Quantum computing progress depends as much on software as on hardware. In this keynote, we’ll start with a practical view of how high-quality code supports the development and use of quantum devices—through simulation, compilation, verification, benchmarking, and control. We'll also stress the value of state of the art classical methods to delineate where a quantum computer is genuinely required, versus where well-designed classical software is the right (and often faster) choice. We will then zoom in on PauliPropagation.jl, a Julia package we have been developing for efficiently simulating quantum circuits. We will outline the core abstractions and implementation details in the package, and what problems it is meant to make easy. A central thread will be "why Julia". Beyond performance, Julia lets us offer a fully extensible package with custom gates, data structures, and evolving types. We’ll end with an honest account of building Julia tools as a scientist: what has worked well, what has been surprisingly hard, and what we have learned about presenting research software to a community that often defaults to Python expectations.