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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.

admin account info" filetype:log
!Host=*.* intext:enc_UserPassword=* ext:pcf
"# -FrontPage-" ext:pwd inurl:(service | authors | administrators | users) "# -FrontPage-" inurl:service.pwd
"AutoCreate=TRUE password=*"
"http://*:*@www” domainname
"index of/" "ws_ftp.ini" "parent directory"
"liveice configuration file" ext:cfg -site:sourceforge.net
"parent directory" +proftpdpasswd
Duclassified" -site:duware.com "DUware All Rights reserved"
duclassmate" -site:duware.com
KFZUS-F3JGV-T95Y7-BXGAS-5NHHP
T3ZWQ-P2738-3FJWS-YE7HT-6NA3K
KFZUS-F3JGV-T95Y7-BXGAS-5NHHP
65Z2L-P36BY-YWJYC-TMJZL-YDZ2S
SFZHH-2Y246-Z483L-EU92B-LNYUA
GSZVS-5W4WA-T9F2E-L3XUX-68473
FTZ8A-R3CP8-AVHYW-KKRMQ-SYDLS
Q3ZWN-QWLZG-32G22-SCJXZ-9B5S4
DAZPH-G39D3-R4QY7-9PVAY-VQ6BU
KLZ5G-X37YY-65ZYN-EUSV7-WPPBS
@RezaOwliaei
RezaOwliaei / elysia-clean-architecture-guide.md.md
Last active May 25, 2026 16:53
Vertical Slicing & Clean Architecture: A Practical Guide for Elysia Developers

Architecture & Concepts

This handbook serves as a comprehensive guide to the architectural choices, design patterns, and technology stack for projects leveraging Feature-First Clean Architecture and Elysia.


Table of Contents

  1. Overview
  2. Project Structure
@WENDYSGORE
WENDYSGORE / index.html
Created February 13, 2024 20:29
PA MI AMORCITO
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<title>Carta de San Valentín</title>
<link rel="stylesheet" href="./style.css">
</head>
<body>
@Archisman-Mridha
Archisman-Mridha / neovim.cheatsheet.md
Last active May 25, 2026 16:24
Neovim cheatsheet

Anatomy of a motion - Command + Count + Motion

Navigation

  • Jump to beginning of line : 0 | jumps to the first non-whitespace character : _
  • Jump to end of line : $
  • Move forward by 1 word : jumps to beginning of the next word : w | jumps to end of the next word : e
  • Move backward by 1 word : jumps to beginning of the previous word : b | jumps to end of the previous word : ge
  • Jump to beginning of the file : gg
  • Jump to end of the file : G
  • Move forward to the next instance of the character (( in this case) : f( // NOTE : Repeat motion using , (for backwards movement) or ; (for forward movement)
@to-your-now
to-your-now / Antigravity_Windows_AI_Setup_2026.md
Last active May 25, 2026 16:12
The Perfect Setup for Google Antigravity IDE on Windows (2026)

Infographic

The Perfect Setup for Google Antigravity IDE on Windows (2026 Edition)

If you are using Google’s Antigravity IDE on Windows to power autonomous AI agents, you’ve likely encountered terminal hanging, broken token parsing, and endless execution loops. Agents natively default to Unix-style thinking, struggling with pwsh, file path escapes, and the IDE's internal CLI safeguards.

This guide provides the Absolute AI System Prompt (gemini.md) and the Optimal IDE Settings (Allow/Deny lists) to transform your Windows environment into a flawlessly stable workspace for any LLM agent.