Thread

1. anthuswilliams · 1790353553 · focus · HN ↗

   One interesting quirk of the AI-written READMEs these days is how they can include every detail on how it works, thoroughly document every optional flag, known limitation, experimental result, and still not communicate the essence of the project and the problem it solves.

   I have read through the project and I still don't understand what this thing is for and why it is to be preferred over the harness's native memory management tools.

   1. ttul · 1790355499 · focus · HN ↗

      The AI language really stands out, too. "What is automatic and what depends on the agent". A human might write, "jevmen watches your coding session with Claude Code or Codex and picks just the right moment to remember important things that you decided along the way. There are some differences in how jevmem works, depending on which coding harness you are using. The table below summarizes these differences:"

      I don't know why the models were generally trained to be so brief, but it's definitely not the way anyone I know actually writes. A second pass is always a good idea to clean this stuff up. And, thankfully, the models are all pretty good at that.

      1. SOLAR_FIELDS · 1790358373 · focus · HN ↗

         The big tell for me is assuming the reader has context straight out the gate. "What is automatic and what depends on the agent" assumes the reader, like the LLM at the time it wrote that sentence, has all of this pre-context available. That sentence makes more sense as an h3 header further down in some detailed list where the human has all of the knowledge of how the system works. Whereas a human obviously does not, so they lead with the important context of why you give a shit

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