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[–] 70 points 6 months ago (54 children)

We need the equivalent investment now. If average code is cheap, then the scarce resource is no longer the ability to produce it. The scarce resource is the ability to read it, to navigate it

You know what would help a lot with understanding the code one is working on? Writing it yourself without turning your brain off via AI.

But that's an insight the article somehow seems to be missing.

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  • [+] -15 points 6 months ago (44 children)
  • [–] 28 points 6 months ago (13 children)

    I have over 25 years of development experience. My current role is vice president of development and architecture where I lead a team of 80+ devs, QAs, and architects. By any measure, I am one of those "engineer level" developers you speak of.

    Yes, LLMs are a tool, but it's a tool one should use sparingly. LLMs are pattern recognition machines and are great for routine, been-there-done-that type development. For anything that deviates from the norm, LLMs will try to force everything back into common patterns... even when those patterns are not correct. A well designed system can be mangled into junk because the LLM doesn't have enough context or because something is new.

    Be skeptical of the rave reviews around coding agents and the use of LLMs for development. Much of the hype seems tied to developer skill. Less capable developers can use LLMs to appear more capable than they are. For good developers, LLMs seem to erode their skills as they rely on the tool instead of their own knowledge. I have seen this first hand.

    Overall, it seems LLMs raise skills of bad developers and hamper the skills of good developers. It's creating a bunch of middling developers who are incapable of handling anything novel or complex.

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  • [+] 27 points 6 months ago* (last edited 1 month ago) (3 children)
  • [–] 11 points 6 months ago* (5 children)
  • [–] 6 points 6 months ago (4 children)

    please review this Lemmy thread and come up with a good way to keep moving the goal posts so that I can feel like I'm right

    @onlinepersona prompting chatgpt right now

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  • [–] 4 points 6 months ago*

    My degree is in Computer Engineering, dipshit.

    You made up this fantasy that somehow I don't know what I'm talking about based on nothing other than you wanting me to be wrong so your world view isn't challenged.

    I stared out with the assumption that you were having a good faith discussion. It's now clear that you're a troll, tech bro, AI lover, or all of the above. At this point, I'm done with you and encourage others to be as well.

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  • [+] 12 points 6 months ago (6 children)
  • [–] 10 points 6 months ago* (last edited 6 months ago) (3 children)

    I also think there still hasn't been a study showing consistent long term significant(!) productivity gain for coders. (Other than lines of code in total, but that alone is a poor measure.) The amount of new hidden bugs and other issues seem to outweigh most of the perceived gains.

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  • [–] 23 points 6 months ago (4 children)

    LLMs are a tool that can lift up the quality of coding work

    Imagine telling on yourself like this.

    And that is right after implying that you are a "proficient professional coder" that is "like engineer level" unlike those pesky "anti ai warriors". Jesus fucking Christ.

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  • [–] 7 points 6 months ago (2 children)

    My entire point was in one single sentence, and yet you managed to shit out three sentences, not even remotely addressing that.

    I'm saying that if the output puked out by an LLM is of better quality than your own code, something you literally just confessed to, then you're nothing but a hack. An impostor.

    What does the fact that you've been training anyone have to do with that? What does a degree, or lack thereof, have to do with anything? I've seen plenty of hacks employed as "seniors", some with a CompSci degree. The kind of hacks that used to be overly reliant on StackOverflow in the past. The kind of hacks that write poorly performing garbage, yet quote Knuth's "premature optimization is the root of all evil" (completely missing the context) when you confront them about it.

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  • [–] 2 points 6 months ago

    I mean its more like self driving cars than cars themselves; it can work, but also steering wheels were created by the devs for a reason - even if most are too lazy to understand that reason.

    Like I'd agree hand coding in assembly is (mostly) useless these days, but honestly I feel like the efficiency problems ai is trying to solve were largely solved 50 years ago with compilers.

    (and like isnt digesting large outputs the entire point of being an engineering level dev? like if youre just there to pray to the software gods, you'd do much better as a CRUD script kiddie anyways)

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  • [–] 3 points 6 months ago (12 children)

    Even if AI were the miracle people like you suggest, you're still destroying the environment. But also it's not miraculous. Which you conflictingly say is and is not the case...

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  • [+] -5 points 6 months ago (11 children)
  • [–] 11 points 6 months ago* (7 children)

    All the studies I've found so far seem to disagree, so why should we believe you?

    https://www.anthropic.com/research/AI-assistance-coding-skills (2026 study)

    We found that using AI assistance led to a statistically significant decrease in mastery.

    Using AI sped up the task slightly, but this didn’t reach the threshold of statistical significance.

    https://futurism.com/artificial-intelligence/new-findings-ai-coding-overhyped (2025 study)

    But those claims appear to be massively overblown, as The Register reports, with researchers finding that productivity gains are modest at best — and at worst, that AI can actually slow down human developers.

