6 ms·

Seems like the wrong question to ask. I've been programming my whole life but basically stopped writing code by hand in 2026. The LLM writes better code than I

by edg5000 19d ago

Seems like the wrong question to ask. I've been programming my whole life but basically stopped writing code by hand in 2026. The LLM writes better code than I do, much better.

9cb14c1ec0 19d ago
Same here. I'm still a better software architect that AI, but there is no question that my AI generated and reviewed code has fewer bugs than code I hand write. It takes some humility to acknowledge that your coding prowess is less of a useful skill than it used to be.
- cik 19d ago
  There's an issue where people assumed the syntactic activity of writing code was what mattered. The reality is that this was always a smaller part of the role, as opposed to thinking about observability, serviceability, and test automation. The ability to write software that is properly separated from concerns and when to enact those separations matters. At the same time, I think we're far too far down the systems path now. We've hit a point where interviewing has become purely systems design "because the AI writes the code". Not that I'm ever asked, but I inherently believe the act of critical thinking, communication, and expression are the key skills for those who already have the appropriate coding/engineering/cs/etc background. I now only interview for those skills - but through the lens of impossible to solve systems design conversations as opposed to problems. It tells me a lot about how people think.
  - jeltz 19d ago
    Not sure what you mean as system design conversations because while in theory those can be good in practice the ones I have been at had been techbro wankery where the interviewer had a particular answer in mind. Like designing your own memcached clone for example is a terrible task for systems design.
    - cik 19d ago
      What you're mentioning is 100% what's wrong with the industry. Agreed! To me a systems design conversation is a conversation - not a design goal. The idea is to determine ability and psychology: 1. When you press on someone's design respectfully, do they get defensive. Do they become argumentative. 2. When thoughtfully pointing out a concern, how does the candidate take it? 3. When you suggest a technology that makes no sense to intentionally challenge knowledge, does the candidate recognize why it makes no sense? Are they able to share what the negative of the approach is. If you indicate that you know the question is "senseless" but want their feedback, how do they communicate? 4. When you hard request a change that requires a literal rethink and rewrite do they become argumentative? Do they embrace the change? 5. When discussing testing, how do they think about it? I come down to the nitty gritty and ask about postive vs negative cases, table driven testing, what types of tests matter (for our situation) and why. 6. We discuss timeline tradeoffs, and then have the conversation about the candidate's approach given updates to see how they think. You'll notice that I am never looking for a solution. I'm seeking communication, description, partnership while having a (relatively) thorough gasp of the subject matter. Every single time I get a response from a candidate such as "I don't know, I'd have to learn more - or use AI to, or.. what do you think" turns out to be something I LOVE, because it creates a great fabric for the interview.
  - 0x696C6961 19d ago
    Writing is thinking
    - tomrod 19d ago
      So is architecting, testing, validating, and even occasionally using. This isn't the first time I've seen this phrase recently, but I'm not sure what the thought is a cliche or what it is intended to convey (don't read my note as negative, I sincerely am unsure what connotation folks are trying to say).
      - jplusequalt 19d ago
        The idea behind "writing is thinking" is that people often overestimate their understanding until pressed to express it in words (or code). How many times in your career did you sit down to tackle a task thinking you knew exactly how to approach it only to realize during implementation that there were edge cases you hadn't considered, API contracts that were now broken, or that the feature was trying to solve the wrong problem. Having to be the one at the helm during implementation made you intimately aware of not only the problem at hand, but the current state of the codebase. That's something you can't replace with automation. You can't compress all of that context into your brain in a handful of prompts with Claude. Remember the words of your math teacher-- "Watching someone else solve the problem doesn't mean you can now solve it too."
