GitHub Copilot for Beginners: How to Get Started with AI Pair Programming

GitHub Copilot is an AI-powered coding assistant that lives directly where you write code: in your IDE or editor and on GitHub.com.

Instead of copying code from Stack Overflow or constantly jumping to a browser to ask a chatbot for help, Copilot appears as inline suggestions (often called ghost text) right in your editor. It predicts what you’re trying to do and offers code to help you get there faster.

Some of the key things GitHub Copilot can help with include:

• Code completion beyond a single line – It doesn’t just finish variable names; it can generate whole functions and even larger code blocks.
• Writing code from natural language – You can describe what you want in plain English (or another natural language), and Copilot suggests relevant code.
• Understanding shell commands – It can help interpret or generate terminal commands.
• Explaining existing code – If you’re dropped into a new codebase or just forgot what you wrote 6 months ago, Copilot Chat can summarize and explain it.
• Describing changes for pull requests – It can help you write descriptions of what changed and why.
• Debugging assistance – It can point out potential issues and suggest fixes or improvements.

In my experience, the biggest shift is that Copilot feels less like a search engine and more like a teammate quietly handing you suggestions as you type.

And importantly, it’s not limited to a single environment. GitHub Copilot is available in:

• Visual Studio Code
• Visual Studio
• JetBrains IDEs (like PyCharm, IntelliJ IDEA, WebStorm, etc.)
• Neovim
• Xcode
• GitHub Mobile
• Your terminal
• On GitHub.com itself

You can use it with a wide variety of programming languages—Python, JavaScript, TypeScript, Java, C#, Go, and many others—inside your editor of choice.

It doesn’t replace your skills. Instead, it amplifies them by handling a lot of the repetitive or boilerplate parts of coding.

It’s easy to mistake GitHub Copilot for “just a fancy autocomplete,” but that really undersells it.

Here’s what makes it feel more like a companion than a basic completion tool:

• Context awareness: Copilot looks at the file you’re working on, neighboring code, comments, and sometimes your broader project context (depending on settings and environment) to generate more relevant suggestions.
• Natural language prompts: You can literally write a comment like `# validate email addresses` and Copilot will try to generate a function that does that.
• Conversational chat: With GitHub Copilot Chat, you can ask questions like:
• “Explain what this function does.”
• “Improve this regex for better email validation.”
• “Refactor this code to be more readable.”

One important note: Copilot is non-deterministic. That’s a fancy way of saying:

> The same prompt or code context may give you different suggestions each time.

So if you and a colleague both try the same experiment, you might get slightly different solutions. That’s normal. The point isn’t to get identical output; it’s to get useful output that you can then review, tweak, or reject.

You’re always in control. Copilot suggests; you decide what to accept, modify, or ignore.

GitHub currently offers four main licensing options for Copilot:

1. GitHub Copilot (Free) for individuals
2. GitHub Copilot Pro for individuals
3. GitHub Copilot Business (through your employer or organization)
4. GitHub Copilot Enterprise (for larger organizations with advanced needs)

The exact feature list can evolve over time, so it’s always smart to check GitHub’s official documentation or pricing page for the latest comparison. But the high-level idea is:

• Individual plans (Free and Pro) are for personal use.
• Business and Enterprise plans are for organizations that want centralized management, policy controls, and sometimes additional features around security and compliance.

If you’re just getting started and you’ve never used Copilot before, the easiest path is to try the free option first. It lets you get hands-on without committing to anything.

From there, you can decide if Pro or an organization-level plan makes sense for you.

One of the really nice touches from GitHub is that certain groups can get upgraded access at no cost.

You may be eligible for free GitHub Copilot Pro if you are:

• A student
• An educator
• A popular open source project maintainer (as recognized by GitHub)

This access is typically managed through GitHub Education for students and educators. If you fall into that category, it’s worth taking a few minutes to verify your eligibility and unlock the full Pro experience.

