I am going to try to put this kindly: it is very glib, and people will find it offensive and obnoxious, to implicitly round off all resistance or skepticism to incuriosity. Perhaps to alienate AI critics even further is the goal, in which case - carry on.

But if you are genuinely confused by the attitudes of your peers, try asking not "what do I have that they lack" ("curiosity"?) but "what do they see that I don't" or "what do they care about that I don't"? Is it possible that they are not enthusiastic for the change in the nature of the work? Is it possible they are concerned about "automation complacency" setting in, precisely _because_ of the ratio of "hundreds of times" writing decent code to the one time writing "something stupid", and fear that every once in a while that "something stupid" will slip past them in a way that wipes the entire net gain of AI use? Is it possible that they _don't_ feel that the typical code is "better than most engineers can write"? Is it possible they feel that the "learning" is mostly ephemera - how much "prompt engineering" advice from a year ago still holds today?

You have a choice, and it's easy to label them (us?) as Luddites clinging to the old ways out of fear, stupidity, or "incuriosity". If you really want to understand, or even change some minds, though, please try to ask these people what they're really thinking, and listen.

My feeling is that the code it generates is locally ok, but globally kind of bad. What I mean is, in a diff it looks ok. But when you start comparing it to the surrounding code, there's a pretty big lack of coherency and it'll happily march down a very bad architectural path.

In fairness, this is true of many human developers too.. but they're generally not doing it at a 1000 miles per hour and they theoretically get better at working with your codebase and learn. LLMs will always get worse as your codebase grows, and I just watched a video about how AGENTS.md actually usually results in worse outcomes so it's not like you can just start treating MD files as memory and hope it works out.

I don't think that people who don't want to use these tools or clean old ways are incurious. But I think these developers should face the fact that those skills and those ways they are reticent to give up are more or less obviated at this point. Not in the future, but now. It's just that the adoption of these tools isn't evenly distributed yet.

I think there's a place for thoughtful dialogue around what this means for software engineering, but I don't think that's going to change anything at this point. If developers just don't want to participate in this new world, for whatever reason, I'm not judging them, but also I don't think the genie is going back in the bottle. There will be no movement to organize labor to protect us and there be no deus ex machina that is going to reverse course on this stuff.

It's important to point out that you're the one working hard to define AI critics as a camp/group/class when a stronger argument can be made that we're all in the same camp/group/class. I use agentic LLMs for coding every day and I think that it's incredibly important to maintain a critical lens and be open to changing our minds.

However, history suggests that creating artificial divisions is the first step towards all of the the bad things we claim not to like in this world.

Tech adoption generally moves like Time's Arrow. People who use LLMs aren't geeks who changed; we're just geeks. If you want to get off the train, that's your call. But don't make it an us vs them.

Underlying this and similar arguments is the presumption that the "old way" was perfect. You or your colleagues weren't doing one mistake per 100 successful commits. I have been in an industry for decades, and I can tell you that I do something stupid when writing code manually quite often. The same goes for the people that I work with. So fear that the LLM will make mistakes can't really be the reason. Or if it is the reason, it isn't a reasonable objection.

I read the parent comment as calling the majority of AI users "incurious", and not referring to us who resist AI for whatever reasons. The curious AI users can obtain self-improvement, the incurious ones want money or at least custom software without caring how its made.

I don't want the means of production to be located inside companies that can only exist with a steady bubble of VC dollars. It's perfectly reasonable to try AI or use it sparingly, but not embrace it for reasons that can be articulated. Not relevant to parent commenters point, though. Maybe you are "replying" to the article?

Time and time again that I observe it is the AI skeptic that is not reacting with curiosity. This is almost fundamentally true, as in order to understand a new technology you need to be curious about it; AI will naturally draw people who are curious, because you have to be curious to learn something new.

When I engage with AI skeptics and I "ask these people what they're really thinking, and listen" they say something totally absurd, like GPT 3.5-turbo and Opus 4.6 are interchangeable, or they put into question my ability as an engineer, or that I am a "liar" for claiming that an agent can work for an hour unprompted (something I do virtually every day). This isn't even me picking the worst of it, this is pretty much a typical conversation I have on HN, and you can go through my comment history to verify I have not drawn any hyperbole.

you make it seem like ai hesitation is a misunderstood fringe position, but it's not. i don't think anyone is confused about why some people are uninterested in ai tooling, but we do think you're wrong and the defensive posturing lines in the sand come off as incredibly uncurious.

I simply have no need for these things. I am faster, smarter, and I understand more. I syntesize disparate concepts your SoT models could never dream of. Why should I waste the money? I have all that I need up in my brain.

When everyone forgets how to read, I'll be thriving. When everyone is neurotic from prompting-brain, I will be in my emacs, zen and unburdened.

I love that yall have them though, they are kinda fun to mess with. And as long as I can review and reject it, all yalls little generations are acceptable for now.

  > But if you are genuinely confused by the attitudes of your peers, try asking not "what do I have that they lack" ("curiosity"?) but "what do they see that I don't" or "what do they care about that I don't"?

There's two critical mistake that people often make: 1) thinking there's only one solution to any given problem, and 2) that were there an absolute optima, that they've converged into the optimal region. If you carefully look at many of the problems people routinely argue about you'll find that they often are working under different sets of assumptions. It doesn't matter if it's AI vs non-AI coding (or what mix), Vim vs Emacs vs VSCode, Windows vs Mac vs Linux, or even various political issues (no examples because we all know what will happen if I do, which only illustrates my point). There are no objective answers to these questions, and global optima only have the potential to exist when highly constraining the questions. The assumptions are understood by those you closely with, but that breaks down quickly.

If your objective is to seek truth you have to understand the other side. You have to understand their assumptions and measures. And just like everyone else, these are often not explicitly stated. They're "so obvious" that people might not even know how to explicitly state them!

But if the goal is not to find truth but instead find community, then don't follow this advice. Don't question anything. Just follow and stay in a safe bubble.

We can all talk but it gets confusing. Some people argue to lay out their case and let others attack, seeking truth, updating their views as weaknesses are found. Others are arguing to social signal and strengthen their own beliefs, changing is not an option. And some people argue just because they're addicted to arguing, for the thrill of "winning". Unfortunately these can often look the same, at least from the onset.

Personally, I think this all highlights a challenge with LLMs. One that only exasperates the problem of giving everyone access to all human knowledge. It's difficult you distinguish fact from fiction. I think it's only harder when you have something smooth talking and loves to use jargon. People do their own research all the time and come to wildly wrong conclusions. Not because they didn't try, not because they didn't do hard work, and not because they're specifically dumb; but because it's actually difficult to find truth. It's why you have PhD level domain experts disagree on things in their shared domain. That's usually more nuanced, but that's also at a very high level of expertise.