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Coding expertise is going to collapse from AI reliance

• deepamt31 1mo ago
  [dead]
• GiorgioG 1mo ago
  I learned BASIC, Pascal and x86 Assembly language by the age of 14-15. None of which I remember (nor care to). The strict instructions (aka language) we gave the compiler was not the point. Those experiences taught me how to think logically, and over time develop a taste/structure for how software should be built, as well as foot guns to avoid. I don't know how you teach that without coding, but the "coding expertise" was always a means to an end. LLMs are just another abstraction layer above programming languages, machine language, etc.
  • larsfaye 1mo ago
    > I don't know how you teach that without coding That's the neat part: you don't! Even Robert "Uncle Bob" Martin, who's as AI pilled as they come and doesn't read code any longer, says that junior developers shouldn't even look at AI tooling for the first three years: https://www.youtube.com/watch?v=RxxxGkFIUJ0&t=1356s https://www.youtube.com/watch?v=RxxxGkFIUJ0&t=1356s
    • GiorgioG 1mo ago
      Robert Martin has caused me so much frustration over the years, but he's spot on. "Young people with power tools tend to lose fingers"...I like that!
  • alexjplant 1mo ago
    > LLMs are just another abstraction layer above programming languages, machine language, etc. Programming languages are (largely) deterministic. LLMs are not. The boundary between an abstract concept and something executable sits comfortably in the mind of the programmer in non-LLM contexts. This boundary shifts when using an LLM and becomes shared between the programmer and the matrix multiplication machine. The "layer of abstraction" analogy is therefore technically true but essentially false. "Just another" papers over how seismic of a paradigm shift all of this is.
    • GiorgioG 1mo ago
      Sure, you're right - at the end of the day, LLMs are non-deterministic code generators. I certainly wouldn't trust one for a medical device manufacturer's software. For line of business apps it's totally adequate. And to be clear, I don't love it. I'm just coming to terms with the fact that these LLMs have gotten good enough, that with enough instruction and guidance, they can generate code/features at speeds we can only dream of if we were to code them by hand.
  • nemomarx 1mo ago
    We don't teach kids math with access to calculators, and so on. Making students code by hand at first is a very moderate proposition
    • philote 1mo ago
      Yeah I was taught coding in a fake programming language so it couldn't be compiled or run. It really was "by hand" coding since we had written tests.
  • Zigurd 1mo ago
    In contrast with Pascal, I could see in my mind the PDP-11 instructions behind my C code. By the time I started running code on x86, there were debuggers that could step through source code, and I didn't really want to think like an i386.
• faislopids 1mo ago
  [flagged]
  • monkpit 1mo ago
    Not to mention the idea in the article has kinda been beaten to death
    • throwawayqqq11 1mo ago
      Not quite, but maybe some day, an AI company will succeed in cornering the market of competence to haul in their impossible returns.
  • wonnage 1mo ago
    It is difficult to get a man to understand something, when his salary depends on his not understanding it
• micromacrofoot 1mo ago
  Very few people know how to hand set typography anymore, but many of the conventions still exist and people don't have to understand the origin of a lot of them to use them properly.
• paul7986 1mo ago
  Are engineers still making 100s of thousands a year still just for vibe coding while a nurse and other skilled / highly trained medical professionals working their butt off make half of that? Do we think there is going to be a correction for the vibe coders? Pardon I know such question is controversial but thinking ahead.
  • swader999 1mo ago
    I'm solving harder and harder problems for real users/customers than I was a year ago and our sales are increasing as a result.
    • paul7986 1mo ago
      Are you saving lives?
      • ok_dad 1mo ago
        Is it my job to make sure that nurses are paid more than I am? I'll readily admit that they deserve it, I'm a lazy dickhead and they help people, but I think your blame is misplaced if you're insinuating that software engineers are to blame for nurses being paid less than ourselves.
        • deleted 1mo ago
          [deleted]
  • nemomarx 1mo ago
    There's something weird about nurse pay where it doesn't seem to raise even during large shortages of qualified nurses. I think it's artificially lowered by hospital admin, with temporary traveling nurses acting as "scabs" to avoid the normal wage increasing
    • Ekaros 1mo ago
      It is weird how it works with anyone there but the doctors... Do they have some type of cartel or mafia that nurses and other staff don't have?
• toenail 1mo ago
  And math skills are going to collapse from calculator reliance.
  • what 1mo ago
    They probably have though.
    • jckahn 1mo ago
      Seems like we're doing fine though, yeah?
      • larsfaye 1mo ago
        Could be a doing a whole lot better. Do you think there's an abundance of critical thinking in society? Because math skills aid in that.
        • r_lee 1mo ago
          I honestly can't tell what reward there is for this "critical thinking" since the entire world is bathing in "AI will replace you" what point is there to be a human calculator if nobody rewards you for it? and I'm not talking about wealthy Bay Area tech workers doing it so that they can write their substack blogs but rather the average person
          • esafak 1mo ago
            Getting to live in a civilized society with a responsible government. Witness the counterexample.
            • r_lee 1mo ago
              that's not something you can accomplish just by practicing critical thinking yourself, you'd need to convince a majority of the population to do the same. we can vent here but it's not gonna change things, a wider cultural shift is needed. and even then I don't see it guaranteeing a "responsible govermment", e.g. see PRC China for example
• vitalnodo 1mo ago
  Saw a quote comparing pre-LLM code to pre-WWII steel, low-background steel, essentially.
  • sixothree 1mo ago
    No matter how robust my code is and however many eventualities I considered, it certainly feels like AI can find and address issues.
    • dan_ggggg 1mo ago
      > it certainly feels like AI can find and address issues. LLM chatbots are good at making you feel good. Facts don't care about your feelings.
      • deleted 1mo ago
        [deleted]
• j45 1mo ago
  It may bifurcate the average skill from the skill of figuring out new solutions.
  • causal 1mo ago
    Yeah I'm not convinced people are just going to give up solving problems
    • j45 1mo ago
      It's possible a new kind of false belief might come up, but people thinking new ways aren't possible is nothing new at the same time.
• deaton 1mo ago
  Going to? It already is.
• add-sub-mul-div 1mo ago
  I'm also concerned about people asking an opaque machine for an answer and stopping there instead of going to different sources, evaluating their credibility, exercising their own ability to construct their own worldview from disparate facts and opinions.
  • dan_ggggg 1mo ago
    Flagged for the expressing the most obvious and legitimate concern about LLM-backed "research". "I use AI to generate a summary which I print out and read slowly every time I use a new codebase" is the new propaganda line pushed by Anthropic and OpenAI. They cannot tolerate this rebuttal.
• waffletower 1mo ago
  Coding expertise is going to collapse from compiler reliance (1985 Turbo Pascal detractors)
  • larsfaye 1mo ago
    Do you think LLMs and compilers have a lot of overlap?
    • sampullman 1mo ago
      In an abstract sense, yes. Compilers let programmers work at a higher level of abstraction. LLMs bring it to an even higher level, though the abstraction is much leakier. For the time being, a good understanding of programming and domain knowledge gets you much farther than without it. There might not be room for as many (professional) programmers as before, though.
    • Daishiman 1mo ago
      Almost nobody knows how to program in assembly but we're doing fine.
      • larsfaye 1mo ago
        That's because the institutional knowledge was passed along through the act of coding. Skills that I learned in Assembly and FORTRAN are applicable to even modern programming languages...but not to "natural language."
        • svachalek 1mo ago
          It really wasn't. Ask the average young coder these days how many registers their CPU has, or even the difference between the stack and the heap.
        • Daishiman 1mo ago
          I don't agree. Certain optimization skills are learned on the job if people work in specific areas of compilers or performance. Also the reality is that modern CPU microarchitectures are so different from what old-school assembly programmers used that their supposed optimizations are likely to be counterproductive.
• Zigurd 1mo ago
  Coders should be treated as as well as as other software users. Tools like Claude code, Antigravity, and others are applying AI to solving that problem. I know how to create a multi year P&L projection from scratch. It gives me some insight into how much capital a startup will need to get to breakeven. A good AI tool that creates that same spreadsheet in minutes should also be able to explain why different businesses have different shaped cash flow troughs. I don't think people using tools like that is bad even if they don't gain deep insight.
• rvz 1mo ago
  Ah yes. Selling courses is the oldest grift in town, which is what the author here is doing.
• randusername 1mo ago
  Does anyone else feel like the web has become so "readable" it is illegible? I have such a hard time quickly reading pages like TFA. Headings, bullets, line-spacing, width, link hover animations, even the font. Even reader mode defaults aren't great for me. Compared to, for example, https://www.paulgraham.com/best.html https://www.paulgraham.com/best.html
• chojeen 1mo ago
  I'm looking forward to having the same experience as COBOL engineers did after retirement: companies backing up the brinks truck to anyone with the skills to keep the lights on.
  • bigmattystyles 1mo ago
    It's like I said in another article, I've spent my life in C# and JavaScript. I'm a low-level programmer now, did even have to learn C or assembly.
  • xdavidliu 1mo ago
    > backing up the brinks truck now that's a phrase I have only heard in one other context: as an alleged quote from former Boston Celtics player Isaiah Thomas (who was really about 5'7 despite his official listed 5'9; yes, professional basketball player in NBA). This was around 2017 when he had just come off a career year and was soon due for a contract extension in the low 9 figures. He got injured and bounced around for a few years before eventually leaving the league, and never got that payday.
    • snapetom 1mo ago
      It’s commonly used in college sports where one school’s fan base argue for poaching a coach at another school. “Back up the Brinks truck” == throw money at him.
  • spogbiper 1mo ago
    that would be nice, but unfortunately I think the supply vs demand situation is quite different this time
    • shimman 1mo ago
      Yeah, every COBOL job paid pretty terrible relative to other types of work (like web dev). Sure there might be a dozen individuals making over $300k but most COBOL devs live in the deep south making less than $100k for their entire careers. Fine salary, but that line of work is severely limited and the salaries do not reflect how valuable that work is.
• ryandvm 1mo ago
  100% We're already seeing this at the enterprise level. Companies have dictates from leadership that "if you're writing code manually, you're doing it wrong." Okay, that kind of works for a while. We are indeed producing a shit-ton of code, but the reality is that engineers are pumping out code faster than the humans can understand and (honestly) review it. That sounds great until you realize that "hey Claude, read this Jira ticket and implement the feature in this code base" isn't really worth $200K/year. This is all complicated by the fact that we're also losing our grasp on reality from the other direction because we have leadership air dropping AI generated manifestos on the product owners and product owners having to use AI to transmute all that shit into 1,500 word Jira tickets that are 10% necessary feature work and 90% LLM boilerplate. So now you have software engineers whose job has changed radically to the point that the hardest part about being a software engineer is just filtering through AI generated artifacts from all directions just to try to get a feature out the door.
