23 ms·

Ah, the "skill issue" argument again. Same crap aswhen everyonewas worshiping Musk 5-6 years ago, this time it's dario and altman with a claude/chatgpt mask. Cr

by axegon_ 12d ago

Ah, the "skill issue" argument again. Same crap aswhen everyonewas worshiping Musk 5-6 years ago, this time it's dario and altman with a claude/chatgpt mask. Crash can't come soon enough.

ModernMech 12d ago
I think the point is just it doesn’t have to get worse, so there are things you can do to prevent / change it if it is deteriorating.
- Sharlin 12d ago
  Yes, but it doesn't matter if nobody actually does that. Either because 1. they don't care 2. the rest of the team doesn't care 3. the powers that be actively discourage it because velocity.
  - bucket2015 12d ago
    That's a fair point. I guess step 0 is that you have to care about code/product quality and prioritize it.
  - rgoulter 12d ago
    Without LLMs, you can still have bad development processes which lead to increasing technical debt with no plan for paying it off. LLMs let you move faster. But it's not as if introducing them is the only reason your codebase isn't high quality.
    - hajile 12d ago
      When you’re required to approve thousands of lines a day (code you can’t possible understand), it certainly IS causing issues that didn’t exist before. Every study I’ve seen correlates the use of AI with large increases in the number of bugs. Look at Amazon dialing back AI after massive outages. Microsoft patch Tuesday releases are bricking computers (they even managed to break notepad somehow). The rash of Facebook bugs also coincided with their move to AI. Leaks from Google have engineers saying AI either doesn’t save any time because it takes so to remote stuff or it causes breakages if they speed up. These companies can afford to get the best devs. They have access to essentially unlimited token budgets. They have STILL fallen off a cliff in quality. What more proof could there be that this isn’t sustainable?
      - bitwize 11d ago
        A correlation-causation link between AI use and these bugs has not been established. Until it has proven to come from the region of AI-pagne, it's just sparkling enshittification.
        hajile 11d ago
        This isn’t the human body or some other thing with billions of unknown parameters. It’s a single (relatively simple) math equation that you are ascribing tons of non-existent complexity to. Left to its own devices, that system will result in AI autophagy (model collapse) and iterative degradation. The only area with serious uncertainty is how humans interact, but we now have research showing humans suffer cognitive issues very quickly using AI (some studies indicate effects happen in as little as 10 minutes) with cognitive surrender being a particularly big issue. In a lot of systems, the only new data seems to be a few brainstorming sentences (you can read slop as entropy decaying things). The AI slops that into requirements. That slop feeds into an agent which generates a bunch of “reasoning” slop, maybe compacts everything (more slop), and spins up agents that get handed slop. They then open files with who knows how many generations of slop (maybe never even touched by a human) and write out a bunch more slop (it’s ironic that humans get better the more they edit a file, but AI gets worse). That slop gets “tested” by another agent reading all the other slop and maybe all this recurses a few generations. At the end of this AI equivalent to “the human centipede”, you get a developer who’s handed 10x or maybe even 100x more code than their brain would possible process. They are suffering complete cognitive surrender (not to mention often reaching mental and maybe physical collapse from the workload and stress). They don’t understand the system and rubber stamp it so they can move on to the next 50 PRs of the day. From start to finish, it’s 100% entropy outside a handful of lines worth of human input. Many people predicted bugs and even discussed entropy issues before AI coding was popular. The buggy mess timing aligns not only with AI adoption, but happens to each company ramping up as they ramp up AI usage. This is like seeing Einstein’s predictions happen, but arguing he can’t prove correlation/causation. What evidence would you actually accept that is feasible to study?
    - Sharlin 12d ago
      So you're saying that LLMs let you accrue technical debt faster? I suppose that's like the fact that living on payday loans let you accrue monetary debt faster.
      - rgoulter 12d ago
        Yes. I think if you're on a team that cares about quality, LLMs can help you write quality code faster. If you're on a team that's mindful about technical debt, you can have make practical trade-offs for velocity now at the expense of paying off technical debt later. And if you're on a team that's unable to care about code quality ("I gotta merge this code now!"), then you can write mountains more code than you can understand.
  - axegon_ 12d ago
    Exactly. Most restaurants you go to don't care about the food they serve you nor do they care about the products they use, as long as it doesn't harm their business. Same with groceries - manufacturers don't care, as long as what they sell you is acceptable and passes regulations. But once you go to a restaurant with standards, you can immediately tell the difference. I do not come from a wealthy family and even as such, I certainly prefer paying the higher price now that I can afford it.
