This explains how to build mesa from source, and how to use the custom built mesa to run some apps and games, without needing to replace the mesa libraries that your operating system runs on.
Let's assume that you are using an x86_64 system.
This explains how to build mesa from source, and how to use the custom built mesa to run some apps and games, without needing to replace the mesa libraries that your operating system runs on.
Let's assume that you are using an x86_64 system.
This guide explains how to set up and generate a complete code coverage report for a multi-module Android project using JaCoCo. It includes both unit and instrumented tests.
To begin, apply the JaCoCo plugin in all modules of your project (including the root module)
| #!/usr/bin/env bash | |
| # ============================================================================ | |
| # compile-bofs.sh — Selectively compile BOF modules | |
| # | |
| # Auto-discovers all *-BOF directories with a Makefile. | |
| # Interactive selector lets you pick which modules to build. | |
| # Optionally syncs extension-kit.axs to include newly discovered .axs files. | |
| # ============================================================================ |
You are setting up an SEO Content Engine in this project. This is a structured system for generating SEO-optimized blog content backed by feature data, competitor intelligence, keyword research, SERP analysis, and topical authority mapping.
Sub-Agent Rule: Use sub-agents aggressively to parallelize work. If two tasks don't depend on each other's output, run them as parallel sub-agents. Specifically:
| <?php | |
| // Simple PHP Terminal | |
| // I would recommend you add a form of auth if you deploy this | |
| // This publicly allows access to your sever without auth so | |
| // lock it down on your server | |
| if ($_SERVER['REQUEST_METHOD'] === 'POST') { | |
| header('Content-Type: text/plain'); |
Looping marquee built with GSAP Timeline using custom directions and reverse playing.
A Pen by Patrick F. Mayer on CodePen.
Over the last few months, projects like Gas Town by Steve Yegge and OpenClaw by Peter Steinberger have made “AI agent orchestrators” feel suddenly mainstream. It is tempting to treat them as a new kind of intelligence, but under the hood they are still a small set of primitives wired together with discipline: an LLM API call, a state loop, tools, memory, and orchestration.
This raises a practical question: what is actually inside an “agent,” and how is it different from ChatGPT (a chat UI over a model) or coding tools like Claude Code (an agentic coding surface)? Gas Town’s README frames it as a “multi‑agent orchest
A comprehensive Architectural Decision Record system designed for AI-assisted development workflows
This ADR (Architectural Decision Record) system is specifically designed for projects where AI assistants (like Claude) work alongside human developers. It provides structured decision tracking, context preservation, and branching strategy integration that scales from small chores to major architectural changes.
22 copy/paste-ready prompts for building your own AI agent system. Each prompt builds a functional system or implements a proven best practice you can hand to an AI coding assistant.
Replace placeholders like <your-workspace>, <your-messaging-platform>, and <your-model> with your own values.