19 ms·

Human coders are still better than LLMs

• RayMan1 1y ago
  of course they are.
• vouaobrasil 1y ago
  The question is, for how long?
  • deleted 1y ago
    [deleted]
  • jppittma 1y ago
    It's really gonna depend on the project. When my hobby project was greenfield, the AI was way better than I am. It was (still is) more knowledgable about the standards that govern the field and about low level interface details. It can shit out a bunch of code that relies on knowing these details in seconds/minutes, rather than hours/days. Now that the project has grown and all that stuff is hammered out, it can't seem to consistently write code that compiles. It's very tunnel visioned on the specific file its generating, rather than where that fits in the context of what/how we're building what we're building.
    • sixQuarks 1y ago
      Again, the question is for how long
    • jonator 1y ago
      We can slightly squeeze more juice out of them with larger projects by providing better context, docs, examples of what we want, background knowledge, etc. Like people, LLMs don't know what they don't know (about your project).
  • sixQuarks 1y ago
    Exactly! We’ve been seeing more and more posts like this, saying how AI will never take developer jobs or will never be as good as coders. I think it’s some sort of coping mechanism. These posts are gonna look really silly in the not too distant future. I get it, spending countless hours honing your craft and knowing that AI will soon make almost everything you learned useless is very scary.
    • sofal 1y ago
      I'm constantly disappointed by how little I'm able to delegate to AI after the unending promises that I'll be able to delegate nearly 100% of what I do now "in the not too distant future". It's tired impatience and merited skepticism that you mistake for fear and coping. Just because people aren't on the hype train with you doesn't mean they're afraid.
      • vouaobrasil 1y ago
        Personally, I am. Lots of unusual skills I have, have already been taken by AI. That's not to say I think I'm in trouble, but I think it's sad I can't apply some of these skills that I learned just a couple of years ago like audio editing because AI does it now. Neither do I want to work as an AI operator, which I find boring and depressing. So, I've just moved onto something else, but it's still discouraging. Also, so many people said the same thing about chess when the first chess programs came out. "It will never beat an international master." Then, "it will never beat a grandmaster." And Kasparov said, "it would never beat me or Karpov." Look where we are today. Can humanity adapt? Yes, probably. But that new world IMO is worse than it is today, rather lacking in dignity I'd say.
        • sofal 1y ago
          I don't acquire skills and apply them just to be able to apply them. I use them to solve problems and create things. My learned skills for processing audio are for the purpose of getting the audio sounding the way I want it to sound. If an AI can do that for me instead, that's amazing and frees up my time to do other things or do a lot more different audio things. None of this is scary to me or impacts my personal dignity. I'm actually constantly wishing that AI could help me do even more. Honestly I'm not even sure what you mean by AI doing audio editing, can I get some of that? That is some grunt work I don't need more of.
  • spion 1y ago
    Vibe-wise, it seems like progress is slowing down and recent models aren't substantially better than their predecessors. But it would be interesting to take a well-trusted benchmark and plot max_performance_until_date(foreach month). (Too bad aider changed recently and there aren't many older models; https://aider.chat/docs/leaderboards/by-release-date.html https://aider.chat/docs/leaderboards/by-release-date.html has not been updated in a while with newer stuff, and the new benchmark doesn't have the classic models such as 3.5, 3.5 turbo, 4, claude 3 opus)
    • vouaobrasil 1y ago
      I think that we can't expect continuous progress either, though. Often in computer science it's more discrete, and unexpected. Computer chess was basically stagnant until one team, even the evolution of species often behaves in a punctuated way rather than as a sum of many small adaptations. I'm much more interested (worried) of what the world will be like in 30 years, rather than in the next 5.
      • spion 1y ago
        Its hard to say. Historically new discoveries in AI often generated great excitement and high expectations, followed by some progress, then stalling, disillusionment and AI winter. Maybe this time it will be different. Either way what was achieved so far is already a huge deal.
  • kilroy123 1y ago
    My crackpot guess is ~5 years. The incentives are just too damn high to not keep innovating in the space. We'll find new ways to push the tech.
• chuckreynolds 1y ago
  for now. (i'm not a bot. i'm aware however a bot would say this)
• mattnewton 1y ago
  This matches my experience. I actually think a fair amount of value from LLM assistants to me is having a reasonably intelligent rubber duck to talk to. Now the duck can occasionally disagree and sometimes even refine. https://en.m.wikipedia.org/wiki/Rubber_duck_debugging https://en.m.wikipedia.org/wiki/Rubber_duck_debugging I think the big question everyone wants to skip right to and past this conversation is, will this continue to be true 2 years from now? I don’t know how to answer that question.
  • marcosdumay 1y ago
    LLMs will still be this way 10 years from now. But IDK if somebody won't create something new that gets better. But there is no reason at all to extrapolate our current AIs into something that solves programing. Whatever constraints that new thing will have will be completely unrelated to the current ones.
    • smokel 1y ago
      Stating this without any arguments is not very convincing. Perhaps you remember that language models were completely useless at coding some years ago, and now they can do quite a lot of things, even if they are not perfect. That is progress, and that does give reason to extrapolate. Unless of course you mean something very special with "solving programming".
      • marcosdumay 1y ago
        Why state the same arguments everybody has been repeating for ages? LLMs can only give you code that somebody has wrote before. This is inherent. This is useful for a bunch of stuff, but that bunch won't change if OpenAI decides to spend the GDP of Germany training one instead of Costa Rica.
        • rhubarbtree 1y ago
          That’s not true. LLMs are great translators, they can translate ideas to code. And that doesn’t mean it has to be recalling previously seen text.
• lodovic 1y ago
  Sure, human coders will always be better than just AI. But an experienced developer with AI tops both. Someone said, your job won't be taken by AI, it will be taken by someone who's using AI smarter than you.
  • bluefirebrand 1y ago
    > Someone said, your job won't be taken by AI, it will be taken by someone who's using AI smarter than you. "Your job will be taken by someone who does more work faster/cheaper than you, regardless of quality" has pretty much always been true That's why outsourcing happens too
• wanderingstan 1y ago
  “Better” is always task-dependent. LLMs are already far better than me (and most devs I’d imagine) at rote things like getting CSS syntax right for a desired effect, or remembering the right way to invoke a popular library (e.g. fetch) These little side quests used to eat a lot of my time and I’m happy to have a tool that can do these almost instantly.
  • gherkinnn 1y ago
    I have found it to be good at things I am not very strong at (SQL) but terrible at the things I know well (CSS). Telling, isn't it?
    • ch4s3 1y ago
      I kind of agree. It feels like they're generally a superior form of copying and pasting fro stack overflow where the machine has automated the searching, copying, pasting, and fiddling with variable names. It be just as useful or dangerous as Google -> Copy -> Paste ever was, but faster.
    • mywittyname 1y ago
      Ironically, I find it strong at things I don't know very well (CSS), but terrible at things I know well (SQL). This is probably really just a way of saying, it's better at simple tasks rather than complex ones. I can eventually get Copilot to write SQL that's complex and accurate, but I don't find it faster or more effective than writing it myself.
      • ehansdais 1y ago
        Actually, you've reinforced their point. It's only bad at things the user is actually good at because the user actually knows enough in that domain to find the flaws and issues. It appears to be good in domains the user is bad at because the user doesn't know any better. In reality, the LLM is just bad at all domains; it's simply whether a user has the skill to discern it. Of course, I don't believe it's as black and white as that but I just wanted to point it out.
• burningion 1y ago
  I agree, but I also didn’t create redis! It’s a tough bar if LLMs have to be post antirez level intelligence :)
  • ljlolel 1y ago
    Seriously, he’s one of the best on the planet of course it’s not better than him. If so we’d be cooked. 99% of professional software developers don’t understand what he said much less can come up with it (or evaluate it like Gemini). This feels a bit like a humblebrag about how well he can discuss with an LLM compared to others vibecoding.