- markb139 19d ago
  Programming languages, design languages and architecture are all inventions made to help humans write understandable source. LLMs don’t really need to do any of that. They can store very large trees of understanding and therefore implement any application in raw binary. Why bother with abstractions at all
  - jeltz 19d ago
    LLMs for sure need those things. maybe not the same abstractions as humans do but without understabdable code an LLM will just fail to accomplish the task you ask it to do.
  - flir 19d ago
    It might be less ambitious and more practical to target bytecode. But you effectively lose the human review component.
    - _1 19d ago
      There's more python and typescript in the training data than bytecode.
      - flir 19d ago
        I was thinking about that. I reckon generating massive amounts of synthetic training data for that goal should be possible - you've already got the Python, after all. It's also possible for machine code, but you'd have to target more platforms. But ultimately, I think human readability outweighs any theoretical advantage you get from removing a step in the compilation process.
    - redox99 19d ago
      Targeting byte code or asm instead of high level would be silly for everyday tasks. You blow up the number of tokens, reduce your effective context, and there's just more places for it to make a mistake, which most likely won't be caught by the assembler (unlike compilers).
dakolli 19d ago
Well, you must have some low fkn standards.
- eloisant 19d ago
  If you truly think LLM are not useful tools for programming, you haven't tried the right tools.
  - jeltz 19d ago
    That is not the same topic. LLMs are useful tools, and that is despite them producing fucking awful code.
    - Gigachad 19d ago
      I would have agreed with you 6 months ago but things have changed rapidly.
      - wizzwizz4 19d 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 19d 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.
staszewski 19d ago
Skill issue then
- 0x000xca0xfe 19d ago
  I just asked Astra to bring an old Windows XP game to the browser. It objdump'ed the whole thing, built a fitting Win32-like wrapper that exposes required functionality like DirectDraw, DirectSound, SEH etc., then wrote an x86-32/x87 interpreter in WASM, benchmarked how the game runs, lifted the hotspots of the executable to WASM too and now it is playable! I mean, I'm proud of my low-level skills too but this is some Fabrice Bellard level sorcery. Very, very few humans are able to do this without AI tools.
  - erfgh 19d ago
    If there are very few humans that can do this is because the market for such a task is very small and thus there is little incentive to learn how to do it or produce tools that can do it.
  - RHSeeger 19d ago
    But good code isn't just "does it work", it's also - is it understandable - is it maintainable - how much work is adding new features - is it written in a way that adding new features means rewriting a lot of it - is it written in a consistent style - and lots of other things I use AI to write a lot of my code, but the only time it's clearly "better" than a competent human is for one-off things. That being said - AI + human is, without any doubt in my mind, better than either one alone.
    - tomrod 19d ago
      Aye. Some of these targets are far away, others perhaps closer. Human+AI systems is a good match. Like Human+docs or Human+encyclopedia.
    - ModernMech 19d ago
