requests for your review. We'll demonstrate how to build custom agents using .agent.md files to create specialized assistants for testing, planning, or code review. You'll learn where GitHub Copilot shines, where it struggles, and how to make the most of its capabilities.

If you're already experimenting with AI-augmented programming and want to unlock its full potential, this talk will give you the insights and techniques you need to work at the speed of thought.