• decasia 1y ago
  We aren't expecting LLMs to come up with incredibly creative software designs right now, we are expecting them to execute conventional best practices based on common patterns. So it makes sense to me that it would not excel at the task that it was given here. The whole thing seems like a pretty good example of collaboration between human and LLM tools.
  • ehutch79 1y ago
    Uh, no. I've seen the twitter posts saying llms will replace me. I've watched the youtube videos saying llms will code whole apps on one prompt, but are light on details or only show the most basic todo app from every tutorial. We're being told that llms are now reasoning, which implies they can make logical leaps and employ creativity to solve problems. The hype cycle is real and setting expectations that get higher with the less you know about how they work.
    • ldjkfkdsjnv 1y ago
      you will almost certainly be replaced by an llm in the next few years
      • einpoklum 1y ago
        You mean, as a HackerNews commenter? Well, maybe... In fact, maybe most of has have been replaced by LLMs already :-)
    • bgwalter 1y ago
      After the use-after-free hype article I tried CoPilot and it outright refused to find vulnerabilities. Whenever I try some claim, it does not work. Yes, I know, o3 != CoPilot but I don't have $120 and 100 prompts to spend on making a point.
    • prophesi 1y ago
      > The hype cycle is real and setting expectations that get higher with _the less you know about how they work_. I imagine on HN, the expectations we're talking about are from fellow software developers who at least have a general idea on how LLM's work and their limitations.
• habnds 1y ago
  seems comparable to chess where it's well established that a human + a computer is much more skilled than either one individually
  • hatefulmoron 1y ago
    I don't think that's been true for a while now -- computers are that much better.
  • vjvjvjvjghv 1y ago
    Can humans really give useful input to computers? I thought we have reached a state where computers do stuff no human can understand and will crush human players.
  • bgwalter 1y ago
    This was the Centaur hypothesis in the early days of chess programs and it hasn't been true for a long time. Chess programs of course have a well defined algorithm. "AI" would be incapable of even writing /bin/true without having seen it before. It certainly wouldn't have been able to write Redis.
    • NitpickLawyer 1y ago
      > This was the Centaur hypothesis in the early days of chess programs and it hasn't been true for a long time. > Chess programs of course have a well defined algorithm. Ironically, that also "hasn't been true for a long time". The best chess engines humans have written with "defined algorithms" were bested by RL (alphazero) engines a long time ago. The best of the best are now NNUE + algos (latest stockfish). And even then NN based engines (Leela0) can occasionally take some games from Stockfish. NNs are scarily good. And the bitter lesson is bitter for a reason.
      • bgwalter 1y ago
        No, the alphazero papers used an outdated version of Stockfish for comparison and have always been disputed. Stockfish NNUE was announced to be 80 ELO higher than the default. I don't find it frustrating. NNs excel at detecting patterns in a well defined search space. Writing evaluation functions is tedious. It isn't a sign of NN intelligence.
• AnimalMuppet 1y ago
  OK. (I mean, it was an interesting and relevant question.) The other, related question is, are human coders with an LLM better than human coders without an LLM, and by how much? (habnds made the same point, just before I did.)
  • vertigolimbo 1y ago
    Here’s the answer for you. Tldr; 15% performance increase, in some cases up to 40% increase, in the others 5% decrease. It all depends. Source: https://www.thoughtworks.com/insights/blog/generative-ai/experiment-github-copilot-practical-guide https://www.thoughtworks.com/insights/blog/generative-ai/exp...
• uticus 1y ago
  same as https://news.ycombinator.com/item?id=44127956 https://news.ycombinator.com/item?id=44127956, also on HN front page
• deleted 1y ago
  [deleted]
• varispeed 1y ago
  Looks like this pen is not going to replace the artist after all.
• smilbandit 1y ago
  From my limited experience, former coder now management but I still get to code now and then. I've found them helpful but also intrusive. Sometimes when it guesses the code for the rest of the line and next few lines it's going down a path I don't want to go but I have to take time to scan it. Maybe it's a configuration issue, but i'd prefer it didn't put code directly in my way or be off by default and only show when I hit a key combo. One thing I know is that I wouldn't ask an LLM to write an entire section of code or even a function without going in and reviewing.
  • haiku2077 1y ago
    Zed has a "subtle" mode like that. More editors should provide it. https://zed.dev/docs/ai/edit-prediction#switching-modes https://zed.dev/docs/ai/edit-prediction#switching-modes
  • PartiallyTyped 1y ago
    > One thing I know is that I wouldn't ask an LLM to write an entire section of code or even a function without going in and reviewing. These days I am working on a startup doing [a bit of] everything, and I don't like the UI it creates. It's useful enough when I make the building blocks and let it be, but allowing claude to write big sections ends up with lots of reworks until I get what I am looking for.
• oldpersonintx2 1y ago
  but their rate of improvement is like 1000x human devs, so you have to wonder what the shot clock says for most working devs
• pupppet 1y ago
  If an LLM just finds patterns, is it even possible for an LLM to be GOOD at anything? Doesn't that mean at best it will be average?
  • jaccola 1y ago
    Most people (average and below average) can tell when something is above average, even if they cannot create above average work, so using RLHF it should be quite possible to achieve above average. Indeed it is likely already the case that in training the top links scraped or most popular videos are weighted higher, these are likely to be better than average.
  • lukan 1y ago
    There are bad patterns and good patterns. But whether a pattern is the right one for a specific task is something different. And what really matters is, if the task gets reliable solved. So if they actually could manage this on average with average quality .. that would be a next level gamechanger.
  • riknos314 1y ago
    My experience is that LLMs regress to the average of the context they have for the task at hand. If you're getting average results you most likely haven't given it enough details about what you're looking for. The same largely applies to hallucinations. In my experience LLMs hallucinate significantly more when at or pushed to exceed the limits of their context. So if you're looking to get a specific output, your success rate is largely determined by how specific and comprehensive the context the LLM has access to is.
  • JackSlateur 1y ago
    Yes, IA is basically a random machine aiming for average outcome IA is neat for average people, to produce average code, for average compagnies In a competitive world, using IA is a death sentence;
  • bitpush 1y ago
    Humans are also almost always operating on patterns. This is why "experience" matters a lot. Very few people are doing truly cutting edge stuff - we call them visionaries. But most of the time, we're just merely doing what's expected And yes, that includes this comment. This wasnt creative or an original thought at all. I'm sure hundreds of people have had similar thought, and I'm probably parroting someone else's idea here. So if I can do it, why cant LLM?
• darkport 1y ago
  I think this is true for deeply complex problems, but For everyday tasks an LLM is infinitely “better”. And by better, I don’t mean in terms of code quality because ultimately that doesn’t matter for shipping code/products, as long as it works. What does matter is speed. And an LLM speeds me up at least 10x.
  • nevertoolate 1y ago
    How do you measure this?
  • kweingar 1y ago
    You're making at least a year's worth of pre-LLM progress in 5 weeks? You expect to achieve more than a decade of pre-LLM accomplishments between now and June 2026?
• vjvjvjvjghv 1y ago
  I think we need to accept that in the not too far future LLMs will be able to do most of the mundane tasks we have to do every day. I don't see why an AI can't set up kubernetes, caching layers, testing, databases, scaling, check for security problems and so on. These things aren't easy but I think they are still very repetitive and therefore can be automated. There will always be a place for really good devs but for average people (most of us are average) I think there will be less and less of a place.
  • bluefirebrand 1y ago
    > There will always be a place for really good devs but for average people (most of us are average) I think there will be less and less of a place You open your post with "we need to accept" and then end with this This terrifies me. The idea that AI results in me having "less of a place" in society? The idea of mass unemployment? We should be scared
• pknerd 1y ago
  Let's not forget that LLMs can't give a solution they have not experienced themselves
  • willmarch 1y ago
    This is objectively not true.
