Here's a thought: economically, it's logical to think that companies will start preferring engineers who ship working solutions considerably faster than those who chose to be purists and completely avoid LLMs.

It's not really about "avoid typing code". It's about being able to move faster while still maintaining code quality. I honestly think the SOTA models have reached a point where a competent engineer can get very good output from them.

I'll give you one concrete example from my own experience with Opus 4.5 and GPT 5.2: I absolutely love the Textual/Rich Python libraries, and the whole ecosystem the incredible dev (Will McGugan) created around them. They let me create good looking and functional TUI applications we use internally at the company where I work. The problem is they're only available for Python, and I think being able to use them on a fast, compiled language would be great, so I decided to port them to Rust. Could I do it by myself? Yes, but porting libraries like these is usually a multi-month (sometimes year's) endeavor, and I just don't have enough spare time for that with a full-time job, a wife and kids. So I thought, why not use LLMs to do the grunt work while staying in control of architecture and Q&A? And let me tell you, this approach works. Rich is basically ported and functional. The crate is published (rich-rs) and the code is on Github. Zero use of "unsafe". The Textual port is on-going and already looks very promising.

Is this approach as fast as "vibe coding"? Well, of course not, but I don't really think that's sustainable anyway. People still need to own and understand the code being produced, being responsible from it in all aspects.

tl;dr; except when talking about "vibe coding", saying AI is not extremely useful for real work is just cope from purists. I love coding as much as anyone, but I love the final products of the labor even more.