GitHub Copilot build performance for Windows

Key Takeaways

Every extra minute spent waiting for your build is time you could be coding, testing, or debugging. From our many customer conversations over the years, we know that long build times are a recurring painpoint for our C++ community. Today, I'm excited to show you an early preview of GitHub Copilot build performance for Windows, available now in private preview. This new capability uses the power of MSVC's trace capture technology to analyze your build and automatically suggest optimizations that help you speed up your build times. Let me show you how the agent can accelerate the build time of a real world project with a new GitHub copilot build performance capabilities in Visual Studio 2026. In this demo, we will be using Jolt Physics, an open- source physics library used by major AAA titles. With Visual Studio 2026 open, let's switch to GitHub Copilot Chat and select the agent at buildp. Here we can ask the agent to make my build faster. Copilot prompts us to start a build. Let's accept it so the agent can run the tool and capture the insights it needs. When the trace capture is complete, GitHub C-Pilot will analyze the data to highlight expensive header inclusions, long function generation bottlenecks, and costly template instantiations. In our case, because the agent is reading header files, we know that it has found several expensive header inclusions are slowing down our build. With this knowledge, the agent begins optimizing and moves identified headers into a pre-ompiled header or PCH, a common workflow to reduce expensive header inclusions. Next, the agent kicks off another build to verify the changes are compiled successfully. As you can see, there were some build errors, but the agent is addressing them without needing further input from me. The agent continues to iterate to address the error and complete a successful build. Finally, with the build successful, the new GitHub copilot build performance capability summarize the changes, highlights the hot spots that were fixed, and shows how much time you saved. In our case, we have saved 5,000 milliseconds, shaving off about 20% of the total build time. The summary not only lists expensive headers but also suggests opportunities for further improvement. At this point, you have the option to keep or undo the changes suggested by GitHub copilot. Build times are more than a technical metric. They shape how quickly you can iterate, respond to feedback, and deliver value. Every minute saved means you stay focused on your tasks and your ideas can flow faster. GitHub Copilot Build Performance for Windows is designed to help you achieve just that. It analyzes your build traces and applies targeted optimizations to help you improve your workflow. But it's not just about shaving off build time. It's about eliminating friction in your workflow so you can keep your momentum, scale your productivity and stay focused as your codebase grows. Of course, as your codebase evolves in complexity, you can run this agent periodically to keep performance in check and ensure that speed and efficiency grow with the size with your code base. Ready to see how the new GitHub copilot build performance capabilities work for your project? Sign up for the private preview today at aka.mscpp agents private preview. Thank you and we'll see you next time.