token budget is becoming part of my agent workflow design

I think token budget is becoming part of agent workflow design.

If every run feels expensive, people under-test. They save quota, overthink prompts, and avoid the repetition that reveals failure modes.

If every run feels cheap, people can over-delegate. They generate more output than they can review.

So the useful question is not "which model is best?"

It is:

Which step deserves which level of model?

My current rule:

• cheap / lower-reasoning runs for bounded, reviewable repetition
• stronger models for ambiguity, hard judgment, debugging, and review
• human review for acceptance

Do not spend premium reasoning on an unclear task.

First make the task smaller.

Then choose the model.