If you’re not sure:

• Log into your GitHub account
• Visit GitHub Education (or Copilot’s official page)
• Check the requirements and follow the verification steps

To be honest, if you’re a student learning to code right now, having Copilot as a pair programmer can be a massive shortcut to understanding patterns and syntax—as long as you still take time to read and understand what it generates.

Here’s a straightforward way to get GitHub Copilot running in VS Code.

1. Open VS Code
Make sure you’re on a reasonably up-to-date version.

2. Go to the Extensions Marketplace
- Click the Extensions icon on the left sidebar (or press `Ctrl+Shift+X` / `Cmd+Shift+X` on macOS).

3. Search for “GitHub Copilot”
- You should see an extension named GitHub Copilot.

4. Click Install
Installing this also brings in GitHub Copilot Chat, the conversational AI assistant that lives in a dedicated panel.

5. Sign in with your GitHub account
- If you haven’t already authorized VS Code with your GitHub account, you’ll be prompted to do so.
- VS Code will open your browser and ask you to approve the necessary permissions.
- Click Continue and authorize Visual Studio Code.

6. Confirm Copilot is ready
Back in VS Code, you’ll notice:
- A Copilot icon at the top (near the command center)
- A Copilot icon at the bottom of the editor

Clicking the bottom icon usually shows a status like “Ready”. If you see that, Copilot is installed and active.

If you’re asked to pick an account, select the GitHub account that has your Copilot license. After that, everything should be wired up automatically.

From this point on, you’re ready to start typing and see inline suggestions appear as ghost text.

Let’s walk through a simple Python example to show what using Copilot actually feels like in VS Code.

1. Create a new Python file
- In VS Code, create a new file named `validate.py`.

2. Start writing some code
Type:

```python
import re
```

After you hit Enter, GitHub Copilot will often detect the file name (`validate.py`) and infer you might want to validate something like email addresses. It may suggest a function such as `validate_email` or something along those lines.

3. Accepting suggestions
- Copilot’s suggestion appears as gray “ghost text.”
- Press Tab to accept the suggestion.

If the suggestion is close but not perfect, you can accept and then tweak it, or just keep typing to nudge Copilot toward what you actually want.

4. Seeing multiple completions
If you hover over the suggested code, you’ll often see that there are:
- Additional options
- A completions panel you can open to view multiple generated variants

This is handy when you want to compare a few different approaches.

5. Inline code completion in action
As you keep working—maybe adding a `main` function or hooking up input handling—Copilot continues suggesting the next logical lines.

Again, don’t worry if your suggestions differ from someone else’s. Because Copilot is non-deterministic, outputs can vary, but the overall behavior is the same: it’s trying to follow your intent based on the context you give it.

Now, that’s only half of the story. The other half is Copilot Chat, which is where things get surprisingly powerful for understanding and modifying code.

Let’s say you’ve got that `validate.py` file with a function to validate email addresses, but you’re seeing it for the first time and you’re not fully sure how it works.

Here’s how you can use Copilot Chat to get up to speed quickly:

1. Open Copilot Chat
- In VS Code, click the Copilot Chat icon (usually in the sidebar or near the Copilot controls).

2. Ask it to explain the code
You can type something like:

```
/explain
```

or in some setups, `@workspace explain this file`, or simply, “Explain the code in the current file.”

Copilot Chat is aware of the currently open file, which is indicated by an icon or context marker in the chat window.

3. Read the explanation
Copilot will provide a nicely formatted breakdown of what your code is doing:
- What the regex is for
- How the function validates input
- How the main function runs the validation, etc.

This is incredibly helpful when you’re joining a new project, revisiting old code, or trying to learn by example. It’s like asking a senior engineer, “Walk me through this, please,” but without worrying about interrupting anyone.

Now imagine you want to go a step further:

You don’t just want to understand the email validation. You want to improve it and allow users to enter multiple email addresses for validation.

Here’s how Copilot Chat can help:

1. Describe what you want changed
In Copilot Chat, you might write:

> Allow users to enter multiple email addresses for validation and also improve the regex to be more robust.

