Less code, more performance! Runtime compilation with NVRTC offers many potential benefits to new and existing codes, but also presents challenges when it comes to implementation. To help solve this dilemma, we've developed a small C++ library called "Jitify" that hides the complexities of runtime compilation behind a simple, high-level interface. Jitify takes care of issues like kernel caching, template instantiation, type reflection, and compilation of host code for the device. It also provides a convenient parallel_for function and lambda wrapper that enables dynamic runtime selection of host or device execution. Since source code passed to NVRTC does not require CUDA-specific annotations, porting a large C++ code to CUDA using Jitify can be as simple as replacing a for loop with Jitify's parallel_for construct. We'll present some examples of Jitify in action, demonstrating how it enables better code generation, faster compilation times, and rapid code porting.