4 ms·

If you truly think LLM are not useful tools for programming, you haven't tried the right tools.

by eloisant 17d ago

jeltz 17d ago
That is not the same topic. LLMs are useful tools, and that is despite them producing fucking awful code.
- Gigachad 17d ago
  I would have agreed with you 6 months ago but things have changed rapidly.
  - wizzwizz4 17d ago
    People say this every 6 months. I've stopped even paying attention to it, because (A) the code quality remains below the floor, and (B) the people saying it continue to ignore all the other issues with LLM code generation.
    - Zambyte 16d ago
      Up until the last couple of months, I have treated LLMs as a supercharged stackoverflow. I would ask it questions on how to do something in a general sense, and then adapt the answer to my use case. Now, my entire programming flow does not even include an editor. The tools I use are: pi.dev to write and implement openspec specifications, herdr to manage many pi instances, and ollama to run qwen 3.8 27b on my single 7900 XTX. Writing good specifications is the key detail here. I will often iterate on a spec for hours until I am happy with it all of the details. Once I am happy with the spec, I can be quite confident that when I tell pi to apply the spec, the changes that I want will be done, and done how I want them, when I come back to check when it reports itself as done. The landscale is fundamentally different from what it was. Feel free to ignore it, but you can absolutely generate high quality code if you know what you're doing.
      - panny 16d ago
        >ollama to run qwen 3.8 27b Installed this recently to try it out. >pi.dev to write and implement openspec specifications, herdr to manage many pi instances Thanks for mentioning the tools you're using successfully. It seems like most people using LLMs are keen to keep their cards close to their chest.
        Zambyte 16d ago
        No problem. I think it's less of people withholding information to have an advantage, and more people still not having settled on a workflow they like. Herdr is the most recent addition in my workflow as of only a few days ago, but it directly solves problems I have been having (juggling tons of terminals, even with my tiling wm has been a little unwieldy). The rest I've pretty much settled into for a while now.
        Zambyte 15d ago
        The other tool I wanted to throw out there is voxtype (plus wtype). I've been looking for a good, global, local dictation solution for wayland for a while now, and finally landed on this one. It's great for rambling details that pi+qwen can then convert into concrete openspec specifications.
    - kuboble 16d ago
      N=1 and might be a raw skill issue on my end. But I all but stopped writing code 13 months ago. At the beginning the code was often bad. In the last 6 months alone I had received more praise from my customers for excellent work than ever before.
  - jeltz 16d ago
    Not sure what I can say but the LLMs simply do not write good code without tons of handholding. As a C developer most LLMed patches I have seen the last couple of months have been awful and the few good ones I know from the author themselves that they did a ton of iteration and/or manual cleanup. Maybe they are less bad at writing other languages.
    - Gigachad 16d ago
      At least what I have seen in Ruby and Typescript, they are excellent at doing what you asked for. But if what you asked for is stupid they will happily make it happen. They don’t make normal mistakes like typos and they aren’t lazy so things like tests and checking error cases is usually done.
roblabla 17d ago
I tried a lot of tools. Claude code, deepseek with kilocode and OMP, codex... I still use claude quite a bit. But frankly, all of them produce some absolutely godawful code. Review load went way up with AI, and it's not just the volume that caused it, but also the quality. It's extremely verbose, hard to read, often repeats code instead of factoring it into reusable components. And yes, sometimes it's also buggy. Except now, you have to debug a problem that's in code you didn't write yourself, and is awful to read. LLM is incredibly valuable for debugging complex problems, codebase exploration, and planning large changes. But the writing code part itself, I find, LLMs are just not very good at it yet.
- api 16d ago
  I’ve had some luck prompting them to be concise, both in writing and in code, and with code doing an approach where they get it working, write tons of tests, and then refactor for conciseness and readability. All the tests prevent regressions doing this. Without such prompting and a conciseness and clarity pass you get a slop grenade. They overall work better with tests, and Rust is a great language for them. Overall they do better with lots of walls and alarms that go off if they mess up. I don’t need nearly as much of this, can mentally simulate it, which is a good “are we superintelligence yet” reality check. Still not even as good as my wet meat brain. But impressive given what was possible even two years ago! The result is still not as clean as a good programmer but it’s better than the slop grenade you get first pass.
- user43928 16d ago
  I don't have to debug anything. Vaguely telling the agent what the issue is and what behavior I expect solves the issue with a fraction of the effort. Some claim that the tech debt only keeps increasing and that the result will be unmaintainable. This is not my experience, and I don't think it is theirs either. These claims are often entirely speculative.
  - RHSeeger 16d ago
    I, and I think most experienced developers, can recognize the type of code that incurs a maintenance cost down the line; that will make adding new code take longer. And AI writes such code "relatively" frequently. I love having the AI to write code, but I find it extremely important to review it - to make sure that it's correct, understandable, and not going to be a problem later.

