How to Use GitHub Copilot with VS Code (2026 Guide)

According to GitHub’s productivity research, developers using GitHub Copilot completed coding tasks ~56% faster in controlled experiments.

But most of that speed gain evaporates when you factor in the time spent debugging AI-generated errors or hunting through scattered tools to understand what you’re even supposed to build.

This guide walks you through how to use GitHub Copilot with VS Code, from installation and inline suggestions to chat features and customization options. We hope that it helps you code faster without sacrificing quality. 🧑🏻‍💻

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What Is GitHub Copilot in VS Code?

Why do you need GitHub Copilot in VS Code?

Picture this: You’re three hours into debugging a tricky async function when you realize you need to look up the exact syntax for Promise.allSettled(). By the time you’ve found the MDN docs, scanned three Stack Overflow threads, and returned to your editor, you’ve completely lost your train of thought.

Instead of you manually looking up and typing every line, Copilot analyzes the context of your code—including your comments and function names—and suggests entire lines or blocks of code in real time.

This is a more advanced use case for AI in software development than simple autocomplete, which just predicts the next few characters. Copilot uses a machine learning model to understand your intent, helping you write code faster and maintain consistency across your team. It keeps you in your editor, focused on building, not on tedious repetition.

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Prerequisites for GitHub Copilot in VS Code

Want your Copilot setup to be smooth and take only a few minutes? You’ll need:

• A GitHub account: This is essential for authentication, as Copilot is a GitHub product
• An active Copilot subscription: You’ll need a subscription to a paid plan (Individual, Business, or Enterprise) or be on an active free trial
• VS Code installed: For the best experience and full compatibility, we recommend using the latest stable version of VS Code
• A stable internet connection: Copilot sends code context to its cloud-based models to generate suggestions, so it needs to be online to work

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How to Set Up GitHub Copilot in VS Code

Good news: setting up GitHub Copilot in Visual Studio Code is one of those rare “AI things” that actually is as easy as people claim.

If you already use VS Code and have a GitHub account, you’re about five minutes away from having an AI pair programmer quietly working beside you.

1. Install the GitHub Copilot extension

First, you need to add the Copilot extension to your VS Code installation. This is done through the built-in Extensions Marketplace.

1. Open Visual Studio Code. In the Activity Bar on the left, click the Extensions icon, or use the keyboard shortcut (Ctrl+Shift+X on Windows/Linux, Cmd+Shift+X on Mac)
2. In the search bar at the top of the Extensions view, type “GitHub Copilot”
3. Find the official extension published by GitHub and click the blue Install button

2. Sign in to your GitHub account

After the installation finishes, Copilot needs to connect to your GitHub account to verify your subscription. This process uses a standard OAuth flow to securely authorize the extension.

• A notification will pop up in the bottom-right corner of VS Code asking you to sign in
• Click the “Sign in to GitHub” button. This will open a new tab in your web browser

• In the browser, authorize the GitHub Copilot extension to access your account information
• Once authorized, you’ll be prompted to return to VS Code, where the authentication will complete automatically

3. Verify Copilot is active

Once you’ve signed in, you should confirm that Copilot is running correctly. You can check its status by:

• Looking for the Copilot icon in the status bar at the bottom right of the editor window
• Ensuring the icon doesn’t have a slash through it or any warning symbols
• Hovering your mouse over the icon to see the status tooltip, which should read “GitHub Copilot: Ready”

The final test is to open a code file and start typing. If you see light gray “ghost text” appearing ahead of your cursor, Copilot is active and generating suggestions. If you see a warning on the icon, double-check your subscription status and internet connection.

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How to Use Inline Code Suggestions

A lot of coding comes down to repetitive typing. Think boilerplate, common patterns, and small syntax you already know but still have to write out. This repetitive work isn’t only slow and boring but also error-prone, distracting you from the core logic of the feature you’re building.

Copilot’s inline suggestions address this problem directly. As you type, Copilot analyzes the context of your current file, your other open tabs, and even your comments to predict what you intend to write. These predictions appear as light gray “ghost text” right ahead of your cursor.

