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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.

@BashedCrab
BashedCrab / JumpyOctopus.py
Created February 12, 2014 03:25
JumpyOctopus
from scene import *
from PIL import Image
import sound
import random
GAME_READY = 0
GAME_PLAY = 1
GAME_DYING = 2
GAME_DEAD = 3
@Pythonation
Pythonation / prompt.md
Last active May 9, 2026 02:50
3 PROMPTS OF CODING AGENTS

1. برومبت التخطيط المطوّر (The Planning Protocol)

[الدور والمسؤولية] أنت الآن تعمل بصفة Staff Software Engineer ومدير تقني Tech Lead. مهمتك التخطيط المعماري الصارم للمشروع التالي: [أدخل وصف المشروع هنا]

[قواعد ما قبل التتخطيط] قبل البدء بالبروتوكولات، يجب أن تطبق مبدأ "Think Before Coding":

@roman-rr
roman-rr / ruflo-audit-gist.md
Last active May 9, 2026 02:50
Ruflo / Claude-Flow Audit: 300+ MCP Tools — 99% Theater, 1% Real, 5x Token Waste

Ruflo / Claude-Flow: 300+ MCP Tools Exposed — 99% Theater, 1% Real, 5x Token Waste

A deep technical audit of the ruflo (@claude-flow/cli) ecosystem — what it claims vs what it actually does.

Investigated 2026-04-04 by spawning 8 research agents across two analysis phases, reading source code from the ruflo GitHub repo, tracing local process execution, and testing every major tool category hands-on.


TL;DR

@shyouhei
shyouhei / gist:266178ffedab5767a5b69b972c76f88a
Created September 27, 2017 07:31
優秀なプログラマーになるためのコツ

優秀なプログラマーになるためのコツ

重要な順で

優秀なプログラマーになるには非常に長い時間がかかるという現実を直視すべし

優秀なプログラマーというのは寝ている間に異世界に召喚されて無双するのとはわけが違うんですよ。

自分の例で言うとプログラミングを始めた中学生の時から優秀なプログラマだったかって、そんなわけない。みんなヘッポコからスタートしているに決まってるわけです。以来二十余年、地道に生き恥を晒し続けてきた結果として、現在いちおう業界の末席を汚すところまで来ている。このプロセスから目を背けるべきではないです。優秀なプログラマーに生まれる人間なんかいない。優秀なプログラマーに「育つ」んだし、それには時間が必要。今日から無双したいと思うな。

@Ackthbpt
Ackthbpt / LR5Pro.md
Last active May 9, 2026 02:40
Litter-Robot 5 Pro — Local Camera Interface Reverse Engineering

Litter-Robot 5 Pro - Local Camera Interface Reverse Engineering

Status: Work in progress - login credentials not yet cracked
Device: Litter-Robot 5 Pro (serial format: LR5-XX-XX-XX-XXXX-XXXXXX)
Camera OEM: iENSO Inc. (Toronto, ON, Canada) - ienso.com
Goal: Local RTSP access to the integrated camera without Whisker+ cloud subscription


Background