Yufeng Li contributed to the microsoft/onnxruntime repository by focusing on codebase hygiene, specifically removing the unused neural-speed component. This work involved analyzing the software architecture to identify legacy code that no longer aligned with the project’s roadmap. Using C++ and CMake, Yufeng streamlined the codebase, reducing architectural complexity and minimizing future maintenance risks. The removal of neural-speed not only lowered the potential for technical debt but also improved onboarding and maintainability for the ONNX Runtime project. Over the course of the month, Yufeng’s efforts centered on thoughtful refactoring rather than feature expansion or bug fixing, demonstrating careful engineering judgment.