This article discusses Autocomp, a framework designed to optimize code for tensor accelerators using large language models. It highlights how Autocomp outperforms human experts in efficiency and portability, particularly when applied to AWS Trainium. The authors explore the challenges of programming tensor accelerators and the unique optimizations required for effective performance.