11 ms·

The LLM Critics Are Right. I Use LLMs Anyway

• bantunes 2mo ago
  > And this is where the value is for me: I can simply make things higher quality than I could do them alone. It's sad that this can be true because if you did them alone the quality would be non-existent.
• msdz 2mo ago
  > LLM’s amplify what you already have: opinions, structure, frameworks. So far, so agreeable, but… > If you have thoughts, they come out sharper and faster. I can’t help but wonder whether constant use of “agent” harnesses will lead to an atrophy of the software engineering (or really any field) muscles. Actual muscles need exercise to stay in shape (let alone grow), so does the brain. Can we really be sure that thoughts, opinions, taste will still come out sharper and faster after five, ten, 20 years of using these tools almost every day? Conversely, I also am a user of LLMs (true shocker these days, I know), and am noticing a speedup in areas I was already familiar with, and a quicker introduction to new ones. The obvious benefit cannot be denied, and doing so regardless makes you look uninformed. [0] So what’s the ideal “middle ground” in this situation? Stoically continuing to sharpen your skills on your own, but risking being left in the dust productivity-wise? Or taking an “agent first” approach and trying to learn and improve more only on the side, as more of an afterthought? [0] Excluding people who don’t want anything to do with LLMs out of moral principle, which curiously just like the overarching topic I also both respect and understand, but on the other hand don’t do myself.
  • dominotw 2mo ago
    > I can’t help but wonder whether constant use of “agent” harnesses will lead to an atrophy of the software engineering (or really any field) muscles. For sure. You cannot have "only higher level thoughts" without doing lower level work. Ironically llm themselves prove that because you cannot remove facts like 'paris is capital of france' from llm and have it just retain 'high level thoughts' like 'countries have capitals that you can look up'
    • skinfaxi 2mo ago
      > For sure. You cannot have "only higher level thoughts" without doing lower level work What do you mean? I think people routinely think about things at a very high level with almost no understanding of the lower levels. How many people use a computer each day and reason about them at a very high level while knowing nothing of capacitors, logic gates, or programming languages?
      • throw10920 2mo ago
        I think they didn't phrase it precisely, but my guess is the underlying idea is actually "high-level software architecture doesn't have a clear abstraction layer you can use to separate it from low-level coding (unlike logic gates, the CPU's ISA, the kernel API, etc), and so delegating the latter leads to delegating the former".
        • skinfaxi 2mo ago
          That makes sense but I'm still not so sure—we have things like software architecture patterns that can be discussed at a high level without knowing the intricacies. Like you can be aware of load balancing and even use it but be unaware of how load balancing might work algorithmically. Let's consider even the original example. > You cannot remove facts like 'paris is capital of france' from llm and have it just retain 'high level thoughts' like 'countries have capitals that you can look up' Wouldn't the knowledge that countries have capitals precede the knowledge that Paris is the capital of France? This says nothing about the accuracy of our own models based on these abstractions that lack the lower-level understanding.
          • throw10920 2mo ago
            > we have things like software architecture patterns that can be discussed at a high level without knowing the intricacies I think the counterargument would be "you can't teach people architecture alone and get good architects". I've observed this myself in "systems engineers" whose job is to connect boxes together without understanding how the boxes work. They, invariably, design ridiculous architectures on their own and need to basically find a domain expert to route their opinions through to come up with anything sane.
  • Levitz 2mo ago
    >Conversely, I also am a user of LLMs (true shocker these days, I know), and am noticing a speedup in areas I was already familiar with, and a quicker introduction to new ones. The obvious benefit cannot be denied, and doing so regardless makes you look uninformed. My largest concern comes from something tangential to this: I'm not sure we're all that good at deciding what should be learned and sticking to it. Silly example: regex. LLMs are, as far as I know, well above the average dev when it comes to writing regex. Regex is also one of those things that for many people goes unused for months, but then you encounter the occasional perfect regex problem, and it's really easy to just lean on the LLM to write the regex for you rather than spending some time tinkering and testing. Regex can be frustrating and fickle, I think we've all been there. But then, you just don't learn regex. So where does the intuition for what regex can do come from? Do you just become unable to write regex with no LLM? People stop writing resources for regex I guess? My concern is that there's stuff I feel I can just chuck onto the LLM but I'm sure my judgement is not perfect. It's still probably worth it, all in all, but I'm not even sure of what I might be losing along the way and that's an uneasy feel.
    • xnorswap 2mo ago
      I've been using regex decades, but it never really stuck to do anything too complex, it was the perfect intersection of difficult and infrequent. ( And also variable - PCRE vs others customisations / non-regular parts, etc ). I am very glad that I can now just ask claude for a regex to achieve my intent. Does it mean I'll never master regex? Yes it does, but decades has shown that was unlikely to ever happen anyway.
      • jmartrican 2mo ago
        Regex came up so infrequent that I found myself referring to documentation whenever I needed to use it. But I always wondered, what are the jobs or roles that use it so often that they have mastered it.
        • parineum 2mo ago
          anything with large amounts of user text input.
  • throw10920 2mo ago
    > whether constant use of “agent” harnesses will lead to an atrophy of the software engineering (or really any field) muscles Well, I think most neuropsychologists would agree that the answer is "yes, there will be atrophy" - if you don't use it, you lose it. > So what’s the ideal “middle ground” in this situation? I've been thinking a lot about this myself. My current plan is to train myself to get good at recognizing the feeling of "there's potential effort here that I want to outsource to the LLM" and occasionally choosing to not outsource it and do it by hand - especially with personal projects, where there's far less pressure to ship with velocity than work projects - but I'm not settled on this. I'll take any idea!
  • mtklein 2mo ago
    I don't think there is necessarily one ideal middle ground here. It still feels to me like what's best is a function that depends on who and when. I see it as something like a personal gradient descent. You're working on a problem, there are solutions down there somewhere, and you can kind of feel the gradient of the tools-and-techniques ground around you. Any way you walk means you're investing time improving some skill or another. So you should go the way that personally feels to you will best get you moving in the direction that you want to go. For some people it's obvious LLMs are competent coders, getting better, sticking around... and those people should lean into that gradient. For some people what's obvious is nearly the exact opposites of all that, and I'd encourage those people to also follow their gradient/heart/nose down the path of sharpening their personal traditional coding skills. Some people are in a relatively flat area where nothing is obvious, and need to explore and maybe just keep doing their best to hedge with a bit of both.
  • prettyblocks 2mo ago
    > I can’t help but wonder whether constant use of “agent” harnesses will lead to an atrophy of the software engineering (or really any field) muscles. It will, but I'm not sure the impact of this will be all too great. We suffer from not knowing how to use an abacus because we have a calculator, and people who feel a pull to keep their low-level chops up will do so anyway.
    • cj 2mo ago
      Now imagine if your calculator billed per button press. And imagine you can't own a calculator because owning one outright requires too much hardware (or whatever).
      • quantummagic 2mo ago
        The exact same arguments were made against electronic computing in general, in the early days. Pearl clutching is a very human thing to do as new technologies are integrated and become common place. A whole generation or two of developers are going to have to pass away before we stop hearing incessant diatribes about LLMs.
        • cj 2mo ago
          Don't use calculator as an analogy, then. Calculators are a simple machine that implement very basic rules. LLMs are in a different category. The parallels you can draw between LLMs and calculators.. just don't make sense.
          • quantummagic 2mo ago
            > The parallels you can draw between LLMs and calculators.. just don't make sense. The technology doesn't matter, you can compare to say the power loom from the 1700's. I'm comparing the reaction of humans; human's haven't changed that much. They always react the same when they feel threatened and emotionally challenged by a technology.
  • qsera 2mo ago
    >Can we really be sure that thoughts, opinions, taste will still come out sharper and faster after five, ten, 20 years of using these tools almost every day? After 5 years, I think the thought profile every power user of the LLMs would be an LLM derived carbon copy of each other. Prepare the world to get even more boringly uniform
  • iugtmkbdfil834 2mo ago
    << So what’s the ideal “middle ground” in this situation? Putting all this in 2nd paragraph so that you can skip it if you think 'coding' is your primary portion of your job. I suppose I am in a mildly privileged position in a sense that my work is a weird intersection of tech, finance, and comprehension. In other words, I don't code much, but I absolutely benefit from now being able to play with various projects I would otherwise have no business touching without a bigger support team. I don't want to invoke Accelenrando, but the muscle imagery and analogy fits. I will give an example. I recently decided to pick up Go for a project ( have experience in some other languages, but I will still be starting fresh ). I could have codex build me what I want, but I am purposefully taking it slow so that I can learn the foundation so that I can have a frame of reference ( because I assume it won't be the only go project for me ). Otoh, most of my one off python scripts I barely even skim anymore. And honestly,that is the part that scares me more.
