| /********************************************************************* | |
| * | |
| * Name: user.js | brainfucksec | |
| * Descr.: Mozilla Firefox configuration file: `user.js` | |
| * Version: 0.26.0 (tested on Firefox 157.0) | |
| * Date: 2026-10-04 | |
| * URL: https://gist.github.com/brainfucksec/68e79da1c965aeaa4782914afd8f7fa2 | |
| * Maintainer: brainf+ck | |
| * | |
| * Info: |
From Zero to Git Hero - The Ultimate Hands-On Tutorial
🏷️ Topics: Git GitHub GitLab Version Control CI/CD DevOps Tutorial
This is the most comprehensive Git tutorial covering everything from your first git init to expert-level workflows. By the end, you'll be a Git master capable of handling any scenario.
Written by the speakers and attendees of AIE Code Summit 2026
In 2001, 17 software engineers and leaders got together at a ski lodge in Snowbird, Utah to understand the biggest challenge of their time: heavyweight, documentation-driven software development processes.
Out of this we got the Agile Manifesto, four values and twelve principles that changed how most of the industry builds software.
Today we convene to build our own manifesto - the No AI Slop manifesto.
| // http://codepen.io/incompl/pen/KwOqYx | |
| var games = [["PP","Pianissimo"], | |
| ["Fairy","Tale"], | |
| ["Fork","Tale"], | |
| ["Game","Thrones","Genesis"], | |
| ["Hat","Time"], | |
| ["Mind","Forever","Voyaging"], | |
| ["Ace","Spades"], | |
| ["Aces","Pacific"], | |
| ["Act","War","Direct","Action"], |
This guide will walk you through creating a custom MCP (Model Context Protocol) server that integrates with Claude Code, allowing you to extend Claude's capabilities with external tools, APIs, or even other AI models.
MCP (Model Context Protocol) is a protocol that allows Claude to communicate with external servers to access tools and capabilities beyond its built-in features. Think of it as a plugin system for Claude.
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.
| Welcome to Git (version 1.9.5-preview20150319) | |
| Run 'git help git' to display the help index. | |
| Run 'git help <command>' to display help for specific commands. | |
| Trum-Ma-Tuy@TRUM-MA-TUY-PC /D/xamp/htdocs/blog (master) | |
| $ git add -alll | |
| error: unknown switch `a' | |
| usage: git add [options] [--] <pathspec>... |
| BIT.LY link zu dieser Seite: | |
| https://bit.ly/weather-api | |
| API Key: | |
| bd5e378503939ddaee76f12ad7a97608 | |
| API Doku: | |
| http://openweathermap.org/current | |
| How to use an API key: |
