3 ms·

> With AI, our role also shifts. It's mainly to know what to spend effort on, to set priorities and, to be able to verbalize requirements, missing social contex

> With AI, our role also shifts. It's mainly to know what to spend effort on, to set priorities and, to be able to verbalize requirements, missing social context and unwritten rules, to anticipate what additional documents the agent needs, to prioritize deadlines, feature necessity, and other judgment calls. Did you not do that before AI? It’s so strange to me when people are calling out these kind of tasks like they were not already a requirement for the job. What were you doing before? > Soon there will be as little point to a human diving into the code as to trying to beat a chess engine, or humans constructing buildings by hand Chess is way less complex than coding. The rules are like a few pages. While the specs for an 8 bit chip like the AVR is in the hundreds of pages. Books like “The Linux Programming Interface” are thousand pages long. Also humans are using tools for building. Tools that do exactly what you control them to do. When you use a drill for a hole, you don’t have to worry that pressing the trigger have a good chance of sending the bit in your guts.

bonoboTP 2mo ago
> Did you not do that before AI? It’s so strange to me when people are calling out these kind of tasks like they were not already a requirement for the job. What were you doing before? No, you didn't have to explicitly say it in words. My mind doesn't run on internal monologue. Many people can just do their work without ever having reflected on it in words. Tacit knowledge, routines, shared assumptions and culture in a team, common knowledge etc. People have a hard time using AI because they are bad at modeling the knowledge state / information context from the AI POV. You need good theory of mind for this, and being a good programmer is distinct from that soft skill. Yes yes blabla soft skills are more important than hard skills blabla, I don't buy it. It used to be valuable to be great at the hard skills even with mid-tier soft skills. You can have a ton of smooth talkers who are attuned to feel each others emotion and desires super well, but the thing has to actually work too. > What were you doing before? Wrote code. Yes, you have to explain the outcome to your boss or your team at some point, but people generally have better developed theories of mind for people than for AI. > Also humans are using tools for building. Tools that do exactly what you control them to do. When you use a drill for a hole, you don’t have to worry that pressing the trigger have a good chance of sending the bit in your guts. Right. I'm not sure how to reconcile the two though. A tool whose job is to do some of the thinking part seems to be a contradiction to me. If I so much know what there is to do that it's pure execution and can reliably be executed in a way that basically ensures no potential surprises to me, then I wouldn't need more thinking. But I agree, it would be better to somehow find a hybrid that is both doing thinking and feels more like a tool also while using it.
- skydhash 2mo ago
  > No, you didn't have to explicitly say it in words. My mind doesn't run on internal monologue. Many people can just do their work without ever having reflected on it in words. Were you a solo developer? I think the amount of reports and explanations (either written or verbal) dwarfs by large the amount of code I’ve written. From training juniors to drafting a design specs for a feature. That is why people say code is the trivial part of the job because it’s easy. I’m pretty sure the mailing list of the Linux kernel is bigger than the code itself.
  - bonoboTP 2mo ago
    I'm in academic ML research. Coding is mostly scoped to myself. And it's often nontrivial. My communication is more in papers, reports on experimental results, deciding what to try next, but how the code is organized is rarely the focus of discussion. Of course this may be entirely different in a software shop building routine features where the difficulty is indeed the social part and the software itself is more clearly understood. But I'd say that's when AI can be even more effective since it can do mundane coding even better proportionally than research code. Of course Amdahl's law kicks in and even if you reduce that drudgery to 0, the proportion is small when taking total work effort into context.
    - skydhash 2mo ago
      > Of course this may be entirely different in a software shop building routine features where the difficulty is indeed the social part and the software itself is more clearly understood. But I'd say that's when AI can be even more effective since it can do mundane coding even better proportionally than research code And here’s another fallacy that is always thrown around. Always underestimating the other’s tasks when you are not an expert in it and don’t know intimately what’s involved.
      - bonoboTP 2mo ago
        So which is it? Is the coding part easy or hard? If it's easy and the task is mainly all the song and dance with the client, the stakeholders, getting approval and whatnot, then AI can take care of that easy coding and at least save that time. But then that is proportionally not much. I do have friends in industry, and they do sit quite a lot of hours in front of an IDE typing and fighting compilation issues, etc. It's not like they are always in meetings. I know people who work in the computer vision industry, 3D perception, and they have relatively few meetings and report to their boss occasionally, are not micromanaged, there is little red tape. They are getting real benefits from AI. It has eliminated several efficiency problems in their code that nobody took the time to fix, like consolidating repeated computations to just being done once, or similar things. They have solved a lot of CI pain with it, where they used to have an entire employee just taking care of keeping the CI in shape and updating it and remembering all the quirks, it's no longer a full time job, though also not fully automated. The CI person of course doesn't like the fact that his arcane knowledge has become un-moated. (I've worked on maintaining servers myself and I was the only one who really knew how it worked or how to fix it when it was broken, how to use it in specific special contexts, e.g. in context of a Slurm cluster. Today a lot of that hard-earned detailed knowledge is obviated by Claude, because it can answer similarly well to how I could, or better. So I have experienced such things myself too.) I don't think we should be making sweeping claims. But everyone generalizes. The person on top claimed that productivity doesn't increase for competent people and that coding is anyway very easy. That may be true in some contexts but not in others. Some software jobs require a lot of face-to-face, others less. Some managers micromanage, others just care about results on a longer timeframe. Some people build technically difficult, computationally heavy code, deployed on special hardware with efficiency requirements, others deploy website-like iPhone apps and CRUD webapps all day. There's no single shape for a software-related job.

