This thread makes me think of when I was refactoring a COBOL application when I just started my SWE career in 2016/2017. The original program was from 1989 and things like git blame, ticket systems etc. wasn't there. There was rudimentary version control, but that didn't go back to far, and also surprisingly there was some documentation. But the major thing that helped me answer the "why's" was that the original programmer still worked in the same department, and he actually remembered some of the choices he made.
Other than that, it was a matter of remaking the same mistakes and figuring out the "why's" the hard way.
Readit Newskrupers commented on Ask HN: How do you find the "why" behind old code decisions? · Posted by u/siddhibansal9
krupers commented on Show HN: I've been using AI to analyze every supplement on the market pillser.com/... · Posted by u/lilouartz
I just searched the most popular/researched supplement of all time: creatine. There is a mistake in the data there: the Wellnesss Code Whey Protein indeed contains creatine, but not 2g per container, but 2g per serving (that is correctly reflected). Error is easily spotted due to the price per gram being an extreme outlier. That is perhaps something you can look for when evaluating the data gotten from the LLM.