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  • [+] 0 points 6 months ago (6 children)
  • [–] 2 points 6 months ago* (5 children)

    AIs are (apparently) stupid and fail at non-trivial tasks. They also enjoy deleting production databases. They seem atrocious with any sort of quality.

    What would AI possibly be useful for, if you care about quality work?

    (I suppose they can sometimes help with vulnerability scanning and writing mindless e-mails if you're some sort of overworked customr agent, but those are pretty narrow uses. And I'm not going to upload my stuff to big tech data sloppers myself just for some slightly better vulnerability scanning.)

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  • [+] 1 point 6 months ago (4 children)
  • [–] 2 points 6 months ago* (3 children)

    That's the thing, I don't think LLMs bring many benefits. Too many lies, and so on.

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  • [–] 2 points 6 months ago (2 children)

    Explain how this amount of electricity use could ever be "ethically sourced". That's not even much of a thing for meat, which at least provides nutrients. AI slop is everywhere and most of it is not helping anyone with anything.

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  • [–] 1 point 6 months ago* (1 child)

    There are definitely real engineers being strongly anti-AI. The problem, in my opinion, is that they just didn't really try working with them.

    They're incredibly powerful tools, and they don't only amplify bad developers, they amplify every developer that really tries to work with it.

    The mistake people make is delegating the decision making to the AI. Let the tool be a tool, not a brain. You architect, you design, you order, it writes the code. You review the code. There you go, you have a pretty good quality code, better than most devs will produce, following your design and architecture, you controlled the entire decision making, and you did it in 5x less time.

    I also think that it has become too useful to disappear in engineering.

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  • [+] -6 points 6 months ago (8 children)

    Take away a calculator halfway through an exam, and suddenly, people are surly and unmotivated about simple long division.

    That's how every 'AI makes you stupid!' article works. Like, 'doctors used AI to detect more cancer, but when we took it away, they were worse at eyeballing it.' Sorry, can we go back to the part about detecting cancer better?

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  • [–] 8 points 6 months ago* (7 children)

    The doctors were worse, not just taking longer. So this would be more like people unlearning division.

    While people using calculators may occasionally be unlearning division, this seems less problematic than doctors unlearning how to spot cancer on their own (since then I'm guessing you won't have AI training data anymore since apparently AI can't feed into AI without collapse) or software engineers unlearning how to write correct code.

    You also wouldn't want a mathematician unlearning how to do division.

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  • [–] 0 points 6 months ago (6 children)

    The doctors were better, until someone yanked the tool away. That's how every tool works! Even going from a handsaw to a table saw and back will make you lose some skill with the handsaw, because your brain focused on higher-level goals and finer motions. That's not proof a table saw is bad for woodworking. The problem is "and back."

    since apparently AI can’t feed into AI without collapse

    Have you checked on that narrative? It's been a while. Things stopped getting yellow. Improvements continued.

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  • [–] 2 points 6 months ago* (5 children)

    Have you checked on that narrative?

    The only workaround known so far seems to be to make sure enough data is fresh: https://www.inria.fr/en/collapse-ia-generatives https://en.wikipedia.org/wiki/Model_collapse But read for yourself.

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  • [–] 0 points 6 months ago (4 children)

    That's a lot of "could" and "will" from an article a year old, primarily about concerns from two years ago, while image models to-day keep getting smaller and better. They didn't find a second internet's worth of JPEGs. Better training on the same data, or even better labels on less data, beats a simple obsession with scale.

    Yes, photocopying a photocopy will degrade, but diffusion is a denoising algorithm. Un-degrading an image is its central function. 'Make it look less AI' is how you get generative adversarial networks.

    Anyway, the grim truth is that the central concern is mistaken. Training data for cancer screening does not require the patient lived.

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  • [–] 2 points 6 months ago* (3 children)

    The article links a study. What's your study that collapse isn't a concern?

    For what it's worth, my worry was never focused on cancer, these doctors were just an example measured for the likely universal unlearning effect.

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  • [–] 0 points 6 months ago* (2 children)

    I again submit the last two years where model collapse did not happen. The doom-and-gloom predictions - some rather gleeful - plainly missed the mark. The proliferation of generated content has not in fact ruined the content generators, and it's sure not because we're any good at marking generated content. Early symptoms went away entirely and the problem has been practically addressed.

    As for "unlearning," universality is why it's a made-up problem. Nobody loudly complains that x-rays make doctors worse at feeling around for lumps.

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  • [–] 2 points 6 months ago (1 child)
  • [–] 1 point 6 months ago

    This is approaching unfalsifiable.

    Is classifying generated data ever intractable, when you can just... generate some? Even if the portion of human content dwindled - rather new human content, since there's a recent hard cutoff - there's a faucet for counterexamples. You can have as much for-sure machine-generated content as you like, to point at and go, wrong.

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