      - is it understandable Yes you can ask the agent anything about it and interrogate it until you understand. - is it maintainable Yes it’s easy to ask the ai to add new features or to refactor it entirely. - how much work is adding new features Depends, it could just be one prompt, it’s usually many prompts. If the refactor is large it can take weeks. But before AI something g equivalent would take months. - is it written in a way that adding new features means rewriting a lot of it Usually no, but that depends on how well the agent is being directed and what the features are. If you come up with a feature that requires a new architecture, ai makes it doable rather than saying “would be nice but we’d also have to implement this whole new architecture and that’s a lot of work” - is it written in a consistent style Styles can be applied mechanically with linters and formatters, so as much as any codebase written by multiple people.
47282847 19d ago
"There are naïve questions, tedious questions, ill-phrased questions, questions put after inadequate self-criticism. But every question is a cry to understand the world. There is no such thing as a dumb question". (Carl Sagan) Just because you don’t seem to be interested in the answer - then don’t read it? - doesn’t make the question wrong.
ModernMech 19d ago
The AI machine can write better code. It can also write an interpreter which implements function calls by instantiating a new interpreter + entire standard library per function call. Or it will build a 300kloc cathedral of scaffolding and maintain that forever, never writing actual code. Or it will create a CI system that takes 2 hours to run and constantly fails, and the agent loops there all day, fixing a small bug and waiting 2 hours. (All things I’ve experienced latest frontier models do) Agentic engineering faces all kinds of new problems that couldn’t exist before, and need experienced engineers to solve them.
walrus01 19d ago
With the "intelligence" of code focused and capable llm in the last six months, the main problem I'm seeing now is where some total amateur who has no previous knowledge of coding tries to one shot a project. People who have previous experience and know how to architect things (and when to stop an LLM from doing something wrong that will cause maintenance and scale and extensibility problems in the future) are doing much better building actually useful things.
- ModernMech 19d ago
  This one shot thing I just don’t understand. The way I’m using it, it takes weeks of constant prompts because it never does exactly what I ask no matter how well I specify. I just don’t see how it’s possible to one shot anything unless you don’t have strong requirements on the output.
  - orangecat 19d ago
    I had pretty good success with a language learning app. Initial prompt below, about an hour to get it working very close to how I imagined, then extended to Japanese, French, and audio generation. ====================================== Hi! I'd like to create an app for interactively learning Chinese using AI. My current idea is: - The AI generates a Chinese sentence at a specified vocabulary level (e.g. HSK2) - The user translates the sentence into English, and the AI evaluates the response. If the answer is wrong or is partially correct but could be improved, the AI offers a hint. If correct, the AI confirms and explains any particularly important vocabulary or grammar points that the sentence demonstrates. - The user should be able to click on an individual character once to see the pinyin, and again to see its definition and any helpful techniques to remember it (radicals, similarity to other characters, visual meaning) - The app should also be able to go the other way, giving the user an English sentence and having them translate to Chinese. App details: - UI is a web app - The AI should be pluggable. We'll start with a local Ollama install running gemma4, but it should be easily possible to add support for Claude/OpenAI/Gemini or other models (may need to provide an API key). - Not actually sure if we need a backend. It might be useful to keep track of characters or concepts that the user has difficulty with, or to keep track of what sentences the AI has previously generated so it doesn't become repetitive. - Build everything in a Docker container (or multiple if needed with docker compose)
ndiddy 19d ago
For me the usefulness of a survey like this has nothing to with how effective LLMs are themselves. It's more that when someone's able to produce an app in an afternoon, and submitting the app to F-Droid becomes a checkbox, how confident can you be that they'll continue maintaining the app? Sure if it's open source you can have your own LLM maintain it, but at that point what's the value in having it on F-Droid?

