I agree. Language models are good at codegen, in some sense they are just another codegen tool, except instead of transforming a structured language (like a config file or markdown) into code, they can convert natural language into code. Genuinely useful for the repetitive boilerplate grunt work. If that's all you do, then I can see fearing getting replaced. Thankfully by handling the drudgery, it frees us up to work on more complex and cutting edge work.

Like, it's not surprising that the developers who frequently talk about +90% of their work being delegated to LLMs are web developers. That is a field with very little innovative or complex code, it's mostly just grunt work translating knowledge of style rules and markup to code, or managing CRUD. I'm really thankful I can have a language model do that drudgery for me.

But compare that to eg. writing a multithreaded multiplayer networking service in Rust, they fall woefully short at generating code for me. They can be used in auxiliary aspects, like search or debugging, but the code it produces without substantial steering is not usable. It's often faster for me to write the code myself, because it's not a substantial amount of low impact code required, but a small amount of complex high impact code which needs to satisfy many invariants. This is fast to type, the majority of the work is elsewhere. At the end of the day, they work really well to replace typing the boilerplate, which is much appreciated.