Why is the answer of LLM-maximalists always you are holding it wrong?
I think a lot of experienced programmers, who have adopted LLMs early on, have the same finding: yes, LLMs give a great productivity boost. No, you cannot let agents completely wild without plenty of human supervision, because it will lead to a big ball of mud and atrophy knowledge of humans. I think these are relevant data points and they should be taken into account during the adoption of LLMs.
This type of LLM-maximalist thinking is thoroughly anti-scientific, they want to throw away data points that are not in line with the hypothesis they want to see confirmed at all cost.
look at the sibling reply. these back-handed concessions are always either “AI is a great productivity boost if you’re just slamming out a CRUD web app” or the special snowflake “my big beautiful codebase is too complex.” maybe they are holding it, wrong with attitudes like that it’s hard to take them seriously. the phd holders at my office are some of the most prodigious vibe coders we have
ps: since when was complexity ever a good defense for why your codebase is difficult to work in?