  • javcasas 1mo ago
    My job improved significantly since I managed to get into their (managers) thick skulls to tell Claude to not be verbose. I'm tired of 1200-word tickets for "put the totals in the automated emails".
  • ben_w 1mo ago
    > That sounds great until you realize that "hey Claude, read this Jira ticket and implement the feature in this code base" isn't really worth $200K/year. Nor even €50k/year. Two things are true: 1) The coding part of my career is over. LLMs are capable of doing everything I've ever been paid to *write*. 2) My actual job also included non-coding work: Does this attempted solution even work at all? Is this solving the right problem? Even if it's a valid solution to the right problem, is it the best solution given the time constraints? That last one, "given the time constraints", is a place where my experience is still useful. The AI is as lazy (or as optimised for fast wins) as the humans whose examples it was trained upon; but an LLM costs so little that the answer is always "do it right" rather than "do it fast". A lot of people don't know what "do it right" even looks like, having only ever known e.g. websites that take 5 seconds to load because of all the adverts and analytics, and never the world where machines with 1% of the CPU and no GPU at all could fit a fully playable first person shooter in the same memory footprint as that page. At least, I hope this "is a place where my experience is still useful"; I may just be telling myself a nice story, same as all the other people through history who have found themselves obsoleted when the automation came for them.
• VCFundedGenYer 1mo ago
  I'm seeing it happen in real time. I've seen several folks claim they "vibe-coded" something and upon review it's some seriously low quality garbage. Unfortunately it's just "functional enough" where it's encouraging the one who talked to the robot to continue thinking they can code for some reason. It is important to ensure that any LLM code is named and shamed.
  • dan_ggggg 1mo ago
    > It is important to ensure that any LLM code is named and shamed. You need to take it further. We need to shame and mock the people (read: delusional imbeciles) who think this is acceptable if we want it to stop. AI users need to fear for their careers and reputations if we want to get software development back on the right track.
    • svachalek 1mo ago
      The industry has always had niches where quality is really important, such as NASA where you install your product in a multi-billion-dollar, one-of-a-kind robot and launch it into space. However, for the most part all that matters is that it roughly does what it advertises to do and ships as quickly as possible. LLMs are ideally suited to the latter form of software and the need for humans to ever see or think about the code will drop to zero soon, if it hasn't already.
• LandoCalrissian 1mo ago
  The snake eating it's own tail for llm software development has really been met with a shoulder shrug whenever it gets brought up. At best you might have a small cohort of developers that don't cook their brains with AI and their reward for that appears to be having to review terrible AI code written by people who have cooked their brains. Completely unsustainable.
  • roblh 1mo ago
    Maybe I’m naive, or misguided, or something else, but I decided almost 2 years ago that I’m going to bank on not using LLMs to do my job. I still write code by hand everyday. I don’t use AI to write code or lookup docs, or anything else. I just figure that if we really, truly, indisputably hit the point of AI assisted coding being mandatory, I can learn it and get up to speed in a few weeks (or at worst a couple months), whereas uncooking my brain is way way more expensive and time consuming and difficult. We’ll see how it plays out, but so far I don’t feel left behind at all really.
    • chrismarlow9 1mo ago
      I would agree if companies did not have a vested interest in over complicating things and creating eco systems to sell certifications and offer a consulting arm aka FDE. Using AI to improve your coding is quick, as you say, but learning all the jargons and protocols and RFC specs so some single company can try to control the new "open source" world is what is going to take a while. All the weird little token and model nuances and stuff. I would say at least keep up with knowing the acronyms of you're not going to learn it directly.
      • dragandj 1mo ago
        Luckily, the jargon in the vibe coding space go away even sooner than it comes :)
    • Seattle3503 1mo ago
      Where do you work where there isn't pressure to use agents?
• causal 1mo ago
  So far I think I have learned far more from LLMs than I've lost to them. I forget some syntax, definitely. But I now reach for a much wider range of tools that I have become familiar with because of LLMs. So, partly agree, partly disagree.
  • lanstin 1mo ago
    Yeah, I have to say some of this deskilling argument sounds like Socrates complaining about the invention of writing ruining people's ability to truly own the text. I really don't mourn my lost assembly skills or my lost C skills. And I'm not missing the details of whatever web framework du jour my Claude is vibing for me on my extremely useful dataviz internal tools; and I have learned how to rein the agents in to not ruin my high-performance Go code and yet debug concurrency issues. Maybe coding qua coding is what some people find their summum bonum, but for me programming is instrumentive - to build real things in the world that do things to make something better. When I want pure virtuosity of intellectual construction, I read maths papers in arxiv. (Not to say that the current state of the art with LLMs merits borrowing money for a multi-trillion spend on hardware that will be obsolete in 5 years, but for me that is a different issue). The master decrying the invention that resulted in more wisdom for more people than anything prior: "For this invention will produce forgetfulness in the minds of those who learn to use it, because they will not practice their memory. Their trust in writing, produced by external characters which are no part of themselves, will discourage the use of their own memory within them. You have invented an elixir not of memory, but of reminding; and you offer your pupils the appearance of wisdom, not true wisdom, for they will read many things without instruction and will therefore seem [275b] to know many things, when they are for the most part ignorant and hard to get along with, since they are not wise, but only appear wise." (quoting from https://www.historyofinformation.com/detail.php?id=3439 https://www.historyofinformation.com/detail.php?id=3439)
    • causal 1mo ago
      Yeah. Thought in Socrates' defense I think the jury is still out on writing, in the scale of human existence it's still very new. Give it a hundred thousand years or so.
• sleepgummies 1mo ago
  [dead]
• xyzelement 1mo ago
  // The need for ongoing friction in long-term skill formation. The subtitle of the story tells it all. There are some people who seek out friction. Think about an athlete or a hardcore nerd. The best engineers are ones who were fascinated with computers and learning as kids and persued it at every opportunity. Found their own friction in other words. For those kinds of people, friction-seeking is the constant and what LLMs did is moved the point of where the friction occurs. For example - the best engineers I've worked with didn't necessarily have lots of experience coding in assembly because that kind of friction was no longer necessary. But they could solve hard problems (and if a problem really required assembly they could go learn it) What I think will be hit much harder by AI is the low tier engineer. Someone who was never truly curious and committed to it, for whom it was just a job. For example a typical offshore ticket pusher kind of person. That kind of person never went out to find friction and that's the kind of thing that's never going to fly again - if I want mediocre or average, the LLMs are sufficient
  • hypfer 1mo ago
    I mean if you think about it, that sounds like a miserable existence to begin with. I would not rule out that some people will use this.. uh.. disruption, to start pursuing something that actually brings them joy. Of course, bills need to be paid and it's not all that simple. But at least there might be such a silver lining.
  • massagedpelican 1mo ago
    I think this expresses what I've been trying to form in my mind. I've been trying to map the LLM advancements and the current state of software development onto prior technological improvements. History is littered with similar cases where the abstraction layer ends up getting lifted, and people struggle with getting accustomed to working at that higher abstraction level. For the people that fall in love with a single abstraction layer or don't have an interest in learning new paradigms, when their known pattern is abstracted away, they're condemned to being left behind, either unwilling or unable to adapt. I don't think any industry is free from this, any person in any industry/profession over a period of 20 years or more has likely had to undergo massive adjustments as technology changed their field. We're not unique, but that doesn't stop it from feeling so jarring when it happens to us
• fechols 1mo ago
  "Assembly expertise is going to collapse from compiler reliance".
  • yoyohello13 1mo ago
    Did this not happen?
    • MattDamonSpace 1mo ago
      It did, it’s just a question of “would it have been worth preventing compiler adoption/usage to attempt to preserve assembly knowledge”
• aledevv 1mo ago
  I strongly agree with the concept that cognitive friction is the engine of learning. First and foremost, it's an issue of "dependency": if you stop training the "muscle" of logic and reasoning, it gradually atrophies, just like unused physical muscles. You become dependent on external tools that replace a capability you once had yourself. A historical example that brought about a similar shift is this: when the production process moved from the craftsman's mind and hands to the Fordist factory (and the assembly line), the skill of building things shifted from human craftsmanship to anonymous, structured processes. Bit by bit, traditional artisans lost their knowledge and "know-how." Today, having a piece of furniture in our home depends on a massive production and supply chain; the "average" person no longer has the ability to build it themselves. The exact same thing is happening to software. We are the (now "former") software craftsmen.
  • ksd482 1mo ago
    > cognitive friction is the engine of learning. I agree 100% too. This is why in order to understand new codebase or to ramp up to new projects, I use AI to generate a textbook style reading material for me along with "verify yourself" types of exercises along the way. Then I print them on a paper and read it using a pencil/pen and take notes. Because of my math training, I am in the habit of slowing down to read textbook style texts which helps.
    • larsfaye 1mo ago
      Exactly the type of usage I would hope to see advocated for in the future. As I wrote, when leveraged with Socratic methods and a sort of "interactive documentation", they can really boost one's understanding. Of course, this is predicated on the individual having enough information to know the right questions to ask.
    • GPerson 1mo ago
      I also do this. It would be better I think to generate exact references to primary and canonical sources to avoid learning LLMisms, or to feed it these and have it ensure its material is anchored to those good references.
    • 1mo ago
• phyzix5761 1mo ago
  I'm still waiting to see how LLMs have made the world a better place because it honestly feels like its done the opposite.
  • ksd482 1mo ago
    I think a lot of good might come from medical sciences or chemistry, where LLMs will be used in coming up with new medicines, methods or synthesis.
    • platevoltage 1mo ago
      I can totally see where that could be the case. I'm sure there have been breakthroughs already, but it's not mainstream news. The mountain of AI slop is all over the mainstream though. You have to wonder why.
  • bigstrat2003 1mo ago
    They haven't. They have made the world significantly worse.
• 01100011 1mo ago
  TBH it was already pretty bad. There is a stark difference between the best and the average in my experience. The top, say, ten percent of coders are vastly better than anyone else when it comes to anything but boilerplate glue code(which is still needed and is better done by average coders anyway). This is speaking from my experience as a systems/c/c++ guy. If you are a js web frontend guy, python, or whatever I have no idea if this applies to you.
  • rozap 1mo ago
    Yea, it does apply. Honestly I'd argue that as you move up the abstraction layer cake, it applies even more. If a team gets a tool which 2x's their output (maybe a higher level language vs writing in C), then the difference in absolute output someone who produces 1 widget per day and 5 widgets per day becomes substantial. If you're given a tool which 10x's your output in a day, then it's even bigger. And of course you can have devs on a team who produce -.5 widgets per day. Think about the worst colleague you've had, now give them a tool which 10x's their output :)
• deadbabe 1mo ago
  I used to think this was a problem. But now? I don’t think it matters. Why? Because people are going to get so much more ambitious about the stuff they build with AI, that code expertise for the stuff they are building is already scarce anyway. People will choose difficult and less popular languages, and will replace open source packages with stuff built entirely in-house by AI. Going forward, there is no choice except for AI to fully replace the need for code expertise. Depending on humans won’t be scalable.