    • nssnsjsjsjs 1y ago
      So LLMs have sweated to debug a production issue, got to the bottom of it, realised it is worth having more unit tests so values that and then produces a solution that has more unit tests. So when you ask the LLM to write code it is opinionated and always creates a test to go with it?
      • willmarch 1y ago
        I don't know how your comment relates to our comments above. I took the original comment to mean that the poster believes LLMs cannot come up with novel solutions they have never seen before. It has been proven again and again that they absolutely can solve original problems and come up with solutions that were not in their training data.
• rel2thr 1y ago
  Antirez is a top 0.001% coder . Don’t think this generalizes to human coders at large
  • ljlolel 1y ago
    Seriously, he’s one of the best on the planet of course it’s not better than him. If so we’d be cooked. 99% of professional software developers don’t understand what he said much less can come up with it (or evaluate it like Gemini). This feels a bit like a humblebrag about how well he can discuss with an LLM compared to others vibecoding.
  • justacrow 1y ago
    Hey, my CEO is saying that LLMs are also top 0.001% coders now, so should at least be roughly equivalent.
• yua_mikami 1y ago
  The thing everyone forgets when talking about LLMs replacing coders is that there is much more to software engineering than writing code, in fact that's probably one of the smaller aspects of the job. One major aspect of software engineering is social, requirements analysis and figuring out what the customer actually wants, they often don't know. If a human engineer struggles to figure out what a customer wants and a customer struggles to specify it, how can an LLM be expected to?
  • malfist 1y ago
    That was also one of the challenges during the offshoring craze in the 00s. The offshore teams did not have the power, or knowledge to push back on things and just built and built and built. Sounds very similar to AI right? Probably going to have the same outcome.
    • hathawsh 1y ago
      The difference is that when AI exhibits behavior like that, you can refine the AI or add more AI layers to correct it. For example, you might create a supervisor AI that evaluates when more requirements are needed before continuing to build, and a code review AI that triggers refinements automatically.
      • nevertoolate 1y ago
        Question is, how autonomous decision making works, nobody argues that llm can finish any sentence, but can it push a red button?
        • johnecheck 1y ago
          Of course it can push a red button. Trivially, with MCP. Setting up a system to make decisions autonomous is technically easy. Ensuring that it makes the right decisions, though, is a far harder task.
          • 1y ago
• catigula 1y ago
  Working with Claude 4 and o3 recently shows me just how fundamentally LLMs haven't really solved the core problems such as hallucinations and weird refactors/patterns to force success (i.e. if account not found, fallback to account id 1).
• kristopolous 1y ago
  Correct. LLMs are a thought management tech. Stupider ones are fine because they're organizing tools with a larger library of knowledge. Think about it and tell me you use it differently.
• some-guy 1y ago
  The main thing LLMs have helped me with, and always comes back to, tasks that require bootstrapping / Googling: 1) Starting simple codebases 2) Googling syntax 3) Writing bash scripts that utilize Unix commands whose arguments I have never bothered to learn in the first place. I definitely find time savings with these, but the esoteric knowledge required to work on a 10+ year old codebase is simply too much for LLMs still, and the code alone doesn't provide enough context to do anything meaningful, or even faster than I would be able to do myself.
  • mywittyname 1y ago
    LLMs are amazing at shell scripting. It's one of those tasks where I always half-ass it because I don't really know how to properly handle errors and never really learned the correct way. But man, perplexity and poop out a basic shell script in a few seconds with pretty much every edge case I can think of covered.
    • tcoff91 1y ago
      It really is the thing they are best at.
• am17an 1y ago
  All the world's smartest minds are racing towards replacing themselves. As programmers, we should take note and see where the wind is blowing. At least don't discard the possibility and rather be prepared for the future. Not to sound like a tin-foil hat but odds of achieving something like this increase by the day. In the long term (post AGI), the only safe white-collar jobs would be those built on data which is not public i.e. extremely proprietary (e.g. Defense, Finance) and even those will rely heavily on customized AIs.
  • bgwalter 1y ago
    The Nobel prize is said to have been created partly out of guilt over having invented dynamite, which was obviously used in a destructive manner. Now we have Geoffrey Hinton getting the prize for contributing to one of the most destructive inventions ever.
    • reducesuffering 1y ago
      At least he and Yoshua Bengio are remorseful. Many others haven't even gotten that far...
  • AstroBen 1y ago
    Ultimately this needs to be solved politically Making our work more efficient, or humans redundant should be really exciting. It's not set in stone that we need to leave people middle aged with families and now completely unable to earn enough to provide a good life Hopefully if it happens, it happens to such a huge amount of people that it forces a change
    • lyu07282 1y ago
      But that already happened to lots of industries and lots of people, we never cared before about them, now it's us so we care, but nothing is different about us. Just learn to code!
      • AstroBen 1y ago
• agumonkey 1y ago
  There's also the subset of devs who are just bored, LLMs will end up as an easier StackOverflow and if the solution is not one script away, then you're back to square one. I already had a few of "well, uhm, chatGPT told me what you said basically".
• UncleOxidant 1y ago
  There's some whistling past the graveyard in these comments. "You still need humans for the social element...", "LLMs are bad at debugging", "LLMs lead you astray". And yeah, there's lots of truth in those assertions, but since I started playing with LLMs to generate code a couple of years ago they've made huge strides. I suspect that over the next couple of years the improvements won't be quite as large (Pareto Principle), but I do expect we'll still see some improvement. Was on r/fpga recently and mentioned that I had had a lot of success recently in getting LLMs to code up first-cut testbenches that allow you to simulate your FPGA/HDL design a lot quicker than if you were to write those testbenches yourself and my comment was met with lots of derision. But they hadn't even given it a try to form their conclusion that it just couldn't work.
  • bgwalter 1y ago
    Yet you are working on your own replacement, while your colleagues are taking the prudent approach.
    • nialse 1y ago
      Ahh, the “don’t disturb the status quo” argument. See, we are all working on our replacement, newer versions, products, services and knowledge always make the older obsolete. It is wise to work on your replacement, and even wiser to be in charge of and operate the replacement.
      • bgwalter 1y ago
        No, nothing fundamentally new is created. Programmers have always been obsessed with "new" tooling and processes to distract from that fact. "AI" is the latest iteration of snake oil that is foisted upon us by management. The problem is not "AI" per se, but the amount of of friction and productivity loss that comes with it. Most of the productivity loss comes from being forced to engage with it and push back against that nonsense. One has to learn the hype language, debunk it, etc. Why do you think IT has gotten better? Amazon had a better and faster website with far better search and products 20 years ago. No amount of "AI" will fix that.
• palavrov 1y ago
  From my experience AI for coders is multiplier of the coder skills. It will allow you to faster solve problems or add bugs. But so far will not make you a better coder than you are.
• AlotOfReading 1y ago
  Unrelated to the LLM discussion, but a hash function function is the wrong construction for the accumulator solution. The hashing part increases the probability that A and B have a collision that leads to a false negative here. Instead, you want a random invertible mapping, which guarantees that no two pointers will "hash" to the same value, while distributing the bits. Splitmix64 is a nice one, and I believe the murmurhash3 finalizer is invertible, as well as some of the xorshift RNGs if you avoid the degenerate zero cycle.
  • antirez 1y ago
    Any Feistel Network has the property you stated actually, and this was one of the approaches I was thinking using as I can have the seed as part of the non linear transformation of the Feistel Network. However I'm not sure that this actually decreases the probability of A xor B xor C xor D being accidentally zero, bacause the problem with pointers is that they may change only for a small part. When you using hashing because of avalanche effect this is going a lot harder since you are no longer xoring the pointer structure. What I mean is that you are right assuming we use a transformation that still while revertible has avalanche effect. Btw in practical terms I doubt there are practical differences.