    • AnimalMuppet 2mo ago
      Why would you be very careful with a one-off script? The only point is the output. On the other hand, if you actually care about the output, how do you know it's right, unless you review the script? I mean, if all you care about is plausible-looking output, you could have the LLM produce that, and skip the Python script entirely...
      • iugtmkbdfil834 2mo ago
        Eh, unlike some of my contemporaries, I am not as interested in merely plausible-looking output. I want good output each time, but I am clearly still trying to find a good balance.
  • Diogenesian 2mo ago
    I will just point out the benefit is not as obvious as you think. Developers have consistently overestimated LLM productivity gains, which still seems true for agentic AI: https://metr.org/blog/2026-05-11-ai-usage-survey/ https://metr.org/blog/2026-05-11-ai-usage-survey/ It is particularly striking how similar the results are to LLMs before agents. Along with the total absence of long-term data, I think the benefit can be (weakly) denied. Maybe not in the employmemt marketplace, but certainly for myself.
    • pydry 2mo ago
      The productivity depends upon the requirements. If slop is fine (and sometimes it is), the benefits are undeniable. If the dev was the kind that would have produced slop anyway - again, undeniable boost. If the quality needs to be high I think it actually can slow you down, though.
      • someoneiam 2mo ago
        Agreed, but also to expand, if the dev is mediocre and ai-assisted coding is a skill, the productivity gains are 10x more mediocre code. Since code is a liability, this is not desirable. Hence, mediocre devs being more productive is an underestimated problem of the age of ai-assisted coding. I see this every day. The result is a whole bunch of dysfunctional systems unnecessarily dislodging perfectly acceptable processes.
        • ermantrout 2mo ago
          "Code is a liability" is the part that usually gets hand-waved, and there's a number on it now. Veracode's 2025 GenAI report ran 80 tasks across 100+ models: when a task could be solved securely or insecurely, the models picked the insecure path 45% of the time, at roughly 2.7x the vulnerability density of human-written code (Java was worst, at a 72% failure rate). So the mediocre-dev case may be worse than "10x more mediocre code." It's more code that also skews insecure by default, and that cost shows up downstream in review and incidents, not at the PR. Throughput goes up, and so does the liability per line.
    • 2mo ago
  • jmartrican 2mo ago
    > So what’s the ideal “middle ground” in this situation? I use agents to code. But I remember the early days of just AI smart complete in the IDE, where as the programmer I had to be more involved with designing and implementating the solution. This kept me engaged with the implementation as it was being built out. Now with agents, I find myself trying to catch up with what the agent did and spend more time code reviewing. Maybe you end up in the same place in the end. But building the implementation, vs code reviewing, feels more rewarding and I think helps keep your mental tool sharpened.
    • jmartrican 2mo ago
      I think that the onus is on us to get better at using agents and AI to solve the pain points and speed things up while keeping quality high and our mental tools sharpened. I do nto think turning back is an option, but managing the pain points and leveling up is.
    • nullbio 2mo ago
      I think it's the opposite. Being only the code reviewer devolves into being lazy and cutting corners. The sharpening comes from hands-on practice.
      • budrscotch89 2mo ago
        That's what he was saying
  • grayhatter 2mo ago
    > Conversely, I also am a user of LLMs (true shocker these days, I know), and am noticing a speedup in areas I was already familiar with, and a quicker introduction to new ones. The obvious benefit cannot be denied, and doing so regardless makes you look uninformed. [Excluding people who don’t want anything to do with LLMs out of moral principle, which curiously just like the overarching topic I also both respect and understand, but on the other hand don’t do myself.] Setting aside my moral outrage over the magic token machines. What about me, who gets so tripped up over minor factual errors, that I'm unable to let them go, and it taints the whole conversation such that I'm too wrapped up in my frustration that I can't think about it clearly? Or my innate drive for correctness that's so strong that I eval the minor errors in output, as catastrophically incompatible with my goals? > Stoically continuing to sharpen your skills on your own, but risking being left in the dust productivity-wise? I don't believe there's a meaningful productivity increase. Please cite your published (not preprint) peer-reviewed research that proves the productivity improvement. Until then, I'm unconvinced. (Believe me I'd like to be convinced of reality, the answer is still unresolved, and I have my opinions, but I'd rather something conclusive that I can have confidence in) Then, even if you did show a significant productivity improvement, it wouldn't help me. I have too many qualms over the output quality that I simple can not let go, (I don't think I should, but everyone keeps trying to convince me to lower my quality standards). I don't want something fast, I have plenty of really "fast" things in my life. I exclusively want to add things that are high quality to my life. Things that don't endlessly frustrate me. The question about where the middle ground is a rhetorically dishonest question. You'd first have to prove/convince me, that there IS a middle ground. Instead of what I believe where that middle ground belongs is quality, and everything emitted by an LLM moves reality in the wrong direction. Are any of these absolutes? nah, hence my request/demand for peer-review research. All the productivity claims and quality assertions (mine included) are still *exclusively* vibes. But exactly none of them are pristine, (especially not any of the LLM output.)
    • epihelix 2mo ago
      > What about me ... While I can see that you feel very passionately about this, the reality is that it's the majority experience that will dictate adoption. There may never be published research on productivity -- blinding in this instance is impossible, so I don't know how you'd ever do fully-controlled behavioural studies that carried any weight. It doesn't matter. If enough of us decide that LLMs are useful to us, then this form of coding will become the norm. If that ends up causing more harm than good, then eventually there will be a course correction. But for now, for enough people that matter, LLMs are at least giving the perception of productivity increases. And our decisions and choices come down to the perception of reality, not reality itself (for better or worse). So I think it's far more useful to take a pragmatic approach, as per TFA. Accept that LLMs have issues, but also bring advantages, and that LLM use in coding is here to stay. What we can do is remain aware of the bad, and make better use of the good. As for you, personally ... if you mentally cannot deal with LLM output, then I think you have two choices. You can either learn to author system prompts, so that LLM output better fits your needs and no longer triggers you; or you can sit more and more on the outer, raging against the machine while the world changes around you. Eventually, you'll be like a master craftsman in an era of mass-production. But that's potentially highly valuable in niche markets (consider a watchmaker working in Glashutte, for example), so you may yet win from this. Remember that every day, LLMs are making your own coding skills and knowledge more elite and therefore lucrative, sit back, and smile.
  • Orphis 2mo ago
    > I can’t help but wonder whether constant use of “agent” harnesses will lead to an atrophy of the software engineering (or really any field) muscles. Compiler evolutions really harmed how well software engineers understand or how often they have to drop down to assembly language. Is that a problem for the 99% of developers around? Probably not. I view LLMs as the next evolution. Some people will still need to care about the layer below, the shape of the code that is being written. But over time, just as it was with the transition from crafted ASM to higher level languages, the compilers became better, more efficient and trustworthy and I think the same will happen to LLMs, and we probably won't have to check the generated code as much, at least for most of the code around. Is that a problem? Yes, for code that is intended to interface with humans (most of it still). The quality will probably become better and it won't be much of an issue.
    • rafaelRiv 2mo ago
      LLMs are not deterministic and I still look at compiler result and I encourage people to look at it. That people don't look at the result of compiler is a problem and not a an argument
  • nottorp 2mo ago
    > and am noticing a speedup in areas I was already familiar with, and a quicker introduction to new ones. Only problem is that, like a LLM, you don't retain anything. Hobby projects may become a lot more important now because if you do them without LLMs you may retain a brain cell or two.
  • nullbio 2mo ago
    > I can’t help but wonder whether constant use of “agent” harnesses will lead to an atrophy of the software engineering (or really any field) muscles. This will and is 100% happening. I have a friend who hasn't written code by hand in around a year, but uses LLMs every day, and he tells me he can't remember how to write code by hand anymore. He has been a developer for 10 years. But he's not working for anyone at the moment, so I imagine if he was in a workplace the circumstances would be different and they probably wouldn't settle for this. I think that as a result of this it likely also atrophies the problem solving and architecture building skills that writing the code manually gives you. It just ends up degrading into a loop of tell the agent to do X and assume it knows what it is doing.
