Worked on stabilizing core infrastructure in the pytorch/FBGEMM and pytorch/pytorch repositories, focusing on reliability and workflow improvements. Addressed a critical shape mismatch in 3D tensor processing by correcting the output shape calculation in f8f8bf16_rowwise_meta, ensuring alignment with the WQ dimension and enhancing the robustness of quantization routines using C++ and PyTorch. In addition, improved continuous integration practices by reverting ineffective auto_request_review.yml changes, restoring CODEOWNER-driven review requests, and clarifying review ownership. Leveraged DevOps skills and GitHub Actions to streamline pull request workflows, laying groundwork for future automation and reducing review noise for maintainers and contributors.