skybrian 12d ago
And why wouldn’t writing software be a skill issue? Yes, it’s an annoying meme, but we should expect that there are better and worse ways to write software. It would be weird if everyone got the same results regardless of experience. I’m doubtful that the author’s recommendation always work, but I do some similar things and they do seem to help.
- malfist 12d ago
  Anyone who thinks they can produce high quality code from an LLM is mistaken about how to judge code. Trust me, I've seen enough PRs to last a life time. A lot of professionals wouldn't know good code if it slapped them in the face.
  - asutekku 12d ago
    I'd argue for most people LLM produces much better code than they would be able to write themselves.
    - malfist 12d ago
      That is not an argument that LLMs produce good code
      - bluGill 12d ago
        They produce good code when I'm personally reviewing them. There are a few other people who work with who likewise know how to review code and thus can get good code out of an LLM. There are, however, a lot of people who just accept the first slop that they get out of it and that's not good code. The larger issue of good code isn't the actual individual lines, it's the overall architecture. And that's what I'm going to be reviewing first is, is this a good approach? Then the interfaces to other code is this a good interface. Get those two right and we can go back for the details. In a lot of cases, the LLM is plenty good at those details. In some cases, an LLM is better than what I could do. Well, I suppose I can trace down all the locks in all the different special cases, and I have done that, but that was a huge amount of effort that I really don't want to repeat. Note that I'm talking about recent models. If you're asking about the models of just one year ago, I would give a very different answer about the type of code an LLM produces.
Sharlin 12d ago
In a way it reminds me of the good old "if agile doesn't work for you, you're not doing agile right".
- osigurdson 12d ago
  Agree. These days, if you think you have a methodology that works better than others, you can actually try it / compare it and publish it so that others can replicate and critique your work. Articles like this one, that merely claim they've found the secret sauce, therefore should not carry much weight. That wasn't the case with 00s agile / Uncle Bob stuff since proving that any of it was helpful was impossible - you just had to believe (and if you didn't believe there was something wrong with you!).
CrimsonRain 12d ago
It is indeed skill issue. You don't think crash will happen because XYZ. You _wish_ for the crash because you are hateful of progress that you are not part of.
- mitxela 12d ago
  Studies (e.g. METR) show AI programmers think they're better but they're worse.
  - Madmallard 12d ago
    assuredly true
  - vasko 12d ago
    Anthropic's own study showed the same, yet people ignore it.
  - bitwize 11d ago
    METR has admitted that that study was flawed, and when they tried to rerun it they hit a snag: nobody wants to not use AI to code anymore!
- axegon_ 12d ago
  > You _wish_ for the crash because you are hateful of progress that you are not part of. Microsoft 2000 > You _wish_ for the crash because you are hateful of progress that you are not part of. Facebook 2008 > You _wish_ for the crash because you are hateful of progress that you are not part of. Cryptobros 2013 > You _wish_ for the crash because you are hateful of progress that you are not part of. Altman/Dario/Musk 2020-onwards. There might be a trend here...
  - SaucyWrong 12d ago
    Microsoft is a monopolist that makes some of the most hated products on earth. Facebook has been shown to derange young minds and has been a nonstop firehose of disinformation into global public discourse. Crypto moved an insane amount of wealth from the poor to the rich through and uncountable number of scams and empty promises. These? These are what you call progress? Yes, the created wealth for a few individuals, but progress? No, my friend.
hypfer 12d ago
It actually is though? Though arguably more of a process and judgement issue than skill. What makes LLM-generated code a bit special there is that misjudging how to deal with it seems to be what most people do. So the default is broken. Whereas in prior iterations of "skill issue", the default was working.
post-it 12d ago
What's a crash going to do? The internet didn't disappear after the dot com bubble popped.
rgoulter 12d ago
LLMs are not magical tools which take slop as input, and produce well thought out documentation and tests and code as a result. Over the last year, LLM coding agents gotten pretty good. It's no longer "if your results suck, you gotta try the latest and greatest model". You can get capable results on a wide variety of tasks, with a wide variety of models, used in a wide variety of ways.
mitxela 12d ago
What were people worshipping Musk for 5-6 years ago?

by axegon_ 12d ago

Ah, the "skill issue" argument again. Same crap aswhen everyonewas worshiping Musk 5-6 years ago, this time it's dario and altman with a claude/chatgpt mask. Crash can't come soon enough.

