We have substantially similar opinions, actually. I agree on your points of good developers having a clear grasp over all of their code, ethical issues around AI (not least of which are licensing issues), skill loss, hardware prices, etc.

However, what I have observed in practice is different from the way you describe LLM use. I have seen irresponsible use, and I have seen what I personally consider to be responsible use. Responsible use involves taking a measured and intentional approach to incorporating LLMs into your workflow. It’s a complex topic with a lot of nuance, like all engineering, but I would be happy to share some details.

Critical review is the key sticking point. Junior developers also write crappy code that requires intense scrutiny. It’s not impossible (or irresponsible) to use code written by a junior in production, for the same reason. For a “good developer,” many of the quality problems are mitigated by putting roadblocks in place to…

1. force close attention to edits as they are being written,
2. facilitate handholding and constant instruction while the model is making decisions, and
3. ensure thorough review at the time of design/writing/conclusion of the change.

When it comes to making safe and correct changes via LLM, specifically, I have seen plenty of “good developers” in real life, now, who have engineered their workflows to use AI cautiously like this.

Again, though, I share many of your concerns. I just think there’s nuance here and it’s not black and white/all or nothing.

You’re wrong, whether you figure that out now or later. Using an LLM where you gatekeep every write is something that good developers have started doing. The most senior engineers I work with are the ones who have adopted the most AI into their workflow, and with the most care. There’s a difference between vibe coding and responsible use.