What is GitHub Copilot? A Comprehensive Guide to Getting Started

Latest Update: 

• GitHub Copilot has introduced the integration of OpenAI's GPT-4.1 and GPT-4.5 models, offering improved performance in code completion and problem-solving tasks. 
• Additionally, Copilot now supports the @workspace context in Xcode, allowing developers to query their entire codebase for more comprehensive assistance.

GitHub Copilot is a powerful, AI-driven code assistant that enhances productivity by offering real-time code suggestions, writing boilerplate code, picking up a new framework, or working in an unfamiliar language. With over 30 million users worldwide in 2025, Copilot is quickly becoming a go-to tool for developers at every level. 

It helps with tasks ranging from simple code completion to solving complex AI engineering problems, all while saving time on repetitive coding tasks.

In this blog, we’ll explain what is GitHub Copilot, its core features, and how it can streamline your development process and boost coding efficiency.

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What is GitHub Copilot? Key Features and Capabilities

GitHub Copilot is an AI-powered code assistant built on OpenAI's Codex model, integrated directly into your code editor. It provides context-aware code suggestions, making development faster by automating repetitive tasks and allowing developers to focus on logic. Supporting multiple programming languages, Copilot helps you write better code with ease.

However, it’s important to be aware of some concerns. GitHub Copilot generates code based on publicly available repositories, which can raise data privacy issues and potential licensing risks. Always verify generated code for compliance with your project’s legal requirements.

What is GitHub Copilot X?

GitHub Copilot X builds on the original Copilot, offering enhanced contextual suggestions and deeper integration with development tools. This version aims to further streamline coding by providing smarter, more relevant suggestions based on the project’s broader context. So, what is GitHub Copilot X? It’s an upgraded version designed to make development more efficient by offering advanced code completions

Despite its advancements, Copilot X still lacks true reasoning. While it generates syntactically correct code, it doesn't fully grasp your business logic or specific project needs, making manual review essential for ensuring relevance and correctness.

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With a clear understanding of what GitHub Copilot is, let’s explore its core features and see how they can boost your coding efficiency.

Core Features of GitHub Copilot

GitHub Copilot’s core features include AI-driven code suggestions, context-aware completions, and multi-language support. It helps you write code faster by auto-generating entire code snippets or functions based on your prompts. 

Here’s a breakdown of its key functionalities:

• Contextual Code Suggestions and Multi-Language Support: GitHub Copilot offers intelligent, context-aware suggestions by understanding your existing code, making it more than just an auto-completion tool. Supporting languages like Python, JavaScript, C++, and Java, it adapts to various tech stacks, ensuring highly relevant completions for every developer.
• Function and Snippet Generation: Copilot quickly generates entire functions or snippets from minimal input, such as a function signature or a comment. This reduces the need for repetitive code, allowing developers to focus on more complex tasks and boosting productivity.
• Comment-Based Suggestions and Code Documentation: By generating code directly from your comments, Copilot streamlines both coding and documentation. This feature helps maintain clear, concise documentation while automating the implementation of described functions.
• Editor Integration and Code Assistance via Chat: Integrated into popular code editors like Visual Studio Code, Copilot provides real-time assistance as you write. With the new Copilot X chat interface, developers can ask for code clarifications or assistance directly within the editor, improving workflow efficiency.
• Pull Request Descriptions and Knowledge Base Management (Copilot Enterprise Only): GitHub Copilot Enterprise automatically generates pull request descriptions and manages knowledge bases, ensuring consistency in coding practices and saving valuable time for development teams, especially in larger projects.

Handling Ambiguous Prompts and Limitations in Accuracy

GitHub Copilot is highly effective at generating code suggestions, but it struggles with ambiguous or unclear prompts. When context is lacking, it may produce code that doesn’t align with the intended logic, requiring further refinement.

The quality of Copilot’s suggestions depends on how clearly the prompt is written. Vague or poorly defined inputs can lead to less relevant results. To get the best code, provide clear, precise prompts.

Now that you understand the core features, let's explore its capabilities in depth.

Key Capabilities of GitHub Copilot

GitHub Copilot offers a suite of advanced capabilities that go beyond basic code suggestions. From in-line code completion and unit test generation to debugging and multi-file edits, Copilot enhances every aspect of the development process. 

Here’s a look at how these features can streamline your workflow and boost productivity.

• In-Line Code Completion: GitHub Copilot accelerates coding by completing entire lines or blocks of code as you type. This real-time completion eliminates the need to search for syntax or boilerplate code, making your development process faster and more accurate.
• Unit Test Generation: Copilot infers potential unit tests from the function’s logic, automatically suggesting test cases to ensure your code is tested from the start. While it’s useful for generating initial test cases, Copilot doesn’t guarantee full test coverage or handle edge cases, meaning manual adjustments may still be necessary.
• Codebase Explanation: Copilot offers explanations for complex or unfamiliar code, making it easier to understand legacy code or new frameworks. This feature acts like a tutor, breaking down sections of code so you can quickly grasp their functionality and purpose.
• Upgrading Frameworks: Copilot may suggest updated syntax or imports, but it doesn’t intentionally detect outdated frameworks or libraries. Tools like Dependabot or linters are more suited for identifying outdated dependencies, while Copilot focuses on offering coding suggestions based on your current code.
• Code Translation: Copilot makes the code translation process seamless, helping you migrate projects or learn new languages without manually rewriting code. This feature is especially useful for teams working with multiple languages or transitioning between them.
• Documentation Generation: GitHub Copilot generates documentation for functions or methods, saving you time on writing descriptions. By creating clear, concise documentation, it helps maintain code readability and improves collaboration across teams.
• Debugging: Copilot assists in debugging by suggesting potential fixes for errors in your code. This feature makes troubleshooting quicker and more efficient, enabling you to identify and resolve issues without having to dig through your entire codebase.
• Refactoring: Copilot helps refactor your code for better performance, readability, and maintainability. For example, consider this before/after refactoring suggestion:
  Before:

def sum_numbers(a, b, c):
    total = a + b + c
    return total

After:

def sum_numbers(*args):
    return sum(args)

Copilot optimizes the code by simplifying the logic for summing numbers, improving readability and reducing repetitive code.