  • pandemic_region 1mo ago
    Do we even need to get LLMs to create code in the end then? Can we imagine a future where the thing simply does it all, you deploy the LLM like a docker image and have it process all requests directly. Sounds far fetched today, coming to your cluster in five years.
    • deadbabe 1mo ago
      In theory yes, but you would need LLMs that basically have frontier level capabilities but with zero latency, meaning you enter a prompt and as you type the prompt is regenerating instantly like some kind of autocomplete. I think that would feel like crack for some people who are addicted to using or building stuff with LLMs.
• fedpost 1mo ago
  Something I noticed trying to learn rust through models, they're inherently tuned to just finish everything with even the slightest provocation so it's very hard to use them to actually learn anything, they kinda just want to do everything themselves.
  • chasd00 1mo ago
    just add to your prompt or to an agents.md "don't write any code, just present me the solution so i can learn from it". that should do it.
• chris_money202 1mo ago
  Most computer science programs don't teach "coding" though. There is pretty heavy emphasis on datastructures, algorithms, and system design. I don't think AI atrophies those skills / knowledge as much as the coding language and I think in many cases actually improves them, especially if you are reading the code that is produced and at least understanding the flow of it. I agree that AI reliance is hurting engineer's language understanding, but I don't know how much we should care.
  • francisofascii 1mo ago
    > especially if you are reading the code that is produced and at least understanding the flow of it. This is the key point. Should we stay vigilant and review all the code, ensuring we have a decept grasp of what it does. Or just green light everything and treat the code itself as a black box. I would hope we do the former, but many are pushing for the latter.
    • Revanche1367 1mo ago
      The issue with this in practice is that the rate at which code is produced is often substantially higher than what any human reviewer is capable of processing mentally. Example from my workplace: pull requests that were already too long before LLMs by a few hundred or a couple of thousand lines are now several thousand lines longer and they get opened much more frequently. The primary source of these PRs is a well-respected senior team member with a ton more experience than everyone else by a measure of decades so nobody dares tell him to stop. Other team members aren’t far behind in the PR opening rate and admittedly I am one of them, but I try to mitigate the issue by doing multiple LLM reviews and anticipating when it’s ok to just approve it myself (have never had an issue in making this judgement thankfully). Part of this IMO is almost certainly because there’s now peer-pressure within the team to churn out a ton more code and that’s adding to the already clear message from leadership that we need to leverage AI to deliver things at unprecedented levels. My point is that it’s not just that some people are pushing for greenlighting everything without due diligence, it’s also that they’re pushing others to toward that outcome with their extreme AI enthusiasm which they don’t see the ramifications of or just don’t care.
• kylepomykala 1mo ago
  This seems right to me, but I think that it's likely that we haven't fully figured out how to integrate AI into coding imo. I think there is user side thing that we haven’t fully worked out yet.
• not_the_fda 1mo ago
  Writing code was never the job. It was a small part of the job that can now be delegated to AI. Eliciting the right requirements and user needs. Creating a sound architecture and design. Validating final product meets the requirements. Ensuring there is good test coverage. You know `Engineering`. Mechanical and Electrical engineers didn't go away because of CAD.
  • greenowl 1mo ago
    > Eliciting the right requirements and user needs. Creating a sound architecture and design. Validating final product meets the requirements. Ensuring there is good test coverage. Besides your first point, the rest can be delegated to AI as well. And you don't need to be a "software engineer" to spec out requirements and user needs.
    • ydat 1mo ago
      [dead]
    • daringrain32781 1mo ago
      This is happening at my company: all of these software phases are being delegated to AI. And the people without any understanding of software have absolutely no idea what they're doing. Features no one needs are being made in minutes. It hasn't been long enough to really tell how that's turning out. Everything seems to be in endless development.
  • chasd00 1mo ago
    > Mechanical and Electrical engineers didn't go away because of CAD. that is a very good point! I'm going to use it in the future.
  • larsfaye 1mo ago
    Literally all those skills are the result of decades of friction, challenge, and deep domain knowledge...all of which are circumvented when LLMs are utilized early in the process. CAD is also useless to Mechanical and Electrical engineers who didn't learn fundamental the skills that it streamlines.
• feverzsj 1mo ago
  Except sloppy experts.
  • dan_ggggg 1mo ago
    [dead]
• nautilus12 1mo ago
  I think the hope of the business end is that coding expertise will at some point no longer be needed at all.
• dan_ggggg 1mo ago
  That's the whole scam. It's a ransom with more steps. First they fuck up your codebase with so much slop that no human does (or could) understand it. Now if you want to keep making bug fixes, you're on the hook for whatever Anthropic wants to charge you. The solution is to make AI developers the scapegoat. Fire the people at the top of the AI leaderboards, with malice. Otherwise, lazy AI-addict developers are going to destroy what remains of your company's IP.
• romanovcode 1mo ago
  To be fair nobody codes in ASM and things are fine for decades.
  • rhdunn 1mo ago
    ASM is still used in some areas, such as: 1. function trampolines, such as in libraries like ATL (Microsoft's COM template library); 2. hand-optimized encoders/decoders for things like ffmpeg; 3. niche applications such as Ben Eater's 6502 breadboard computer (using a modified WozMon and Microsoft BASIC); 4. reading ASM output from C/C++ code in things like the GodBolt site for performance comparisons/analysis; 5. reverse engineering old DOS games; 6. people working on things like compilers (generating optimized assembly), JIT engines, or other code generation -- though this will typically be machine code, possibly with assembly instruction comments; and other performance critical places where assembly can speed up that part of the code.
    • romanovcode 1mo ago
      Absolutely, by 1% of developers. So analogy would be that those 1% would understand the code fully in the coming years.
  • adamddev1 1mo ago
    ASM to a higher level language is a jump to a clearly defined higher level language through a deterministic compile step. The jump away to LLMs is something completely different.
• hypfer 1mo ago
  > This applied friction is directly what builds "developer intuition" (or "taste"). The Germans have a great word for this: Fingerspitzengefühl (fingertip feeling). It’s the muscle memory that triggers when a developer looks at something and thinks, “yeah...this is probably going to cause problems.” No, we do not have that word for that. Yes, we have that word. No, it does not mean that. Any LLM proofreading could've told the author that, for that matter. __ What Fingerspitzengefühl actually means could be described as "tact", a precise approach to something and general attention to detail that leads to success. Or.. the lack of all of that leading to blunt failure. __ I would of course comment with more Fingerspitzengefühl for the emotional needs of the author if the writing wasn't just a sales funnel for their courses and whatever else (+ posted by them themselves.)
• kodoman 1mo ago
  I think we now entering this state where code is cheap but good well made programs will be rarer then ever, a lot of crap can be made and a lot of programs made without ever thinking the problem through properly will occur. It might be like how an archeologist since the invention of plastic can date the period of the soil as post plastic, if one could cut open the software stack of the coming systems that will be built in the near future one would could data that code as post agentic LLM as programs are going to be mostly bloated ad-hoc, poorly thought-out and patched in a way that does not concern it's self with the correctness of the algorithms or data structures chosen. I am not Anti-AI but I think it's going to be interesting and I am surprised at how bad a program ends up when one tries to "vibe code", though often ends up working, though in isolation and when used with discipline (that the tools themselves psychologically make it harder to do) can produce some very good code and being able to use loops to solve difficult problems or problems that simply would have require banging ones head against the problem many times is very profitable.
  • mentos 1mo ago
    How many programs can dispense with 50% of their complexity by just offering an API for LLMs to execute? By way of example I use Kdenlive 90% less and just use Codex to issue the ffmpeg CLI commands directly when I want to crop/format video on my PC.
    • QuercusMax 1mo ago
      All those crazy complicated CLIs are now super useful for LLMs!
      • kodoman 1mo ago
        Yes every time I tried to understand ffmpeg I got a little of it for a little bit and then lost it by 2 days or so. Just getting LLM's to do their thing for ffmpeg is great. the other one is socat an utility I used before but LLM's can do magic with it.
  • stuxnet79 1mo ago
• chrsw 1mo ago
  At some point it won’t be realistic to ask a human to solve a technical problem any more. I’m not suggesting it will happen soon but I can at least imagine that day coming. Whereas before modern “AI”, that possibility wasn’t even on my radar.
• js8 1mo ago
  Fair enough, let's say that happens. But what we're gonna manage the codebase in, then? What kind of language? Will it be a natural language, or a formal one? I feel that "coding" cannot collapse. Coding is just translation from natural to formal language. Somebody needs to write the specs. And writing/maintaining them in natural language brings a lot of fun - shifting interpretation, inconsistency, missing specification, etc. I don't think it's progress for the field of SW engineering. But at least more "shareholder value" will be created.
• ath3nd 1mo ago
  [dead]
• hombre_fatal 1mo ago
  While true, I'm not sure it matters. It kinda seems like wishful thinking on our part as software engineers that one day we'll be able to go "Hah, miss me now?" but that just isn't the writing that I see on the wall. Over the past year, I've AI-generated two large pieces of software over 2000 commits without having much depth in either domain, and my ability to deliver value as a veteran software engineer has only shrunk over the months or it can be trivially extracted into a reusable markdown file like "design bar: ensure things 'by construction' where possible", a lesson I learned viscerally over decades.
  • _dwt 1mo ago
    > without having much depth in either domain I don't mean to pick on you, but to present this in the service of this kind of fatalism... you know the inevitable follow-up question, right?
    • hombre_fatal 1mo ago
      Is it: "How do you know the solution is good?" Because I can still reason and dig into things and ask questions and have the domain explained to me out of curiosity, the same way I could build anything that was originally out of my depth. But what I've noticed is that the need for any corrective power has gone or is going to nil and I'm mainly doing directional work. And even then, I can constantly have sota models "rank the top options and recommend one", and it's almost always the right way forward. I used to read every line of every plan that LLMs generated, but over time I've realized I have less and less to correct or, more impressively, the LLM had foresights I never considered. The same thing happens with implementation. Periodically I can spawn a bunch of agents to evaluate the system adversarially to find improvements, and the findings have been so good that it's evident that soon I can just automate that too. In other words, the skills I need to excel here are more curiosity and patience than tech expertise -- the things that got me into software engineering in the first place since that was the only way to build things.
      • _dwt 1mo ago
        You got it. You may well be right, but from my standpoint it's hard to see how you'd know if you weren't. Yeah, the models fill in vagueness with detail sourced from "what's likely and helpful". (In one of my particular domains, that's "use SHAP values for everything everywhere".) Yeah, that detail's increasingly unlikely to be "wrong" in a way that you could explicitly argue. Is it what an expert would come up with? Is it the best it could be? Is there something else that we would have done had we been forced to think it through? Will it ever be _surprising_? I know, all irrelevant little philosophical roadbumps. The artifact satisfies the buyer. I think I'm going to have to step away from this industry pretty soon, at least for a while.