bonoboTP 2mo ago

> Did you not do that before AI? It’s so strange to me when people are calling out these kind of tasks like they were not already a requirement for the job. What were you doing before? No, you didn't have to explicitly say it in words. My mind doesn't run on internal monologue. Many people can just do their work without ever having reflected on it in words. Tacit knowledge, routines, shared assumptions and culture in a team, common knowledge etc. People have a hard time using AI because they are bad at modeling the knowledge state / information context from the AI POV. You need good theory of mind for this, and being a good programmer is distinct from that soft skill. Yes yes blabla soft skills are more important than hard skills blabla, I don't buy it. It used to be valuable to be great at the hard skills even with mid-tier soft skills. You can have a ton of smooth talkers who are attuned to feel each others emotion and desires super well, but the thing has to actually work too. > What were you doing before? Wrote code. Yes, you have to explain the outcome to your boss or your team at some point, but people generally have better developed theories of mind for people than for AI. > Also humans are using tools for building. Tools that do exactly what you control them to do. When you use a drill for a hole, you don’t have to worry that pressing the trigger have a good chance of sending the bit in your guts. Right. I'm not sure how to reconcile the two though. A tool whose job is to do some of the thinking part seems to be a contradiction to me. If I so much know what there is to do that it's pure execution and can reliably be executed in a way that basically ensures no potential surprises to me, then I wouldn't need more thinking. But I agree, it would be better to somehow find a hybrid that is both doing thinking and feels more like a tool also while using it.

skydhash 2mo ago
> No, you didn't have to explicitly say it in words. My mind doesn't run on internal monologue. Many people can just do their work without ever having reflected on it in words. Were you a solo developer? I think the amount of reports and explanations (either written or verbal) dwarfs by large the amount of code I’ve written. From training juniors to drafting a design specs for a feature. That is why people say code is the trivial part of the job because it’s easy. I’m pretty sure the mailing list of the Linux kernel is bigger than the code itself.
- bonoboTP 2mo ago
  I'm in academic ML research. Coding is mostly scoped to myself. And it's often nontrivial. My communication is more in papers, reports on experimental results, deciding what to try next, but how the code is organized is rarely the focus of discussion. Of course this may be entirely different in a software shop building routine features where the difficulty is indeed the social part and the software itself is more clearly understood. But I'd say that's when AI can be even more effective since it can do mundane coding even better proportionally than research code. Of course Amdahl's law kicks in and even if you reduce that drudgery to 0, the proportion is small when taking total work effort into context.
  - skydhash 2mo ago
    > Of course this may be entirely different in a software shop building routine features where the difficulty is indeed the social part and the software itself is more clearly understood. But I'd say that's when AI can be even more effective since it can do mundane coding even better proportionally than research code And here’s another fallacy that is always thrown around. Always underestimating the other’s tasks when you are not an expert in it and don’t know intimately what’s involved.
    - bonoboTP 2mo ago
      So which is it? Is the coding part easy or hard? If it's easy and the task is mainly all the song and dance with the client, the stakeholders, getting approval and whatnot, then AI can take care of that easy coding and at least save that time. But then that is proportionally not much. I do have friends in industry, and they do sit quite a lot of hours in front of an IDE typing and fighting compilation issues, etc. It's not like they are always in meetings. I know people who work in the computer vision industry, 3D perception, and they have relatively few meetings and report to their boss occasionally, are not micromanaged, there is little red tape. They are getting real benefits from AI. It has eliminated several efficiency problems in their code that nobody took the time to fix, like consolidating repeated computations to just being done once, or similar things. They have solved a lot of CI pain with it, where they used to have an entire employee just taking care of keeping the CI in shape and updating it and remembering all the quirks, it's no longer a full time job, though also not fully automated. The CI person of course doesn't like the fact that his arcane knowledge has become un-moated. (I've worked on maintaining servers myself and I was the only one who really knew how it worked or how to fix it when it was broken, how to use it in specific special contexts, e.g. in context of a Slurm cluster. Today a lot of that hard-earned detailed knowledge is obviated by Claude, because it can answer similarly well to how I could, or better. So I have experienced such things myself too.) I don't think we should be making sweeping claims. But everyone generalizes. The person on top claimed that productivity doesn't increase for competent people and that coding is anyway very easy. That may be true in some contexts but not in others. Some software jobs require a lot of face-to-face, others less. Some managers micromanage, others just care about results on a longer timeframe. Some people build technically difficult, computationally heavy code, deployed on special hardware with efficiency requirements, others deploy website-like iPhone apps and CRUD webapps all day. There's no single shape for a software-related job.