2. Review the generated plan and code
Copilot will typically:
- Propose a plan (what it intends to change)
- Show an updated code block with the modifications
- List out the specific changes it made (e.g., “Added loop to handle multiple emails,” “Strengthened regex to check domain structure,” etc.)

3. Apply changes to your editor
You’ll often see an “Apply in editor” (or similar) button.
- Click that, and Copilot will go ahead and update your actual file with the new code.

4. Verify and test
This part is crucial and easy to skip: you still need to review and test the code.

In my experience, Copilot is very helpful, but not infallible. Treat its output as a strong first draft, not unquestionable truth.

Over time, you’ll probably find a nice rhythm:

• Type a bit of code or comments
• Let Copilot suggest completions
• Use Copilot Chat to refactor, explain, or enhance sections
• Test, debug, and refine as you normally would

That combination—inline suggestions plus conversational chat—is where it starts feeling like a real AI pair programmer rather than a simple autocomplete tool.

Here’s how to get Copilot working in JetBrains IDEs. The example here references PyCharm, but the process is essentially the same across JetBrains products.

1. Open your JetBrains IDE
Launch PyCharm, IntelliJ IDEA, WebStorm, or whichever JetBrains editor you’re using.

2. Open the Plugins Marketplace
- Go to Settings/Preferences → Plugins.
- Search for “GitHub Copilot”.

3. Install the GitHub Copilot plugin
- Click Install.
- Restart your IDE when prompted.

4. Look for Copilot icons
After reopening your project, you should notice:
- A Copilot icon on the right-hand side of the editor
- Two icons on the left-hand side:
- A GitHub Copilot icon with a question mark (for general info and a welcome message)
- A chat icon for GitHub Copilot Chat

If you see those, it means the plugin is active and you’re nearly ready to go.

You’ll now need to authorize the plugin with your GitHub account that has Copilot access.

1. Sign in to GitHub from the IDE
If you haven’t previously authorized JetBrains with your GitHub account:
- Click the Copilot icon at the bottom or in the side panel.
- Choose “Login to GitHub” (or similar wording).

2. Approve permissions in your browser
- The IDE will give you a code and a “Copy and open” button.
- Click it to open your browser on GitHub’s authorization page.
- Paste the code if prompted (using `Cmd+V` or `Ctrl+V`).
- Click Continue and then Authorize GitHub Copilot plugin.

3. Confirm Copilot is active
Return to your IDE. You should see a message that GitHub Copilot has been successfully installed and authorized.

4. Authorize GitHub Copilot Chat
- Click the chat icon in the IDE.
- Click the Authorize button.
- Again, you’ll get a code and a “Copy and open” button.
- Paste the code in your browser.
- Click Authorize GitHub Copilot for JetBrains IDE.

5. Check for a greeting
Back in the IDE, you should see a greeting from GitHub Copilot Chat, confirming it’s ready to use.

From there, the usage is very similar to VS Code:

• Start typing to see inline suggestions.
• Use Copilot Chat to explain, refactor, or generate code.

The only real difference is the look and feel of the IDE around it.

While lots of AI tools can generate code, GitHub Copilot is:

• Purpose-built for programming – It’s designed primarily for software development tasks, not for general-purpose chat.
• Deeply integrated with your tools – It lives directly inside your editor and on GitHub.com, so you don’t need to constantly switch between browser tabs and your code.
• Contextual to your actual project – It can leverage the open file and, in many cases, your workspace context to provide more accurate and useful suggestions.

In my experience, that integration is the real differentiator. When you stay inside your IDE:

• You reduce context switching (which is surprisingly tiring over long coding sessions).
• You get suggestions directly where they matter—next to the code you’re editing.
• You can test and iterate immediately without bouncing between a browser and terminal.

So when you hear “GitHub Copilot”, think of it as:

> Your personal AI pair programmer that works where you work—inside your editor and GitHub workflows.

It’s not just a chatbot that sometimes writes code; it’s a coding assistant designed around the realities of software development.