Especially if you're having an LLM write non-interactive scripts to calculate complex things from large datasets, glancing at the output is not enough to know if the output is remotely accurate (unless the output is so trivial you could literally do it in your head).

Case in point: I recently asked an LLM to write a pile of code to compile historical baseball stats to test betting success against the results of my hand-written code that evolves genetic algorithms. I marveled for a little while at the unbelievable improvement in EV/ROI that this script was showing could have been achieved from certain small tweaks. I only noticed after pushing a total bet that the push registered on the output as a win - and only because I was carefully staying on top of it. A single stupid recursively operating >= instead of > had caused completely nonsensical results that looked plausible.

Imagine, like, trusting a 10k loc script to give you data for something you were going to build in the physical world, and hoping an LLM hadn't made a mistake like that.