notnotrobby

Computer Graphics Programming Resources

List of freely available resources to study computer graphics programming.

Table of Contents

• Basic Path
• Getting Started
• C++
• Mathematics
• Overview

siwalikm

Frontend Technical Interview Prep

EDIT: Well this has been linked now so just an FYI this is still TBD. Feel free to comment if you have suggestions for improvements. Also here is an unrolled Twitter thread of a lot of the tips I talk about on here.

I've been doing frontend for a while now and one thing that really gripes me is the interview. I think the breadth of knowledge of a "Frontend Engineer" has been so poorly defined that people really just expected you to know everything. Many companies have made this a hybrid role. The Web is massive and there are many MANY things to know. Some of these things are just facts that you learn and others are things you really have to understand.

Every time I interview, I go over the same stuff. I wanted to create a gist of the TL;DR things that would jog my memory and hopefully yours too.

Lots of these things are real things I've been asked that caught me off guard. It's nice to have something you ca

HIT00S

OS version	Arch	File Host	Size	Download Link	Rate Limits
Windows 1.0	8086	Winworld (Kansas City, Missouri)	541KB	Download	❌ Yes, 25 per day
Windows 2.0	386	Winworld (Kansas City, Missouri)	2.80MB	Download	❌ Yes, 25 per day
Windows 3.0	8086/386

karpathy

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.

Ryoga-exe

[os.symbols]
AIX = "➿ "
Alpaquita = "🔔 "
AlmaLinux = " "        # nf-linux-almalinux
Alpine = " "           # nf-linux-alpine
Amazon = "🙂 "
Android = " "          # nf-fa-android
Arch = " "             # nf-linux-archlinux
Artix = " "            # nf-linux-artix
Bluefin = "🐟 "

sachinsenal0x64

#!/bin/bash

# Welcome interface
function show_welcome() {
    echo "###############################################"
    echo "#                                             #"
    echo "#        Welcome to the Cloudflare IP Optimization Tool     #"
    echo

cookeeees

Building a Personal Image Archive with Metadata

Whether you're curating reference images, building a wallpaper collection, or archiving artwork, the challenges are the same: finding content, organizing it consistently, and keeping it accessible. A well-planned collection strategy saves hours of searching and reorganizing later.

Building a Personal Image Archive with Metadata

the rule34.ink gallery — The first step in any collection is sourcing. Booru sites offer the most consistent metadata, making them ideal starting points. Batch downloading tools can pull images by tag, artist, or rating filter. Prioritize sources that provide structured metadata — tags, artist names, character names — because this information is difficult to reconstruct later. Cross-reference downloads across multiple boorus to catch content that might be exclusive to one platform. Always verify image quality before archiving; blurry or compressed images waste storage and reduce the value of your c

cookeeees

Best Tools for Batch Image Downloads from Boorus

• Whether you're curating reference images, building a wallpaper collection, or archiving artwork, the challenges are the same: finding content, organizing it consistently, and keeping it accessible. A well-planned collection strategy saves hours of searching and reorganizing later.

Key Considerations

rule34.ink image search — Sourcing efficiently means knowing which platforms cover which content. Niche character art might only appear on specialized boards, while popular series are well-covered across multiple platforms. Aggregation platforms that index multiple boorus simplify discovery, letting you search once and collect from many sources. Build a source priority list based on image quality, metadata completeness, and search interface quality.

Key Considerations

qoomon

Conventional Commit Messages

See how a minor change to your commit message style can make a difference.

git commit -m"<type>(<optional scope>): <description>" \
  -m"<optional body>" \
  -m"<optional footer>"