Jeremy Roush jeremedia

Notes

This guide uses Kamal 2.5.3

Motivation

Kamal was designed with 1 service = 1 droplet/VPS in mind.
But I'm cheap and I want to be able to deploy multiple demo/poc apps apps on my $20/month dedicated server.
What the hell, I'll even host my private container registry on it.

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.

	using UnityEditor;
	using UnityEngine;

	public class SnapRectTransformAnchorsToCorners : MonoBehaviour
	{
	[MenuItem("CONTEXT/RectTransform/Snap Anchors To Corners", priority = 50)]
	private static void Execute(MenuCommand command)
	{
	RectTransform rectTransform = command.context as RectTransform;
	RectTransform parent = rectTransform.parent as RectTransform;

	using UnityEditor;
	using UnityEngine;
	using UnityEngine.LowLevel;
	using System.Linq;
	using System.Threading;

	namespace EditorUtils {

	//
	// Serializable settings

	# frozen_string_literal: true
	# config/initializers/colorized_logger.rb

	# This initializer adds color to the Rails logger output. It's a nice way to
	# visually distinguish log levels.
	module ColorizedLogger
	COLOR_CODES = {
	debug: "\e[36m", # Cyan
	info: "\e[32m", # Green
	warn: "\e[33m", # Yellow