  • forshaper 2mo ago
    In a way, this happened before LLMs with more workforce-fit education, decision tree flowcharts, then software, and so on. If you take most people who started any field, the way they started the field would look very unorthodox, inefficient, etc. "From the margins," as pg might say. Margins where more intuitive skills for the craft are present. Ie, the skills to come up with the model pastry are not the same skills for the pastry line to be baked in a factory.
  • MisterTea 2mo ago
    > but risking being left in the dust productivity-wise? What's the risk here? Left behind by who or what? > Or taking an “agent first” approach and trying to learn and improve more only on the side, as more of an afterthought? This reads like anxiety resulting from FOMO. Here's my take: I don't care about LLMs or AI in the sense that I don't feel any need or want to use them. I've only ever tinkered with the free ChatGPT. Never opened an account with any LLM vendor and never even considered it. I program by hand for the joy of it and sometimes for work. Still by hand as I have been doing. MY work gives me that luxury. For now. Am I obsolete? Am I no longer of any value to society? Of course not. That thinking is just implanted by a group of money hungry individuals who don't give a fuck about me, you or society as a whole. So why would or should I care about LLMs?
    • hodder 2mo ago
      Economically if you are vastly outcompeted by other programmers on productivity, yes that is "no longer of value" from a purely employment perspective. Much like an old person who cant use a computer has little value in the job market beyond being a greeter at Walmart, a programmer who hand codes a loop is next to useless on a productivity basis such that it makes zero sense to employ them. It is unfortunate but true. Why pay someone to accomplish less per dollar pf cost. Feels?
      • JackSlateur 2mo ago
        Last month, there has been a billing-related incident at work: it has been detected that the GCP bill had increased vastly since early 2026 The related team investigated, found nothing; They escalated to other teams, found nothing; Gemini, claude and whatnot were involved, found nothing; Somebody raised to topic to me, solution has been found See my point ? Like GP, I do not use AI. If there is only one person thinking left, being that person does not looks like a bad idea; Mixing code and "productivity" is trying to remake coder as bluecollars, and most of them probably are (not thinking, replaceable cogs that are overpaid and shall be decommissionned), they will not be missing. The only coder's output is its idea, everything else is a mean to that end.
      • patrickmay 2mo ago
  • snarfy 2mo ago
    I have some hobby projects I write for fun without an LLM, just to learn. And also have hobby projects that use LLM extensively, also just to learn. Get some hobby projects.
  • GenerocUsername 2mo ago
    If cars did not exist, I would be healthier, able to walk and run many times further due to constant cardio exercise. I would still travel much less distance. And just like cars, LLMs will reshape the world to the point that our brains could not even get us to the supermarket because soon it will be 5 miles away and require a car ( or at least a local LLM bike )
    • deadbabe 2mo ago
      [dead]
    • Diogenesian 2mo ago
      FWIW a 5 mile walk is not a long walk. Humans are very much designed to make that trek without too much trouble. Lots of the world has people walking similar distances for fresh water, to go to school, etc. The point being that cars also reshape your perception of the world. METR had trouble replicating their dev productivity study because devs have already become much whinier about doing things "manually." Things that were slightly tedious in 2022 have become impossibly difficult without AI in 2026. It is striking to reread Lord of the Rings: so much of the story is spent walking in and observing the Middle-Earth wilderness, and there is a distinct "pantheism" absent from the movies. JRR Tolkien, being one of the first modern fantasy writers, was one of the last who remembered a life without cars.
      • annzabelle 2mo ago
        I had the chance recently to do several of New Zealand's Great Walks (3-4 day scenic wilderness treks with more expensive huts than the rest of the hut system), and I highly recommend doing something similar if you can swing it. Walking 15-30 km a day (9-18 miles) for several days while carrying supplies on your back really gives you new context for what you can do and what life was like without cars.
    • player1234 2mo ago
      [dead]
  • ElFitz 2mo ago
    > I can’t help but wonder whether constant use of “agent” harnesses will lead to an atrophy of the software engineering (or really any field) muscles. Used to think so, but they actually can also be used to train and strengthen skills, and learn new ones. I had a coding interview, where they kindly sent a brief beforehand to help prepare, presenting a list of topics and concepts that might be useful during the interview, the tech stack, what kind of expectations they would have, and what they’d be paying attention to. Obviously, it’s not exact list, and there are probably other evaluation dimensions. But since I was out of practice on some of those, I had Claude generate a dozen sample projects, with each a list of tasks in one document and the solutions in another, and got to it. Midway, I thought of using codex to role play as an interviewer, to tell it my train of thought and ideas as I went, get feedback, question my choices, etc. Sure I only went through two and half, maybe three of those projects… but it’s the first time I actually enjoyed prepping for an interview. And I actually learned some things in the process. Hardest part was probably stopping the LLM from doing the tasks, but nothing unsolvable given a bit more time, clearer instructions, and separation.
  • whattheheckheck 2mo ago
    You can run to the farm to kill your own chicken so you can stay sharp and fit or figure out what's economically valuable. Or make a bet on what will be valuable later and commit to a brand of yourself
  • nonameiguess 2mo ago
    I guess I'm lucky to have taken the career path I have, but I write very little code these days being in pre-sales now. "Productivity" is pretty stark and obvious in sales. You can output all the text you want, maybe it even compiles and passes test suites and looks pretty in a demo. But does it sell? It's nice to be able to have the only true measure that matters actually be measurable. I have yet to use an LLM for anything at all, haven't touched an agent, not because I'm ideologically opposed, but I just haven't seen the need. Part of it is the largely advisory role. I'm largely expected on the customer side to field and answer questions and render technical assistance. I'm not much good at that if I'm just deferring to Claude. The customer can do that themselves. I need to know more than Claude. The other part is just I'm not being paid to generate text. I'm being paid to generate revenue. If there's a convincing argument that LLMs can help me, well, it's an argument, but truth on the ground is I'm performing every bit as good if not better than any of my peers that are blowing a grand a month on tokens. They're definitely having a lot of fun and flooding internal Github orgs with new repos and tooling, but it demonstrably isn't generating new revenue.
    • budrscotch89 2mo ago
      "The customer can do that themselves." >> You would probably be surprised how few actually have the agency to do even this small step.
  • justthehuman 2mo ago
    [dead]
  • FunHearing3443 2mo ago
    I'm frankly baffled by the number of commenters saying they've seen little productivity gains using LLMs/agents. My team got cut in half at the end of last year and we've probably increased our output by 25% primarily due to LLMs. Personally it's probably doubled my productivity. And we generally use a pretty structured spec based approach with consistent human code review, and six months into adoption we've had virtually no bugs attributable to an AI mistake (in fact production issues have gone down, knock on wood). My point being we aren't vibe coding. I speculate the gains must be heavily context dependent (no pun intended). Different teams, tech stacks, product types, and company policies perhaps have an outsized effect on what gains LLMs give. We are allowed to be pretty independent and don't have much of a restriction on token usage.
    • windward 2mo ago
      >My team got cut in half at the end of last year and we've probably increased our output by 25% primarily due to LLMs. Personally it's probably doubled my productivity. Love to see worker unity in action.
    • rafaelRiv 2mo ago
      What is your metric ? How do you calculate ROI ? Strange that you didn't specify that. Also, are you sure your "25% increase" is due to LLMs ? Every time I see this claim, it is always for a short time period or the increase was not due to LLMs at all
  • butterisgood 2mo ago
    C led to an atrophy of assembly muscles. Though this is mostly different. A spec is NOT CODE. Someone still needs to understand what the code means. C optimizers are not the same as the radical departure of an LLM.
    • xxs 2mo ago
      >C led to an atrophy of assembly muscles. This is not true, though. Technically I don't do C but I used to do Assembly. Yet in Java code paths, to have a decent proof (and satisfactory results) of the optimizations made by JIT, PrintAssembly still works. Assembly is not just the raw instructions that trigger microcode or knowing the latency of each one of them, or the (un)expected cache misses, it's the understanding the hardware, itself.
  • dannersy 2mo ago
    Your suspicion is already being studied with increased effort, and the starting point has solid bones: https://arxiv.org/pdf/2604.04721 https://arxiv.org/pdf/2604.04721 For what it is worth, my colleagues who use these tools more liberally see a much higher regression rate and are left refactoring more as well. While they definitely put out more PRs, I can confidently say that mine are more valuable and better stand the test of time. Whether that matters or not is up to debate as I guess you could argue there may be some point where the productivity overcomes their regression rate. My position is, if the technology will be so good and progressing so fast to the point that I don't have to write code anymore and I'm just dictating our needs and what I want architecturally, then I don't really feel the need to put in the time to learn the tools as they are now. That seems way easier to learn than anything computer science related that I had to learn to build robust systems.
