Question 20
Domain 3A user gets a disappointing answer and clicks 'regenerate' four times, picking the best of the four. What is the structural critique?
Correct answer: A
Explanation
The critique is that repeated regenerations only resample the same model output, so the user is exploiting "sampling variance" rather than improving the system. Since there is no persistent update, it is "not iteration" and "no learning is encoded for the next run," so the underlying prompt problem remains unaddressed.
Why each option is right or wrong
A. It's sampling variance, not iteration — no learning is encoded for the next run, and the underlying prompt gap is never named.
The issue is that each click invokes a fresh stochastic decode from the same fixed model state, so the user is merely drawing multiple samples from the same distribution rather than changing the system. There is no parameter update, no memory, and no feedback loop that would carry into the next run; structurally, this is resampling under sampling variance, not an iterative improvement process, and the original prompt deficiency remains unnamed and uncorrected.
B. Regenerating costs token budget; cheaper to use one good shot.
Cost may matter, but the critique is about lack of learning, not token efficiency.
C. Regenerate uses a different model under the hood, so it's not a like-for-like comparison.
Regenerate generally re-samples the same setup; model switching is not the core issue.
D. Regenerate disables temperature controls.
Temperature behavior is separate; regenerate does not inherently remove generation controls.