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Susanne Oberhauser-Hirschoff froh

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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.

@mikepruett3
mikepruett3 / shell-setup.ps1
Last active May 24, 2026 19:50
Packages to install via scoop, winget, choco, and other tools...
<#
.SYNOPSIS
Script to Initialize my custom powershell setup.
.DESCRIPTION
Script uses scoop
.NOTES
**NOTE** Will configure the Execution Policy for the "CurrentUser" to Unrestricted.
Author: Mike Pruett
Date: October 18th, 2018
@vasanthk
vasanthk / System Design.md
Last active June 23, 2026 11:15
System Design Cheatsheet

System Design Cheatsheet

Picking the right architecture = Picking the right battles + Managing trade-offs

Basic Steps

  1. Clarify and agree on the scope of the system
  • User cases (description of sequences of events that, taken together, lead to a system doing something useful)
    • Who is going to use it?
    • How are they going to use it?