    • AlotOfReading 1y ago
      You can guarantee that the probability is the theoretical minimum with a bijection. I think that would be 2^-N since it's just the case where everything's on a maximum length cycle, but I haven't thought about it hard enough to be completely certain. A good hash function intentionally won't hit that level, but it should be close enough not to matter with 64 bit pointers. 32 bits is small enough that I'd have concerns at scale.
• jonator 1y ago
  I think will will increasingly be orchestrators. Like at a symphony. Previously, most humans were required to be on the floor playing the individual instruments, but now, with AI, everyone can be their own composer.
• loudmax 1y ago
  Companies that leverage LLMs and AIs to let their employees be more productive will thrive. Companies that try to replace their employees with LLMs and AIs will fail. Unfortunately, all that's in the long run. In the near term, some CEOs and management teams will profit from the short term valuations as they squander their companies' future growth on short-sighted staff cuts.
  • janalsncm 1y ago
    Very well said. Using code assistance is going to be table stakes moving forward, not something that can replace people. It’s not like competitors can’t also purchase AI subscriptions.
    • bbarn 1y ago
      Honestly, if you're not doing it now, you're behind. The sheer amount of time savings using it smartly can give you to allow you to focus on the parts that actually matter is massive.
      • kweingar 1y ago
        If progress continues at the rate that AI boosters expect, then soon you won't have to use them smartly to get value (all existing workflows will churn and be replaced by newer, smarter workflows within months), and everybody who is behind will immediately catch up the moment they start to use the tool.
        • abletonlive 1y ago
          But if it doesn't and you're not using it now then you're gonna be behind and part of the group getting laid off the people that are good at using these tools now will be better at it later too. you might have closed the gap quite a bit but you will still be behind using LLMs are they are now requires a certain type of mindset that takes practice to maintain and sharpen. It's just like a competitive game. The more intentionally do it, the better you get. And the meta changes every 6 months to a year. That's why I scroll and laugh through all the comments on this thread dismissing it, because I know that the people dismissing it are the problem. the interface is a chatbox with no instructions or guardrails. the fact that folks think that their experience is universal is hilarious. so much of using LLM right now is context management. I can't take most of yall in this thread seriously
• prmph 1y ago
  There's something fundamental here. There is a principle (I forget where I encountered it) that it is not code itself that is valuable, but the knowledge of a specific domain that an engineering team develops as they tackle a project. So code itself is a liability, but the domain knowledge is what is valuable. This makes sense to me and matched my long experience with software projects. So, if we are entrusting coding to LLMs, how will that value develop? And if we want to use LLMs but at the same time develop the domain acumen, that means we would have to architects things and hand them over to LLMs to implement, thoroughly check what they produce, and generally guide them carefully. In that case they are not saving much time.
  • jonator 1y ago
    I believe it will raise the standard of what is valuable. Now that LLMs can now handle what we consider "mundane" parts of building a project (boilerplate), humans can dedicate focused efforts to the higher impact areas of innovation and problem solving. As LLMs get better, this bar simply continues to rise.
• ntonozzi 1y ago
  If you care that much about having correct data you could just do a SHA-256 of the whole thing. Or an HMAC. It would probably be really fast. If you don’t care much you can just do murmur hash of the serialized data. You don’t really need to verify data structure properties if you know the serialized data is correct.
• janalsncm 1y ago
  Software engineering is in the painful position of needing to explain the value of their job to management. It sucks because now we need to pull out these anecdotes of solving difficult bugs, with the implication that AI can’t handle it. We have never been good at confronting the follies of management. The Leetcode interview process is idiotic but we go along with it. Ironically LC was one of the first victims of AI, but this is even more of an issue for management that things SWEs solve Leetcodes all day. Ultimately I believe this is something that will take a cycle for business to figure out by failing. When businesses will figure out that 10 good engineers + AI always beats 5 + AI, it will become table stakes rather than something that replaces people. Your competitor who didn’t just fire a ton of SWEs? Turns out they can pay for Cursor subscriptions too, and now they are moving faster than you.
• zonethundery 1y ago
  No doubt the headline's claim is true, but Claude just wrote a working MCP serving up the last 10 years of my employer's work product. For $13 in api credits. While technically capable of building it on my own, development is not my day job and there are enough dumb parts of the problem my p(success) hand-writing it would have been abysmal. With rose-tinted glasses on, maybe LLM's exponentially expand the amount of software written and the net societal benefit of technology.
  • procaryote 1y ago
    If your own code would have been abysmal, how can you tell if the claude generated code is any good?
• headelf 1y ago
  What do you mean "Still"? We've only had LLMs writing code for 1.5 years... at this rate it won't be long.
  • cess11 1y ago
    More like five years. It's been around for much longer than a lot of people feel it has for some reason.
• nixpulvis 1y ago
  The number one use case for AI for me as a programmer is still help finding functions which are named something I didn't expect as I'm learning a new language/framework/library. Doing the actual thinking is generally not the part I need too much help with. Though it can replace googling info in domains I'm less familiar with. The thing is, I don't trust the results as much and end up needing to verify it anyways. If anything AI has made this harder, since I feel searching the web for authoritative, expert information has become harder as of late.
  • taormina 1y ago
    My problem with this usage is that the LLMs seem equally likely to make up a function they wish existed. When questioned about the seeming-too-convenient method they will usually admit to having made it up on the spot. (This happens a lot in Flutter/Flame land, I'm sure it's better at something more mainstream like Python?) That being said, I do agree that using it as supplemental documentation is one of the better usecases I have for it.
• foobarian 1y ago
  I find LLMs a fantastic frontend to StackOverflow. But agree with OP it's not an apples-to-apples replacement for the human agent.
• 3cats-in-a-coat 1y ago
  "Better" is relative to context. It's a multi-dimensional metric flattened to a single comparison. And humans don't always win that comparison. LLMs are faster, and when the task can be synthetically tested for correctness, and you can build up to it heuristically, humans can't compete. I can't spit out a full game in 5 minutes, can you? LLMs are also cheaper. LLMs are also obedient and don't get sick, and don't sleep. Humans are still better by other criteria. But none of this matters. All disruptions start from the low end, and climb from there. The climbing is rapid and unstoppable.
• dbacar 1y ago
  I disagree—'human coders' is a broad and overly general term. Sure, Antirez might believe he's better than AI when it comes to coding Redis internals , but across the broader programming landscape—spanning hundreds of languages, paradigms, and techniques—I'm confident AI has the upper hand.
  • EpicEng 1y ago
    What does the number of buzzwords and frameworks on a resume matter? Engineering is so much more than that it’s not even worth mentioning. You’re comparison is on the easiest aspect of what we do. Unless you’re a web dev. Then youre right and will be replaced soon enough. Guess why.
    • dbacar 1y ago
      Not everyone builds Redis at home/work. So you do the math. And now Antirez himself is feeding the beast by himself.
  • nthingtohide 1y ago
    Do you want to measure antirez and AI on a spider diagram, generally used to evaluate employee? Are you ignoring why society opted for division of work and specialization?
    • dbacar 1y ago
      They are not investing billions on it so a high schooler can do his term paper on it, is is already much more than a generalist. It might be like a very good sidekick for now, but that is not the plan.
• jbellis 1y ago
  But Human+Ai is far more productive than Human alone, and more fun, too. I think antirez would agree, or he wouldn't bother using Gemini. I built Brokk to maximize the ability of humans to effectively supervise their AI minions. Not a VS code plugin, we need something new. https://brokk.ai https://brokk.ai
• callamdelaney 1y ago
  LLMs will never be better than humans on the basis that LLMs are just a shitty copy of human code.
  • danielbln 1y ago
    I think they can be an excellent copy of human code. Are they great at novel out-of-training-distribution tasks? Definitely not, they suck at them. Yet I'd argue that most problems aren't novel, at most they are some recombination of prior problems.
• elzbardico 1y ago
  I use LLMs a lot, and call me arrogant, but every time I see a developer saying that LLMs will substitute them, I think they are probably shitty developers.
