I have worked with a lot of code generation systems.

LLMs strike me as mainly useful in the same way. I can get most of the boilerplate and tedium done with LLM tools. Then for core logic esp learning or meta-programming patterns etc. I need to jump in.

Breaking tasks down to bite size, and writing detailed architecture and planning docs for the LLM to work from, is critical to managing increasing complexity and staying within context windows. Also critical is ruthlessly throwing away things that do not fit the vision and not being afraid to throw whole days away (not too often tho!)

For ref I have built stuff that goes way beyond CRUD app with these tools in 1/10th of the time it previously took me or less -- the key though is I already knew how to do and how to validate LLM outputs. I knew exactly what I wanted a priori.

Code generation technically always 'replaced' junior devs and has been around for ages, the results of the generation are just a lot better now., whereas in the past it was mixed bag of benefits/hassles doing code generation regularly, now it works much better and the cost is much less.

I started my career as a developer and the main reasons I became a solutions systems guy were money and that I hated the tedium boilerplate phase of all software development projects over a certain scale. I never stoped coding because I love it -- just not for large enterprise soul destroying software projects.

Quick note that this has not been my experience. LLMs have been very useful with codebases as far from crud web apps as you can get.