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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. Avicebron · · focus · HN ↗
      Or more broadly, LLMs fundamentally don&#x27;t &quot;understand&quot;. They can simulate understanding and generate text&#x2F;code&#x2F;whatever, but they don&#x27;t have will to engage with something holistically and &quot;own&quot; it.
      1. visarga · · focus · HN ↗
        I have been trying to define &quot;understanding&quot;. Is it when you can predict something that you understood it? Or maybe when you can explain it? Or how about when you can control it? Or invent it.

        This time I add another definition &quot;when you can own it&quot;.

        1. bengold14 · · focus · HN ↗
          When you can own it - I like that. Humans are still needed to own systems and drive&#x2F;direct changes. The question is how can we collaborate as organizations and teams to still own it when we don&#x27;t write the code and can&#x27;t keep up with the output
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