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AI: Accelerated Incompetence
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Re: AI: Accelerated Incompetence
#72Remember when 3d printing was going to replace all manufacturing? Anybody? AI is closer to this sentiment than it is to the singularity.
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Re: AI: Accelerated Incompetence
#73I think you could make similar arguments about mapping technology like Google and Apple Maps -- that using them decreases people's skills in navigating the physical world, atrophying our sense of direction and geography.
And actually, that's not wrong. People really do often struggle to navigate these days if they don't have the crutch of something like Google Maps. It really has changed our relationship to the physical world in many ways.
But also, a lot of people weren't especially good at navigation before? The overall average ability of people being able to get from Point A to Point B safely and reliably, especially in areas they are unfamiliar with, has certainly increased dramatically. And a small subset of people who are naturally skilled at geography and navigation have seen their own abilities complemented, not replaces, by things like Google Maps.
I think AI will end up being similar, on a larger scale. Yes, there are definitely some trade offs, and some skills and abilities will decrease, but also many more people will be able to do work they previously couldn't, and a small number of people will get even better at what they do.
Re: AI: Accelerated Incompetence
#74I disagree with the author here. His point can be summarized as "LLMs produce bad code, LLMs lead to the teams's average skills decreasing and they can't maintain large codebases over time". Yet nowhere he addresses the #1 flaws to his position: rate of improvement of the technology, and its promise to deliver on saved money and gained speed. In all the companies I've seen engineering leadership hardly really gives a…
Your comment is talking about profitability, the op is talking about product quality. These two don't necessarily correlate.
Your examples of people "not giving a shit" about things the OP says are important & Google/Meta boasting about AI use are all revenue driven; people in leadership roles commonly place company revenue over product quality, in which case they shouldn't give a shit about the OP's topic.
As an engineer / IC I care about product quality because that's what gives me personal fulfillment. As a founder I care about product quality because I entered into this enterprise to solve a problem, not to sell a solution. Many people do the latter (very successfully) & this article isn't for those people. But it's relevant to me.
Re: AI: Accelerated Incompetence
#75Earlier quoted context omitted.
Definitely. Honestly I was going to write a custom forum in the style of those perl bboards but with https://90s.dev aesthetics (the website, not the os). But maybe first and foremost I need a mailing list so people can be notified of things like this when they're announced/released?
I'm interested. I don't think it should just be an older coders club though. It should be for anyone of any age that's into the craft of fine, well built software, and who wants to learn from people who have been into it a long time. I also like /r/tinycode for its spirit. My #1 saying in coding is "simplicity is harder than complexity." It's gone downhill like the rest of Reddit though. I'm also not totally anti-AI.…
> My #1 saying in coding is "simplicity is harder than complexity."
That's a great way of putting what I've been thinking for a few years now. It's the same reason I designed https://immaculata.dev so differently than Vite. Sure I could throw a ton of code at the problem, but carefully solving the problem correctly is both simpler and harder.
> It's gone downhill like the rest of Reddit though.
Exactly, which is part of the charm of HN. I want to capture that for 90s.dev but focused solely on software skill cultivation (and sharing the wonder and beauty and joy of writing software in the 90s) rather than the topic-soup of HN.
Re: AI: Accelerated Incompetence
#76Remember when 3d printing was going to replace all manufacturing? Anybody? AI is closer to this sentiment than it is to the singularity.
This is an easy quip to make, but it's also pretty wrong. 3D printing has been a massive breakthrough in many industries and fundamentally changed the status quo. Aerospace is a good example, much of what SpaceX and other younger upstarts in the space are doing would not be feasible without 3D printed parts. Nozzles, combustion chambers, turbopumps etc are all parts that are often printed.
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Re: AI: Accelerated Incompetence
#77Remember when 3d printing was going to replace all manufacturing? Anybody? AI is closer to this sentiment than it is to the singularity.
I honestly don’t, although maybe that hype cycle was before my time. But this seems an unfair comparison. For one, I think 3D printing made me better, not worse, at engineering (back when mechanical engineering was my jam), as it allowed me to prototype and make mistakes faster and cheaper. While it hasn’t replaced all manufacturing (or even come close), it plays an important role in design without atrophying the ski…
I find AI has the potential to do that (in my software development job): But so far I'm only using it occasionally, probably not as often as you used 3D printing.
Re: AI: Accelerated Incompetence
#78Remember when 3d printing was going to replace all manufacturing? Anybody? AI is closer to this sentiment than it is to the singularity.
This is an easy quip to make, but it's also pretty wrong. 3D printing has been a massive breakthrough in many industries and fundamentally changed the status quo. Aerospace is a good example, much of what SpaceX and other younger upstarts in the space are doing would not be feasible without 3D printed parts. Nozzles, combustion chambers, turbopumps etc are all parts that are often printed.
OP's comment and your response could both be true at same time
Re: AI: Accelerated Incompetence
#79I disagree with the author here. His point can be summarized as "LLMs produce bad code, LLMs lead to the teams's average skills decreasing and they can't maintain large codebases over time". Yet nowhere he addresses the #1 flaws to his position: rate of improvement of the technology, and its promise to deliver on saved money and gained speed. In all the companies I've seen engineering leadership hardly really gives a…
> Google and Meta also boast publicly +30% of new lines of code are AI-generated in their companies today.
Both are companies with heavy investment into their AI products, hence an extremely biased view. I’d take that with a huge grain of salt.
> assume in 5 years these AIs are 10x better... I simply cannot foresee a world
Over the last 3ish years the improvements to the performance were significant, but incremental. What makes you think that the models will continue to improve at a substantially faster rate than today? Especially considering past releases have already demonstrated the diminishing returns with larger models and more computational power. Then there is also the pressure on the training data: downwards quality as well as ongoing litigation. From my POV there is more reason to believe the future development of LLMs will slow down somewhat rather than accelerate significantly.
Re: AI: Accelerated Incompetence
#80I strongly agree with both the premise of the article, and most of the specific arguments brought forth. That said, I've also been noticing some positive aspects of using LLMs in my day-to-day. For context, I've been in the software trade for about three decades now.
One thing working with AI-generated code forces you to do is to read code -- development becomes more a series of code reviews than a first-principles creative journey. I think this can be seen as beneficial for solo developers, as in a way, it mimics / helps learn responsibilities only present in teams.
Another: it quickly becomes clear that working with an LLM requires the dev to have a clearly defined and well structured hierarchical understanding of the problem. Trying to one-shot something substantial usually leads to that something being your foot. Approaching the problem from a design side, writing a detailed spec, then implementing sections of it -- this helps to define boundaries and interfaces for the conceptual building blocks.
I have more observations, but attention is scarce, so -- to conclude. We can look at LLMs as a powerful accelerant, helping junior devs grow into senior roles. With some guidance, these tools make apparent the progression of lessons the more experienced of us took time to learn. I don't think it's all doom and gloom. AI won't replace developers, and while it's incredibly disruptive at the moment, I think it will settle into a place among other tools (perhaps on a shelf all of its own).