  • killerstorm 2mo ago
    The part of brain which cares about efficiency and waste have "atrophied" decades ago in most devs. More likely they just never cared... E.g. > A 1.6GB Docker image for a Node app. Every code change rebuilds npm install from scratch. CI takes 8 minutes for a one-line fix. > The team's proposal: add more CI runners. Would it be surprising if that team makes a React app which does 10x more requests than necessary, has 10x more JS code than necessary, flickers, etc. People just don't care, and it has nothing to do with AI. "Engineering" is too big of a word for this kind of activity. On the other hand, I think AI can amplify capabilities of those people who still care, and it's a good thing.
  • jonathanlydall 2mo ago
    > Actual muscles need exercise to stay in shape (let alone grow), so does the brain. Can we really be sure that thoughts, opinions, taste will still come out sharper and faster after five, ten, 20 years of using these tools almost every day? It occurred to me recently how because the LLMs have to potential to lead to intellectual/skill atrophy, they are a factor which could lead to an Idiocracy-esque [0] situation. And while it's a well-established Fermi Paradox [1] hypothesis that AI could lead to the violent destruction of a civilization, I think it's also worth considering that they could non-violently lead to their decline due to intellectual atrophy. [0]: https://www.imdb.com/title/tt0387808/ https://www.imdb.com/title/tt0387808/ [1]: https://en.wikipedia.org/wiki/Fermi_paradox https://en.wikipedia.org/wiki/Fermi_paradox
    • sethammons 2mo ago
      The doctor from Idiocracy: it says your shit's fucked up.
  • captainbland 2mo ago
    I think you can use them critically. Probe the code, see how it behaves when tweaked, can you break it etc.? without slowing you down too much. And in doing so you probably learn 80% of what you would have if you'd written it yourself by hand. But then there are definitely cases where LLMs are slower and less reliable than someone using tooling by hand, especially like deterministic refactoring operations can be done close to instantly if you already know what needs to be done and how to do it.
  • thewhitetulip 2mo ago
    The amplification is what is causing the skills atrophy. When everyone is chasing max lines of code, we generate more code than what we can realistically write. And it's not like we can not use LLM because others are using it in a craze to get the next promotion so you have to use it and maximize your output even if your skills are atrophing
  • locallost 2mo ago
    Use it or lose it, but the problem is very old. The introduction of the alphabet/literacy almost certainly made people's memories worse -- up to that point they had to hold a lot more in their heads. At the same time it enabled a different better way to share information and learn. The question is thus, will it make the world better, is it a book or a TV?
• simianwords 2mo ago
  At what point would one say that the LLM critics were wrong in their load-bearing (yes I used it) claims?
  • asdf88990 2mo ago
    When AI frontier labs fire all their engineers.
    • simianwords 2mo ago
      why
      • Zambyte 2mo ago
        ... Because AI is more capable?
  • hatefulheart 2mo ago
    If you have no critiques about a piece of technology in an area of technology that has existed for less than 10 years I think that speaks for itself.
    • simianwords 2mo ago
      so you are saying that the advent of internet also deserved criticism in much the same way as LLM's? - job displacement - ethics - environmental - skill atrophy
      • hatefulheart 2mo ago
        Are you assuming that I believe the advent of the Internet and LLMs are the same thing?
      • frabcus 2mo ago
        The advent of the internet was collaborative and based on introducing shared protocols for a couple of decades. It deserved criticism when globalised capitalism got involved, and monopolies started forming, leading to rent-seeking, excessive centralisation, and enshittification. The impact is that the internet has a fraction of the value to improve people's lives as it should have. It is a very poor free market, incredibly poor competition because of lack of standards and protocols and interoperability. People's minds are ground down by social media, search engines don't work well any more and so on. So yes - every new technology deserves many criticisms, so they can be addressed, and as a society we can gain the benefits of that technology and minimise the disadvantages. The printing press lead to copyright, public libraries, universal literacy... All things which are now widely celebrated. They took centuries to work out, and are all government and regulatory intervention to fix problems critics noticed and campaigned about. AI is the same, only it is at risk of moving much faster and having a much large negative impact before society reacts. So no, most of the criticism of LLMs are not wrong - they are correct, as are the people saying the technology of LLMs is useful to people and the economy. Critics are friends of a new technology - without responding to every criticism in a significant way, AI will rapidly lead to a Butlerian jihad. If you like AI, you should love criticism of AI even more.
• Ellis_dev 2mo ago
  The trust problem feels more important than whether the code was AI-assisted. A small, reproducible change with clear tests is reviewable; a huge opaque diff is not, regardless of who typed it.
• happytoexplain 2mo ago
  The implication is that LLM critics don't use LLMs at all, or that the author is not an LLM critic, but both of those things are incorrect. We are very good at inventing entire people out of single opinions we read, and the AI arguments are maybe the best example of that I've ever seen in my many years watching internet arguments (not least due to the expansiveness of AI, and the sheer breadth of pros and cons it holds within).
  • greggoB 2mo ago
    > We are very good at inventing entire people out of single opinions we read Can you clarify what this is supposed to mean?
    • customguy 2mo ago
      Someone says they like hip hop, and you imagine a young urban male with a baseball cap on backwards, how they view women, that they probably don't like musicals, something like that (not saying you do, but as an example). More than simply the thing they said. You say "I like or do that thing", and instantly get hit with "oh, people like you always complain about X but isn't it weird you never mention Y". At least that's what I thought of when I read that; because answering in place of other people is another thing I find annoying. So I'm speaking for myself, but with some optimism I may have guessed the intent of OP correctly :)
• mohamedkoubaa 2mo ago
  >as a senior, you don’t need juniors anymore. The mundane tasks, at least I find that a lot of people agree with that one, can be fully outsourced to an LLM Master craftsmen didn't take on apprentices to give them chores.
  • erwald 2mo ago
    Master craftsmen paid apprentices almost next to nothing, and they were often contractually guaranteed to stick around for many years, so the teaching was a kind of wage and also a cost that could be recuperated later on. (The apprentice even often had to pay the craftsman to take them on.) None of those things are true for junior software engineers, who are paid to contribute and can leave at any moment. Also, yes apprentices often had to do chores. It is just not analogous at all.
    • andyferris 2mo ago
      Not to mention, the physical trades are not stopping taking on apprentices because... LLMs can't build a house? Not even the mundane bits. It will be interesting how to get the financial incentives to train juniors in knowledge work to line up with the fact that every new generation needs to be trained.
  • 1970-01-01 2mo ago
    >Master craftsmen didn't take on apprentices to give them chores. Is today opposite day?
    • mohamedkoubaa 2mo ago
      So the purpose of a graduate degree is TAing a few classes?
      • swiftcoder 2mo ago
        A big part of the value to the tenured professor is not having to teach an extra couple of sections of CS 101. The other part is plastering their name on a bunch of extra papers to game their h-index :D I don't want to be too flippant here, but senior engineers generally gain very little from training juniors, not least because promo processes suck at basically every tech firm, and so the moment you train up a junior, they are going to leap to another company rather than go through promo...
• post-it 2mo ago
  > And this is where the value is for me: I can simply make things higher quality than I could do them alone. Yeah, that's the thing for me. LLMs have made my work easier and faster, and they've made my side projects easier and faster. I think there are very sensible and valid critiques but so far the tool works for me.
  • p2detar 2mo ago
    Same thing here. I was able to finish side projects on my list and even refactor decades old projects with the help of LLMs. It works great so far and yeah, I can still write source code when needed.
• CuriouslyC 2mo ago
  Criticizing use of agents for skill atrophy is valid, it definitely atrophies blank slate coding ability, though I don't think it atrophies engineering abilities unless you just YOLO all decisions to the agent. The data center/oligarchy complaints are also valid. Saying agents produce shitty code is a bad argument though. They produce shitty codebase organization, but at a micro level their code is solid if not elegant. If you let them turn your codebase into a spaghetti mess, that's on you.
