Frisella, Tiwari, and Ruan present Piper, a system for programmatically composing data, pipeline, and expert parallelism strategies for large-scale model training. As frontier models that power agents increasingly mix parallelism schemes, programmable composition lowers the engineering cost of scaling. Relevant infrastructure for teams training their own foundation or agent models.