The K-Search framework translates decades of CUDA optimization knowledge into architecture-native strategies for MLX. Instead of copying instructions, it maps high-level optimization patterns to Apple Silicon's specific hardware traits. This approach reduces the manual effort required to write efficient GPU kernels. It allows researchers to port complex AI workloads without years of low-level expertise.