That's literally the wrong way to use LLMs though.
LLMs think in tokens, the less they emit the dumber they are, so asking them to be concise, or to give the answer before explanation, is extremely counterproductive.
This is relevant. Your example may be simple enough, but for anything more complex, letting the model have its space to think/compute is critical to reliability - if you starve it for compute, you'll get more errors/hallucinations.
Yeah I mean I agree with you, but I'm still not sure how it's relevant. I'd also urge people to have unit tests they treat as production code, and proper system prompts, and X and Y, but it's really beyond the original point of "LLMs aren't reliable" which is the context in this sub-tree.
LLMs think in tokens, the less they emit the dumber they are, so asking them to be concise, or to give the answer before explanation, is extremely counterproductive.