The trouble with this argument is that fundamentally this whole field has no sound theoretical foundation. It has no deterministic rules you can learn that will reliably get good results.
That also means there is no way to prove that what works well today will continue to work well tomorrow. Nor can you be sure that something you've tried and ruled out in the past because it didn't get satisfactory results won't be the new SOP next week. Any experience you gain in the field might be obsolete within hours.
An important consequence of this is that you can't train someone else to use LLM-based tools effectively either. At best you can train them to use specific tools and models that exist today effectively and hope the knowledge remains useful for a significant period of time. Even that assumes you have the knowledge yourself and aren't relying on something that worked well yesterday but could already be out of date after something new was released last night.
This looks like a fundamental problem that can never be fully solved as long as LLMs of the type that are popular today are behind the tools. People forget in all the hype and rapid change that the whole idea of agentic AI tools in mainstream development is barely a year old. We have no idea yet what the long-term consequences of so many people and organisations in the industry all but abandoning traditional programming skills in favour of AI agents will be. There already seems to be a lot of anecdotal evidence about programming skills atrophying, developers burning out, and the quality of the finished product dropping but it's probably too soon to have serious data to analyse or to draw any big conclusions about what is a good way forward from here.
You don’t have to look too far to see where we are going. But you do need to have your eyes open.
As I said - we have no idea yet what the long-term consequences of the recent rapid shift towards AI and agents will be. I prefer to make decisions based on evidence, not hearsay or wishful thinking.
I have been around long enough to see a lot of hype cycles in programming. They were all going to be revolutionary. They were all going to change the nature of programming forever. They were all going to result in dramatic increases to productivity (or other similar claims).
Many of those phases did turn out to have some good - sometimes excellent - ideas. A lot of those have since been widely adopted in the industry. They also had plenty of ideas that didn't really work out. In the end we have improved some areas to a useful degree but none of those phases resulted in orders of magnitude increases in useful productivity or quality.
So far LLMs and agents are looking like a familiar story. They're proving to be useful tools for some types of work. They're now quite good at producing code to the standard of an average developer doing a well understood task - and in many cases that is all you need! But the jury is still out on whether they'll ever be able to replace good programmers or build genuinely innovative products where there aren't lots of examples of good existing implementations to train the models. Those are the parts of the industry where I do most of my own work and I hear much more scepticism about these tools from those developers than in the average online discussion.
No, it's not. As evidence of intelligence atrophy, I offer up this word salad that barely makes any sense as evidence: someone barely able to write a coherent thought can apparently produce working software.