by edg5000 19d ago

Seems like the wrong question to ask. I've been programming my whole life but basically stopped writing code by hand in 2026. The LLM writes better code than I do, much better.

9cb14c1ec0 19d ago

Same here. I'm still a better software architect that AI, but there is no question that my AI generated and reviewed code has fewer bugs than code I hand write. It takes some humility to acknowledge that your coding prowess is less of a useful skill than it used to be.

cik 19d ago
There's an issue where people assumed the syntactic activity of writing code was what mattered. The reality is that this was always a smaller part of the role, as opposed to thinking about observability, serviceability, and test automation. The ability to write software that is properly separated from concerns and when to enact those separations matters. At the same time, I think we're far too far down the systems path now. We've hit a point where interviewing has become purely systems design "because the AI writes the code". Not that I'm ever asked, but I inherently believe the act of critical thinking, communication, and expression are the key skills for those who already have the appropriate coding/engineering/cs/etc background. I now only interview for those skills - but through the lens of impossible to solve systems design conversations as opposed to problems. It tells me a lot about how people think.
- jeltz 19d ago
  Not sure what you mean as system design conversations because while in theory those can be good in practice the ones I have been at had been techbro wankery where the interviewer had a particular answer in mind. Like designing your own memcached clone for example is a terrible task for systems design.
  - cik 19d ago
    What you're mentioning is 100% what's wrong with the industry. Agreed! To me a systems design conversation is a conversation - not a design goal. The idea is to determine ability and psychology: 1. When you press on someone's design respectfully, do they get defensive. Do they become argumentative. 2. When thoughtfully pointing out a concern, how does the candidate take it? 3. When you suggest a technology that makes no sense to intentionally challenge knowledge, does the candidate recognize why it makes no sense? Are they able to share what the negative of the approach is. If you indicate that you know the question is "senseless" but want their feedback, how do they communicate? 4. When you hard request a change that requires a literal rethink and rewrite do they become argumentative? Do they embrace the change? 5. When discussing testing, how do they think about it? I come down to the nitty gritty and ask about postive vs negative cases, table driven testing, what types of tests matter (for our situation) and why. 6. We discuss timeline tradeoffs, and then have the conversation about the candidate's approach given updates to see how they think. You'll notice that I am never looking for a solution. I'm seeking communication, description, partnership while having a (relatively) thorough gasp of the subject matter. Every single time I get a response from a candidate such as "I don't know, I'd have to learn more - or use AI to, or.. what do you think" turns out to be something I LOVE, because it creates a great fabric for the interview.
- 0x696C6961 19d ago
  Writing is thinking
  - tomrod 19d ago
    So is architecting, testing, validating, and even occasionally using. This isn't the first time I've seen this phrase recently, but I'm not sure what the thought is a cliche or what it is intended to convey (don't read my note as negative, I sincerely am unsure what connotation folks are trying to say).
    - jplusequalt 19d ago
      The idea behind "writing is thinking" is that people often overestimate their understanding until pressed to express it in words (or code). How many times in your career did you sit down to tackle a task thinking you knew exactly how to approach it only to realize during implementation that there were edge cases you hadn't considered, API contracts that were now broken, or that the feature was trying to solve the wrong problem. Having to be the one at the helm during implementation made you intimately aware of not only the problem at hand, but the current state of the codebase. That's something you can't replace with automation. You can't compress all of that context into your brain in a handful of prompts with Claude. Remember the words of your math teacher-- "Watching someone else solve the problem doesn't mean you can now solve it too."
markb139 19d ago
Programming languages, design languages and architecture are all inventions made to help humans write understandable source. LLMs don’t really need to do any of that. They can store very large trees of understanding and therefore implement any application in raw binary. Why bother with abstractions at all
- jeltz 19d ago
  LLMs for sure need those things. maybe not the same abstractions as humans do but without understabdable code an LLM will just fail to accomplish the task you ask it to do.
- flir 19d ago
  It might be less ambitious and more practical to target bytecode. But you effectively lose the human review component.
  - _1 19d ago
    There's more python and typescript in the training data than bytecode.
    - flir 19d ago
      I was thinking about that. I reckon generating massive amounts of synthetic training data for that goal should be possible - you've already got the Python, after all. It's also possible for machine code, but you'd have to target more platforms. But ultimately, I think human readability outweighs any theoretical advantage you get from removing a step in the compilation process.
  - redox99 19d ago
    Targeting byte code or asm instead of high level would be silly for everyday tasks. You blow up the number of tokens, reduce your effective context, and there's just more places for it to make a mistake, which most likely won't be caught by the assembler (unlike compilers).

dakolli 19d ago

Well, you must have some low fkn standards.

eloisant 19d ago
If you truly think LLM are not useful tools for programming, you haven't tried the right tools.
- jeltz 19d ago
  That is not the same topic. LLMs are useful tools, and that is despite them producing fucking awful code.
  - Gigachad 19d ago
    I would have agreed with you 6 months ago but things have changed rapidly.
    - wizzwizz4 19d 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 19d 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.

