My experience is that "the rent ends up due" basically you "pay cognitively" up front (building an understanding from/while doing) or later (when you have to t

My experience is that "the rent ends up due" basically you "pay cognitively" up front (building an understanding from/while doing) or later (when you have to troubleshoot something in a largely LLM-generated tangle. Basically it moves from--"oh yeah I wrote something with this schema earlier" to "I saw some DB code fly out around an hour ago; maybe it's there. Where was it? `grep models ./src` wait, was it in `db` and other silly stuff like that. No free lunches or whatever. I'm not an extensive LLM user for programming and remain mostly agnostic on overall uses for development (sure a brand-new React thing and you're sailing, but a huge old crusty codebase, even in a language well-represented in the training set is a LOT less promising IME) However there's use cases where I'd straight up not do whatever until the latest minute possible that I use LLMs for now: Cloudformation, various utility bash scripts, simple AWS Lambda functions and other things I consider annoying chores. For me, these cases alone have been an unambiguous victory.