  • Fernicia 1y ago
    If it automates 1/5th of your work, then what's unreasonable about thinking that your team could be 4 developers instead of 5?
    • archagon 1y ago
      This just feels like another form of the mythical man month argument.
    • AstroBen 1y ago
      If software costs 80% as much to write, what's unreasonable about thinking that more businesses would integrate more of it, hiring more developers?
      • aschobel 1y ago
        Bingo. This additional throughput could be used to create more polished software. What happens in a free market; would your competitor fall behind or will they try to match your polish?
      • Fernicia 1y ago
        I think both will happen. I was merely demonstrating that just because an AI can't replace the entirety of your work, doesn't mean it won't make you redundant.
    • elzbardico 1y ago
      Because I've never seen a time saver in software development not being used to write even more software than what should be allowed by the time saving itself. So, yes, it could happen, I foresee a steep road ahead for junior developers, but if history can serve as a guide, LLMs coding will more likely lead to MORE CODE, not LESS CODERS in general.
• kurofune 1y ago
  The fact that we are debating this topic at all is indicative of how far LLMs have come in such a short time. I find them incredibly useful tools that vastly enhance my productivity and curiosity, and I'm really grateful for them.
• DrJid 1y ago
  I never quite understand these articles though. It's not about Humans vs. AI. It's about Humans vs. Humans+AI and 4/5, Humans+AI > Humans.
• zb3 1y ago
  Speak for yourself..
• AstroBen 1y ago
  Better than LLMs.. for now. I'm endlessly critical of the AI hype but the truth here is that no-one has any idea what's going to happen 3-10 years from now. It's a very quickly changing space with a lot of really smart people working on it. We've seen the potential Maybe LLMs completely trivialize all coding. The potential for this is there Maybe progress slows to a snails pace, the VC money runs out and companies massively raise prices making it not worth it to use No one knows. Just sit back and enjoy the ride. Maybe save some money just in case
• acquisitionsilk 1y ago
  It is quite heartening to see so many people care about "good code". I fear it will make no difference. The problem is that the software world got eaten up by the business world many years ago. I'm not sure at what point exactly, or if the writing was already on the wall when Bill Gates' wrote his open letter to hobbyists in 1976. The question is whether shareholders and managers will accept less good code. I don't see how it would be logical to expect anything else, as long as profit lines go up why would they care. Short of some sort of cultural pushback from developers or users, we're cooked, as the youth say.
  • JackSlateur 1y ago
    Code is meant to power your business Bad code leads to bad business This makes me think of hosting departement; You know, which people who are using vmware, physical firewalls, dpi proxies and whatnot; On the other edge, you have public cloud providers, which are using qemu, netfilter, dumb networking devices and stuff Who got eaten by whom, nobody could have guessed ..
    • chii 1y ago
      > Bad code leads to bad business Bad business leads to bad business. Bad code might be bad, or might be sufficient. It's situational. And by looking at what exists today, majority of code is pretty bad already - and not all businesses with bad code lead to bad businesses. In fact, some bad code are very profitable for some businesses (ask any SAP integrator).
      • tcoff91 1y ago
        The vast majority of code that makes money is pretty shitty.
      • JackSlateur 1y ago
        It is the survivor bias: "by looking at what is still alive today, majority of code is pretty bad" It eludes all of those who died in the process : those still alives are here despite bad IT, not due to a bad IT
• 65 1y ago
  AI is good for people who have given up, who don't give a shit about anything anymore. You know, those who don't care about learning and solving problems, gaining real experience they can use to solve problems even faster in the future, faster than any AI slop.
• fspoto98 1y ago
  Yes i agree:D
• orangebread 1y ago
  It's that time again where a dev writes a blog post coping.
• ModernMech 1y ago
  The other day an LLM told me that in Python, you have to name your files the same as the class name, and that you can only have one class per file. So... yeah, let's replace the entire dev team with LLMs, what could go wrong?
• anjc 1y ago
  Gemini gives instant, adaptive, expert solutions to an esoteric and complex problem, and commenters here are still likening LLMs to junior coders. Glad to see the author acknowledges their usefulness and limitations so far.
• deleted 1y ago
  [deleted]
• hackernewshomos 1y ago
  [flagged]
• Poortold 1y ago
  For coding playwright automation it has use cases. Especially if you template out function patterns. Though I never use it to write logic as AI is just ass at that. If I wanted a shitty if else chain I'd ask the intern to code it
• marcosno 1y ago
  LLMs can be very creative, when pushed. In order to find a creative solution, like antirez needed, there are several tricks I use: Increase the temperature of the LLMs. Ask several LLMs, each several time the same question, with tiny variations. Then collect all answers, and do a second/third round asking each LLM to review all collected answers and improve. Add random constraints, one constraints per question. For example, to LLM: can you do this with 1 bit per X. Do this in O(n). Do this using linked lists only. Do this with only 1k memory. Do this while splitting the task to 1000 parallel threads, etc. This usually kicks the LLM out of its confort zone, into creative solutions.
  • dwringer 1y ago
    Definitely a lot to be said for these ideas, even just that it helps to start a fresh chat and ask the same question in a better way a few times (using the quality of response to gauge what might be "better"). I have found if I do this a few times and Gemini strikes out, I've manually optimized the question by this point that I can drop it into Claude and get a good working solution. Conversely, having a discussion with the LLM about the potential solution, letting it hold on to the context as described in TFA, has in my experience caused the models to pretty universally end up stuck in a rut sooner or later and become counterproductive to work with. Not to mention that way eats up a ton of api usage allotment.
• bouncycastle 1y ago
  Last night I spent hours fighting o3. I never made a Dockerfile in my life, so I thought it would be faster just getting o3 to point to the GitHub repo and let it figure out, rather than me reading the docs and building it myself. I spent hours debugging the file it gave me... It kept on adding hallucinations for things that didn't exist, and removing/rewriting other parts, and other big mistakes like understanding the difference between python3 and python and the intricacies with that. Finally I gave up and Googled some docs instead. Fixed my file in minutes and was able to jump into the container and debug the rest of the issues. AI is great, but it's not a tool to end all. You still need someone who is awake at the wheel.
  • throwaway314155 1y ago
    Pro-tip: Check out Claude or Gemini. They hallucinate far less on coding tasks. Alternatively, enable internet search on o3 which boosts its ability to reference online documentation and real world usage examples. I get having a bad taste in your mouth but these tools _aren't _ magic and do have something of a steep learning curve in order to get the most out of them. Not dissimilar from vim/emacs (or lots of dev tooling). edit: To answer a reply (hn has annoyingly limited my ability to make new comments) yes, internet search is always available to ChatGpT as a tool. Explicitly clicking the globe icon will encourage the model to use it more often, however.
    • Sohcahtoa82 1y ago
      > enable internet search on o3 I didn't know it could even be disabled. It must be enabled by default, right?
      • throwaway314155 1y ago
        You're correct. Tapping the globe icon encourages the model to use it more often.
  • halpow 1y ago
    They're great at one-shotting verbose code, but if they're generate bad code the first time you're out of luck. I don’t think I ever got to write "this api doesn't exist" and then gotten a useful alternative. Claude is the only one that regularly tells me something isn't possible rather than making sh up.
• gxs 1y ago
  Argh people are insufferable about this subject This stuff is still in its infancy, of course its not perfect But its already USEFUL and it CAN do a lot of stuff - just not all types of stuff and it still can mess up the stuff that it can do It's that simple The point is that overtime it'll get better and better Reminds me of self driving cars and or even just general automation back in the day - the complaint has always been that a human could do it better and at some point those people just went away because it stopped being true Another example is automated mail sorting by the post office. The gripe was always humans will always be able to do it better - true, in the meantime the post office reduced the facilities with humans that did this to just one
• bachmeier 1y ago
  I suspect humans will always be critical to programming. Improved technology won't matter if the economics isn't there. LLMs are great as assistants. Just today, Copilot told me it's there to do the "tedious and repetitive" parts so I can focus my energy on the "interesting" parts. That's great. They do the things every programmer hates having to do. I'm more productive in the best possible way. But ask it to do too much and it'll return error-ridden garbage filled with hallucinations, or just never finish the task. The economic case for further gains has diminished greatly while the cost of those gains rises. Automation killed tons of manufacturing jobs, and we're seeing something similar in programming, but keep in mind that the number of people still working in manufacturing is 60% of the peak, and those jobs are much better than the ones in the 1960s and 1970s.
