sekstini

cnemri

Write a complete, production-ready, single-file HTML/JavaScript application that renders a highly detailed, photo-realistic, navigable 3D scene of the iconic cliffside village of Sidi Bou Said, Tunisia using Three.js.

CRITICAL INSTRUCTIONS — NO LAZY CODE

• Do NOT use any external asset URLs (no external .gltf, .obj, .jpg, or .png files) as they can break or fail CORS. All textures, heights, and models must be generated dynamically and procedurally within the script (e.g., using HTML Canvas to draw textures, procedural noise algorithms for plaster and stone, or mathematical structures for 3D meshes).
• Do NOT write placeholder comments, truncated code blocks, "// TODO" markers, or "left as an exercise" shorthand. Every single function, shader, loop, and variable must be written out in its entirety.
• The output must be a single, copy-pasteable HTML file that runs perfectly immediately when opened in a browser.

TECHNICAL REQUIREMENTS & FEATURES

1. Libraries: Load Three.js and OrbitControls vi

prostko

[CORE IDENTITY] 
You are a collaborative software developer on the user's team, functioning as both a thoughtful implementer and constructive critic. Your primary directive is to engage in iterative, test-driven development while maintaining unwavering commitment to clean, maintainable code through rigorous application of Clean Code principles.

[CLEAN CODE FOUNDATIONS]

CORE PRINCIPLES {
	YAGNI (You Aren't Gonna Need It) {
		- Implement only what's needed NOW
		- No speculative generality
		- No "future-proofing"

darconeous

Tesla Key Card Protocol

Researched by Robert Quattlebaum darco@deepdarc.com.

Last updated 2020-02-03.

GhostBoyBoy

AI-Collaborative Project Workspace: An RFC for Multi-role Context Engineering in Software Projects

中文

Background

Traditional software development is usually organized around humans.

A project is typically completed by multiple roles working together: product, design, frontend, backend, QA, operations, and others. Each role uses its own tools, documents, and working style:

• Product maintains PRDs, business rules, meeting notes, and requirement change records;
• Design maintains prototypes, interaction notes, visual designs, and flow diagrams;

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.

thisAdo

// © Ado | 2026
// Spotify Download 
const format = "mp3";
const url = ""; // Aquí la URL de la canción a descargar :D
async function sleep(ms) {
    return new Promise(resolve => setTimeout(resolve, ms));
}

const defaultHeaders = {
    "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/124.0.0.0 Safari/537.36",

imaurer

Unsloth Gemma 4 MOE Setup Guide

Running a 26B parameter model with only 6GB RAM using mmap

Overview

This guide covers running Gemma 4 26B MOE (Mixture of Experts) locally on an Apple Silicon Mac using llama.cpp with memory-mapped files. The MOE architecture activates only 8 of 128 experts per token, making it incredibly efficient.

Spec	Value