ModernMech 12d ago

I think the point is just it doesn’t have to get worse, so there are things you can do to prevent / change it if it is deteriorating.

Sharlin 12d ago
Yes, but it doesn't matter if nobody actually does that. Either because 1. they don't care 2. the rest of the team doesn't care 3. the powers that be actively discourage it because velocity.
- bucket2015 12d ago
  That's a fair point. I guess step 0 is that you have to care about code/product quality and prioritize it.
- rgoulter 12d ago
  Without LLMs, you can still have bad development processes which lead to increasing technical debt with no plan for paying it off. LLMs let you move faster. But it's not as if introducing them is the only reason your codebase isn't high quality.
  - hajile 12d ago
    When you’re required to approve thousands of lines a day (code you can’t possible understand), it certainly IS causing issues that didn’t exist before. Every study I’ve seen correlates the use of AI with large increases in the number of bugs. Look at Amazon dialing back AI after massive outages. Microsoft patch Tuesday releases are bricking computers (they even managed to break notepad somehow). The rash of Facebook bugs also coincided with their move to AI. Leaks from Google have engineers saying AI either doesn’t save any time because it takes so to remote stuff or it causes breakages if they speed up. These companies can afford to get the best devs. They have access to essentially unlimited token budgets. They have STILL fallen off a cliff in quality. What more proof could there be that this isn’t sustainable?
    - bitwize 11d ago
      A correlation-causation link between AI use and these bugs has not been established. Until it has proven to come from the region of AI-pagne, it's just sparkling enshittification.
      - hajile 11d ago
        This isn’t the human body or some other thing with billions of unknown parameters. It’s a single (relatively simple) math equation that you are ascribing tons of non-existent complexity to. Left to its own devices, that system will result in AI autophagy (model collapse) and iterative degradation. The only area with serious uncertainty is how humans interact, but we now have research showing humans suffer cognitive issues very quickly using AI (some studies indicate effects happen in as little as 10 minutes) with cognitive surrender being a particularly big issue. In a lot of systems, the only new data seems to be a few brainstorming sentences (you can read slop as entropy decaying things). The AI slops that into requirements. That slop feeds into an agent which generates a bunch of “reasoning” slop, maybe compacts everything (more slop), and spins up agents that get handed slop. They then open files with who knows how many generations of slop (maybe never even touched by a human) and write out a bunch more slop (it’s ironic that humans get better the more they edit a file, but AI gets worse). That slop gets “tested” by another agent reading all the other slop and maybe all this recurses a few generations. At the end of this AI equivalent to “the human centipede”, you get a developer who’s handed 10x or maybe even 100x more code than their brain would possible process. They are suffering complete cognitive surrender (not to mention often reaching mental and maybe physical collapse from the workload and stress). They don’t understand the system and rubber stamp it so they can move on to the next 50 PRs of the day. From start to finish, it’s 100% entropy outside a handful of lines worth of human input. Many people predicted bugs and even discussed entropy issues before AI coding was popular. The buggy mess timing aligns not only with AI adoption, but happens to each company ramping up as they ramp up AI usage. This is like seeing Einstein’s predictions happen, but arguing he can’t prove correlation/causation. What evidence would you actually accept that is feasible to study?
  - Sharlin 12d ago
    So you're saying that LLMs let you accrue technical debt faster? I suppose that's like the fact that living on payday loans let you accrue monetary debt faster.
    - rgoulter 12d ago
      Yes. I think if you're on a team that cares about quality, LLMs can help you write quality code faster. If you're on a team that's mindful about technical debt, you can have make practical trade-offs for velocity now at the expense of paying off technical debt later. And if you're on a team that's unable to care about code quality ("I gotta merge this code now!"), then you can write mountains more code than you can understand.
- axegon_ 12d ago
  Exactly. Most restaurants you go to don't care about the food they serve you nor do they care about the products they use, as long as it doesn't harm their business. Same with groceries - manufacturers don't care, as long as what they sell you is acceptable and passes regulations. But once you go to a restaurant with standards, you can immediately tell the difference. I do not come from a wealthy family and even as such, I certainly prefer paying the higher price now that I can afford it.