• game_the0ry 1mo ago
  I believe it. I haven't written code since March.
• efavdb 1mo ago
  look to past examples. when the greeks developed writing, people complained that the youth were losing the ability to memorize much content. and that is true, but with writing they were able to do better still and that old skill -- though useful -- was lost.
  • larsfaye 1mo ago
    Plato wasn't against just "writing" in a general sense, or that he felt it was going to hold humanity back. He was against treatises and felt that someone could "memorize facts" without having to actually think about them on a deep level. Which I think, ironically, is not all that off the mark especially in the age of the internet and now LLMs, right? He also felt that memory could decay if we relied on written facts instead of having dialogues, which again, not all that off the mark, either. He underestimated the compounding capability of technology and our ability to record data and information, but people remember a lot less these days than they used to because we'd largely given up that ability in exchange for the instant information machines. Of course, he's just one man (or two, if you consider he was conveying Socrates' thoughts, as well) who lived in ancient times and couldn't possibly foresee how technology would evolve...but when I went back and read his concerns, it was ironic to admit that much of what he warned about still applies to this day. People are far less informed despite having access to more information than we've ever had because we've exchanged the ability to remember for the ability to just look things up. And, we also have less meaningful dialog than ever before; people just sit on social media, copying and pasting "facts" to each other, instead of having actual productive discourse. AI tooling can be a boon to learning, but it requires us to stop using them for code generation as a primary purpose (at least for juniors) and instead advocate for Socratic workflows that still require manual coding practices. When someone decides to code something, it's not just learning syntax; it engages a variety of mental disciplines from critical thinking to planning to creative problem solving to logic and math, even.
    • efavdb 1mo ago
      I agree the tradeoffs are real but consider it obvious that reading and writing were in net a boon and I also expect the same for AI / programming. Of course having some understanding is still required in both cases to make good use of the tools.
• _doctor_love 1mo ago
  We're all posers - unless you can implement square root in machine code, you're not a Real Programmer™
• yipinwong 1mo ago
  I do understand the sentiment of applying "constraints" over AI usage to certain scopes of our development work. This has an issue in practice. As an example, Function Programming (FP) has a high constraint on programming, where some don't even have loops (gotta use recursions all the way), and almost no state mutation (Exlixir I believe have a mutable state? forgot). FP sounds great with all those constraints. But what about the adoption? It's hard to switch your mindset, and not as natural, thus long leraning curve, and not as wide adopted <- productivity goes down as all others need to know and use it well. That's why still imperative and OOP languages are ruling the world. Same for these constraints. The author promoting using AIs only to subsets (no coding? wtf) is something the majority won't follow. Yes, the constraints sound great, but at what cost? By the time one learns everything, and everyone moves along with AI building stuff fast and cheap, they will be left behind. --- I do not like the author trying to make his points authoritative by using Halo effect using quotes from the industry and could have had been taken out of context (That's where AIs mess up the most, they only get chunks of text and lost context of before and after exerpts).
  • switchbak 1mo ago
    Your inclusion of FP is interesting in an unintended way: LLMs actually thrive in a highly constrained system like you describe. "It's hard to switch your mindset" - isn't nearly as true for an LLM, it can usually adopt those languages quite readily. LLMs don't particularly care how hard the type system or borrow checker is (as long as it has good error messages that can guide it to a solution), they can grind away at these things, and what you describe as a negative actually becomes a strong positive. I think we'll see strongly typed systems plus some level of formal verification become popular as an AI-preferred language. When the burden of review is lowered because you have purely functional building blocks, with lots of formally verified chunks - people will choose that simply out of (productive, beneficial) laziness. Not to mention we're in a ram crunch, and being able to run your stuff far cheaper has an immediate financial incentive.
• doctoboggan 1mo ago
  I often think back to the early GPT days before agents as maybe the last time I will deeply learn a technical subject. I think that was when I actually learned the most as I had to stay completely in the loop. I had recently started a new job and had to work with k8s for the first time. Using GPT to help me implement new services and help me diagnose and fix issues with kubectl taught me so much. Now with agents I don't have any insights into what its doing with kubectl and would have no reason to learn how it works (other than my own curiosity). I agree that the human no longer gains expertise, but I am not sure that will matter in the long run.
  • larsfaye 1mo ago
    The end result is a total and complete reliance on AI providers. It's not really a secret; that's why I started the article with the direct quote from Altman. They would love to see a world where nobody is able to do any type of development work without an LLM subscription enabled...even though they also admit that these models perform best when they are steered by someone who is highly capable and knowledgeable in the first place. They're powerful, but they are also VERY fallible. Local AI would thwart this vision (which is why they're desperately also trying to ruin the hardware market at the same time), but the effort it would take to get local models to run as well as these frontier models is an odd thing to pursue just to avoid learning the fundamentals and gaining direct experience.
    • doctoboggan 1mo ago
      > Local AI would thwart this vision While I agree Local AI would be a good goal, even the huge open weight models that can't be run locally are already thwarting the US AI lab's duopoly. Other companies can and do serve up these open weight models, and without having to amortize R&D they are able to serve the tokens at a pretty cheap rate.
  • netniuq 1mo ago
    yes, this seems sadly very true for me, too. In some ways, it feel like I'd be "stuck" at my 2024 capabilities if I didn't push myself constantly, and I'm really glad for every hour I spent learning/applying new stuff before that, because now it feels way harder.
• GPerson 1mo ago
  I don’t think there’s a big societal problem here, except that the agentic programming developers may be out of a job like the rest of us. If AI continues improving it will just keep taking over whatever skills are involved in the current AI coding meta are. If it stops improving then the meta will stabilize and after 10 years everyone will have longevity in it. I also see no evidence that AI programming is a difficult skill that cannot be learned by any intelligent person in much shorter amounts of time than previous professional skills required.
  • lrvick 1mo ago
    Depends on what you are programming. I have been using it to build things that have never existed before, that I have wanted for over a decade. Experience gives one more imagination.
    • GPerson 1mo ago
      Me too. I’m failing to connect the dots from your post to mine though.
      • lrvick 1mo ago
        > I also see no evidence that AI programming is a difficult skill that cannot be learned by any intelligent person in much shorter amounts of time than previous professional skills required. I do not think anyone could do the job I do with AI without my decades of experience, is my point. For now.
        • GPerson 1mo ago
          I’m assuming you’re a software engineer. The AI programming meta that keeps evolving (last month it was loops) seems like a relatively trivial skill to adopt compared to learning what it’s like to do high quality work and to participate in a team, and these kinds of things. If the AI stops improving then everyone will master the AI skill set that everyone else is using, and people will acquire maturity and experience over time, like always. This is my point.
• schopra909 1mo ago
  I think this is more “gray” than this. I feel like I can rip through ideas more quickly then ever before and as a result get a lot better at designing systems and (for my work) get a lot better at designing data/model experiments. But I empathize with the author. I think the frustration comes from the fact that other folks in your organization use these tools to “get by” more effectively then before. In the past, a disinterested engineer might ship less under the umbrage of a difficult engineering problem. With the pressure to “ship more” now that there’s AI, the same engineer is using AI to spam PRs to prove they’re working, even the quality of work is low (because quality of thought is low).
• azakai 1mo ago
  > LLMs can detect patterns at a scale that no human ever could, but patterns only get you so far. This is asserted without evidence, and from a scientific standpoint, unjustified. First, "detect patterns" makes it sound like a classification task, "is this a picture of a cat". But LLMs transform the input. For example, an LLM can translate text between two languages while properly handling the names of the people described, no matter what those names are. That shows they are representing the text in a somewhat abstract way, that they can perform operations on that representation, and also convert it to useful output. And, what I just described is the most general form of information processing algorithm. Science is not aware of any limitations in principle on such systems. I am not saying LLMs have no limits, but "they only recognize patterns, and that is a true limit" is not a good argument.
• ex1fm3ta 1mo ago
  Keep in mind also that LLMs are currenctly heavily subsidized. Once VCs money are gonna run out, you will see the real price, and your 200K per year dev is probably nothing.
  • lrvick 1mo ago
    A $1200 GPU is all a reasonably capable engineer needs for each work stream. The cloud prices are a scam.
    • ex1fm3ta 1mo ago
      hmm that's a bit low right now, since you need at least 48Gb of VRAM to be confortable. 32Gb might do it (on quantitized models + optimized) but it would be very slow.
      • lrvick 1mo ago
        That may have been true a few months ago, but shit changes fast in this space! I run Qwen 3.8 27b on each of my six AMD AI PRO r9700 GPUs at 80tps decode each and they cranks for days with 256k context, doing complex kernel, compiler, debugging, enclave, bootstrapping, pentesting, hardening, and systems work full time. ~$1200-1500/ea on ebay. Also ~40tps on my strix halo now but with room for several sessions at once.
        • nicce 1mo ago
          What is your config for getting 80tps decode?
          • lrvick 1mo ago
            Qwen 3.8 27b Q4_K_M w/ matching dflash drafter, 256k context, llama.cpp+dflash2, draft-n-max=5 Also using with Charmbracelet Crush with Froggerinc fixed chat templates.
            • 1mo ago
• greenowl 1mo ago
  Of course it will. Doesn't matter though. Coding expertise is no longer valuable. What is valuable now is productivity. Which in today's day and age is the ability to quickly and efficiently drive AI. Hence the never-ending growth and spewing out of tooling: harnesses, TUIs, multiplexers, agent frameworks, software "factories", etc, etc. Software engineers are chasing opportunity and expertise in the only thing that's left.
• linuxhansl 1mo ago
  Yep. In my experience human design -> agent code -> agent review -> release -> agent observer, does not (at all!) work. One absolutely has to be understand what is going on, how the system works, how the H/W works, etc, to catch agent errors. The proposition of us losing those skills is terrifying. Maybe AI will get better and we truly won't need a human in the loop. Then please also have all PRs signed by whatever model wrote them, and do not come to me for trouble-shooting.
• jstummbillig 1mo ago
  A list of things, that were supposed to lead to our intellectual demise: - Writing (starting from Platos Phaedrus) - Printed books - Photography - Typewriters, keyboards - Telephones - Recorded music - Television - Wikipedia - GPS navigation - Smartphones - Automation in aviation, medicine, industries
  • rf15 1mo ago
    If current trends are anything to go by, who's to say that these aren't stepping stones towards it?
