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…
- force close attention to edits as they are being written,
- facilitate handholding and constant instruction while the model is making decisions, and
- 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.
Not a problem if you believe all code should be free. Being cheeky but this has nothing to do with code quality, despite being true
This argument can be used equally well in favor of AI assistance, and it’s already covered by my previous reply
It’s deterministic
This is not what a “good developer” uses it for