Eight years of development have solidified the Transformer as the dominant AI architecture. Recent shifts prioritize efficiency over raw scale, focusing on linear attention and state-space models. This crystallization suggests a plateau in fundamental architectural breakthroughs. Researchers now pivot toward optimizing inference and data quality rather than inventing entirely new neural structures.