I've been working on a project using C++ modules in Godot. At some point I was doing a lot of small incremental builds in a single file and they got to be slow, at around 10-15 seconds per recompile.

You're probably thinking "wow 10 seconds is actually really fast to compile c++", it certainly could be a lot worse. For me 10 seconds on this project was pretty inconvenient. I had to recompile very often to tweak small things such as how graphics look, ui adjustments, gameplay values, or other small algorithm changes. With graphics and UI in particular, unlike programming something that is pure math, there isn't really a point where you get it "correct" and the algorithm is completed. To make graphics "correct" requires tweaking it to make it "look good" and "feel good" which are totally arbitrary things that are difficult to get r

What this is: the follow up to From spare computer to home lab. Part one got you Proxmox, TrueNAS, and Jellyfin, playing files you copied by hand. This guide adds a team of small apps that fill your library for you. You pick a movie or a show, and later it is sitting in Jellyfin with the right name, the right picture, and it just plays. You never touch a file.

Who this is for: someone who finished guide one, or already has Proxmox, a TrueNAS media share, and Jellyfin running. You do not need to know what any of the apps in this guide are. Every one of them gets introduced from zero.

Time: about two hours of mostly clicking, plus one evening signing up for two accounts on the internet side.

The one rule that matters most: every app in this guide will look at your media folder from the same spot, /mnt/media. When every app agrees on where the files ar

What this is: a build-it-yourself guide for turning one or two old computers into a proper home lab: virtual machines, containers, a shared storage box your whole house can use, and a full media library stack (Jellyfin, the download manager apps, and where the files come from), plus how to reach it from outside your house safely.

Who this is for: you have an old desktop or two, you can follow instructions, and you have never touched a hypervisor. No Linux experience assumed. Every command and every screen is explained, and each step tells you what you should see before you move on.

Time: about 1 hour for the first box (Proxmox), 45 minutes for the storage box (TrueNAS), plus however long your data takes to copy. Most of it is waiting.

The single most important thing in this guide: give every box a fixed IP address so it never moves. Everything else you can fix later by reading a screen. If a machine changes address,

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.

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.

Executing commands across nested shells (e.g., SSH or Docker) often results in complex quoting issues. This snippet shows how to avoid this by wrapping each environment-specific command into a function. By doing so, you let the shell handle the nesting and escaping. Just make sure to invoke them properly (see declare) and explicitly expand necessary environment variables.

VAR1=dockername
VAR2=filename

inside_ssh() {
  inside_docker() {
    CMD1_RESULT=$(sed -nE 's/.*"version":"(\w+?)".*/\1/gp' /opt/*/frontend/*.js)
 CMD2_RESULT=$(cat /etc/version.d/$VAR2)