Suggestions can be as simple as completing the rest of a variable name or as complex as generating an entire multi-line function. Whatever they are, they’re designed to keep you in flow and reduce grunt work.

Accept a suggestion

When Copilot shows a suggestion you like:

1. Press the Tab key to accept the entire suggested code block
2. The accepted code is inserted directly at your cursor’s position, becoming part of your file
3. If you only want to accept the suggestion one word at a time, use the keyboard shortcut Ctrl+Right Arrow (Cmd+Right Arrow on Mac). Please note that these key combinations may depend on your OS

Cycle through alternative suggestions

If the first suggestion isn’t quite what you’re looking for, Copilot usually has other ideas ready.

1. When a suggestion is visible, press Alt+] (Option+] on Mac) to cycle to the next alternative
2. To go back to a previous suggestion you liked better, press Alt+[ (Option+[ on Mac)

Cycling through the options helps you find the best fit for your specific needs, whether you’re looking for a different implementation or just a different coding style. Just note that not every completion will have alternatives. Simpler completions may only yield one option.

Reject or modify suggestions

Copilot is a collaborator, not a dictator. If a suggestion is incorrect or not what you had in mind, you can discard it and continue on your own.

1. To dismiss a suggestion completely, simply press the Escape key
2. Alternatively, just keep typing. Your new input will override the suggestion, and Copilot will try to generate a new one based on what you’ve written
3. After you accept a suggestion, the code is yours to edit. It’s not locked in, and you can modify it just like any other code you’ve written manually

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How to Use GitHub Copilot Chat in VS Code

When you’re deep in a coding session and hit a roadblock—like a cryptic error, a complex piece of legacy code, or the need to write unit tests—your first instinct is to leave your editor, open a tab, and start searching online. That context switch is small, but it adds up fast.

GitHub Copilot Chat keeps you out of the rabbit hole by bringing a conversational AI directly into your IDE. It allows you to have a natural, back-and-forth dialogue about your code without ever leaving VS Code. You can ask it to explain code, help you debug, suggest refactors, and more, keeping your focus right where it needs to be.

Open the Chat view

There are a few ways to open Copilot Chat, depending on how you like to work:

1. Open Copilot Chat from the Activity Bar on the far left of the VS Code window
2. Alternatively, open the Command Palette (Ctrl+Shift+P or Cmd+Shift+P) and search for “GitHub Copilot: Open Chat”

This opens the Chat panel in the sidebar, where Copilot keeps track of your current conversation so you can refer back to earlier answers as you go.

Ask questions about your code

Copilot Chat works best when you treat it like a teammate who can see what you’re working on.

You can ask things like:

• “Explain what this selected function does”
• “Why might this code be throwing a null reference error?”
• “How can I refactor this loop to be more efficient?”
• “Generate three unit tests for this method using the Jest framework”

Use inline chat for quick edits

For making targeted changes to a specific block of code, the inline chat feature is often faster than using the full sidebar panel. Here’s how it works:

1. Select a block of code directly in your editor
2. Press Ctrl+I (Cmd+I on Mac) to open a small inline chat window right above your selection
3. Type your request, such as “Add JSDoc comments” or “Convert this to an async/await function”
4. Copilot will show you a diff preview of the proposed changes. You can then choose to accept or discard them

This method is perfect for quick refactoring and code transformations without breaking your visual flow.

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How to Use Copilot Agents for Autonomous Coding

Inline suggestions and chat are great for working inside a single file. But bigger tasks—like implementing a feature or cleaning up a cross-cutting bug—usually involve multiple files and coordinated changes.

That’s where Copilot’s newer agent-style features come in.

Instead of just answering questions, these tools help Copilot understand a higher-level goal and propose changes across a wider scope. They don’t replace your judgment, but they can dramatically cut down the setup and search work.

🎥 Curious how AI agents are transforming coding workflow and enabling more autonomous development? Watch this overview of the top AI agents for coding and their practical applications.

