I'd actually bet against this. The "bitter lesson" suggests doing things end-to-end in-model will (eventually, with sufficient data) outcompete building things outside of models.
My understanding is that GPT5 already does this by varying the quantity of CoT done (in addition to the kind of super-model-level routing described in the post), and I strongly suspect it's only going to get more sophisticated
My understanding is that GPT5 already does this by varying the quantity of CoT done (in addition to the kind of super-model-level routing described in the post), and I strongly suspect it's only going to get more sophisticated