    • jstummbillig 1mo ago
      Dear lord
  • _verandaguy 1mo ago
    Speaking on a handful of these that I'm familiar enough with to opine on: - Photography hasn't erased other visual arts. Both require a separate skillset; both have their uses and their enthusiasts. Photography benefits from having a lower skill floor, in my experience doing it, and this in turn has led to commercial photography eclipsing commercial painting (barring things like painting buildings) as a viable business model, largely. I'm not sure if we're better or worse off as a society for having gone through that shift. - Television is arguably not a net positive in society (I won't say net negative yet, but there are some reasonable arguments for that position). It enables a form of passive consumption that allows bad arguments to come through as persuasive through the gradual (on the scale of months and years) numbing of critical appraisal of the media being consumed. This has more- and less-pronounced areas. In the US (which is geographically close to me and which has an outsize proportion on my own country's culture), Fox News is an excellent example of how TV can erode critical thinking. - Smartphones arguably reproduce and amplify this problem, and tack on others: they make it increasingly easy to dissociate from daily life, and make it easier to continue consuming content from actors increasingly interested in steering conversations in one direction or another (on the most benign end, it's influencers trying to get you to buy things, which obviously has negative economic impacts on an individual scale; on the more overtly harmful end, they serve as a hardware channel for less-regulated or unregulated extreme and hateful content). Just like with TV, smartphones have clear benefits and utility in daily life. They aren't abjectly bad inventions, but they have a serious societal toll, and it's difficult to ignore that. - In aviation, the first generation of (relatively modern) automation did lead to a high number of accidents and loss of life. American Airlines flight 965, in 1995, is a well-studied case of an over-reliance on flight automation before it was widely understood among pilots what the limits of these early-modern incarnations of autoflight were. In the wake of that accident, many aviation regulators instituted or began requiring that manufacturers and airlines formalize training and operational procedures that protect thoroughly against this sort of cognitive gap. I think that last example (and many aviation accidents) are an interesting example to study in the context of software. Aviation's extremely and conspicuously responsive to accidents, often requiring procedural and hardware changes as a result of these. They can be as simple as a software patch, or as complex as the redesign of a component because a human factors analysis found that it could be confusing under stress. In software, we like to think that we're a serious industry, sometimes. We spent much of the 2010s going in what I found to be a good direction: the development of IaC, the popularization and standardization of tools like Git, registries for vulnerabilities like the NVD, and even the development of languages like Rust which address historical technical shortfalls of high-performance, low-level languages like C; but we always fell short, industry-wide, on matching these toolchain upgrades with technically-rigorous procedures. For every borrow checker, there's vibe coding.
• jameson 1mo ago
  It appears to be a pattern where I work "expert novice" eventually causes serious incident but is unable to root-cause on their own. They've become a meat proxy[0] prompting LLM to root cause for them and the ability to fix is capped by LLMs ability, not the engineer's. I've tried to convince management before this happened and yet here we are. [0] https://gruhn.me/blog/2026-08-03/ https://gruhn.me/blog/2026-08-03/
• epolanski 1mo ago
  I personally write lots of code manually and use AI to review it. Sounds like a good compromise, if not even positive from many points of view.
• TonyAlicea10 1mo ago
  As a tech educator I 100% agree. LLMs are not going to become a "new compiler" where we don't have to worry about the code any more. There's a reason we trust deterministic systems. I've been worried about this a lot, I even created an agent skill called do-i-understand that's designed for novice devs (and experienced too, because atrophy) where the LLM asks you questions about the PR you're about to submit. I've found it helps a lot: https://github.com/AnthonyPAlicea/skills/blob/main/skills/do-i-understand/SKILL.md https://github.com/AnthonyPAlicea/skills/blob/main/skills/do... One way or another, there will be a skill reckoning.
  • chrisjj 1mo ago
    A deterministic LLM is possible. Would you trust it?
    • xdavidliu 1mo ago
      they probably mean deterministic in the sense of traditional computer programs consisting of if-else decision points and ordinary cpu logic, as opposed to numerical models (which can of course be deterministic too, as you pointed out)
      • chrisjj 1mo ago
        Model inference is just that same logic but faster. I think the point is determined. No-one can determine what the LLM might do.
        • xdavidliu 1mo ago
          > Model inference is just that same logic but faster. This statement is nonsensical.
    • TonyAlicea10 1mo ago
      I mean in the traditional software sense. We trust autopilots to fly planes. Would you get on a plane flown by an LLM?
• kaashmonee 1mo ago
  Substantiveness of this article notwithstanding, I do want to point out that the author also runs (or is planning on running) a programming course which to me may be a slight conflict of interest. I think the author may altogether be well-intentioned, but it IS something that I'm going to keep in the back of my mind as I consume this content.
• znnajdla 1mo ago
  This happened before with “real” engineering. Engineers a hundred years ago used to be proficient with slide rules and mental math and 3D assembly by hand. Products designed in that era often lasted a hundred years, like Singer sewing machines and Lada cars and 500 year old churches. Now things aren’t built like they used to be, and few people can rebuild civilization by hand like they did. But the world moves on fine!
  • ifwinterco 1mo ago
    It's different though because for structural engineering finite element models (set up correctly) will give you a deterministic, mathematically correct answer. In fact FEM is arguably more deterministic than the old school pen and paper methods (yield line analysis etc.) which often rely more on correct judgement of the structural engineer doing the analysis. So I don't think the analogy quite holds
• LunicLynx 1mo ago
  In my company the knowledge is starting to be devalued. People are distrusting whole swaths of concepts because they do not understand how things actually work. Like going away from zerotrust architecture to holding open a long polling connection. At least I seem to remember that long polling wasn’t that great, but i start to even doubt myself. Anyone wondering how the Roman Empire was wiped out? I guess we will find out soon
• phoghed 1mo ago
  I've, more than once, gone long spans of time doing purely management and architecture level work, then returned to programming. A little rusty? Sure. But I never forgot how to program or lost the skills that actually matter. Seems mostly like a non-issue for people already in the field. The real issue will be with people that never learn it in the first place. And even that isn't so bad, learning programming isn't some insurmountable hurdle. It took me less than 6 months from no knowledge to my first job.
  • ARandomerDude 1mo ago
    > It took me less than 6 months from no knowledge to my first job. I agreed with you up until this sentence. Entry-level devs with 6 months of require an enormous amount of time and mentoring until they're able to really perform well. I think the greater concern being expressed is not will people be able to type syntactically correct code?, it's will people be able to write software well?.
    • phoghed 1mo ago
      Never worked at a company that had junior devs, so I can’t say. I’ve had interns though, and some that were better than most of the low budget offshore contractors that I’ve ever worked with. I’ve worked with devs that have a decade of experience but can’t really ship anything. I think it just comes down to being good at this type of job or not.
• svara 1mo ago
  Yes, but it's also building other skills. There's no friction to learning something new anymore, and that's really quite amazing. E.g. I've gotten pretty good at git thanks to AI because it forced me into more complex workflows. I still can't remember the commands but I really grok the concepts and terminology on a far deeper level than before, where I made a conscious effort to stay on the happy path lest I get into some odd state I don't understand. Pretty sure those "odd states" would seem quite clear to me now.
• 1vuio0pswjnm7 1mo ago
  Hobbyist programming expertise unaffected Genuine curiosity in learning how stuff works, not necessarily for financial gain, e.g., from a salary or using web to deliver ads No real "pressure" for hobbyist to use "AI" IMO as end user, some of the best software available was originally written by a single unpaid author, not salaried teams Some of the worst software ever written was produced by overpaid teams Hobbyists may use relatively old, handwritten code to learn from That's not necessarily bad. Software quality has declined over time
• jp57 1mo ago
  I fall into the category of senior engineers who benefit from LLMs for all the reasons mentioned in this post. I find it's possible to agree completely with sentiments like this and still feel as if this is all written in the sand below the high tide line, and ten years from now nobody will care about this. Horsemanship and sailing were both specialized skills of high value to society, and now they're not. But in each case there was probably a liminal period, when being an accomplished horseman or sailor was still valuable, even as motors were taking over. Eventually that period ended, as the new generations without those skills found ways to get by with cars and motorboats.
  • TehCorwiz 1mo ago
    This analogy breaks down because computers aren't going away unlike horse drawn carriages or sailing vessels. Computers aren't being replaced by something. It's that fewer people will understand how they work while the efficiency and reach of computers extends into areas of life previously unreachable due to the scale of having humans build it or the refusal of humans. I could wax philosophical about what that leads to but enough people already have.
    • jp57 1mo ago
      Boats didn't go away with the demise sailing as a commercially viable mode of transport.
      • jplusequalt 1mo ago
        >Boats didn't go away with the demise sailing as a commercially viable mode of transport. No, but there's now more people who know how to engineer reliable ships then ever before. In 10 years, how many people will still understand the codebases they work on?
    • tim333 1mo ago
      Quite a lot of people do competitive sailing and horse riding so the skills are there but amongst less people.
  • 1mo ago
• dingaling911 1mo ago
  It's pretty simple. You treat the AI like a junior. You make it write pseudo code in the tickets. Then you make it write code in the tickets for the tricky stuff. Have it reference relevant documentation/APIs. Then there is no lost knowledge. (Still, sometimes it sneaks in some "helpful" belt and suspenders, but for the most part, I know everything that is going on in the code base with this method.)
• gwbas1c 1mo ago
  This just feels like someone whining about how ORMs result in $#1tty data access code because lazy programmers don't take the time to learn how to use a database. When that happens, (developer thinks using an ORM means they don't need to know how to use a database,) the project eventually fails. It's the same thing with AI; just like companies learned that they need to make sure developers actually know how to use a database, companies will learn that their engineers actually need to know how to program.
• chrisjj 1mo ago
  > AI models lack judgment Very interesting is how divisive is this statement. In that almost every response is either hard agree or hard disagree. Does agreement come from observer judgement, or lack thereof?
• tosh_vance 1mo ago
  [flagged]
• thenoblesunfish 1mo ago
  I hope that this will expose the true value of education. It's a new scale perhaps, but not a new problem. We sit in classrooms even though books and YouTube videos make available the teachings of far more illustrious teachers than the one in front of us. We watch things written out agonizingly slowly in chalk. We learned to do algebra and calculus even though we had our TI-86s and Mathematica. We learn in Haskell and Scheme even though those are rarely used later. We write toy compilers and write essays and repeat experiments with known outcomes in labs. We do it to learn how to think, how to build. We just have to be even more deliberate about it now.
• gos9 1mo ago
  Sewing expertise is going to collapse from sewing machine reliance
• lab14 1mo ago
  "Punching card expersite is going to collapse from interactive terminals reliance"
• osigurdson 1mo ago
  My personal antidote is to write unassisted Zig in my spare time (though C would be fine as well). While I can't back with data I certainly feel sharper.
• kjohnston71 1mo ago
  Hand weaving expertise has also collapsed.
