Learn how to build and deploy custom CUDA kernels using the kernel-builder library, which streamlines the development process and ensures scalability and efficiency. The guide walks through creating a practical RGB to grayscale image conversion kernel with PyTorch, covering project structure, CUDA coding, and registration as a native PyTorch operator. It also discusses reproducibility, testing, and sharing the kernel with the community.