Here’s how you can access these emerging agentic features:

• The @workspace agent: In the Copilot Chat view, you can type @workspace followed by a question like “Where is the authentication logic defined?” to get answers based on your entire codebase, not just your open files
• Copilot Edits: Describe a change in natural language, and Copilot will identify the relevant files and propose a set of coordinated edits for you to review
• GitHub Copilot coding agent: Assign issues directly to Copilot on GitHub, and it will create a branch, implement changes, and open a pull request for your review—all running in the background while you focus on other work

What to keep in mind

Copilot’s agentic features are powerful—but they’re still assistive, not autonomous in the “set it and forget it” sense.

They work best when you:

• Give clear, scoped instructions
• Review changes carefully
• Treat them as accelerators, not decision-makers

These features are evolving quickly, and some may require a Copilot Pro or Enterprise subscription to access.

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How to Customize GitHub Copilot for Your Workflow

If Copilot feels too noisy, too eager, or just out of sync with your project’s style, that’s usually a settings issue—not a reason to give up on it. Visual Studio Code gives you several built-in ways to tune how GitHub Copilot behaves, so it supports your workflow instead of fighting it.

With a few small adjustments, Copilot can fade into the background when you don’t need it—and show up exactly when you do.

You can adjust the following options in your VS Code settings:

• Enable or disable for specific languages: If you don’t want suggestions in Markdown or JSON files, you can turn Copilot off for those languages while keeping it active for others
• Adjust suggestion behavior: You can configure Copilot to show suggestions automatically as you type or only when you manually trigger them with a keyboard shortcut (Alt+\ or Option+)
• Configure keyboard shortcuts: If Copilot’s default shortcuts don’t fit your muscle memory, you’re not stuck with them. All Copilot commands—accepting suggestions, cycling alternatives, opening chat—can be remapped through VS Code’s keyboard shortcut settings
• Content exclusions: For enterprise users, administrators can prevent Copilot from using the content of certain files or repositories as context, which is useful for compliance
• Create a Copilot instructions file: You can add a .github/copilot-instructions.md file to your repository to give Copilot specific guidance on your project’s coding standards or preferred libraries

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Limitations of Using GitHub Copilot for Coding

Relying too heavily on any AI tool without understanding its weaknesses can be risky. You don’t want to be shipping code that’s buggy, insecure, or doesn’t comply with licensing requirements. And let’s not even talk about creating technical debt and potential legal issues for your org.

Always sanity-check Copilot’s output for:

• Logic and edge cases
• Performance implications
• Security concerns

Be aware of Copilot’s limitations and treat it as a talented but fallible collaborator:

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Streamline Your Development Workflow with ClickUp

Writing better code faster with GitHub Copilot is a win. But as any developer knows, coding is only one piece of the puzzle. Once you’ve written or fixed that function, you still need to:

• Track the work (update tickets and sprint boards)
• Communicate the change (Slack, Teams, email)
• Document what you did (specs, API docs, release notes)

Switching between all these tools—Jira for tickets, Slack for chat, Confluence for docs—is more than annoying. It pulls you out of flow, consumes mental energy, and slows down delivery.

ClickUp addresses this exact problem by giving teams a single, Converged AI Workspace where development work and context live together, so your workflow stays smooth from task creation to delivery.

Let’s see how:

Link code snippets and tasks together

In real development, a task often spans multiple systems: a GitHub PR here, a Jira ticket there, docs somewhere else.

In ClickUp, organize every piece of work as an actionable item with its own status, assignee, and priority.

With ClickUp Tasks and the ClickUp-GitHub integration, you can link pull requests, commits, and branches directly to the relevant task in ClickUp.

This connection helps you:

• See at a glance what code changes are related to which task
• Trace history from planning to merged code
• Avoid context loss between environments

Your task becomes a single source of truth for the feature or bug you’re working on.

Plan and track work without manual status updates

Manage your entire agile workflow in one place with ClickUp Sprints. Add tasks from your backlog, monitor your team’s velocity with ClickUp Dashboards showing burndown and burnup charts, and easily move unfinished work to the next sprint.

