Show HN: 10x better performance from the Coding Harnesses with LLM-wiki(llm-wiki.net)
15 pointsby nvk5 hours ago7 comments
  • xnx3 hours ago
    Some say text files work even better: https://cloud.google.com/blog/products/data-analytics/how-th...
  • jarbus4 hours ago
    Where is this 10x number coming from?
  • superfrank3 hours ago
    I've got a couple of LLM wikis running for different purposes. I just pointed Claude at Karpathy's Github Gist and said "do this" and it set up and has maintained them ever since. So far no issue with that.

    Can you explain why the version linked is better?

    Gist link: https://gist.github.com/karpathy/442a6bf555914893e9891c11519...

  • dolebirchwood4 hours ago
    What if I only want 6x better performance? Is there a knob or slider to dial it down?
  • adithyassekhar3 hours ago
    Edit: On closer look this looks useful without the coding harness pitch.
    • nvk3 hours ago
      This is not a product, its a foss lib
  • sppfly4 hours ago
    This kind of llm bragging title and AI generated webpage makes me gross.
  • esafak4 hours ago
    How does this differ from https://context7.com/ ?
    • kordlessagain4 hours ago
      LLM Wiki is client-side and local-first (plain Markdown, Obsidian-friendly) designed for deep multi-agent topic research (e.g. automated thesis/counter-thesis runs, local session memory redaction).

      Context7 is a hosted SaaS/on-premise MCP server indexing API/library docs (GitHub, Confluence, OpenAPI) to provide coding assistants with fresh, version-specific developer context.

      Essentially: LLM Wiki compiles topic research vaults on your local disk, whereas Context7 acts as a semantic doc/API search gateway for programming.

      • esafak3 hours ago
        So the benefit is in caching the resources to avoid web queries, and massaging them to make them amenable to analysis? For intellectual work I imagine it would be useful if it could access gated content, like commercial reports?