Artificial intelligence has rapidly advanced molecular science, yet progress has largely unfolded through specialized models tailored to specific tasks. In this issue of Cell, Peng et al. introduce PocketXMol, a unified 3D generative framework that reframes molecular design problems as conditional reconstruction of atomic interactions. Demonstrations across design scenarios highlight its potential in molecular engineering.