Alex Zhang discusses how language model input/output shapes have remained static since ChatGPT, with harnesses designed around autoregressive models rather than vice versa. He argues that alternative model architectures with constrained output spaces—like Jev, which outputs values in [0,1]—could enable more efficient solutions for specific use cases and agent designs.