Show HN: 10x better performance from the Coding Harnesses with LLM-wiki

xnx•about 2 hours ago

Some say text files work even better: https://cloud.google.com/blog/products/data-analytics/how-th...

superfrank•about 2 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...

jarbus•about 2 hours ago

Where is this 10x number coming from?

dominotw•about 2 hours ago

from llm wiki

esafak•about 2 hours ago

The 10x coder who wrote it: https://www.youtube.com/watch?v=d2BuP7-m5Ww

dolebirchwood•about 2 hours ago

What if I only want 6x better performance? Is there a knob or slider to dial it down?

adithyassekhar•about 2 hours ago

Edit: On closer look this looks useful without the coding harness pitch.

nvk•about 2 hours ago

This is not a product, its a foss lib

sppfly•about 2 hours ago

This kind of llm bragging title and AI generated webpage makes me gross.

esafak•about 2 hours ago

How does this differ from https://context7.com/ ?

kordlessagain•about 2 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.

esafak•about 2 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?

kordlessagain•about 1 hour ago

Right, it's the whole search pipeline problem defined. Check this out: https://github.com/deepbluedynamics/lume

Show HN: 10x better performance from the Coding Harnesses with LLM-wiki

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