staszewski 19d ago

Skill issue then

0x000xca0xfe 19d ago
I just asked Astra to bring an old Windows XP game to the browser. It objdump'ed the whole thing, built a fitting Win32-like wrapper that exposes required functionality like DirectDraw, DirectSound, SEH etc., then wrote an x86-32/x87 interpreter in WASM, benchmarked how the game runs, lifted the hotspots of the executable to WASM too and now it is playable! I mean, I'm proud of my low-level skills too but this is some Fabrice Bellard level sorcery. Very, very few humans are able to do this without AI tools.
- erfgh 19d ago
  If there are very few humans that can do this is because the market for such a task is very small and thus there is little incentive to learn how to do it or produce tools that can do it.
- RHSeeger 19d ago
  But good code isn't just "does it work", it's also - is it understandable - is it maintainable - how much work is adding new features - is it written in a way that adding new features means rewriting a lot of it - is it written in a consistent style - and lots of other things I use AI to write a lot of my code, but the only time it's clearly "better" than a competent human is for one-off things. That being said - AI + human is, without any doubt in my mind, better than either one alone.
  - tomrod 19d ago
    Aye. Some of these targets are far away, others perhaps closer. Human+AI systems is a good match. Like Human+docs or Human+encyclopedia.
  - ModernMech 19d ago
    - is it understandable Yes you can ask the agent anything about it and interrogate it until you understand. - is it maintainable Yes it’s easy to ask the ai to add new features or to refactor it entirely. - how much work is adding new features Depends, it could just be one prompt, it’s usually many prompts. If the refactor is large it can take weeks. But before AI something g equivalent would take months. - is it written in a way that adding new features means rewriting a lot of it Usually no, but that depends on how well the agent is being directed and what the features are. If you come up with a feature that requires a new architecture, ai makes it doable rather than saying “would be nice but we’d also have to implement this whole new architecture and that’s a lot of work” - is it written in a consistent style Styles can be applied mechanically with linters and formatters, so as much as any codebase written by multiple people.

47282847 19d ago

"There are naïve questions, tedious questions, ill-phrased questions, questions put after inadequate self-criticism. But every question is a cry to understand the world. There is no such thing as a dumb question". (Carl Sagan) Just because you don’t seem to be interested in the answer - then don’t read it? - doesn’t make the question wrong.

ModernMech 19d ago

The AI machine can write better code. It can also write an interpreter which implements function calls by instantiating a new interpreter + entire standard library per function call. Or it will build a 300kloc cathedral of scaffolding and maintain that forever, never writing actual code. Or it will create a CI system that takes 2 hours to run and constantly fails, and the agent loops there all day, fixing a small bug and waiting 2 hours. (All things I’ve experienced latest frontier models do) Agentic engineering faces all kinds of new problems that couldn’t exist before, and need experienced engineers to solve them.

walrus01 19d ago

With the "intelligence" of code focused and capable llm in the last six months, the main problem I'm seeing now is where some total amateur who has no previous knowledge of coding tries to one shot a project. People who have previous experience and know how to architect things (and when to stop an LLM from doing something wrong that will cause maintenance and scale and extensibility problems in the future) are doing much better building actually useful things.

ModernMech 19d ago
This one shot thing I just don’t understand. The way I’m using it, it takes weeks of constant prompts because it never does exactly what I ask no matter how well I specify. I just don’t see how it’s possible to one shot anything unless you don’t have strong requirements on the output.
- orangecat 19d ago
  I had pretty good success with a language learning app. Initial prompt below, about an hour to get it working very close to how I imagined, then extended to Japanese, French, and audio generation. ====================================== Hi! I'd like to create an app for interactively learning Chinese using AI. My current idea is: - The AI generates a Chinese sentence at a specified vocabulary level (e.g. HSK2) - The user translates the sentence into English, and the AI evaluates the response. If the answer is wrong or is partially correct but could be improved, the AI offers a hint. If correct, the AI confirms and explains any particularly important vocabulary or grammar points that the sentence demonstrates. - The user should be able to click on an individual character once to see the pinyin, and again to see its definition and any helpful techniques to remember it (radicals, similarity to other characters, visual meaning) - The app should also be able to go the other way, giving the user an English sentence and having them translate to Chinese. App details: - UI is a web app - The AI should be pluggable. We'll start with a local Ollama install running gemma4, but it should be easily possible to add support for Claude/OpenAI/Gemini or other models (may need to provide an API key). - Not actually sure if we need a backend. It might be useful to keep track of characters or concepts that the user has difficulty with, or to keep track of what sentences the AI has previously generated so it doesn't become repetitive. - Build everything in a Docker container (or multiple if needed with docker compose)

ndiddy 19d ago

For me the usefulness of a survey like this has nothing to with how effective LLMs are themselves. It's more that when someone's able to produce an app in an afternoon, and submitting the app to F-Droid becomes a checkbox, how confident can you be that they'll continue maintaining the app? Sure if it's open source you can have your own LLM maintain it, but at that point what's the value in having it on F-Droid?