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Engineering Introduction

In 2026, engineering is built around collaboration with AI. This guide helps beginners set up a development environment from scratch, manage work with Git, use AI tools effectively, and understand how production AI services are structured.

Learn the basics of the command line. Most AI tools run in the CLI, so this is the starting point.

  • What a terminal is
  • Basic commands such as ls, cd, and mkdir
  • How to install and use Homebrew

Set up the tools needed to write code. Configure your shell, editor, and language runtimes.

  • Choose a shell: Zsh, Fish, or Bash
  • Install VS Code and useful extensions
  • Install Node.js with nvm and Python with pyenv

Learn the tools used to manage dependencies in JavaScript and Python projects.

  • The basics of npm, the default Node.js package manager
  • How pnpm works and when to use it
  • Python package management with pip and uv

Learn the core skills needed to manage code history and collaborate with a team.

  • Basic Git commands
  • GitHub accounts and SSH keys
  • Forks, clones, branches, and merges

Learn the basic rules for OSS licenses and the main points to watch in practice.

Learn the authentication, permission, audit logging, and data protection patterns needed for enterprise AI systems.

  • SSO and authentication design
  • Permission management and RBAC
  • Audit logging and evidence management
  • Data protection and privacy

Learn the API, database, monitoring, and deployment patterns needed to operate production AI services.

  • API design and API gateways
  • Database design patterns
  • Observability and monitoring
  • Deployment and CI/CD