9 ms·

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

by _dwt 7mo ago

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.

godelski 7mo ago
> 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"? I'd argue these are good questions to ask in general, about many topics. That it's an essential skill of an engineer to ask these types of questions. 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.
prescriptivist 7mo ago
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.
- _dwt 7mo ago
  Well, no, not with that attitude there won’t! I am not trying to insinuate that there is a conspiracy, or that posts like yours are part of it, but there has been a huge wave of posts and comments since February which narrow the Overton window to the distance between “it’s here and it’s great” and “I’m sad but it’s inevitable”. Humanity has possessed nuclear weapons for 80 years and has used them exactly twice in anger, at the very beginning of that span. We can in fact just NOT do things! Not every world-beating technology takes off, for one reason or another. Supersonic airliners. Eugenics. Betamax. The best time to air concerns was yesterday. The next best time is today. I think we technologists wildly overestimate public understand and underestimate public distrust of our work and of “AI” specifically. We’ve got CEOs stating that LLMs are a bigger deal than nuclear weapons or fire(!) and yet getting upset that the government wants control of their use. We’ve got giddy thinkpieces from people (real example from LinkedIn!) who believe we’ll hit 100% white collar unemployment in 5 years and wrap up by saying they’re “5% nervous and 95% excited”. If that’s what they really think, and how they really feel, it’s psychopathic! Those numbers get you a social scene that’ll make the French Revolution look like a tea party. (“And honestly? I’m here for it.”) So no, while I _think_ you’re correct, I don’t accept the inevitability of it all. There are possibilities I don’t want to see closed off (maybe data finally really is the new oil, and that’s the basis for a planetary sovereign wealth fund. Maybe every man, woman, and child who ever wrote a book or a program or an internet comment deserves a royalty check in the mail each month!) just yet.
doug_durham 7mo ago
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.
axus 7mo ago
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?
distrill 7mo ago
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.
overgard 7mo ago
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.
- jihadjihad 7mo ago
  > 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. I had an idea earlier this week about this, but haven’t had a chance to try it. Since the agent can now “see” the whole stack, or at least most of it, by having access to the repos, there’s becoming less of a reason to suspect they won’t be able to take the whole stack into account when proposing a change. The idea is that it’s like grep: you can call grep by itself, but when a match is found you only see one line per match, not any surrounding context. But that’s what the -A and -B flags are for! So you could tell the agent that if its proposed solution lies at layer N of the system, it needs to consider at least layers N-1 (dependencies) and N+1 (consumers) to prevent the local optimum problem you mentioned. The model should avoid writing a pretty solution in the application layer that conceals and does not address a deeper issue below, and it should keep whatever contract it has with higher-level consumers in good standing. Anyway, I haven’t tried that yet, but hope to next week. Maybe someone else has done something similar and (in)validated it, not sure!
beepbooptheory 7mo ago
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.
johnfn 7mo ago
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.
- samiv 7mo ago
  AI will naturally draw people who are lazy and not interested in learning. It's like flipping through a math book and nodding to yourself when you look at the answers and thinking you're learning. But really you aren't because the real learning requires actually doing it and solving and struggling through the problems yourself.
  - johnfn 7mo ago
    This is just completely inaccurate. There is more to learn now than ever before, and I find myself spending more and more time teaching myself things that I never before would have been able to find time to understand.
    - samiv 7mo ago
      This is just completely inaccurate. There's the same amout of information available as before. It's not like LLMs provide you with information that isn't available anywhere else. But I agree that it can serve as a tool for a person who it's interested in learning but I bet you that for every such person there's 10x as many who are happy to outsource all their thinking to the machine. We already have reports from basically every school in the world struggling with this exact problem. Students are just copy pasting LLMs and not really learning.
peteforde 7mo ago
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.

by _dwt 7mo ago

godelski 7mo ago

> 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"? I'd argue these are good questions to ask in general, about many topics. That it's an essential skill of an engineer to ask these types of questions. 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.

prescriptivist 7mo ago

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.

_dwt 7mo ago
Well, no, not with that attitude there won’t! I am not trying to insinuate that there is a conspiracy, or that posts like yours are part of it, but there has been a huge wave of posts and comments since February which narrow the Overton window to the distance between “it’s here and it’s great” and “I’m sad but it’s inevitable”. Humanity has possessed nuclear weapons for 80 years and has used them exactly twice in anger, at the very beginning of that span. We can in fact just NOT do things! Not every world-beating technology takes off, for one reason or another. Supersonic airliners. Eugenics. Betamax. The best time to air concerns was yesterday. The next best time is today. I think we technologists wildly overestimate public understand and underestimate public distrust of our work and of “AI” specifically. We’ve got CEOs stating that LLMs are a bigger deal than nuclear weapons or fire(!) and yet getting upset that the government wants control of their use. We’ve got giddy thinkpieces from people (real example from LinkedIn!) who believe we’ll hit 100% white collar unemployment in 5 years and wrap up by saying they’re “5% nervous and 95% excited”. If that’s what they really think, and how they really feel, it’s psychopathic! Those numbers get you a social scene that’ll make the French Revolution look like a tea party. (“And honestly? I’m here for it.”) So no, while I _think_ you’re correct, I don’t accept the inevitability of it all. There are possibilities I don’t want to see closed off (maybe data finally really is the new oil, and that’s the basis for a planetary sovereign wealth fund. Maybe every man, woman, and child who ever wrote a book or a program or an internet comment deserves a royalty check in the mail each month!) just yet.

doug_durham 7mo ago

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.

axus 7mo ago

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?

distrill 7mo ago

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.

overgard 7mo ago

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.

jihadjihad 7mo ago
> 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. I had an idea earlier this week about this, but haven’t had a chance to try it. Since the agent can now “see” the whole stack, or at least most of it, by having access to the repos, there’s becoming less of a reason to suspect they won’t be able to take the whole stack into account when proposing a change. The idea is that it’s like grep: you can call grep by itself, but when a match is found you only see one line per match, not any surrounding context. But that’s what the -A and -B flags are for! So you could tell the agent that if its proposed solution lies at layer N of the system, it needs to consider at least layers N-1 (dependencies) and N+1 (consumers) to prevent the local optimum problem you mentioned. The model should avoid writing a pretty solution in the application layer that conceals and does not address a deeper issue below, and it should keep whatever contract it has with higher-level consumers in good standing. Anyway, I haven’t tried that yet, but hope to next week. Maybe someone else has done something similar and (in)validated it, not sure!

beepbooptheory 7mo ago

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.

johnfn 7mo ago

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.

samiv 7mo ago
AI will naturally draw people who are lazy and not interested in learning. It's like flipping through a math book and nodding to yourself when you look at the answers and thinking you're learning. But really you aren't because the real learning requires actually doing it and solving and struggling through the problems yourself.
- johnfn 7mo ago
  This is just completely inaccurate. There is more to learn now than ever before, and I find myself spending more and more time teaching myself things that I never before would have been able to find time to understand.
  - samiv 7mo ago
    This is just completely inaccurate. There's the same amout of information available as before. It's not like LLMs provide you with information that isn't available anywhere else. But I agree that it can serve as a tool for a person who it's interested in learning but I bet you that for every such person there's 10x as many who are happy to outsource all their thinking to the machine. We already have reports from basically every school in the world struggling with this exact problem. Students are just copy pasting LLMs and not really learning.

peteforde 7mo ago

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.