This means no more manually updating tickets in another system after every commit. Your view in ClickUp reflects real progress automatically.

Keep specs, docs, and code side by side

Create and store all your project and code documentation—from architectural decisions to API guides—right alongside the tasks they relate to with ClickUp Docs.

ClickUp Docs also support code block formatting and nested pages, which are perfect for keeping technical documentation structured and readable. With Docs’ version history and live collaboration, your team always has the information they need to build the right thing.

Use natural language and AI to do more, faster

Most AI tools for developers focus on writing code. That’s useful, but it’s only part of the job.

Where work really slows down is everywhere around the code: understanding requirements, translating context into implementation, keeping docs updated, and answering the same questions across issues, PRs, and tickets.

ClickUp’s AI is designed to work inside that messy middle, where context usually gets lost.

Generate code in context, not in isolation

ClickUp’s AI code generation isn’t a generic “paste a prompt, get code” experience. It’s designed to work inside tasks, docs, and comments, so the code you generate reflects what the work is actually about.

📌 Example use cases:

• Generate a boilerplate API handler directly inside a task that already contains acceptance criteria
• Create a regex, utility function, or validation snippet while reviewing a bug report
• Draft test cases or mock data based on task descriptions instead of starting from scratch

Because the prompt lives next to the task context, you’re not re-explaining requirements every time you need a snippet.

Turn unclear requirements into developer-ready starting points

With ClickUp Brain, you can use AI to translate product or stakeholder language into something actionable before you ever open your editor.

📌 Example use cases:

• Summarize a long task description into a clean implementation checklist
• Convert vague feedback into concrete acceptance criteria
• Rephrase a feature request into technical requirements or edge cases

Instead of guessing what the task really means, you start with a clearer plan, which makes Copilot more effective once you do start coding.

Answer questions without a full IDE search

With ClickUp Brain, you can also ask natural-language questions across your workspace, like:

• “Where is authentication handled for this feature?”
• “What tasks are related to this endpoint?”
• “Has this bug been addressed before?”

Instead of hunting through tickets, Slack threads, and old docs, you get contextual answers pulled from tasks, comments, and documentation.

Use Codegen for scoped, reviewable work

ClickUp’s Codegen Agent is built for situations where you want help with execution, not just suggestions—but still want to stay in control.

You can assign the Codegen Agent to a task or invoke it from comments to:

• Generate a first-pass implementation based on task context
• Fix a clearly scoped bug described in the task
• Create a PR-ready change that you review before merging

The key difference from IDE-only AI? The agent understands the task, comments, linked docs, and acceptance criteria, not just a single file.

That makes it better suited for:

• Small features with clear boundaries
• Refactors tied to specific tickets
• Cleanup or consistency work across related files

⚠️ Nothing is auto-merged. The output is reviewable, editable, and treated like any other contribution.

Automate routine work that used to slow you down

Updating task states, looping in QA, or notifying stakeholders after a PR merges are all necessary, but they don’t require human judgment every single time.

Build if-then rules that automatically take care of these updates with ClickUp Automations. You can:

• Automatically move a task to In Review when a pull request is merged
• Assign a QA engineer when work is deployed to staging
• Notify stakeholders when a feature is ready for testing or approval

On top of that, AI Super Agents can step in when context does matter. Instead of just changing a status, they can:

• Generate a clear status update based on recent task activity
• Summarize what changed for reviewers or non-technical stakeholders
• Flag missing information before work moves to the next stage

Watch how Super Agents automate workflows end-to-end for you:

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The Whole Story: From Idea to Release, One Workspace

GitHub Copilot in VS Code helps you with the thinking and writing of code. ClickUp helps you with the entire lifecycle of that work: from capturing requirements, to tracking progress, generating snippets or feature prototypes, linking code, storing docs, and automating status changes.

That’s how you turn faster code into faster shipping.

If you want a single place where the why, what, and how of your software development life cycle live together, try ClickUp for free today!

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