• xdavidliu 1mo ago
  > JetBrains, a major player in developer tools, recently completed a study of junior and novice developers The article links to this as the study: https://dl.acm.org/doi/epdf/10.1145/3632620.3671116 https://dl.acm.org/doi/epdf/10.1145/3632620.3671116. It doesn't appear to be related to JetBrains in any way?
  • larsfaye 1mo ago
    I originally found the paper through this video: https://www.youtube.com/watch?v=HTUh0OO6Kmo https://www.youtube.com/watch?v=HTUh0OO6Kmo The video seemed to indicate it was a study they ran (she refers to the examples as "our subjects were two of twenty four participants"). It seems they are just citing the study. While it doesn't change the study or the takeaways, I'll update the post for clarification!
• 0xbadcafebee 1mo ago
  Coding expertise was on a downward trend way before AI arrived. Does nobody remember how most "engineers" were literally copying and pasting snippets from StackOverflow they didn't understand, and the snippets usually had tons of bugs? How many of you know Assembly well? How many of you can decompile a program, or write your own compiler or VM? How many of you could pass a computer science course (that you didn't take at Uni)? We've been hearing about the demise of skills since before the invention of the loom. The only skills we've truly lost are for things nobody uses or makes anymore. What actually happens is, we develop a new tool that's better than the old tool, and we get good at using the new tool. We then have a class of people whose job it is to maintain the new tools. We don't need that many of them because the whole point is to eliminate that labor. Your jobs as software engineers are going away, it's that simple. Your new job is to use the AI tools to make products. Somebody else's job will be to make the AI a better software engineer.
  • watwut 1mo ago
    > Does nobody remember how most "engineers" were literally copying and pasting snippets from StackOverflow they didn't understand, and the snippets usually had tons of bugs Not in companies I worked for, no. > How many of you know Assembly well? How many of you can decompile a program, or write your own compiler or VM? How many of you could pass a computer science course (that you didn't take at Uni)? None of these was ever an expectation most coders. Some are bonkers as an expectation for all.
    • 0xbadcafebee 1mo ago
      They used to be normal expectations. My point is the "decline" is a natural movement away from highly-skilled generalists toward specialized-and-less-skilled labor and has nothing to do with AI
• foldr 1mo ago
  One interesting feature of vibe coding is that it allows you to write code in specialized areas where you have no expert knowledge. That makes the code effectively impossible to review in any useful way. For example, I have a vibe coded Python monstrosity which I use for stitching together scans of large format negatives. The enlarging lens that I use for scanning has strong chromatic aberration in the red channel but is otherwise very sharp†. I got Codex to figure out some way of using the green and blue channels to sharpen the luminance while preserving the color information from the red channel. I sort of vaguely understand how this works, but not nearly well enough to review all the horrid numpy code that implements it. For my use case, there is really no reason to look at the code, as I am only interested in the output. As disconcerting as it is, I feel that this is going to become more and more normalized. Looking at the code that your LLM generates will become like looking at the assembly output of your C compiler. † This makes a lot of sense, if you think about the color of a darkroom safelight...
• efficax 1mo ago
  And so what? How do you think people are going to be working on software in 10 years. They're going to use coding agents and harnesses that work much better than the current ones (although I don't think we're getting anything but incremental improvement from here on out). They will run on commodity hardware. I first got paid for writing code in 1999, I've worked at publicly traded software companies and failed startups, in every language out there. And if LLMs "atrophy" the expertise I built up over those years, then so what? What is lost, exactly? I stopped programming in C++ about 10 years ago when Rust seemed to get good. I no longer remember a lot of the specialized knowledge I had in C++. My life goes on. I am now becoming an expert at building software with agents. The problem is still the same, you still have to apply engineering principles. You just don't have to write the code.
• jason_oster 1mo ago
  As always, the innovators will thrive and become the new experts in the field. Everyone else will die out. It's impossible to buy the FUD that expertise will somehow vanish because people use AI. People come in a variety of capabilities, challenges, and personal interests. Expertise varies from person to person. Those with personality traits that are more likely to take risks and persist against adversity will be the innovators and experts. We've seen this played out countless times. You have to ignore everything you know intrinsically but can't articulate about innovation, technology, and evolution to drink this FUD Kool-Aid.
• xtracto 1mo ago
  Yes, and it doesn't matter. Writing code in programming languages is a skill/necessity created by us to instruct computers what we want them to do Initially in the 60s, this was done by connecting circuits one way or another (think ENIAC). Then we devised "programmable" computers and devised a bunch of codes (computer code instructions) that abstracted away those cables. The we created Programming Languages to further abstract away the hardware complexity, and to be able to write down our wishes in a way that is more transferable between us humans, but that is still computable by machines. But with LLMs and neural networks, at some point these abstractions wont be necessary. The computers will still be making computations, but the way we tell them what we want is going to evolve. It's fascinating.
  • badc0ffee 1mo ago
    Not to detract from your point, but there were software-programmable computers in the 50s. Check out Usagi Electric's videos about the Bendix G-15, where he loads software from punched tape.
  • deleted 1mo ago
    [deleted]
  • foltik 1mo ago
    Computers are useful because we can instruct them what we want to do precisely. It’s true we usually don’t care about all the details, which is why abstractions exist. An abstraction hides details by fixing them, and lets you specify the rest precisely. An LLM isn’t an abstraction in this sense any more than asking a coworker to do something is. The details are not fixed, but decided for you. If you can’t understand or modify what was decided yourself, the only interface left is going back and forth in natural language. So no, the abstractions won’t become unnecessary. The details don’t just go away. Plenty of people really don’t care about them, and for them the LLM is fine, but only because it’s gluing together the millions of LoC of existing libraries and frameworks where the details have already been fixed, overwhelmingly by humans. There will always be a need for human professionals who aftually understand all that obscure stuff, and per TFA, it’s looking like it won’t be the ones who went all in on AI.
• xenadu02 1mo ago
  There have always been opportunities for those who seek out the less traveled paths. If all your peers are only accepting what LLMs tell them then you should do the opposite. Spend some of your time writing code by hand, especially when working at a new layer of the system or on new things you've never looked at before. While the agents churn out more CRUD crap in the background spend your attention learning how everything works. I do way more experiments with way more things by taking advantage of LLMS. When I have them do research I use that as a starting point for my own reading (but don't blindly trust them). I find I am learning more faster. Change is an opportunity. Use it to your advantage. Let other people while and moan while you get things done.
• oscillonoscope 1mo ago
  It believe the most likely consequence of AI is to promote generalists: people who have a domain expertise, can work cross discipline, and has enough programming knowledge to keep the LLMs on track. I don't think 'pure' software engineers will end up being as highly valued as the last decade though I also think that will be true for other disciplines as well. Just as an example, in signal processing, it's not uncommon to have a person designing the general algorithm and another person dedicated to implementing the algorithm in the embedded system. With the quality of coding agents, it's not really necessary to have both of those people anymore. A person who is moderately experienced in both can do the job now.
• adamddev1 1mo ago
  We are spending sooo much for our intellectual time and energy on discussions about alchemy-like experiments with different models, agents, harnesses, orchestrations. And there are huge amounts of time, energy, and writing sunk into arguing about AI or trying to convince people of the danger or problems. Sadly all of this is taking time away that could be spent on real progress and learning about coding/FP/PL/algorithms/type theory/etc.
  • calvinmorrison 1mo ago
    > Sadly all of this is taking time away that could be spent on real progress and learning about coding/FP/PL/algorithms/type theory/etc. Well we could also put a halt to the production of tesla and go back to producing the perfect vehicle, the Saab 900 Turbo, but you know, I don't get to (yet - I will be King one day) determine what others do
• deleted 1mo ago
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• vain 1mo ago
  This seems sadly very true. Just yesterday I was implementing some slightly tricky javascript (not my main language) on hover show n neighbours to each side, and if a deficit on either side, expand to the other side. After about 20 minutes of struggling to get the offsets just right, I succumbed to just asking an agent to do it. I'm sure I'd still be able to do it, but was saddened that I didn't get it as quickly as I think I used to be able to. Atrophy might already be in play.
• danielovichdk 1mo ago
  Would you work for less money and use AI ? Or would you step out - professionally - of the industry and program for passion and fun ? I think that is a question we are all mulling about these years. Our expertise has been packaged into a 200$ product and the competition has become ourselves.
• hirvi74 1mo ago
  Ever since I was a teenager, I started to develop cyclical bouts of existential crises. While I have been feeling better for quite some time, I feel another starting to brew. While I was never one of the fabled 10x or rockstar developers, I still derived a lot of enjoyment and and sense of purpose from my work. With the utility of LLMs becoming more ubiquitous by the day, what purpose can I provide anymore? I struggled greatly to get where I am today, and while it might not be impressive to any of my fellow programmers, I am still proud to be a programmer. I obtained a degree in CS because I found the entire field to be fascinating. I had great passion for learning many of the subjects. What I learned in my degree changed my life forever. I seriously went from one of the, "What's the point in learning most math if you never use it?" to being absolutely infatuated with the subject. (I'm still bad at math, but that does not detract from my pleasure). With the utmost certainty, I did not push through all my struggles just to prompt LLMs all day. Maybe's its my insecurities manifesting, but I want people to say, "You did a great job" and not "Claude did a great job." I understand the Buddhist were likely correct. My suffering really does come from my attachment, but at the same time, I do not want to let it go. I have no opposition to using LLMs as tools. I think a fine balance can be achieved. LLMs can even be exceptional learning tools when used appropriately. If programming is just a means to an end to you, then you will receive no ill judgements from me. We all have different motives in life. But programming has always meant something more to me.
• andai 1mo ago
  Wasn't everyone making these arguments for the last 50 years with each wave of advances and convenience? "Real programmers use [current_tech - 1]." I mean, they were right, then, too. My meaning is that expertise already collapsed several decades ago. -- One of my favorite talks of all time: Jonathan Blow, Preventing the Collapse of Civilization (2019) https://www.youtube.com/watch?v=ZSRHeXYDLko https://www.youtube.com/watch?v=ZSRHeXYDLko
• applicative 1mo ago
  It's surprisingly late for him to notice. But wait til you think through the consequences of the already collapsing human capacity for extended written composition, which is orders of magnitude more significant.
• UncleOxidant 1mo ago
  Alternate take: How many people have known how to program in assembly for the last 30 years or so? It's been a skill on the decline. Good compilers made that happen.
  • zbentley 1mo ago
    I don’t buy the “LLMs are the new compilers” claim. Compilers take an agreed upon specific intention “implement X via Y code in order to achieve Z” and make it executable. LLMs in the hyped methodology just take “Z”, and decide on an X and Y. They’re doing things a compiler doesn’t: picking an approach/behavior, and picking a way to perform that approach in code. Those are subjective judgment calls, not mechanical processes that could be encoded in a classical program. That saves time, but given their reward system (“what the user requests is always the desirable goal”), they add considerable risks to the process of software development as well. No amount of guardrails and code quality agents can sidestep the fact that the decisions they make are substantially unpredictable and only as good as the prompter knows to ask for.