• a1o 2mo ago
  One thing about open source is a lot of people are throwing low quality PRs that should have been an issue or even a discussion, so you can understand what was the problem the person encountered that motivated such PR. This is hard to get because usually people use LLMs to also answer questions you make about the PR. I am tending towards blocking PRs from people outside the main developers in most of my open source projects. If the person CAN discuss the problem, authoring the PR is easier if I do it myself, even if using an LLM, because reviewing a PR authored by random internet people/bots is hard because of how much the entire code tends to change after minimal questions are asked. What I am sad of this approach is that I did met a few interesting people through receiving PRs and establishing trust and some relationships in the past (eight years ago and before)
• glasffordd 2mo ago
  The critics are absolutely right, LLMs have a lot of faults. But they also have a few great benefits. I use them every day for the benefits, fully aware of the faults, and I watch those faults like a hawk.
• mschuster91 2mo ago
  > I think the core issue here is trust. You should never trust random people on the internet anyway. But before LLMs, there was this base thing: creating a proper PR with proper descriptions would require at least some human time, so it would keep trolls and low quality submissions out. Or at least you could easily filter them out within a couple of seconds. So even if a new person came in, you could trust that this person would have at least spent a couple of hours on that. And then it was probably worth taking a closer look at it. Ding ding ding. This is my biggest gripe with AI. Even the SEO blogspam, the fluff in front of every recipe, yarnwork or DIY instruction, it all was clearly written by a human. Someone had invested time (and money) in getting something in front of my eyes. But now, it's all just slop. Everywhere. And hell I'm tired because the onslaught breaks my trust filters. Maybe I think this is an age thing. Boomers? They trust everything written down somewhere. No matter what, and no matter if they didn't spend half my childhood to "never trust what people write on the Internet", and now they fall for scams left and right. My generation as said grew up with this "never trust, always verify" thing. And the younger generation? They DGAF about anything any more, all they care about is trying to survive. > And b), the teaching, aka “How do we teach new people?”: previously, there was this balance aka “the junior does some pretty mundane tasks, but for this the senior reviews it together with him and helps him to grow”. GOD YES YES YES THIS x1000. There is barely anything more rewarding than teaching someone something, to watch the other person grow - and eventually surpassing your own abilities. That is when you know you did right and well. My wife is the best example, she started out at "can you help me with Excel", and these days, she pulls off stuff that would make more than a few finance people blush.
  • lnfromx 2mo ago
    > There is barely anything more rewarding than teaching someone something, to watch the other person grow I think many junior devs (or aspiring junior devs) look for exactly this experience. This is a matching problem we haven't solved yet. Is Open Source the solution ? I really think it has to be solved if we want truely reliable software in the future.
    • mschuster91 2mo ago
      There's a tangential problem - companies do not want trainees or juniors any more, they (usually) cost more money than they bring in for half a decade if you don't fraudulently bill your customers... something the "consulting" industry is infamous for. And when the juniors got enough experience to be considered intermediate or senior, they jump ship to get a larger pay rise, leaving you with the need to hire another senior. The entire economy is broken due to the focus on short term quarterly result instead of the health of a company in 5, 10 or even 20 years.
• tibordp 2mo ago
  Good article! This matches how I feel about the situation. It's really not incongruent to use LLMs and be in awe of their frankly incredible capabilities while at the same time recognize the risks and frankly real damage we are already seeing to junior training and hiring, open source communities and (in my opinion) very soon the entire fabric of our society. I respect that people don't want to use agents themselves for whatever personal reason. I respect maintainers not accepting AI-authored contributions. It's a tradeoff between progress, growing new contributors and maintainer sanity. Though I do feel that categoric opposition to anything AI will likely be futile in the mid-term. I respect people pushing for regulation of AI or a global pause or whatever. I don't particularly respect people dismissing everything AI authored as slop. Categorically refusing to read an article because it contains em-dashes or the term "load-bearing" is silly. While this is slowly changing now, many people are still in complete denial as to what the frontier AI is capable of. Love it, hate it - I don't care, but at least respect it, goddamit.
• jdw64 2mo ago
  I think both the LLM critics and the LLM advocates are right. Even this article has some cognitive dissonance in it. What it really comes down to is how much you trust your own verification process. The branches of questions an LLM generates are still trapped within the biases of its training data. Of course, the authority to craft that initial prompt, the very first question, comes from human experience and learning. But I think thought itself is the easiest resource to outsource. People say the human did the thinking and the LLM just amplified it, but the truth is, the LLM outsources the thinking. Otherwise, when the result is good, people say "human thought was present," and when it's bad, they say "human thought was absent." But a part of the actual thinking really is outsourced. The alternatives, the counterexamples, the sentence structure. In programming terms, the reader's experience gets outsourced. When you write a blog post, you find yourself thinking about how to make something you understand easy for someone else to understand. With an LLM, that part gets outsourced. But at the same time, I don't get the argument that you shouldn't use it at all. We don't "think" about everything. We have limited cognitive resources. So we study deeply the things we care about, but for the things we don't need, we mostly leave them to "common sense" or prejudice. We just skim the surface. I think of "common sense" as "the largest collection of prejudice." Because what we call common sense usually just amounts to surface level knowledge, the kind of thing we know just enough about to get by. That's why I think LLMs are good. The reason is simple. I don't think deeply about everything in the world anyway. For everything else, I'm buried in some kind of bias. You see it on HN all the time, right? People fight over some technology, but they often don't think about its internal structure or why it works the way it does. They just treat it as an identity. They fight over a particular language, a framework, an operating system, but they rarely check how that technology actually works internally or why it was designed that way. Why use MVC, why a different architecture might be better for my case, it's easier to just go with what's popular. Put more elegantly, "job mobility" gets bundled in there too. I use Windows. In my country, if it's not Windows, you literally can't do anything. You can't even do basic online banking. From regional context like that all the way down to personal interests, people are bound to be different. So I'm just going to use LLMs. The most common excuse you hear around this is the whole "reinventing the wheel" thing. So yeah, I'm going to use LLMs. Because I recognize that I bias myself toward only thinking about what I want to think about. And I know that bias isn't cognitively healthy. But on the flip side, I think what the world values, whether it's knowing a lot or knowing one thing deeply, is going to change. Honestly, I don't know what's right. I think both the advocates and the critics are making valid points. I respect the people who don't use it, and the people who do just have their own workflow. There's really no reason to fight over whose workflow is superior.
• deleted 2mo ago
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• trescenzi 2mo ago
  It depends upon why you have issues with LLMs. If you’re just concerned about quality then sure the dissonance isn’t intolerable. If you’re concerned about their ethics then this becomes a much more challenging position to have.
  • pornel 2mo ago
    But that's the thing - people can live with the contradictions. You can find people at a gas station who will totally agree that air pollution and CO2 emissions are killing people, but still fill up the tank.
• 1970-01-01 2mo ago
  Because it's a machine, not an oracle. If you "hold it right" you are more productive. When you catch them being "dumb" you're reinforcing your own deep knowledge on the topic. When it is correct, you're either learning something new or your task is complete. You are still at risk when you know little and trust it to work alone.
• SaturnIC 2mo ago
  This sounds like typical german small mindedness and self-importance. The tech world does not care about woke ideology, german technical illiteracy and self importance. LLMs are useful and here to stay.
  • M04RPYLON5 2mo ago
    [dead]
• adamas 2mo ago
  Do I understand that spend report right ? 10k USD in a month for AI tokens ? After talking about the environmental cost of AI ?
  • jmuguy 2mo ago
    Yeah this is where I stopped. I use AI every day for work but 10k spend to me is a signal that OP is doing something extremely stupid with their AI use.
    • elicash 2mo ago
      That's the cost of one employee (and not an expensive one). Do you think it's impossible he's getting more value from the AI than he would from a single employee?
      • adamas 2mo ago
        If it's an employee, which I doubt but ok, it's an employee you constantly have to probe, talk to, give instructions to, so, not a really good employee.
        • elicash 2mo ago
          Neither of us have any idea whether his manufacturing startup is successful. It looks to be a 5 person team. A google search suggests they had a funding round early this year. It might, in fact, be that you are more successful with your approach. I have no idea. Congrats if so.
          • adamas 2mo ago
            I mean, he must be pretty successful to be able to burn 10k in tokens. If he is successful because or despite of the AI, I don't know and I don't really care ? That wasn't the question.
            • 2mo ago
• matsemann 2mo ago
  My use of AI is correct. My coworkers use is not. I'm saying it in jest, but it's also a bit true. Not necessarily because we use it any differently. But because my use of AI saves me time. But their use of AI adds more to my plate, no matter if it's slop or not.
