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“I built a thing with AI and I don’t understand it. I want to make changes and fix things and have no ability to theorize why it fails or how to fix it.” Oh my

“I built a thing with AI and I don’t understand it. I want to make changes and fix things and have no ability to theorize why it fails or how to fix it.” Oh my. See, you have to be able to program it yourself before you can build it with an LLM. Otherwise you have no way of judging the output. AI isn’t going to make you a programmer. Learning to program is. Interesting article. My advice is to do it the old fashioned, hard way. There’s no royal road to knowledge, skill, and learning.

JeremyNT 17d ago
> Interesting article. My advice is to do it the old fashioned, hard way. There’s no royal road to knowledge, skill, and learning. I had a colleague tell me "it's not vibe coding when a programmer does it." I fully believe there's still value in understanding the internals of software and the patterns developers use to structure it, but I do wonder for how much longer any of this knowledge will be more than of academic interest.
meowface 17d ago
A lot of successful startups start out with good ideas and atrocious, unmaintainable code. Current LLMs kind of let you speedrun that. Dutifully slapping more and more mud onto their week-old ball of mud. The sacred, canonical ball of mud they must faithfully preserve at all costs. But the product will probably work decently enough. And as long as the humans are sufficiently devoted to testing and nitpicking and improving the product design and UX choices made by the LLM, they can get away with not caring much about its system design. Also, by the time the code really needs to be rewritten (1 - 3 years), the latest models will probably be noticeably less bad at this. Humans who are persistent enough in their attempts to tip the model away from these basins already see at least some success. Combined with other general improvements, model companies will probably find ways to do more post-training on not just "can it complete all of these isolated coding tasks with a 100% pass rate" but "can it consistently inhabit a mindset that values the art of elegant code and simple, clean architecture as an intrinsic goal over a very long time horizon". Perhaps in a way where a harness instruction can make the model especially tap into that mode. You're right that even in years from now an experienced programmer will get better results with an LLM than a non-programmer will, but I think with each passing year that gap will slowly shrink. Learning programming will always only ever help, but if the non-programmer actually has sufficiently good ideas that they want to start working on immediately, it probably actually is a better use of their time to make the initial version before knowing anything about software development and then to teach themselves (real) software development as they continue working on things. I think this would be the case even if LLMs never got any better than they are today, and I think they're almost definitely going to get way better at programming than they are today.
- agentultra 17d ago
  I think the harnesses might get better. And the alignment and pre training. But I don’t think the LLMs will get much better… I don’t have any sources for that though. Just napkin math. At the end of the day, even if it gets to 99.9999% reliably generate what an experienced programmer would expect… you still need to be an experienced programmer to know what to want and how to specify it. I think the experience, institutional knowledge, and process knowledge are never going to be replaceable. You’ll still need to learn what a cache miss is and how the heap works and when to use skip lists and all that. Otherwise you will just generate slop. An AI system is not able to replace a human.
xboxnolifes 17d ago
We're relearning why you do math by hand before you use a calculator, and why you (usually) dont get internet access during tests even though in the real world you can quickly look things up.

JeremyNT 17d ago

> Interesting article. My advice is to do it the old fashioned, hard way. There’s no royal road to knowledge, skill, and learning. I had a colleague tell me "it's not vibe coding when a programmer does it." I fully believe there's still value in understanding the internals of software and the patterns developers use to structure it, but I do wonder for how much longer any of this knowledge will be more than of academic interest.

meowface 17d ago

A lot of successful startups start out with good ideas and atrocious, unmaintainable code. Current LLMs kind of let you speedrun that. Dutifully slapping more and more mud onto their week-old ball of mud. The sacred, canonical ball of mud they must faithfully preserve at all costs. But the product will probably work decently enough. And as long as the humans are sufficiently devoted to testing and nitpicking and improving the product design and UX choices made by the LLM, they can get away with not caring much about its system design. Also, by the time the code really needs to be rewritten (1 - 3 years), the latest models will probably be noticeably less bad at this. Humans who are persistent enough in their attempts to tip the model away from these basins already see at least some success. Combined with other general improvements, model companies will probably find ways to do more post-training on not just "can it complete all of these isolated coding tasks with a 100% pass rate" but "can it consistently inhabit a mindset that values the art of elegant code and simple, clean architecture as an intrinsic goal over a very long time horizon". Perhaps in a way where a harness instruction can make the model especially tap into that mode. You're right that even in years from now an experienced programmer will get better results with an LLM than a non-programmer will, but I think with each passing year that gap will slowly shrink. Learning programming will always only ever help, but if the non-programmer actually has sufficiently good ideas that they want to start working on immediately, it probably actually is a better use of their time to make the initial version before knowing anything about software development and then to teach themselves (real) software development as they continue working on things. I think this would be the case even if LLMs never got any better than they are today, and I think they're almost definitely going to get way better at programming than they are today.

agentultra 17d ago
I think the harnesses might get better. And the alignment and pre training. But I don’t think the LLMs will get much better… I don’t have any sources for that though. Just napkin math. At the end of the day, even if it gets to 99.9999% reliably generate what an experienced programmer would expect… you still need to be an experienced programmer to know what to want and how to specify it. I think the experience, institutional knowledge, and process knowledge are never going to be replaceable. You’ll still need to learn what a cache miss is and how the heap works and when to use skip lists and all that. Otherwise you will just generate slop. An AI system is not able to replace a human.

xboxnolifes 17d ago

We're relearning why you do math by hand before you use a calculator, and why you (usually) dont get internet access during tests even though in the real world you can quickly look things up.