Tools & Workflows
Choose the task you want to complete. These guides explain setup and everyday use; the references help when you have forgotten a command or need to compare options.
Set up a project and work on it
- How do I get started with an Omarchy desktop? Omarchy Linux covers installation, daily use, updates, configuration, and recovery, including the differences between current and older setups.
- How do I keep a Python environment reproducible? Python environments with uv covers versions, dependencies, lockfiles, and running project commands. Use the Conda reference when you are working in an existing Conda environment.
- How do I track and share changes? Git and GitHub leads to version-control basics, branching, collaboration, and ignore rules.
- How do I give a coding agent useful project context? The repository-centered Codex workflow uses project instructions, architecture notes, and tests. Herdr workspaces addresses the separate problem of organizing agent terminals and understanding what survives a session restart.
- How do notebook cells reach a Python process? Jupyter architecture explains the browser, server, and kernel, including where execution state lives.
Find documents and keep useful context
QMD searches a local Markdown collection for concepts and past explanations. Choose zvec-grep for semantic search within code or documents. Basic Memory lets people and agents read, write and connect notes across sessions. Their capabilities overlap; choose based on what you need to retrieve or retain, rather than installing all three.
Work in a terminal or on a server
Vim covers editing and navigation inside files; Tmux covers terminal sessions, windows, and panes. For a remote machine, Personal VPS Fundamentals offers a path through SSH access, networking, firewall rules, containers, and routine operations.
Build an API or deploy a service
Cloudflare Workers starts with a local HTTP API and explains bindings, storage choices, deployment, and usage limits. Google Cloud introduces projects, permissions, billing, and the path from a local Python application to an authenticated Cloud Run service. Compare them with the VPS guides when deciding how much server administration you want to own.
Compute and draw in the browser
WebGPU explains GPU resources and shaders through standalone compute and rendering examples. Start there before adapting a browser experiment to GPU computation; compare with the existing Site Lab implementations.
Process text and media
Use regular expressions to match and extract text in Python. For media, yt-dlp covers download commands, while FFmpeg provides a FLAC-to-ALAC conversion recipe.
Explore how the website works
The site implementation notes explain Docusaurus and the interactive experiments. The Build Log records changes to the site and its working tools, if you want to follow their evolution.