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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.

Learning Roadmap

1. Terminal Basics

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 work safely with files and directories

2. Development Environment Setup

Set up the shell and editor used to write code, and learn when to use stable or preview tooling.

  • Choose a shell: Zsh, Fish, or Bash
  • Install VS Code and useful extensions
  • Install VS Code Insiders and troubleshoot shell detection

3. Programming Languages

Learn the roles of JavaScript, Node.js, and Python and how to prepare their runtimes.

  • JavaScript and Node.js fundamentals
  • Python fundamentals, JSON, and APIs
  • Installing and managing Node.js and Python versions

4. Package Management

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

5. Git and GitHub

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

6. OSS License Basics

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

7. Enterprise Integration

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

8. Cloud Architecture

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

9. Development Methods

Learn how teams plan, build, operate, and improve software over time.

  • Agile vs waterfall
  • DevOps, MLOps, and AIOps overview