• markus_zhang 1mo ago
  I’m still resisting the AI flood. I use it but I do read code without its help. I also make sure I have the muscle memory of stuffs that will be tested in interviews — somehow big techs have forgotten that maybe they shouldn’t test people on coding problems. So basically I’m still doing things manually for everything that preserves my edge for interviews and as a technical person. But I use AI to generate diagrams and documentation, as well as operation scripts that no one is supposed to memorize.
• tygon 1mo ago
  I wonder if we will eventually see the same drop in general knowledge we saw with manual driving (in some parts of the world), cursive handwriting, clothing repair, etc. Of course, coding was never as prevalent as these practices in the general population, so it might be harder to measure, but I feel we will definitely see it taught less in schools, harder to find resources, etc. in the coming decades, becoming more of an underground hobby.
  • _doctor_love 1mo ago
    It is guaranteed to happen. The key question is when is it a problem? We've lost lots of knowledge as a society but we're still going. Some skills decline in usefulness, others gain utility with the passage of time. Tale as old as time.
    • tygon 1mo ago
      I would hope as long as there is a demand, there will be those willing to fill it. There never would be a problem because the skill set would stick around as long as there is the need for it. At least that has been the historical trend. We still have horse farriers for show horses or for family pets. It is a niche there for those that need it, but nowhere near as common a job as it once was. It will likely be like this. Those that like doing it will stick to it, but we will not see Indeed listing jobs for it as much. Of course with less demand, less will have the skills, so those that do have them can definitely command quite the power when they are called on for something.
• _doctor_love 1mo ago
  I am not personally worried on this front. It is a near-certainty that something catastrophic will happen in the not-too-distant future because of the issues Lars raises in the essay. Not until that moment occurs will there be a broader industry-wide reckoning. Most likely it will get expressed in breathless language like "you'll never believe the crazy gains we got from adding tests!" (or whatever). I feel pretty good asserting that, as always, a few smart leaders will recognize early that quality and stability are the new game now that we have speed 'for free.' And then there will be incumbents whose eventual demise will merely be accelerated.
• deleted 1mo ago
  [deleted]
• rglover 1mo ago
  Not just coding expertise. Wrote this a little over a year ago [1] on this exact topic. [1] https://web.archive.org/web/20250623100834/https://ryanglover.net/blog/chauffeur-knowledge-and-the-impending-ai-crack-up https://web.archive.org/web/20250623100834/https://ryanglove... (sorry for archive link, have a backlog to migrate old posts to my new setup).
• oldsklgdfth 1mo ago
  when the tool becomes a crutch you end up with a limp. at work, i can tell that people are not thinking and losing the ability to thinking hard. I keep coming back to what LLMs "really" are. Recursive autocomplete, it keeps choosing the best fit for the next token. This really demystifies it for me. It also reinforces that is not "reasoning", so there's no hidden mental model.
  • rbtprograms 1mo ago
    >at work, i can tell that people are not thinking and losing the ability to thinking hard. its also wild how quickly and willingly many people handed this over. the apathy and desire for connivence runs extremely deep among my coworkers. we are at the point where people are not even running their local dev servers and clicking around to ensure their work is functionality correct, they just ingest the ticket, dump it into the model, commit the output, and say they're the most productive they've ever been.
    • oldsklgdfth 1mo ago
      reminds of college when everyone would use chegg, but knew it was a shortcut. the difference now is it is shamelessly encouraged. one interesting topic is code reviews of AI code. code reviews have always been a bottleneck on the team and there's lots of trust and rubber stamping. I don't believe people are reading the code they ship. I will say that it is a beautiful tool if you turn it on its head. if you don't quite understand something, it will never tire of answering your questions. It is a great time to need handholding.
• konaraddi 1mo ago
  Great read that brings some rigor (or at least cites rigor) to what has otherwise been anecdotal. > then what is the path for one to become an expert so they can effectively use these tools? The article briefly mentions guard rails and I think on the same note we need the AI agents we use for coding to encourage learning and comprehension in its users. Right now it’s completely voluntary and on the onus of engineers to put in the effort to learn since, as the article states, the friction that led to some degree of required learning is gone.
• rektomatic 1mo ago
  Forcing friction the way this post describes won't work because the genie is out of the bottle. A much easier way to force friction is to expect everyone to read the code they are producing. Yes read all of it and understand what it's doing. A lofty bar sadly.
  • _aavaa_ 1mo ago
    And not just the high level language output, or even the assembly. No no, every single piece of microcode produced.
    • rektomatic 1mo ago
      Why would you read the microcode or assembly?
  • nunez 1mo ago
    I'd like to see posts on the front of HN from companies who instituted PR LOC maximums, i.e. "Anything over 500-1k SLOC needs _n+1_ reviewers" (where _n_ increases every 10k SLOC. PRs needing like seven people to sign off of it might block the pipeline enough to discourage the slop flinging.
• keel-control 1mo ago
  I was thinking about this anti AI sentiment and how it is related to American individualism. In socialist countries like China there has never been a protest related to data centres or job loss etc. unlike in the USA. Because the large scale impact of AI on the country is exclusively a net positive. The reduction of the individuals cost of labour by also reduces perceived egalitarianism which is the mental model used by ultra capitalists to allow themselves to sleep at night whilst homeless people beg for food on the streets. The long term impact of AI on society is exclusively a net positive if utilised in the correct way. But most of the westerners lack faith in government fiscal policy and think that they are going to be left destitute when they can no longer provide for themselves. When in fact UBI is going to be the most likely outcome. They are myopically focusing on the short term labour market effects of AI on their own profession instead of realising the long term utopian societal outcome. "We need to ban AI because I'm going to lose my job!" - This is only said by someone who is winning in their society and wants to maintain the status quo not by those who slipped through the cracks. [copy and pasted comment from a similar post]
  • larsfaye 1mo ago
    > The long term impact of AI on society is exclusively a net positive if utilised in the correct way. Hi, I'm Earth, have we met?
• vcryan 1mo ago
  I hate to day this, but most coding work isn't hard at all - for a human or AI. There are a lot of important skills around coding, but for most people, much of the time, they are not doing any coding that is particularly challenging, difficult, it novel. If you have a truly hard problem - sure write some code or take a hybrid approach. Still, let's not pretend this is what most people are tasked with.
• hintymad 1mo ago
  [flagged]
• keybored 1mo ago
  The boss says we should do it this way. The boss hasn’t got a clue about how to do it. But he knows what he wants, more or less. And we can fill in the details. And we don’t make a stink about him not knowing exactly how things work. That doesn’t serve anyone. And he still thinks that he knows how to do it. Because he tells us how to do it and it gets done. Now everyone can be the boss.
• blutoot 1mo ago
  Software engineering >> Coding. How many times do we have to keep repeating this. Author wrote a fucking marketing piece. Stop the FUD for profit
• apatheticonion 1mo ago
  I see a large emphasis placed on headless agentic/vibe coding, what I don't see people talking about is how great guided coding is. I have over a 15 YoE writing software and guided coding sessions - that is, using an editor like Zed or VSCode with an LLM integrated, writing code how you normally would but using a flash model to prompt away the annoying parts and/or plan - is as productive as vibe coding, produces significantly higher quality, is actually enjoyable, and you actually stay sharp. Flash models (DeepSeek v4 flash) tend to be so fast that you don't have time for parallel agents, you lock in and rapid fire prompts, building high quality software while incrementally reviewing it as you go. VETO bad edits and try again or rewrite them manually. By contrast, I have noticed headless agentic coding tends to be an unreviewable black box. The major issues I've found is that, even with a human-in-the-loop, you accumulate defects which compound and eventually you're spending millions of tokens to make trivial changes in a ridgid codebase. Ultimately, tiny, highly cached, fast models like Qwen's 27b/a3b range or DeepSeek flash are highly capable and relatively inexpensive to run. Hoping people realise we don't need 14 trillion parameter models and I'll be able to buy some ram for my workstation
  • platevoltage 1mo ago
    I've gotten immense benefit from "guided coding". I've learned a lot, and it's saved me a lot of time digging through documentation. I also don't have anyone dictating to me how many tokens I should be burning, and I'm not forced to review my co-worker's 3000 line PR. I agree with your last statement. Frontier models are nonsense. We should be concentrating on focused models that are cheap to run, and don't require destroying the SBC industry, and making my hobbies financially out of reach.
  • piker 1mo ago
    Agreed. I think VS Code + Codex or similar is great, personally. I never (1) hit any kind of limits with the $20 plan or (2) lose control of the code base whatsoever. I'm also not shipping at 300x or whatever some other folks claim.
  • larsfaye 1mo ago
    This is EXACTLY how I am working with these tools, you summarized everything about why I use this approach perfectly. Zed + OpenCode + Mimo/GLM/Kimi models are incredible. I haven't touched a "frontier model" for months. I really treat them as "delegation layer". They're systems that sit right alongside your stack, and at this point, at every level in it, like a connective tissue that intersects at all points. I can delegate a spec, a function, a file, a whole feature set, an app, a debugging loop, etc.. My day-to-day isn't all that different, it's just like having the "Ship's Computer" that I can ping anytime I need something. I'm enjoying the benefits that a smart data processing pattern interpolator provides, but I'm not giving up any personal control or agency. My goal isn't to go faster, nor is it to avoid coding, because coding isn't drudgery or below us just because we have new code generation tools.
• SadErn 1mo ago
  [dead]
• adamtaylor_13 1mo ago
  I'll keep banging the drum: the foregone conclusion is that 90% of the "engineering" out there is necessary and that by "losing" these skills, Bad Things will happen. What if there's always been two general buckets (or more)? One bucket are large systems that must perform to spec, and the rest are "good enough" systems to at must simply not blow up enough to be useful (see: almost every enterprise software ever written) I'm likely wrong. But it's an interesting thought experiment. Humans have produced shit code for a long time, and it's not clear that clueless humans + shit AI code is something the market will reject.
• chrismarlow9 1mo ago
  It is still fundamentally insecure.
