Token price is easy to compare. That is why people overuse it. But AI power users do not buy tokens because tokens are interesting. They buy outcomes. They want: a bug fixed a draft written a document summarized an image generated a workflow automated a decision supported a research question answered That is why token price is an incomplete metric. It is visible, but it is not always useful. The better metric is cost per finished task. Here is the difference. Token price asks: How much does one unit of model usage cost? Cost per finished task asks: How much did I spend to get usable work done? Those are not the same question. A workflow can look cheap at the token-price level and still be expensive at the task level. Why? Because real AI work includes more than raw token cost.…