Comment by ChrisbyMe
3 days ago
this is the right way to try and tackle this problem imo. too much focus in AI dev tooling has been on building "products" that only half work.
making codebases understandable to humans, and LLMs etc, is a better approach
self documenting, interpretable systems would actually solve a lot of dev churn in big companies
plus it's not like artifacts have to be limited to code once that's figured out
I don't think it's a choice; I use both. Code understanding is especially useful in new code bases, but once that's over you need to get work done.