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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.

@pythoninthegrass
pythoninthegrass / com.user.disable-rcd.plist
Created October 12, 2025 02:21
Disable Apple Music (née iTunes) from launching via media keys
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0">
<dict>
<key>Label</key>
<string>com.user.disable-rcd</string>
<key>ProgramArguments</key>
<array>
<string>/bin/launchctl</string>
<string>unload</string>
Product Year Version Product Keys
Visual Studio 2026 18.x
Professional: NVTDK-QB8J9-M28GR-92BPC-BTHXK
Enterprise: VYGRN-WPR22-HG4X3-692BF-QGT2V
https://x.com/massgravel/status/1988306014371008542
Visual Studio 2022 2021 17.x Professional:
TD244-P4NB7-YQ6XK-Y8MMM-YWV2J
Enterprise:
@StevenACoffman
StevenACoffman / Homoglyphs.md
Last active May 24, 2026 16:22
Unicode Look-alikes

Unicode Character Look-Alikes

Original Letter Look-Alike(s)
a а ạ ą ä à á ą
c с ƈ ċ
d ԁ ɗ
e е ẹ ė é è
g ġ
h һ
OS version Arch File Host Size Download Link Rate Limits
Windows 1.0 8086 Winworld (Kansas City, Missouri) 541KB Download ❌ Yes, 25 per day
Windows 2.0 386 Winworld (Kansas City, Missouri) 2.80MB Download ❌ Yes, 25 per day
Windows 3.0 8086/386
"""
The most atomic way to train and run inference for a GPT in pure, dependency-free Python.
This file is the complete algorithm.
Everything else is just efficiency.
@karpathy
"""
import os # os.path.exists
import math # math.log, math.exp