  • Rumudiez 2mo ago
    I noticed very recently I actually prefer reviewing other people’s generated code over handwritten. There’s no ego involved and it usually does a better, more thorough job. We have enough infrastructure that by the time another human lays eyes on it for the first time each pull request has already been through 3+ rounds of automated review. Being the only specialist in my area on the team used to mean more coaching and more involvement in code review. Now my coworkers are sending me idiomatic solutions with modern approaches that I approve right away or with hardly any comments
  • black3r 2mo ago
    So much this. When coding I use my LLM to hone the code to perfection before sending it to review, including running AI reviews on it multiple times and fixing obvious bugs so that reviewers have less work to do. I also test all my code manually (LLM can be helpful by giving me a list of test scenarios to consider). When reviewing PRs I carefully read the AI reviewer output, consider which points are relevant, which are irrelevant and only post the relevant issues when requesting changes. I have coworkers who routinely post PRs with comments stating "all tests green, ready to review" and then I actually start the application, test it manually and it doesn't work. And don't get me started on reviewers who post the raw AI output of their "reviewing skill" and then I have to read through 30 paragraphs of "findings" most of which are irrelevant (just today I got the "valuable" feedback of "View is @api_view(["POST"]); no test asserts GET/PUT/PATCH/DELETE → 405")...
• threethirtytwo 2mo ago
  You're all in denial when you criticize LLMs. It's not necessarily that the criticism isn't true. It's more how self assured the criticism is. That's the biggest problem because AI is a moving target. It is getting better, and it is getting better fast. A lot of the criticism can become outdated in a year or six months. The change is happening in front of your very eyes and yet you can always reliably come on HN and find some sort of self assured criticism to say AI can't design, AI code must always be reviewed. Blah blah blah. The big thing people used to call AI was that it was a stochastic parrot and all it did was summarize things. Clearly. None of this is/was true anymore. And very likely all the current criticism will be eliminated soon and we have to find new excuses about AI that makes us feel we are superior. The status quo is about to change. Every 6 months. And you will always think of yourself as superior to LLMs. Your current criticisms will evolve as most of them will be rendered not true pretty soon.
  • adamas 2mo ago
    > AI code must always be reviewed Yeah, of course AI code must always be reviewed. All code must be reviewed.
    • threethirtytwo 2mo ago
      Nope. Not true anymore. Right now the bottleneck is the review because code comes out so fast there is a measurable and adjustable trade off that can be made. If you review all code, your output will be slow. If you review less code, your output will be faster at the cost of more bugs in production. Bug rate will never go down to zero whether you use AI or not. That is the trade off, if you review everything then output is really slow. If you start only reviewing certain types of code like model changes, database changes. Or only backend code and not frontend code, you hit a sweet spot of speed and reliability. As LLMs improve the need for reviews becomes less and less. Companies who don't adjust are just slowing themselves down. That is the trend.
      • adamas 2mo ago
        With that logic, you would let an intern force push his way to prod, that's not a smart move.
• voidUpdate 2mo ago
  > "Last but not least, even when just researching with LLMs, they have the natural tendency to silently sneak in the thoughts of the majority of the training materials, or sometimes even the political convictions of the ones who created the model." > "Yet I still write all of my texts with LLMs" So I'm guessing the author is actually ok with the point they put in the "LLMs are bad" part of the article?
  • adamas 2mo ago
    That's the problem with human written text, sometimes it hallucinates.
  • dspillett 2mo ago
    As long as, after it writing his texts, he is reviewing and editing them, I don't see the contradiction there. And I'm somewhat anti-AI (if I don't care enough to make the effort of writing it myself, why do I care for it to be written at all?).
• mark_and_sweep 2mo ago
  > a genuinely good tool that enriches your thinking A smartphone is also a genuinely good all-around tool. Even social media is a genuinely good tool for connecting people. Yet, I feel like we've been overly optimistic about the impact of said tools on us and our societies in the past two decades. Smartphones are so good, in fact, in some societies, half of us are addicted to them. Billions of people world-wide. I ask myself: Will LLMs enrich my thinking in the long run, or will they ruin it? And what about most people? Will half of us outsource most of our thinking in a decade from now? Given the speed and global scale that we're running these experiments with, it's fair, I think, to be a bit sceptical of the conclusion that, in the long run, LLMs will enrich our thinking.
  • mekdoonggi 2mo ago
    I agree with this. Tools are good, betting the farm on a single tool is bad. Example, cars are good. Betting the farm on cars to the detriment of bikes, buses, and trains is clearly bad. The tool of an llm is clearly handy. Betting trillions of dollars and linking the future of the nation and globe to this tool is clearly bad.
    • dominicrose 2mo ago
      Yes instead of investing everything in AI the USA should invest in electric versions of their vehicles and in trains that can safely carry them because of their lack of range.
      • mekdoonggi 2mo ago
        You're being sarcastic, but literally every other developed country invests in trains and tens of millions of people drive EV's daily with no issues. If you want to argue that LLMs are 100x more useful than a functioning railroad system I've a bridge for you to subscribe to.
  • threethirtytwo 2mo ago
    There's a saying that the intelligence of an average prehistoric cave man should be, in general, higher than a modern day human simply because the lack of technology required stone age humans to be far more intelligent then we are today. Now you can survive by working as a clerk in McDs, but in the stone age you needed to be on your toes and smart af. LLMs are just continuing the trend humanity has long been traveling down.
• RIMR 2mo ago
  The LLM critics are right, and that's why I try not to use AI in the ways critics point out are bad. I use AI to code tools for myself, but I don't pretend anything I make is production quality. Duct tape engineering has always been a bit sloppy, and AI just made it faster. I use AI to troubleshoot issues and plan out strategies, but I basically consider the AI draft of anything to be "draft 0", and use it as a framework for writing my own works for a real first draft of anything I write that will be read by other people. Sometimes the AI spits out a perfect paragraph that I might copy, but I don't ever blindly trust it or let it speak for me. I also double-check everything it says that I don't have existing knowledge of, rather than trust it to be right. AI images, video, and music are all entertaining, but I only generate these things as a form of self-entertainment and maybe online meming. I could never in good conscience pass these creations off as my own, or publish them online on a personal or business website when something non-synthetic would suffice. And I am never personally confiding in an LLM like it were a person. I have had it help me brainstorm options for office politics stuff, but I'm not about to ask it for relationship advice or to be my friend. I do love that it accelerates the tedious stuff, and helps me learn new things pretty quickly if used right. It has definite utility. But I am always really distrustful of it. Sometimes at work we are asked to share how we use AI, and I have actually refused before, on the grounds that I may have found a useful way to use the AI, but I am worried that others will use my same method badly (e.g., not verifying eveything the AI says first), and I would rather not share. It's like I have a finicky gun. I might be comfortable shooting it since I know its quirks and how to keep it from accidentally discharging, but I'm not loaning it out to anyone I wouldn't want to accidentally shoot themselves with it.
• Lerc 2mo ago
  >I almost agree with all of the LLM critics That seems unlikely given the diverse nature of mutually exclusive opinions that exist out there. Critics seem to run the gamut from LLMs being incapable of even the most basic of functions to already sentient creatures secretly plotting our destruction with steganographic messages to each other. It's maybe a bell curve with some wacky at those tails, but there's some fairly significant differences of opinion amongst the positions that are more mainstream. Just the difference between critics of all LLMs and crutics of all closed weights models are a pretty big gap. Similarly for those who criticise them for over censorship vs those who criticise them for unrestricted generation.
• contentpulse 2mo ago
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• speak_plainly 2mo ago
  I spend my days yelling at various AI agents for lying, misunderstanding, or misrepresentation of facts. It feels like a modern spiritual process.
• xyzsparetimexyz 2mo ago
  This is like meat eaters who wish they were vegan but state that they're not mentally strong enough or whatever. Incredibly annoying. Either shut up or convert.
• deleted 2mo ago
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• swiftcoder 2mo ago
  > I am a little bit scared to say this too: last month I spent almost 10k USD on tokens. It sounds so insane. What are people actually doing with all these tokens? I use LLMs pretty heavily for development, and I'm rarely spending all the tokens that come with a $10/month OpenCode Go subscription...
  • nicce 2mo ago
    If you are reviewing the changes and keep giving input, it is not that token consuming. But many people go with full yolo with agent mode.
