CSP-MACE-Å is the first machine learning model to match DFT accuracy for crystal structure prediction while delivering a 10,000x speedup, and its training demonstrates that a Claude Code agent autonomously driving a cloud GPU experiment loop can replace much of the manual execution and bookkeeping in AI research workflows.