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The problem is not AI code, but not knowing about system architecture or intent

388 points · 240 comments · zazuke

  1. bengold14 · · focus · HN ↗
    I see this everyday. The problem is code is the wrong abstraction for the work we do. LLMs have solved coding, but they haven't solved systems, collaboration or system maintenance.

    Edit: Since I seem to have touched a nerve - I&#x27;ve been working on a project to solve this: <a href="https:&#x2F;&#x2F;www.archme.io" rel="nofollow">https:&#x2F;&#x2F;www.archme.io if you want to know my thoughts on the right abstraction

    1. verdverm · · focus · HN ↗
      When you say &quot;solved coding,&quot; what does this mean, what does it look like?

      I have strong disagreement because it sounds like, by analogy or proxy, we have also &quot;solved writing&quot;

      1. ActorNightly · · focus · HN ↗
        Given a working system, like a web service or services, and their code, non technical people can now make effective changes with LLMs.

        For example, nobody on our team writes manual code anymore, we have basically set up a harness where an engineer types up the requirements for a change, the system implements it given certain constraints, we have automated unit and integration tests that are ran, and if any errors pop up, they get fed back into the loop until fixed.

        But to do that, you need to actually know what you are doing - you have to have good instructions to keep the agents in check and not start making mods outside of their bounds especially when the issue is with a dependant service that is causing errors.

        1. verdverm · · focus · HN ↗
          I&#x27;m well on my way down this path too, but that is a process implemented in markdown. I don&#x27;t see coding as solved, or a solvable thing at all, like writing

          To solve something, there must be a defined problem, what is the problem that was solved. Or perhaps it is just &quot;coding is solved&quot; is the turn of phrase de jour be ause we haven&#x27;t yet found a more succinct and accurate way to describe the paradigm shift

          When it comes to non technical people using Ai to build things on code, the outcomes are on average pretty poor, which i see as evidence that the driver and their expertise behind the Ai matters a lot. A notable example is Terence Tao&#x27;s conversation with ChatGPT, us math normies could never have done that. The same applies to coding agents ime

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