Thread

1. bengold14 · 1790612793 · 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 · 1790613137 · 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. mwillis · 1790617624 · focus · HN ↗

         maybe it’s more like “abstracted” away, in the same way higher-level languages “solved” needing to code via machine instruction sets. Higher level languages allowed humans to think more like themselves. AI puts another abstraction in front of the outcome, making it even more generally open to human thinking and less defined by the need to give machines exactly what they expect.

         Today, human-language outlines &#x2F; briefs &#x2F; prompts are “compiled” to code which is itself then adapted to hardware. We are stretching less and less across the divide, doing less and less work on the terms of the machine. Now the farthest we’ll stretch is often formatted markdown - the most basic application of machine-parseable structure to very organic human thinking. Because we’re given the chance to be less precise, coherence suffers.

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