Why should a team avoid changing the prompt and model in the same evaluation run?

Why should a team avoid changing the prompt and model in the same evaluation run?

1. Changing one major variable makes regressions attributable and rollback choices clearer.
2. Model APIs reject requests when prompt text changes with the model.
3. Evaluation sets can contain only one prompt version.
4. A prompt change always costs more than a model change.