Jingyi Tang

Today's frontier agents virtually collapse in professional engineering environments, solving just 3.6% of multi-software workflows when held to real-world physical and geometric constraints.

Despite the advancements in multimodal agents, even the best models struggle with interactive spatial reasoning, achieving only a 17.4% success rate in complex real-world tasks.

LLMs can leapfrog state-of-the-art scientific algorithms and human-designed solutions, but only if you scale the evaluation loop, not just the model.