If you truly think LLM are not useful tools for programming, you haven't tried the right tools.

jeltz 17d ago

That is not the same topic. LLMs are useful tools, and that is despite them producing fucking awful code.

Gigachad 17d ago
I would have agreed with you 6 months ago but things have changed rapidly.
- wizzwizz4 17d ago
  People say this every 6 months. I've stopped even paying attention to it, because (A) the code quality remains below the floor, and (B) the people saying it continue to ignore all the other issues with LLM code generation.
  - Zambyte 16d ago
    Up until the last couple of months, I have treated LLMs as a supercharged stackoverflow. I would ask it questions on how to do something in a general sense, and then adapt the answer to my use case. Now, my entire programming flow does not even include an editor. The tools I use are: pi.dev to write and implement openspec specifications, herdr to manage many pi instances, and ollama to run qwen 3.8 27b on my single 7900 XTX. Writing good specifications is the key detail here. I will often iterate on a spec for hours until I am happy with it all of the details. Once I am happy with the spec, I can be quite confident that when I tell pi to apply the spec, the changes that I want will be done, and done how I want them, when I come back to check when it reports itself as done. The landscale is fundamentally different from what it was. Feel free to ignore it, but you can absolutely generate high quality code if you know what you're doing.
    - panny 16d ago
      >ollama to run qwen 3.8 27b Installed this recently to try it out. >pi.dev to write and implement openspec specifications, herdr to manage many pi instances Thanks for mentioning the tools you're using successfully. It seems like most people using LLMs are keen to keep their cards close to their chest.
      - Zambyte 16d ago
        No problem. I think it's less of people withholding information to have an advantage, and more people still not having settled on a workflow they like. Herdr is the most recent addition in my workflow as of only a few days ago, but it directly solves problems I have been having (juggling tons of terminals, even with my tiling wm has been a little unwieldy). The rest I've pretty much settled into for a while now.
        Zambyte 15d ago
        The other tool I wanted to throw out there is voxtype (plus wtype). I've been looking for a good, global, local dictation solution for wayland for a while now, and finally landed on this one. It's great for rambling details that pi+qwen can then convert into concrete openspec specifications.
  - kuboble 16d ago
    N=1 and might be a raw skill issue on my end. But I all but stopped writing code 13 months ago. At the beginning the code was often bad. In the last 6 months alone I had received more praise from my customers for excellent work than ever before.
- jeltz 16d ago
  Not sure what I can say but the LLMs simply do not write good code without tons of handholding. As a C developer most LLMed patches I have seen the last couple of months have been awful and the few good ones I know from the author themselves that they did a ton of iteration and/or manual cleanup. Maybe they are less bad at writing other languages.
  - Gigachad 16d ago
    At least what I have seen in Ruby and Typescript, they are excellent at doing what you asked for. But if what you asked for is stupid they will happily make it happen. They don’t make normal mistakes like typos and they aren’t lazy so things like tests and checking error cases is usually done.

roblabla 17d ago

I tried a lot of tools. Claude code, deepseek with kilocode and OMP, codex... I still use claude quite a bit. But frankly, all of them produce some absolutely godawful code. Review load went way up with AI, and it's not just the volume that caused it, but also the quality. It's extremely verbose, hard to read, often repeats code instead of factoring it into reusable components. And yes, sometimes it's also buggy. Except now, you have to debug a problem that's in code you didn't write yourself, and is awful to read. LLM is incredibly valuable for debugging complex problems, codebase exploration, and planning large changes. But the writing code part itself, I find, LLMs are just not very good at it yet.

api 16d ago
I’ve had some luck prompting them to be concise, both in writing and in code, and with code doing an approach where they get it working, write tons of tests, and then refactor for conciseness and readability. All the tests prevent regressions doing this. Without such prompting and a conciseness and clarity pass you get a slop grenade. They overall work better with tests, and Rust is a great language for them. Overall they do better with lots of walls and alarms that go off if they mess up. I don’t need nearly as much of this, can mentally simulate it, which is a good “are we superintelligence yet” reality check. Still not even as good as my wet meat brain. But impressive given what was possible even two years ago! The result is still not as clean as a good programmer but it’s better than the slop grenade you get first pass.
user43928 16d ago
I don't have to debug anything. Vaguely telling the agent what the issue is and what behavior I expect solves the issue with a fraction of the effort. Some claim that the tech debt only keeps increasing and that the result will be unmaintainable. This is not my experience, and I don't think it is theirs either. These claims are often entirely speculative.
- RHSeeger 16d ago
  I, and I think most experienced developers, can recognize the type of code that incurs a maintenance cost down the line; that will make adding new code take longer. And AI writes such code "relatively" frequently. I love having the AI to write code, but I find it extremely important to review it - to make sure that it's correct, understandable, and not going to be a problem later.