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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.

@karthink
karthink / avy-actions.el
Last active June 26, 2025 14:46
Supplementary code for Avy actions for Emacs
;; Code used in the demos at https://karthinks.com/software/avy-can-do-anything
;; Tweak as desired.
(package-install 'avy)
(setq avy-keys '(?q ?e ?r ?y ?u ?o ?p
?a ?s ?d ?f ?g ?h ?j
?k ?l ?' ?x ?c ?v ?b
?n ?, ?/))
@wmcmurray
wmcmurray / BasicCustomShader.js
Last active September 21, 2024 13:44
A basic example of a ThreeJS (r108) ShaderMaterial with shadows, fog and dithering support.
import { mergeUniforms } from 'three/src/renderers/shaders/UniformsUtils.js'
import { UniformsLib } from 'three/src/renderers/shaders/UniformsLib.js'
export default {
uniforms: mergeUniforms([
UniformsLib.lights,
UniformsLib.fog,
]),
@cadurosar
cadurosar / test_notebook.ipynb
Last active August 4, 2023 22:19
A interactive ipython notebook for: Keras plays catch - https://gist.github.com/EderSantana/c7222daa328f0e885093
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@jboner
jboner / latency.txt
Last active May 8, 2026 20:40
Latency Numbers Every Programmer Should Know
Latency Comparison Numbers (~2012)
----------------------------------
L1 cache reference 0.5 ns
Branch mispredict 5 ns
L2 cache reference 7 ns 14x L1 cache
Mutex lock/unlock 25 ns
Main memory reference 100 ns 20x L2 cache, 200x L1 cache
Compress 1K bytes with Zippy 3,000 ns 3 us
Send 1K bytes over 1 Gbps network 10,000 ns 10 us
Read 4K randomly from SSD* 150,000 ns 150 us ~1GB/sec SSD