Worked on streamlining the GPU programming workflow in the BradLarson/max-recipes repository by simplifying the recipe compiler registration process. The update removed the need to specify the number of output arguments, making GPU development more efficient and less error-prone. To strengthen reliability, numerical comparison utilities were added in Python, enabling direct verification of GPU computation results against NumPy outputs. This approach expanded regression test coverage and improved trust in GPU-based calculations. The work demonstrated practical use of GPU programming, Python scripting, and API integration, focusing on maintainability and robust verification rather than bug fixes during the development period.