skybrian 12d ago

And why wouldn’t writing software be a skill issue? Yes, it’s an annoying meme, but we should expect that there are better and worse ways to write software. It would be weird if everyone got the same results regardless of experience. I’m doubtful that the author’s recommendation always work, but I do some similar things and they do seem to help.

malfist 12d ago
Anyone who thinks they can produce high quality code from an LLM is mistaken about how to judge code. Trust me, I've seen enough PRs to last a life time. A lot of professionals wouldn't know good code if it slapped them in the face.
- asutekku 12d ago
  I'd argue for most people LLM produces much better code than they would be able to write themselves.
  - malfist 12d ago
    That is not an argument that LLMs produce good code
    - bluGill 12d ago
      They produce good code when I'm personally reviewing them. There are a few other people who work with who likewise know how to review code and thus can get good code out of an LLM. There are, however, a lot of people who just accept the first slop that they get out of it and that's not good code. The larger issue of good code isn't the actual individual lines, it's the overall architecture. And that's what I'm going to be reviewing first is, is this a good approach? Then the interfaces to other code is this a good interface. Get those two right and we can go back for the details. In a lot of cases, the LLM is plenty good at those details. In some cases, an LLM is better than what I could do. Well, I suppose I can trace down all the locks in all the different special cases, and I have done that, but that was a huge amount of effort that I really don't want to repeat. Note that I'm talking about recent models. If you're asking about the models of just one year ago, I would give a very different answer about the type of code an LLM produces.

Sharlin 12d ago

In a way it reminds me of the good old "if agile doesn't work for you, you're not doing agile right".

osigurdson 12d ago
Agree. These days, if you think you have a methodology that works better than others, you can actually try it / compare it and publish it so that others can replicate and critique your work. Articles like this one, that merely claim they've found the secret sauce, therefore should not carry much weight. That wasn't the case with 00s agile / Uncle Bob stuff since proving that any of it was helpful was impossible - you just had to believe (and if you didn't believe there was something wrong with you!).

CrimsonRain 12d ago

It is indeed skill issue. You don't think crash will happen because XYZ. You _wish_ for the crash because you are hateful of progress that you are not part of.

mitxela 12d ago
Studies (e.g. METR) show AI programmers think they're better but they're worse.
- Madmallard 12d ago
  assuredly true
- vasko 12d ago
  Anthropic's own study showed the same, yet people ignore it.
- bitwize 11d ago
  METR has admitted that that study was flawed, and when they tried to rerun it they hit a snag: nobody wants to not use AI to code anymore!
axegon_ 12d ago
> You _wish_ for the crash because you are hateful of progress that you are not part of. Microsoft 2000 > You _wish_ for the crash because you are hateful of progress that you are not part of. Facebook 2008 > You _wish_ for the crash because you are hateful of progress that you are not part of. Cryptobros 2013 > You _wish_ for the crash because you are hateful of progress that you are not part of. Altman/Dario/Musk 2020-onwards. There might be a trend here...
- SaucyWrong 12d ago
  Microsoft is a monopolist that makes some of the most hated products on earth. Facebook has been shown to derange young minds and has been a nonstop firehose of disinformation into global public discourse. Crypto moved an insane amount of wealth from the poor to the rich through and uncountable number of scams and empty promises. These? These are what you call progress? Yes, the created wealth for a few individuals, but progress? No, my friend.

hypfer 12d ago

It actually is though? Though arguably more of a process and judgement issue than skill. What makes LLM-generated code a bit special there is that misjudging how to deal with it seems to be what most people do. So the default is broken. Whereas in prior iterations of "skill issue", the default was working.

post-it 12d ago

What's a crash going to do? The internet didn't disappear after the dot com bubble popped.

rgoulter 12d ago

LLMs are not magical tools which take slop as input, and produce well thought out documentation and tests and code as a result. Over the last year, LLM coding agents gotten pretty good. It's no longer "if your results suck, you gotta try the latest and greatest model". You can get capable results on a wide variety of tasks, with a wide variety of models, used in a wide variety of ways.

mitxela 12d ago

What were people worshipping Musk for 5-6 years ago?