Instantly share code, notes, and snippets. If you encounter a problem where you cannot commit changes in Git – neither through the terminal nor via the GitHub Desktop application – the issue might be a freeze during the Git commit process. This is often caused by GPG lock issues. Below is a concise and step-by-step guide to resolve this problem. 1. Check for GPG Lock Messages Open your terminal and try to perform a GPG operation (like signing a test message). If you see repeated messages like gpg: waiting for lock (held by [process_id]) ... , it indicates a lock issue. Markdown-only workbook for Exam GH-600: Developing in Agentic AI Systems. Last updated: May 24, 2026. This version is organized around the official GH-600 domains. Each domain explains the concepts, shows the GitHub implementation artifacts, and includes examples you should be able to read in YAML, Markdown, CLI output, PR timelines, and audit logs. Public sharing note: this guide is not an exam dump and does not contain real exam questions or answer choices. It is a structured study workbook built from official Microsoft and GitHub documentation, with practical examples written for learning and review.

I have compiled all the resources that helped me in my GATE preparation , and I hope they help you too! 🚀 Gavin Sinclair , January 2022 I use Karabiner (configured with Gosu) to make advanced key mappings on my Apple computer. Karabiner allows you to create “layers”, perhaps simulating those on a programmable mechanical keyboard. I make good use of these layers to give me easy access (home-row or nearby) to all symbols and navigational controls, and even a numpad. The motivation is to keep hand movement to a minimum. Decades of coding on standard keyboards has unfortunately left me with hand and wrist pain. I will soon enough own a small split keyboard which will force me to use layers to access symbols etc., so this Karabiner solution, which has evolved over months, is a training run for that. 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.