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LLM Wiki

A pattern for building personal knowledge bases using LLMs.

This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.

The core idea

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.

@jsadoski-rockhall
jsadoski-rockhall / SKILL.md
Created January 30, 2026 13:33
Logging Best Practices Skill
name Logging Best Practices
description Use before implementing logs in a medium to large scale production system.

This skill is adpated from "Logging sucks. And here's how to make it better. by Boris Tane.

When helping with logging, observability, or debugging strategies, follow these principles:

Core Philosophy

@vimishor
vimishor / 503.html
Last active December 31, 2015 05:59
Custom 503 page while deploy on openshift | License: MIT
<!DOCTYPE html>
<html>
<head>
<title>Deploy in progress. Please try again in few minutes</title>
<style type="text/css" />
body {color: #666; text-align: center; font-family: "Helvetica Neue", Helvetica, Arial, sans-serif; sans-serif; margin:0; width: 800px; margin: auto; font-size: 14px; }
h1 { font-size: 56px; line-height: 100px; font-weight: normal; color: #456; }
h2 { font-size: 24px; color: #666; line-height: 1.5em; }
h3 { color: #456; font-size: 20px; font-weight: normal; line-height: 28px; }
hr { margin: 18px 0; border: 0; border-top: 1px solid #EEE; border-bottom: 1px solid white; }