Comment by petcat

11 hours ago

> manually retyping LLM-generated code

This is just a miserable career of "paint-by-number" because people can't be bothered to have a creative thought about their professional work or programming hobbies.

Software developers think that they are being clever with these kinds of strategies to "keep their skills sharp", but unfortunately the entire industry knows about this, and especially the upper management who are already eliminating these assembly line, JIRA-ticket-taker software jobs en masse.

Right, it's just pretending to be able to delay the inevitable. It's like the assembly programmers of the 70s and 80s keeping their assembly-fu sharp. Yes it might come handy, and it's good to have a grasp of the concepts, but most careers have shifted to not needing to use assembly. Yes, I know that better knowledge of the low level would improve performance and efficiency. But people don't work with this any more, and the goal back then also wasn't to keep retyping a GCC output to keep the skill fresh. It was to get to a higher level of control and think about the organization of structured code, code maintenance issues, thinking at the level of how to make the C++ implementation.

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.

We are right at the stage where our coding ability and review ability is still needed though, but this stage won't last long. 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. Of course the discussion and prioritization may involve looking at the code itself, to get a better idea of why the agent says that a certain feature would be tedious to implement in the current architecture, but then most people will just learn to take its word for it, just as you may want to understand a chess engine's step, but you typically wouldn't want to override it.

  • > 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.

    • > 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.

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> upper management who are already eliminating these assembly line, JIRA-ticket-taker software jobs en masse

Is there any proof of this?

  • Some anecdotal trends listed in this report on US demand for Indian tech workers rapidly slowing.

    https://thefederal.com/category/news/h1b-visa-indian-tech-wo...

    > According to the discussion, foreign hiring at Google has fallen by more than half, while approvals at Amazon have dropped by nearly a third.

    > According to Xfino's Active Tech Jobs Outlook, active technology job openings fell to 93,000 in June, down 14 per cent from 108,000 a month earlier.