Yeah but it kind of kneecaps the model. They need tokens to "think". It's better to have them create a long response then distill it down later.
Also, if that works, why doesn't copilot/cursor write lots of excessive code mixed with lots of prose only to distill it later?
The “thinking” models are really verbose output models that summarise the thinking at the end. These tend to outperform non-thinking models, but at a higher cost.
Anthropic lets you see some/all of the thinking so you can see how the model arrived at the answer.