  • noslenwerdna 1y ago
    Sure, it's just that the era of super high paying programming jobs may be over. And also, manufacturing jobs have greatly changed. And the effect is not even, I imagine. Some types of manufacturing jobs are just gone.
    • bachmeier 1y ago
      > the era of super high paying programming jobs may be over. Probably, but I'm not sure that had much to do with AI. > Some types of manufacturing jobs are just gone The manufacturing work that was automated is not exactly the kind of work people want to do. I briefly did some of that work. Briefly because it was truly awful.
    • monocularvision 1y ago
      That might be the case. Perhaps it lowers the difficulty level so more people can do it and therefor puts downward pressure on wages. Or… it still requires similar education and experience but programmers end up so much more efficient they earn _more_. Hard to say right now.
• failrate 1y ago
  LLMs are using the corpus of existing software source code. Most software source code is just North of unworkable garbage. Garbage in, garbage out.
• tonyhart7 1y ago
  I think also it depends on the model of course General LLM model would not be as good as LLM for coding, for this case Google deepmind team maybe has something better than Gemini 2.5 pro
• frogperson 1y ago
  The context required to write real software is just way too big for LLMs. Software is the business, codified. How is an LLM supposed to know about all the rules in all the departments plus all the special agreements promised to customers by the sales team? Right now the scope of what an LLM can solve is pretty generic and focused. Anytime more than a class or two is involved or if the code base is more than 20 or 30 files, then even the best LLMs start to stray and lose focus. They can't seem to keep a train of thought which leads to churning way too much code. If LLMs are going to replace real developers, they will need to accept significantly more context, they will need a way to gather context from the business at large, and some way to persist a train of thought across the life of a codebase. I'll start to get nervous when these problems are close to being solved.
  • zachlatta 1y ago
    I’d encourage you to try the 1M context window on Gemini 2.5 Pro. It’s pretty remarkable. I paste in the entire codebase for my small ETL project (100k tokens) and it’s pretty good. Not perfect, still a long ways to go, but a sign of the times to come.
    • karn97 1y ago
      [flagged]
      • zachlatta 1y ago
        Yes… I did?
        • nssnsjsjsjs 1y ago
          I think by context they meant context as in common usage not context window size.
          • stevenhuang 1y ago
            They know that, and they mean it to be the same thing, because all relevant context can be placed into the context window.
• galaxyLogic 1y ago
  Coding is not like multiplication. You can teach kids the multiplication table, or you can give them a calculator and both will work. With coding the problem is the "spec" is so much more complicated than just asking what is 5 * 7. Maybe the way forward would be to invent better "specifiction languages" that are easy enough for humans to use, then let the AI implement the specifciation you come up with.
• bdbenton5255 1y ago
  The human ability to design computer programs through abstractions and solve creative problems like these is arguably more important than being able to crank out lines of code that perform specific tasks. The programmer is an architect of logic and computers translate human modes of thought into instructions. These tools can imitate humans and produce code given certain tasks, typically by scraping existing code, but they can't replace that abstract level of human thought to design and build in the same way. When these models are given greater functionality to not only output code but to build out entire projects given specifications, then the role of the human programmer must evolve.
• CivBase 1y ago
  In my experience some of the hardest parts of software development is figuring out exactly what the stakeholder actually needs. One of the talents a developer needs is the ability to pry for that information. Chatbots simply don't do that, which I imagine has a significant impact on the usability of their output.
• twodave 1y ago
  If you stick with the same software ecosystem long enough you will collect (and improve upon) ways of solving classes of problems. These are things you can more or less reproduce without thinking too much or else build libraries around. An LLM may or may not become superior at this sort of exercise at some point, and might or might not be able to reliably save me some time typing. But these are already the boring things about programming. So much of it is exploratory, deciding how to solve a problem from a high level, in an understandable way that actually helps the person who it’s intended to help and fits within their constraints. Will an LLM one day be able to do all of that? And how much will it cost to compute? These are the questions we don’t know the answer to yet.
• buremba 1y ago
  If the human here is the creator of Redis, probably not.
• ants_everywhere 1y ago
  I'm increasingly seeing this as a political rather than technical take. At this point I think people who don't see the value in AI are willfully pulling the wool over their own eyes.
• fHr 1y ago
  yes of course they are but MBA regard management gets told by McK/Big4 AI could save them millions and they should let go people already as AI can do there work it doesn't matter currently, see job market
• devmor 1y ago
  I have been evaluating LLMs for coding use in and out of a professional context. I’m forbidden to discuss the specifics regarding the clients/employers I’ve used them with due to NDAs, but my experience has been mostly the same as my private use - that they are marginally useful for less than one half of simple problem scenarios, and I have yet to find one that has been useful for any complex problem scenarios. Neither of these issues is particularly damning on its own, as improvements to the technology could change this. However, the reason I have chosen to avoid them is unlikely to change; that they actively and rapidly reduce my own willingness for critical thinking. It’s not something I noticed immediately, but once Microsoft’s study showing the same conclusions came out, I evaluated some LLM programming tools again and found that I generally had a more difficult time thinking through problems during a session in which I attempted to rely on said tools.
• ww520 1y ago
  The value of LLMs are as a better Stackoverflow. It’s much better than search now because it’s not populated with all the craps that have seeped through over time.
• SKILNER 1y ago
  There's a lot of resistance to AI amongst the people in this discussion, which is probably to be expected. A chunk of the objections indicate people trying to shoehorn in their old way of thinking and working. I think you have to experiment and develop some new approaches to remove the friction and get the benefit.
  • bluefirebrand 1y ago
    > I think you have to experiment and develop some new approaches to remove the friction and get the benefit. What benefit to me? If I'm 50% more productive using AI that's great for my employer, but what do I get out of it? I get to continue to be employed? I already had that before AI So what do I get out of this, exactly?
    • SKILNER 1y ago
      You get to keep your job instead of being replaced by someone willing to use the latest tools.
• ChrisMarshallNY 1y ago
  Really good coders (like him) are better. Mediocre ones … maybe not so much. When I worked for a Japanese optical company, we had a Japanese engineer, who was a whiz. I remember him coming over from Japan, and fixing some really hairy communication bus issues. He actually quit the company, a bit after that, at a very young age, and was hired back as a contractor; which was unheard of, in those days. He was still working for them, as a remote contractor, at least 25 years later. He was always on the “tiger teams.” He did awesome assembly. I remember when the PowerPC came out, and “Assembly Considered Harmful,” was the conventional wisdom, because of pipelining, out-of-order instructions, and precaching, and all that. His assembly consistently blew the doors off anything the compiler did. Like, by orders of magnitude.
  • benstein 1y ago
    +1000. "Human coders are still better than LLMs" is a hot take. "Antirez is still better than LLMs" is axiomatic ;-)
• throwaway439080 1y ago
  Of course they are. The interesting thing isn't how good LLMs are today, it's their astonishing rate of improvement. LLMs are a lot better than they were a year ago, and light years ahead of where they were two years ago. Where will they be in five years?
  • hiatus 1y ago
    Reminds me of the 90s when computer hardware moved so fast. I wonder where the limit is this time around.
• Klaus_ 1y ago
  [dead]
• rubit_xxx17 1y ago
  Gemini may be fine for writing complex function, but I can’t stand to use it day to day. Claude 4 is my go to atm.
