The Underrated Fundamentals: Why Terminal and Git Skills Matter for AI Coding

If you're diving into AI-assisted coding tools, you might be tempted to skip straight to the exciting stuff—prompting, generating code, building apps faster than ever. But here's something that often gets overlooked: the fundamentals we learned in software engineering school are more important than ever.

I'm talking about the terminal and Git.

These tools might seem old-school compared to shiny AI assistants, but they're the foundation that makes everything else work. Once you learn them, AI coding becomes not just more effective, but genuinely more fun.

Why These Fundamentals Matter

Most AI coding tools operate in the terminal. They need to read your files, run commands, and interact with version control. If you're uncomfortable in that environment, you'll constantly feel like you're fighting against the tools rather than working with them.

Understanding Git means you can experiment fearlessly. Made a mess with an AI-generated change? Roll it back. Want to try a different approach? Branch off and explore. Version control gives you a safety net that makes AI coding less stressful and more experimental.

Getting Started with the Terminal

Tip 1: Learn the Navigation Basics First

You don't need to memorize hundreds of commands. Start with just these:

pwd — Print working directory (where am I?)
ls — List files in the current directory
cd — Change directory
cd .. — Go up one directory
cd ~ — Go to your home directory

Practice moving around your file system until it feels natural. That's it for week one.

Tip 2: Get Comfortable with Tab Completion

Press Tab while typing a file or folder name, and the terminal will autocomplete it for you. This saves typing and prevents typos. It's a small thing that makes a big difference in how fluid the terminal feels.

Tip 3: Don't Fear the Manual

Type man followed by any command to see its manual. For example, man ls shows you all the options for listing files. You don't need to read the whole thing—just skim it when you're curious about what else a command can do.

Getting Started with Git

Tip 1: Understand the Core Workflow

Git can be complex, but the daily workflow is simple:

git status — See what's changed
git add <filename> — Stage changes you want to keep
git commit -m "Your message" — Save those changes with a description
git push — Share your changes with others (or back them up remotely)

That's the loop. Status, add, commit, push. Everything else builds on this.

Tip 2: Commit Early and Often

Don't wait until you have a "perfect" chunk of work. Small, frequent commits give you more restore points. When you're working with AI tools that can make sweeping changes, having granular commits means you can surgically undo just the parts that didn't work.

Tip 3: Use Branches for Experiments

Before trying something risky:

git checkout -b experiment-name

Now you're on a new branch. If the experiment works, merge it back. If it doesn't, delete the branch and you're right back where you started. This is especially powerful when letting AI make significant changes to your code.

The Payoff

There's a learning curve, no doubt. The terminal can feel cryptic at first, and Git's mental model takes time to internalize. But once these tools become second nature, something clicks.

You stop fighting the environment and start flowing with it. AI coding tools become extensions of your workflow rather than awkward additions. You experiment more freely because you know you can always recover. And honestly? It becomes fun.

The fundamentals aren't just prerequisites to check off—they're what make the advanced stuff enjoyable. Invest the time, and your future self will thank you.