Part XV — AI × Quantum Computing
Two technology waves are cresting simultaneously, and you are learning to swim in both. AI is already reshaping how quantum engineering gets done — code generation, literature synthesis, decoder learning, calibration automation — while quantum's own relationship to AI (Part XIII's QML) is a separate, more contested story. This part is written from the working reality of 2026: large language models are standard tools in quantum research groups, and the engineers who thrive are neither AI-avoidant nor AI-dependent, but AI-*literate* — fluent with the tools, clear about their failure modes, and deliberate about which human skills they are compounding. The book's thesis gets its sharpest test here: what should you become good at?