• 1vuio0pswjnm7 1mo ago
  1784741652 | AI Coding Will Prevent Expertise | https://larsfaye.com/articles/ai-coding-will-prevent-expertise https://larsfaye.com/articles/ai-coding-will-prevent-experti... | https://news.ycombinator.com/item?id=49010401 https://news.ycombinator.com/item?id=49010401 1784840004 | AI Coding Will Prevent Expertise | https://larsfaye.com/articles/ai-coding-will-prevent-expertise https://larsfaye.com/articles/ai-coding-will-prevent-experti... | https://news.ycombinator.com/item?id=49027909 https://news.ycombinator.com/item?id=49027909 1784909478 | AI Coding will Prevent Expertise The need for friction in skill formation | https://larsfaye.com/articles/ai-coding-will-prevent-expertise https://larsfaye.com/articles/ai-coding-will-prevent-experti... | https://news.ycombinator.com/item?id=49037730 https://news.ycombinator.com/item?id=49037730
• rogerdickey 1mo ago
  X expertise is going to collapse if we stop doing X
• agentultra 1mo ago
  It was already difficult to maintain before these tools went mainstream. I’ve worked with many a senior developer who couldn’t write a hash function, didn’t understand memory allocation, and could go on all day about best practices and lint rules. They could make things that, “work,” but couldn’t tell you why. And that was fine! It was a pain. But people need to learn. If you had experienced people around who did know those things then everyone would learn and improve. Most of the time. Also, we were limited in how much code, and therefore how much slop, we could produce. Now everyone has a firehose aimed at production. It’s hard to keep up.
• Sen_Verilot 1mo ago
  [flagged]
• socketcluster 1mo ago
  My experience is that AI has significantly boosted the value of a quality code-base. A good codebase essentially codes itself. There are project I've built from scratch that I would feel confident to hand off to a bunch of non-technical vibe coders and I know they would be productive and the product would likely be secure; because the existing codebase already exhibits all the patterns and principles that are required for that kind of project. It would probably slowly degrade over time if a lot of vibe-coded logic is added on top but I think they could get very far feature-wise whilst keeping the software reliable. But even though the value of such codebase has increased, people haven't adapted to this new reality. People are generally not good at telling what is good code. Because we don't actually have consensus on a definition. My definition is that good code is code that is easy to extend and maintain. If implementing a feature requires a huge amount of tokens, then there's a good chance the codebase is not great. I've worked on a codebase where a small feature requires might require 3k tokens, but on a different codebase, a feature of similar complexity would require 30k tokens minimum... And it's not about the size of the project; it's more about how the logic is divided and the architecture. And importantly; it's not a one-off; it's a clear observable, repeatable pattern.
• nunez 1mo ago
  This article _perfectly_ summarizes what I mean when I say that AI is "f** you, got mine" technology. Dunning-Kruger at scale, basically.
• ejboy 1mo ago
  I wouldn't say collapse. But given that we started in November 2025 (with wide adoption of Claude Code), we probably have 3 to 15 months before we see widespread impact on quality.
• iepathos 1mo ago
  I see a lot of parallels with how people were worried for decades that kids who learned with calculators wouldn't be able to do math. Instead, studies show the opposite that kids who learned with calculators do better in math even when the calculators are later removed. The reason is our learning bandwidth is limited and if you're learning multiplication and division tables you aren't learning the far more important higher level concepts. There is something similar happening with AI and most people don't understand it and we don't have enough long term studies for data to make conclusions on this yet. Engineers sounding an alarm here but they also don't have the data to support their worry. Certainly some of the lower level understanding of coding languages aren't being acquired and maintained as much as before. Whether that underlying knowledge actually needs to take up the learning bandwidth that it was taking is the real question. My hunch is that it doesn't and that dropping it makes room for higher level concepts and understanding that are actually more important given modern tooling, the same way we don't actually need to know binary and assembly to be effective engineers, but time will tell.
• Melatonic 1mo ago
  Honestly I'm not sure this is true. We may be at a point where coding is simultaneously going to stabilise and standardise more. Maybe it's time we have a new or more universal coding language we teach in schools that is strong on concepts and standardisation. Something that enforces the math, logic and mechanisms that underpin modern software. It could be designed so that any common liguisric language could apply (as in English, Japanese, French, whatever) for the broadest appeal. LLM could then translate architecture and concepts into the specific actual coding language of choice for the best fit. Of course you could also read that code and write it yourself. The whole process could be redesigned with this concept being sort of like a "super compiler". Or hell - if you really wanted to there could be dedicated ASICs with the supercompiler LLM burned in (like Talaas) that could do this on the fly or very quickly for different applications.
• gulugawa 1mo ago
  I do most of my coding with a model called MyselfGPT.
• tehnoslow 1mo ago
  [dead]
• monkaiju 1mo ago
  Happier everyday to completely avoid this cognitohazard. I'm lucky to be on a team with a no-LLM policy too! Despite that, some other parts of the business are trying their hands at playing slop slots...
• feelamee 1mo ago
  > "We see a future where intelligence is a utility like electricity or water and people buy it from us on a meter and use it for whatever they want to use it for" - Sam Altman of OpenAI true, but he missed one point - we already leave in such world. And pretty long time. He mean ofc buying intelligence of AI. But we already buying intelligence of humans.
• scoofy 1mo ago
  "Mathematics expertise is going to collapse from calculator reliance."
• deleted 1mo ago
  [deleted]
• rcr-anti 1mo ago
  I work in higher ed and have been involved in "how do we use this to help people learn" efforts since gpt 3.5 days. The method most reliable and with the best results has been treating LLMs like a glorified interface to classic expert systems. Boring state machine, problem sets and sometimes procedural generation of problems, instructor selected groupings and "hint" policy. Other applications have been building simulations, usually for chem, physics, bio, and giving an in browser agent access to the same interface as the student. Idea being this allows a flow of making predictions and observing results, demonstrating or clarifying a specific point. Counter intuitively it's made creating course material far more laborious, since we have to lay out everything much more thoroughly, plus subject matter experts have to translate it to programmers and back, versus an instructor attempting to teach inherently from their already-expert point of view.
• shadowgovt 1mo ago
  As it stands today, probably. Whether that actually has negative consequences is the more interesting question I think. Higher level languages collapsed understanding of CPU architecture and assembly level programming. But as a result, we are writing more programs, not fewer, since we're operating at a layer of abstraction that matches closer to human thought process than what is dictated by the mechanisms of the underlying machine.
• irjustin 1mo ago
  Yes and that's okay. Very few people know how to read assembly, instruction sets, binary or even transistor combos. All those layers have been "left behind" to become specializations. In many ways coding is always about abstracting and LLMs can be a form of "higher level coding". There's lots of problems with this argument, but it's what's happening and we'll be okay. We've always been.
  • geraneum 1mo ago
    > All those layers have been "left behind" to become specializations. This never happened. The people who understood and worked with all of that still exist. I wouldn’t be surprised if there’s not more of them now. What happened is more people who didn’t need to know all of that joined the circus.
  • QuantumNoodle 1mo ago
    Tell ya what. Go ahead and prompt your agent to build your next project completely from assembly. Why even bother with the higher level inefficiency since it'll be compiled away. Report back how productive debugging is and the velocity of adding new features to a codebase you can't reason about. Without strong coding fundamental, this is what it will feel like for the future of the profession.
    • irjustin 1mo ago
      Bun? Of sorts? Hard port to Rust in a week and then merged in? No way they reason about that entire thing. A business won't die just because an LLM is the only thing that can reason about a particular code base. At least, not like if a company's own engineers couldn't reason about their own code 2 years ago. I recognize you don't agree with it - our world is changing.
• somat 1mo ago
  Hell, critical thinking in general will collapse. I mean, even more than it already has due to easy access to the internet. Thinking through a problem is hard. For the most people will take any chance they can get to not think. Myself included. I probably gain double digits of IQ when my internet goes down.
• deleted 1mo ago
  [deleted]
• sjdhoome 1mo ago
  [dead]
• DesaiAshu 1mo ago
  Assembly expertise crashed from LLVM reliance
• ltbarcly3 1mo ago
  > The trillion-dollar bet that is being made is: this knowledge won't matter, because LLMs will take up the slack and effectively become the new generation of "developers". It starts give off an aire of hubris that drove past no-code movements, and the fever dreams of CEOs, rather than the reality on the ground. Yes, this is the bet being made by everyone, together. No, nobody is actually making it. The cost and benefit of a pipeline to train programmers is an externality. You do not benefit from training programmers as you do not employ them long enough to get a return on that investment. However you will hire some programmer hired by someone else and get the benefit of their investment. It kind of ended up as a wash, and there was enough 'shit shoveling' work to make it economical to keep some junior engineers around to keep senior engineers happy, and some of those junior engineers would learn and grow and end up as the next generation of actually productive engineers. This entire system has already collapsed. Junior engineers are not low value and thus low wage anymore, they are highly negative in value, as before they would puzzle on something for days and finally come back with a small PR that kind-of worked but needed revision. Now they can puke out 50,000 lines of code that they don't understand in 3 hours. You'll never be able to make them sit and just do stuff by hand, and they can't supervise an AI. Having them around means you'll have to basically ignore them and not look at whatever they are trying to do, and never use any of the code, or else you will waste orders of magnitude more senior engineer time as they are forced to de tangle the mess to even understand what it does. Or you just go with it and in 3 months you have 25 million lines of code and no person or AI can make a change anymore without breaking 15 things. There is no benefit to any company, at least in countries where you can't lock someone into a very long term contract, in hiring junior engineers anymore, so they will just stop doing this. If they did hire juniors it wouldn't help them, as they will still demand much more pay and leave if you don't give it to them the moment they can pass interviews at a more senior level. So they are just going to stop, the pipeline will dry up, and they'll pay a lot more for senior people as the supply gets more and more scarce. This is self reinforcing, the more you pay them the earlier they will retire. By the time governments and the industry are feeling enough pain to do something about this salaries will be out of control.
• vivzkestrel 1mo ago
  wrote this on a different HN thread somewhere, let me reiterate again... - it is going to be so bad that vast majority of these "i dont write code anymore" guys are going to be unable to write even a c++ hello world program without an LLM - the argument these guys come up with all the time is "I dont need to" - Big assumption there buddy, big assumption. Lets play both cases shall we. - Case 1: LLMs infinitely improve and nobody has to code anymore. Yea well, writing a paragraph spec isnt that hard for me bro, I already do it for every project while not using an LLM - Case 2: LLMS go bust completely for whatever reason. We have a whole generation of mass programmers and 99% of them cant add 2 numbers in c++. Guess what? I am now one of the most sought after programmers in the entire world and part of an absolute minority
• insane_dreamer 1mo ago
  > "Participants thought it was like having a personal tutor. From the data in our study ... we observed that they did not, in fact, use GenAI tools like a personal tutor. In fact, it was quite the opposite." And this is because if companies are pushing you to "use AI and go faster", then there's no time to learn from GenAI tools, and companies don't care if you do.
• sporkland 1mo ago
  ... and? People don't build programs using nand gates that often. I'm not gonna miss people fetishizing missing the forest for the trees in their professional lives instead focusing on other skills that produced real value. You'll still need to learn stuff and learn your craft but if you don't become an expert at programming switch statements so much the better or the next garbage web framework.
• jreynar 1mo ago
  [dead]
• othmanosx 1mo ago
  On the review part, we all know that github could be part of the problem, did you use other solutions for reviewing code like graphite or pyor.review?