You have to think of the LLMs as more of a better search engine than something that can actually write code for you. I use phind for writing obscure regexes, or shell syntax, but I always verify the answer. I've been very pleased with the results. I think anyone disappointed with it is setting the bar too high and won't be fully satisfied until LLMs can effectively replace a Sr dev (which, let's be real, is only going to happen once we reach AGI)

Yea, I use them daily and that’s my issue as well. You have to learn what to ask or you spend more time debugging their junk than being productive, at least for me. Devv.ai is my recent try, and so far it’s been good but library changes quickly cause it to lose accuracy. It is not able to understand what library version you’re on and what it is referencing, which wastes a lot of time.

I like LLMs for general design work, but I’ve found accuracy to be atrocious in this area.

It will be a system, not a single model, and will depend on what programming task you want to perform

probably need routers, RAG, and reranking

I think there is a role for LLM + deterministic code gen as well (https://github.com/hofstadter-io/hof/blob/_dev/flow/chat/pro...)