• horns4lyfe 1y ago
  Writing about AI is missing the forest for the trees. The US software industry will be wholesale destroyed (and therefore global software will be too) by offshoring.
• hello_computer 1y ago
  Corporations have many constraints—advertisers, investors, employees, legislators, journalists, advocacy groups. So many “white lies” are baked into these models to accommodate those constraints, nerfing the model. It is only a matter of time before hardware brings this down to the hobbyist level—without those constraints—giving the present methods their first fair fight; while for now, they are born lobotomized. Some of the “but, but, but…”s we see here daily to justify our jobs are not going to hold up to a non-lobotomized LLM.
• osigurdson 1y ago
  This is similar to my usage of LLMs. I use Windsurf sometimes but more often it is more of a conversation about approaches.
• codr7 1y ago
  I would say you thought about this solution because you are creative, something a computer will never be no matter how much data you throw at it. How did it help, really? By telling you your idea was no good? A less confident person might have given up because of the feedback. I just can't understand why people are so excited about having an algorithm guessing for them. Is it the thrill when it finally gets something right?
• shayanbahal 1y ago
  Human coders utilizing LLMs are better
• sagarpatil 1y ago
  So your sample size is 1 task and 1 LLM? I would recommend trying o3, opus 4 (API) with web search enabled.
• insane_dreamer 1y ago
  Coders may want to look at translators for an idea of what might happen. Translation software has been around for a couple of decades. It was pretty shitty. But about 10 years ago it started to get to the point where it could translate relatively accurately. However, it couldn't produce text that sounded like it was written by a human. A good translator (and there are plenty of bad ones) could easy outperform a machine. Their jobs were "safe". I speak several languages quite well and used to do freelance translation work. I noticed that as the software got better, you'd start to see companies who instead of paying you to translate wanted to pay you less to "edit" or "proofread" a document pre-translated by machine. I never accepted such work because sometimes it took almost as much work as translating it from scratch, and secondly, I didn't want to do work where the focus wasn't on quality. But I saw the software steadily improving, and this was before ChatGPT, and I realized the writing was on the wall. So I decided not to become dependent on that for an income stream, and moved away from it. When LLMs came out, and they now produce text that sounded like it was written by a native speaker (in major languages). Sure, it's not going to win any literary awards, but the vast vast majority of translation work out there is commercial, not literature. Several things have happened: 1) there's very little translation work available compared to before, because now you can pay only a few people to double-check machine-generated translations (that are fairly good to start with); 2) many companies aren't using humans at all as the translations are "good enough" and a few mistakes won't matter that much; 3) the work that is available is high-volume and uninteresting, no longer a creative challenge (which is why I did it in the first place); 4) downward pressure on translation rates (which are typically per word), and 5) very talented translators (who are more like writers/artists) are still in demand for literary works or highly creative work (i.e., major marketing campaign), so the top 1% translators still have their jobs. Also more niche language pairs for which LLMs aren't trained will be safe. It will continue to exist as a profession, but diminishing, until it'll eventually be a fraction of what it was 10 or 15 years ago. (This is specifically translating written documents, not live interpreting which isn't affected by this trend, or at least not much.)
  • 0points 1y ago
    > When LLMs came out, and they now produce text that sounded like it was written by a native speaker (in major languages). While the general syntax of the language seem to be somewhat correct now, the LLM's still don't know anything about those languages and keep mis-translating words due to its inherit insane design around english. A whole lot of concepts don't even exist in english so these translation oracles just can never do it successfully. If i i read a few minutes of LLM translated text, there's always a couple of such errors. I notice younger people don't see these errors because of their worse language skills, and the LLM:s enforce their incorrect understanding. I don't think this problem will go away as long as we keep pushing this inferior tech, but instead the languages will devolve to "fix" it. Languages will morph into a 1-to-1 mapping of english and all the cultural nuances will get lost to time.
• revskill 1y ago
  The funniest things a llm do to me is they fixed the unit test to pass instead of fixing the code. Basically until a llm can have embedded common sense knowledge, it is untrustable
• solatic 1y ago
  Human coders are necessary because writing code is a political act of deciding between different trade-offs. antirez's whole post is explaining to Gemini what the trade-offs even were in the first place. No analysis of a codebase in isolation (i.e. without talking to the original coders, and without comments in the code) can distinguish between intentional prioritization of certain trade-offs or whether behavior is unintentional / written by a human in an imperfect way because they didn't know any better / buggy. LLMs will never be able to figure out for themselves what your project's politics are and what trade-offs are supposed to be made. The penultimate model will still require a user to explain the trade-offs in a prompt.
  • energy123 1y ago
    > LLMs will never be able to figure out for themselves what your project's politics are and what trade-offs are supposed to be made. I wouldn't declare that unsolvable. The intentions of a project and how they fit into user needs can be largely inferred from the code and associated docs/README, combined with good world knowledge. If you're shown a codebase of a GPU kernel for ML, then as a human you instantly know the kinds of constraints and objectives that go into any decisions. I see no reason why an LLM couldn't also infer the same kind of meta-knowledge. Of course, this papers over the hard part of training the LLMs to actually do that properly, but I don't see why it's inherently impossible.
    • solatic 1y ago
      > associated docs/README Many (I would even argue most) professional codebases either do not have their documentation (including tutorials and architecture diagrams) in the codebase alongside the code, if there is even such formal documentation at all. It's axiomatic as well that documentation is frequently out-of-date, and in any case represents past political decisions, not future ones; human owners can and do change their minds about which trade-offs are required over the lifetime of a project. A simple case may be to plot codebase complexity against required scale; early projects benefit from simpler implementations that will not scale, and only after usage and demand are proven does it make sense to make the project more complex in order to support additional scale. So if you are an LLM looking at a codebase in isolation, do you make changes to add complexity to support additional scale? Do you simplify the codebase? Do you completely rewrite it in a different language (say, TypeScript -> Go or Rust)? How could an LLM possibly know which of these are appropriate without additional sources of telemetry at the very least and probably also needing to converse with stakeholders (i.e. bordering on AGI)?
• h4kunamata 1y ago
  This!!!! LLM is as good as the material it is being trained on, the same applies to AI and they are not perfect. Perplexity AI did assist me in getting into Python from 0 to getting my code test with 94% covered and no vulnerabilities (scanning tools) Google Gemini is dogshit Trusting blindly into a code generated by LLM/AI is a whole complete beast, and I am seeing developers doing basically copy/paste into company's code. People are using these sources as the truth and not as a complementary tool to improve their productivity.
• Corey_ 1y ago
  [dead]
• stabbles 1y ago
  The trick is much like Zobrist hashing from chess programming, I'm sure the llm has devoured chessprogramming.org during training.
• seabirdman 1y ago
  Super hard problems are often solved by making strange weird connections derived from deep experience plus luck. Like finding the one right key in a pile of keys. The intuition you used to solve your problem IS probably beyond current agents. But, that too will change perhaps by harnessing the penchant of these systems to “hallucinate”? Or, some method or separate algorithm for dealing with super hard problems creatively and systematically. Recently, I was working on a hard imaging problem (for me) and remembered a bug I had inadvertently introduced and fixed a few days earlier. I was like wait a minute - because in that random bug I saw opportunity and was able to actually use the bug to solve my problem. I went back to my agent and it agreed that there was virtually no way it could have ever seen and solved the problem in that way. But that too will come. Rest assured.
• austin-cheney 1y ago
  In many cases developers are a low expectation commodity. In those cases I strongly believe humans are entirely replaceable by AI and I am saying that as somebody with an exceptionally low opinion of LLMs. Honestly though, when that replacement comes there is no sympathy to be had. Many developers have brought this upon themselves. For roughly the 25 year period from 1995 to 2020 businesses have been trying to turn developers into mindless commodities that are straight forward to replace. Developers have overwhelmingly encouraged this and many still do. These are the people who hop employers every 2 years and cannot do their jobs without lying on their resumes or complete reliance on a favorite framework.
