General-purpose coding agents can discover hardware optimization patterns automatically by working at scale—using multiple agents to explore different optimization strategies yields significant speedups without domain-specific training.
This paper shows that general-purpose AI coding agents can optimize hardware designs without specialized training. The approach uses multiple agents working together: first decomposing designs into smaller pieces and optimizing each, then launching additional agents to find cross-function improvements.