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Yifan Goh imgyf

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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.

@codediodeio
codediodeio / config.js
Last active April 7, 2025 00:44
Snippets from the Firestore Data Modeling Course
import * as firebase from 'firebase/app';
import 'firebase/firestore';
var firebaseConfig = {
// your firebase credentials
};
// Initialize Firebase
firebase.initializeApp(firebaseConfig);
@kevin-smets
kevin-smets / iterm2-solarized.md
Last active May 10, 2026 07:49
iTerm2 + Oh My Zsh + Solarized color scheme + Source Code Pro Powerline + Font Awesome + [Powerlevel10k] - (macOS)

Default

Default

Powerlevel10k

Powerlevel10k