Shawn Cicoria cicorias

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.

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Beast Mode v3

Beast Mode is a custom chat mode for VS Code agent that adds an opinionated workflow to the agent, including use of a todo list, extensive internet research capabilities, planning, tool usage instructions and more. Designed to be used with 4.1, although it will work with any model.

Installation Instructions

Go to the "agent" dropdown in VS Code chat sidebar and select "Configure Modes".
Select "Create new custom chat mode file"
Select "User Data Folder"
Give it a name (Beast Mode)

Here is how you can emulate Azure managed identity on your local system by running an instance metadata service identity endpoint and simulating the token API to return an access token from Azure CLI. You can use this for example to log into SQL Server Management studio using your Azure CLI identity, or locally test code that uses the "Azure only" [ManagedIdentityCredential](https://learn

	"""
	The most atomic way to train and inference 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

	// -----------------------------------------------------------------------------
	// Azure RG Janitor - Spectre Edition
	// Run with: dotnet run cleanup-rg.cs
	// Targets: .NET 10 Preview 4+
	// -----------------------------------------------------------------------------

	#:package Azure.Identity@1.*
	#:package Azure.ResourceManager@1.*
	#:package Spectre.Console@0.50.0

	import { Router } from 'next/router';
	import { useEffect } from 'react';
	import { publicConfig } from '~/shared/config';
	import { trpc } from '~/utils/trpc';

	let initVersion = publicConfig.GIT_COMMIT;

	function useDetectVersionChange() {
	const healthQuery = trpc.health.useQuery(undefined, {
	refetchInterval: 10_000,

	{
	"configurations": [
	{
	"name": "Linux",
	"includePath": [
	"${workspaceFolder}",
	"LINUX_PATH/include",
	"LINUX_PATH/include/uapi",
	"LINUX_PATH/include/generated",
	"LINUX_PATH/arch/x86/include",

	import inspect
	from django.conf import settings
	from django.utils.importlib import import_module
	from django.core.exceptions import ImproperlyConfigured


	class AlreadyRegistered(Exception):
	pass

	Credits
	# https://c-nergy.be/blog/?p=13655
	# https://askubuntu.com/questions/844245/how-to-compile-latest-pulseaudio-with-webrtc-in-ubuntu-16-04
	# https://askubuntu.com/questions/496549/error-you-must-put-some-source-uris-in-your-sources-list
	# https://unix.stackexchange.com/questions/65167/enable-udev-and-speex-support-for-pulseaudio
	# https://rudd-o.com/linux-and-free-software/how-to-make-pulseaudio-run-once-at-boot-for-all-your-users
	# https://gist.github.com/rkttu/35ecab5604c9ddc356b0af4644d5a226

	# Installation and Enhanced session
	# follow steps on the post below, I installed Ubuntu 22.04 on a Windows 11 machine