    • swiftcoder 2mo ago
      I honestly felt I was going pretty YOLO :) I write specs and review, but the LLM writes all the code, tests, etc and only gets re-prompted when it screws up badly. That said, I'm not running that many agent loops in parallel, so maybe thats where the cost bites
  • perrygeo 2mo ago
    My heaviest LLM usage month came in at $45. So far this July, $6 and counting (it's been a light month). I can certainly imagine increasing my usage by several orders of magnitude but ... why? If I have something that needs to get done and an LLM can do it, great. But I'm not sitting here inventing reasons to waste money, which is apparently what the tokenmaxers are doing - as evidenced by the astounding lack of value produced by all this vibe coding.
    • therealdrag0 2mo ago
      You’re not even trying to use AI if that’s all you spend. I am not a tokenmaxer and it’s easy to max out my 20$ subscription just hacking on a simple web game. Working in a larger enterprise context it’s impossible for me to use AI daily and not spend hundreds of dollars.
  • HDThoreaun 2mo ago
    A lot of their usage was fable which is crazy expensive.
• jszymborski 2mo ago
  > I tend not to actually read most LLM output anymore; I skim it, to check if I vibe with it. But a problem statement of three sentences, that I will fact-check really hard. It is like code review: a review with 1,000 lines of code gets an “LGTM”. A review with 100 lines gets 15 comments. This is where I take issue. I'm in a similar boat to the author. In the last couple of months, I've been experimenting with increasing the use of local and cloud LLMs for my research code. I'll create a prototype, maybe port it to a language I don't use very much like Rust, run some tests... but at the very end when I'm very happy with it, I _need_ to go line by line and understand _everything_ that is happening. Sometimes that means using an LLM to understand it, but even when I do and there is a concept I don't get, I try to read primary resources written by experts. The least bad thing I've found LLMs good for is ideation because it's super easy to take the good nuggets and leave the bad, but even that carries risks of shaping thought and making everyone reach for and ignore the same ideas in the way the Spotify radio or YouTube autoplay has been shaping/flattening tastes for the worse. I'm not sure what I'll rule at the end of my experiments with LLMs, but right now I'm enjoying the rush of having prototypes that run quickly. I've always been a top-down learner, being motivated by hacking a cool demo I half understand and progressively tearing it apart.
• eamonnsullivan 2mo ago
  The one thing that had me reading to the end was the mention near the top of the environmental impact of LLMs, but he never got back to it. I'm currently writing an onboarding doc for my team, encouraging LLM use for some tasks. (OK, well, I'm actually procrastinating by reading HN). At the same time, I'm in a darkened office with tinfoil on the windows and a fan pointed at me because it's hell outside and it has been for weeks, and every year it seems to get hotter and hotter and we have longer and longer heatwaves. This seems ... discordant, at a minimum. Really, _should_ we be using these things to speed up, say, dependency updates if the cost is the planet? I wanted to know what the author thought about that.
  • cognitiveinline 2mo ago
    Your commute is worse for the environment than your day's token usage, by a magnitude.
    • eamonnsullivan 2mo ago
      Well, I doubt that. I mostly work from home. But also I live in a big city (London) with a working public transport system.
      • cognitiveinline 2mo ago
        I dont know what to tell you. I guess - correct your misconceptions? Carbon footprint of commute is in KGs of CO2. A day's worth of AI, depending on model, is ~15-100g of CO2. Heck food you eat has more than a few Kgs of footprint everyday.
        • eamonnsullivan 2mo ago
          I won't belabour the point, but I think someone needs to correct their misconceptions. You're comparing a single, average person's usage of AI in a day -- not the billions who actually use it. Then you are comparing it to an American's two-hour commute in an oversized SUV. (A commute on the Tube costs about 0.02991 kg per passenger, per kilometre.) What about training those models? Or the usage of all of the data centres? The projections are that by 2028 a fifth of all energy consumption in the U.S. alone will be for AI.[1] [1] https://www.technologyreview.com/2025/05/20/1116327/ai-energy-usage-climate-footprint-big-tech/ https://www.technologyreview.com/2025/05/20/1116327/ai-energ...
• luck7710 2mo ago
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• cadamsdotcom 2mo ago
  LLMs are awesome, but sometimes we'd be better off with more friction. This is because.. sometimes an idea is just bad. I learned the hard way the other day when I filed this PR against prek: https://github.com/j178/prek/pull/2302 https://github.com/j178/prek/pull/2302 My idea was bad. The implementation was meant to solve my problem. All it did was expose more problems and waste my time and the maintainer's, and god knows how many tokens from Claude and Codex. In the end the PR was useless so I closed it. The maintainer and I would have both been better off - less time wasted - if I was forced to forever wonder if the idea was good, letting it bounce around the back of my mind.
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• overgard 2mo ago
  My feeling is that LLMs are an interesting technology. I don't feel currently threatened by them, and they're handy in the hands of people that can use them with discipline. However, I think the people controlling and creating the LLMs are by and large scumbags who want to gamble with everyone's future. It's hard for me to look at their public statements and the actions of people like Altman, Amodei, Musk, and come away with any other conclusion than that these are fairly awful people that have bad intentions. Their message is essentially "we want to summon the machine god to destroy your livelihood because it will enrich us and give us power over the world, and there's a really high probability it gets out of control and causes massive problems [that we're completely going to not do anything about]. But we really like money! And we have bunkers!" I suspect a lot of people are in this boat. We both use it and cheer against it. But it's not cognitive dissonance, it's just a recognition that there's a useful tool being controlled by vile people.
• archagon 2mo ago
  > I strongly agree that written text should be from humans to humans. Yet I still write all of my texts with LLMs. Hypocritical garbage. Into the blacklist you go. If you can’t even use your own words for basic communication then there’s absolutely no reason for me to take you seriously.
• gochujang_ 2mo ago
  [flagged]
• bbeonx 2mo ago
  I think I'd put it this way: if I could flip a switch tomorrow and the AI boom was done, I probably would. The negative effects just super duper outweigh the fact that coders are more efficient. But since it exists, I'm going to use it. Hacking on my own small projects isn't using that many resources. But the benefit simply isn't worth the cost, as much as I personally love using LLMs.
• hypfer 2mo ago
  Aren't all conferences just huge piles of cognitive dissonance? At least the "industry" ones used for "networking" and all that other crap. Where's the news here? And why does the author not take a step back and realize that there is none?
• sivakon 2mo ago
  > And then there are the geopolitical tensions. What happens if China or the US cut us off overnight from these technologies? Just a couple of weeks ago the US government showed it was able and willing to cut off non-US citizens from Anthropic’s latest frontier model. The only evidence you have is US here and all the frontier models from China are free to download. Pure projection. You can read China's AI strategy here: https://ipc.court.gov.cn/zh-cn/news/view-5766.html https://ipc.court.gov.cn/zh-cn/news/view-5766.html
  • ryan_n 2mo ago
    I might be missing something but what exactly is being projected here? The US did what the author said. It's not farfetched to imagine geopolitical conflicts could, at some point, drive china to do something similar. > all the frontier models from China are free to download Maybe? Again, not hard to imagine that they might not be releasing their actual frontier models to the public.
    • sivakon 2mo ago
      The link I shared mentions their AI strategy. Short version is this: putting export controls on AI open-source will hinder their own internal open-source ecosystem
    • nicce 2mo ago
      I guess China did not deserve mention. They are the only one releasing open models consitently and not cutting any access. Only US actions show evidence and for the US only.
      • ryan_n 2mo ago
        Fair enough, that makes sense
• tonyedgecombe 2mo ago
  > And then there is the situation about junior engineers. There are actually two different points in there: a) you cannot trust the effort behind your junior’s code anymore, and b) seniors have no incentive left to teach juniors. If you are bringing in juniors with the expectation that they won’t produce any value for some time then it might be better to block them from using LLMs. Do this and you will get a better understanding of where they are in the process and they will probably learn the ropes more quickly.
  • thewhitetulip 2mo ago
    Block juniors from LLM usage. But then how will we show metrics of AI usage??!?!
  • bluefirebrand 2mo ago
    > If you are bringing in juniors with the expectation that they won’t produce any value for some time then it might be better to block them from using LLMs A) I think many companies no longer view juniors as an investment, they want them to be productive. They view juniors as "cheaper almost-seniors" B) Blocking them from using LLMs would mean acknowledging that there is a downside to having your employees using LLMs. If they prevent your juniors from improving, what negative effect are they having on your seniors?