  • zxexz 1y ago
    I find myself wondering about your story, and would love it if you would elaborate more. I have gotten some use out of LLMs, and have been quite involved in training a few compute intensive (albeit domain-specific) ones. Maybe it's the way you talk about 'developers'. Nothing I have seen has felt like the sky falling on an industry; to me at most it's been the sky falling on a segment of silicon valley.
    • austin-cheney 1y ago
      It’s all about perspectives. In many cases the perspectives between how a developer identifies their level of participation versus what they actually do as a work activity differ substantially. For example many developers may refer to themselves as engineers when they have done nothing remotely close to measurements, research, or policy creation in compliance attainment. With that out of the way let’s look only at what many developers actually do. If a given developer only uses a framework to put text on screen or respond to a user interaction then they can be replaced. LLMs can already do this better than people. That becomes substantially more true after accounting for secondary concerns: security, accessibility, performance, regression, and more. If a developer is doing something more complex that accounts for systems analysis or human behavior then LLMs are completely insufficient.
  • ponector 1y ago
    But to job hop every 2 years is the best strategy to earn more money and experience.
• Quenby 1y ago
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• motorest 1y ago
  There is also another side to the mass adoption of LLMs in software engineering jobs: they can quite objectively worsen the output of human coders. There is a class of developers who are blindly dumping the output of LLMs into PRs without paying any attention to what they are doing, let alone review the changes. This is contributing to introducing accidental complexity in the form of bolting on convoluted solutions to simple problems and even introducing types in the domain model that make absolutely no sense to anyone who has a passing understanding of the problem domain. Of course they introduce regressions no one would ever do if they wrote things by hand and tested what they wrote. I know this, because I work with them. It's awful. These vibecoders force the rest of us to waste eve more time reviewing their PRs. They are huge PRs that touch half the project for even the smallest change, they build and pass automated tests, but they enshitify everything. In fact, the same LLMs used by these vibecoders start to struggle how to handle the project after these PRs are sneaked in. It's tiring and frustrating. I apologize for venting. It's just that in this past week I lost count of the number of times I had these vibecoders justifying shit changes going into their PRs as "but Copilot did this change", as if that makes them any good. I mean, a PR to refactor the interface of a service also sneaks in changes to the connection string, and they just push the change?
• gumbojuice 1y ago
  I like to use llm to produce code for known problems that I don't have memorized. I memorize really little and tend to spend time on reinventing algorithms or looking them up in documentation. Verifying is easy except the fee cases where the llm produces something really weird. But then fallback to docs or reinventing.
• unsupp0rted 1y ago
  - LLMs are going to make me a 100x more valuable coder? Of course they will, no doubt about it. - LLMs are going to be 100x more valuable than me and make me useless? I don't see it happening. Here's 3 ways I'm still better than them.
• kaycey2022 1y ago
  It doesn't matter. The hiring of cost center people like engineers depends on the capital cycle. Hiring peaked when money and finance was the cheapest. Now it's not anymore. In the absence of easy capital, hiring will plummet. Another factor is the capture of market sectors by Big Co. When buyers can only approach some for their products/services, the Big Co can drastically reduce quality and enshittify without hurting the bottom line much. This was the big revelation when Elon gutted Twitter. And so we are in for interesting times. On the plus side, it is easier than ever to create software and distribute it. Hiring doesn't matter if I can get some product sense and make some shit worth buying.
• pjmlp 1y ago
  Yes, we are still winning the game, however don't be happy for what is possible today, think what is possible in a decade from now. In that regard I am less optimistic.
  • anhner 1y ago
    I think we will hit a proverbial wall at some point just like with self-driving cars.
    • pjmlp 1y ago
      May be, yet it is working good enough for Waymo, and not so much for those losing their clients to them. Or for the supermarkets now able to have about half the employees they used to have as cashiers. Many times the wall is already disruption enough.
• estensen 1y ago
  Most of the work software engineers do is not fixing complicated bugs.
• deleted 1y ago
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• coldtea 1y ago
  >Gemini was quite impressed about the idea Like sex professionals, Gemini and co are made to be impressed and have possitive things to say about programming ideas you propose and find your questions "interesting", "deep", "great" and so.
  • _fat_santa 1y ago
    I would correct that quote to say “Gemini was trained to respond that it was impressed with my idea” Being “impressed” is a human feeling that can’t be transcribed to an AI period. An AI can tell you that it’s impressed because it’s been trained to do so, it doesn’t “know” (and by this I’m referring to knowing what the feeling is, not knowing the definition) what it means to be impressed
• xnx 1y ago
  ... depending on the human (and the LLM). Results may differ in 6 months.
• ashoeafoot 1y ago
  Human coders also hate the structures they are embedded in and are willing to call the replacement bluff ..
• StillBored 1y ago
  I think there is a common problem with a lot of these ML systems. The answers look perfectly correct to someone who isn't a domain expert. For example, I ask legal questions and it gives me fake case numbers I have no way to know are fake until I look them up. Same with the coding, I asked for a patch for a public project that has a custom !regex style match engine. It does an amazing job, cross referencing two different projects and hands me a very probable looking patch. I ask for a couple changes, one of which can't actually be done, but it creates some syntax that doesn't even compile because its using 'x' as a stand-in for the bits it doesn't have an answer for. In the end, I had to go spend a couple hours reading the documentation to understand the matching engine, and the final patch didn't look anything at all like the LLM generated code. Which is what seems to happen all the time, it is wonderful for spewing the boilerplate, the actual problem solving portions its like talking to someone who simply doesn't understand the problem and keeps giving you what it has, rather than what you want. OTOH, its fantastic for review/etc even though I tend to ignore many of the suggestions. Its like a grammar checker of old, it will point out you need a comma you missed, but half the time the suggestions are wrong.
• Snehil-Shah 1y ago
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• notyouraibot 1y ago
  So funny story, I tried using o3 for a relatively complex task yesterday, installing XCode iOS Simulator on an external SSD, it was my first time owning and using a macOS so I was truly lost, I followed everything it told me and by the end of the hour.. things got so bad that my machine couldn't even run normal basic node projects. I had to a proper fresh boot to get things working again. So yeah lesson learned.
• perrygeo 1y ago
  I'm wondering if this statement might be definitionally self-evident. In other words, the entire reason we write software is that it has value to ourselves and other humans - so we have to be involved in its specification. Computers do things faster, more accurately, and in some cases more creatively than human could. But in the end, what a computer produces is still for the benefit of humans and subject to all the human constraints. Aggregate human behavior determines if software is a success or not. If software is about meeting human demands, humans will always write its requirements, by definition. If we build another machine like LLMs, well the design of those LLMs is subject to human demands. There is no point at which we can demand perfection but not be involved in its definition.
• thegrim33 1y ago
  If LLMs really do eventually replace programmers in X years (I don't believe they will), I wouldn't even care in the slightest about losing my job, since we'd effectively have reached singularity state where computers can now do any task; humans would no longer be needed for anything. I couldn't care less about losing my job in that scenario, the world would be fundamentally changed forever. Would the concept of a job even still exist at that point?
• careful_ai 1y ago
  This post is a brilliant example of why human intuition still dominates when navigating ambiguity and crafting clever systems-level solutions. The XOR accumulator idea was smart—LLMs can help validate or iterate on such thoughts, but rarely originate them. In my experience working on enterprise app modernization, we’ve found success by keeping humans firmly in the loop. Tools like Project Analyzer (from Techolution’s AppMod.AI suite) assist engineers in identifying risky legacy code, mapping dependencies, and prioritizing refactors. But the judgment calls, architecture tweaks, and creative problem-solving? Still very much a human job. LLMs boost productivity, but it’s the developer's thinking that makes the outcome truly resilient. This story captures that balance perfectly.