6 ms·

> 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.

by msdz 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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.
      - skydhash 3mo ago
        > 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. It can be fine as a “user”, but not really as a “designer”. Because discussion about possible solutions is a matter of tradeoffs and tweaking of parameters, not slinging words around. Abstractions are not appliances that are plug and play. They’re often full of parameters that dictate their usefulness and costs, and not understanding those parameters is just roleplaying.
- themgt 3mo ago
  For sure. You cannot have "only higher level thoughts" without doing lower level work. Spend 3 days a week writing Ruby on Rails and 2 days hand rolling x86 assembly. Every web dev I know has been doing this since long before LLMs. Ensures they can keep having high level Rails thoughts.
  - qsera 3mo ago
    Honestly, horrible example.
Levitz 3mo 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 3mo 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 3mo 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 3mo ago
      anything with large amounts of user text input.
throw10920 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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.
- 3mo ago
jmartrican 3mo 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 3mo 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 3mo 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 3mo ago
    That's what he was saying
grayhatter 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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 3mo ago
snarfy 3mo 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 3mo 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 3mo ago
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- Diogenesian 3mo 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 3mo 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 3mo ago
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ElFitz 3mo 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 3mo 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 3mo 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 3mo 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 3mo ago
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FunHearing3443 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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 3mo ago
  The doctor from Idiocracy: it says your shit's fucked up.
captainbland 3mo 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 3mo 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 3mo 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?

by msdz 3mo ago

dominotw 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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.
    - skydhash 3mo ago
      > 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. It can be fine as a “user”, but not really as a “designer”. Because discussion about possible solutions is a matter of tradeoffs and tweaking of parameters, not slinging words around. Abstractions are not appliances that are plug and play. They’re often full of parameters that dictate their usefulness and costs, and not understanding those parameters is just roleplaying.
themgt 3mo ago
For sure. You cannot have "only higher level thoughts" without doing lower level work. Spend 3 days a week writing Ruby on Rails and 2 days hand rolling x86 assembly. Every web dev I know has been doing this since long before LLMs. Ensures they can keep having high level Rails thoughts.
- qsera 3mo ago
  Honestly, horrible example.

Levitz 3mo ago

xnorswap 3mo 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 3mo 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 3mo ago
    anything with large amounts of user text input.

throw10920 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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.
3mo ago

jmartrican 3mo 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 3mo 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 3mo 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 3mo ago
  That's what he was saying

grayhatter 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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 3mo ago

snarfy 3mo 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 3mo 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 3mo ago
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Diogenesian 3mo 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 3mo 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 3mo ago
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ElFitz 3mo 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 3mo 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 3mo 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 3mo 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 3mo ago

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FunHearing3443 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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 3mo 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 3mo ago
The doctor from Idiocracy: it says your shit's fucked up.

captainbland 3mo 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 3mo 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 3mo 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?