• buster_hymen404 2mo ago
  I think that the use of LLMs to expedite the learning process (especially when it comes to learning new things) is extraordinary and should be practiced by anybody with the means to. Think about how far we as the human race have come. Everything eventually plateaus and either flatlines or else regresses.. With the use of AI we can expand our ways of thinking into a new tier we would have never been able to achieve otherwise. It goes without saying that people who refuse to use the tools we've been given are close-minded and susceptible to fail in the new age that we are truly lucky to be a part of. And its here to stay, whether you like it or not lol
• dannersy 2mo ago
  I think folks ITT are trivializing the issue here. Many keep drawing parallels to LLMs being akin to the loom or calculator. That seems intellectually dishonest to me. Those tools were not anthropomorphized interfaces, nor were they instant gratification. To do significant things with a calculator, you still had to know maths, order of operations, formulas, etc. We didn't lose mathematicians as a result of the calculator, nor did the calculator play with our emotions. I have linked this elsewhere in this thread, but the studies on this matter suggest a worse outcome than just losing hand crafted or "artisanal" software: https://arxiv.org/pdf/2604.04721 https://arxiv.org/pdf/2604.04721 > These findings are particularly concerning because persistence is foundational to skill acquisition and is one of the strongest predictors of long-term learning. > We posit that persistence is reduced because AI conditions people to expect immediate answers, thereby denying them the experience of working through challenges on their own. This issue is not that we are losing the ability to write good software by hand. It is possible we are losing our internal tools to learn new things by circumventing a necessary part of the process required by our biology.
  • slfnflctd 2mo ago
    > nor did the calculator play with our emotions It seems to me this here is the dangerous 'force multiplier' for destructive outcomes. It's one thing for a kid to become obsessed with a fictional character. It's a whole different playing field when that character can talk back, remember things, and potentially surface all kinds of subject matter which cannot be predicted and could at times be harmful. Not even remotely the same level of impact. I think we're almost at the point where LLM education (as in, teaching awareness of the basic tech and its shortcomings) needs to start in Kindergarten.
  • encyclopedism 2mo ago
    Exactly this! LLM's are replacing your 'brain' i.e. the deepest most amazing part of you. The potential value of this to business is astronomical! No there won't be an explosion of new software, a minor blip perhaps and even this one of diminishing returns (each cycle of LLM improvements requiring less and less human input). If there are 25 million software developers today then the ROI by OpenAI, Anthropic et al pays off if in a few years time only 15 million developers are needed. That 10 million is the ROI and that is likely to be you.
• ryan_n 2mo ago
  I agree with most of the 'llm's are bad' section. However, I find it extremely hard to believe that llm's will make peoples thoughts sharper and faster. There have already been several studies published demonstrating the obvious. Not hard to imagine that long term, the negative cognitive effects of using llm's constantly will compound and be even worse.
  • reformd 2mo ago
    i was certain of the same worst case scenario until I started to properly read and study the LLMs output. prior to that enlightening, very wise choice, I speedread/skimmed and checked for grave bullshit/hallucinations only. now i am convinced that it's the same matter as with people who forget most of what they learned after the actual exam vs people who go nuts and can't progress if they didn't understand a foundational part of a formula, fact or theory.
  • black3r 2mo ago
    How LLM usage affects your thinking process entirely depends on the workflow you use with them. I can honestly say that while using LLM my thoughts are as sharp and as fast as they were before, if not sharper and faster. But my workflow is that I watch the LLM as it rips, have verbose output turned on so I also read Claude's thinking process (and lots of interesting information is hidden there). This helps me learn new stuff I wouldn't think of. Helps me stop Claude if he's veering off track. Makes it easier to proofread what's Claude doing and why step-by-step and easier to spot any mistakes (because they often come from wrong assumptions you wouldn't see if you didn't see the thinking process). If you just let your agent write thousands of lines of code, reviewing them is painful. If you also run multiple agents for multiple tasks at the same time, your focus is divided, so you aren't spending all your brain power on the task at hand.
• u8 2mo ago
  > I strongly agree that written text should be from humans to humans. Yet I still write all of my texts with LLMs. And I don’t find that contradictory. What distinguishes “AI slop” from “good writing” is whether a human has put thoughts behind it. And you cannot outsource thinking. Writing is thinking. If you're outsourcing your writing to an LLM, you are shortchanging yourself by skipping over much of the refinement of ideas that the process of writing provides. I wish the author had clarified how he uses LLMs for writing. It's perfectly fine to have an LLM proofread and fix your grammatical errors--that's a mechanical task. But I think it's gross when it starts putting words and content on the page.
• YeGoblynQueenne 2mo ago
  >> I am a little bit scared to say this too: last month I spent almost 10k USD on tokens. It sounds so insane. No it just sounds completely stupid. You spent $10k to get a program to write text that you can write yourself just as well and for free. "Dissonance" doesn't even begin to describe it. It's like suddenly everyone has turned into the listless blobs of fat that humans have turned into in Wall-E. I just hope all that will eventually correct itself: open (one way or another) models will reach parity with proprietary ones when diminishing returns eventually make it impossible for LLMs to grow any longer, OpenAI and Anthropic will succeed in bankrupting each other, it will become possible for everyone to run their own, personal, free and open (one way or another) model on their own laptop (assuming we still own our laptops) and at that point most of the problems with LLMs, particularly the ones that come from having to pay someone else to do the things you could always do yourself for free, will go away. I just hope.
  • bitpush 2mo ago
    > You spent $10k to get a program to write text that you can write yourself just as well and for free. "You spent $1k on a flight ticket from SFO to NYC when you could have just walked yourself just as well and for free"
    • pona-a 2mo ago
      "Why spend $1k on a helicopter ride to Costco when you can bike there?"
      • YeGoblynQueenne 2mo ago
        Actually.
    • kaelwd 2mo ago
      0.25 day flight vs 120+ day walk doesn't really seem like a fair comparison, nobody is hundreds of times more productive from this.
      • 2mo ago
• bruce343434 2mo ago
  > last month I spent almost 10k USD on tokens. It sounds so insane It is. That kind of money would change my life and this guy spends it on prompts that "really force him to think". I use LLMs. So far, 20 bucks per month has me covered. I hit the limit sometimes. I just take a walk. Forces me to think.
• plasticeagle 2mo ago
  "Dissonance" is a funny way to spell hypocrisy.
• coldtea 2mo ago
  >If you have thoughts, they come out sharper and faster. No, they come duller and increasingly dependent on the LLM doing them for you. And that happens to the generations that learned to code earlier without the LLM. What would happen to the later ones, those getting in uni after LLMs emerged, that would never get a real feel for the basics to begin with?
• evolve2k 2mo ago
  What a nitemare to read. I stuck with it but wished after I didn’t. Reminds me of a 2.5 star movie that I watch to the end but am so annoyed as the credits roll. Yes there is a dissonance, using LLMS just took their dot point notes and spread them thin. I personally would prefer just the notes and some personal anecdotes to tie the notes into a cohesive whole. This, this approach here, is not better.
• orbitalventures 2mo ago
  LLM's discussion is always the same, if you don't use it you lose it, although true, the question is why and maybe we don't need to do that thing. Humans have been gravitating into cognitive thinking and not specialized tasks, some of us, a handful do repetitive tasks and that is ok, but, the majority of us work better in context, in guidance. LLM offers that, offers that abstraction that we were and are looking into all aspects of our lives. We once plow the fields, and harvest by hand, and was good, but suddenly became cumbersome, too much to handle and machines came along to do the job of 20, faster and better, and there humans just tweak the machine, teach the small repetitive tasks. We did that with everything and we change our lives, the way that we upskill ourselves and our communities, we let specialized human tasks as a comfort/skill/romantic/artistic outlet, like some specialized vineyards or specialized farms that do specific very specific things. But the rest we delegate and move to another areas. I believe the problem is not LLM/AI is how we are going to up skill, repetitive jobs no longer need us, so we need to upskill for context, for management, strategy
• orbitalventures 2mo ago
  The issue that I take on this is ego, we believe that we can do a better job sometimes, an we exhaust ourselves with no reason, Agent delegation works in the same way as Human delegation, the difference is the speed on how that happens, reviews were a good idea when humans toke days to do a product, features, code, document or what ever. The reward piece I believe is faster to see something working, the issue seems to be the control we had. The approach needs to be the same of those we do with almost everything else. We drive a car but no necessarily knows how to assemble, we might now here and there trouble shooting, change tires, oil, do some level of maintenance, but at the end just a few of us can pull an engine apart and check every piece, cars are not even manufactured manually anymore, QA is part of an automated process, as production rates are far to fast for humans to intervene. AI brought that to us, insanely fast automation, and with that, Humans should not become gatekeepers but rather guides.