• Multi-File Edits: While Copilot can assist with code suggestions within individual files, it cannot autonomously edit multiple files unless manually guided. This feature should not be mistaken for automatic multi-file edits, as it currently requires user input for file navigation.
• Customization: GitHub Copilot allows limited personalization, such as adjusting the scope of suggestions based on your coding patterns. However, deeper customizations, such as adjusting specific coding style preferences, are still limited. While some personalization is possible, it doesn't fully cater to advanced style preference tuning.

Also Read: Difference between Testing and Debugging

Having covered its core capabilities, let’s explore how GitHub Copilot can be used for code generation to simplify your development process

How to Use GitHub Copilot for Code Generation?

To use GitHub Copilot for code generation, simply start typing in your code editor, and Copilot will suggest relevant code snippets based on your input. For example, if you begin a function in Python, it will automatically complete the rest of the code. By understanding "what is GitHub Copilot," you’ll see how it can seamlessly integrate into your workflow.

Here’s how you can use GitHub Copilot for code generation to make your development process more efficient.

1. Using Prompts for Code Generation

GitHub Copilot responds to prompts, making it highly flexible for generating code. You can simply write a comment describing what you want to achieve, and Copilot generates the code based on that description. For example, if you need a function to sort an array in Python, you can write a comment like:

# Function to sort a list in ascending order

Copilot will instantly provide the full implementation. This is an easy way to take advantage of GitHub Copilot, especially when you're unsure about syntax or how to write specific code.

Key considerations when using prompts:

• Clarity: The clearer and more concise your description, the more accurate the generated code will be.
• Vague or complex prompts: These may lead to incorrect or generic outputs.
• Large logic jumps: Copilot may struggle with complex algorithms or stateful programs, requiring manual adjustments.

2. Copilot Suggestions While Typing

GitHub Copilot works dynamically as you type, offering continuous suggestions. It predicts function parameters, return types, and even docstrings, speeding up your development process. However, it doesn’t always understand the underlying business logic, so generated code may need significant adjustments to meet your specific needs.

For example, if you start typing:

def calculate_sum(numbers):

Copilot will suggest the entire function body, saving you from writing boilerplate code. This helps you focus on adjusting the finer details rather than writing everything from scratch.

The value of this feature lies in its context awareness. Copilot understands the structure of your code and provides suggestions that integrate seamlessly into your workflow.

• In-Line Suggestions: If you’re typing within a function, Copilot might suggest just the next line or a specific part of the code, like a loop or condition.
• Full Block Suggestions: For larger blocks, Copilot can predict the entire function, offering a more complete solution, which you can then tweak.

This flexibility allows for efficient development, whether you're refining small details or working on larger sections of code.

3. Reducing Repetitive Tasks and Writing Documentation

Writing repetitive code can be time-consuming, but GitHub Copilot helps alleviate this by suggesting repetitive code blocks or generating entire functions based on a simple comment. Whether you’re working with loops, API requests, or setting up classes, Copilot suggests efficient code snippets that follow best practices.

In addition, Copilot can automatically generate documentation for your functions. When you write a comment describing a function, Copilot will add the docstring for you, saving time on documentation. This is particularly useful for projects that require clear and consistent documentation across the codebase.

Key points to consider:

• Repetitive Tasks: Copilot suggests code blocks or entire functions to automate repetitive tasks, letting you focus on the core logic.
• Documentation Generation: Copilot generates docstrings based on the structure and naming conventions of your code, so clear and meaningful inputs lead to better documentation.
• Accuracy: The quality of the generated documentation depends on how well your code is structured and named. Clear naming conventions and well-organized code improve the docstrings Copilot generates.

This feature helps save time on mundane tasks, allowing you to concentrate more on the development itself.

4. Using Copilot Labs Features

Copilot Labs offers experimental features designed to extend the capabilities of GitHub Copilot, providing even more powerful tools for developers. These features aim to improve code understanding, enhance suggestions, and automate additional tasks, offering you more flexibility and control.

Some of the features available in Copilot Labs include:

• Explain Code: This feature provides explanations for complex code snippets, making it easier to understand unfamiliar code or legacy projects. Simply highlight the code, and Copilot will break it down for you, helping you grasp its functionality.
• Brush: The Brush feature helps improve code quality by suggesting optimizations or refactoring options. It can suggest ways to simplify code or make it more efficient, improving readability and maintainability.
• Test Generation: Copilot Labs can assist in generating unit tests automatically. As you write your main functions, Copilot can help create corresponding tests, ensuring your code is well-tested from the start.

These features are experimental, meaning they may vary based on updates or user settings. As such, their availability or effectiveness could change over time as GitHub Copilot continues to evolve.

Also Read: GitHub vs GitLab: Key Differences & Features Compared

What Machine Learning Model is Used by GitHub Copilot?

GitHub Copilot uses advanced machine learning models, primarily OpenAI’s GPT-3 and GPT-4, to understand and generate code suggestions. However, Copilot actually uses Codex, a fine-tuned version of GPT-3, specifically trained for programming tasks. Here's how these models power Copilot:

• Generative Pre-trained Transformer (GPT-3 & GPT-4): GPT-3, with 175 billion parameters, is one of the largest language models. It's used by Copilot to process complex queries and translate them into relevant code suggestions. GPT-4 builds on this, improving accuracy and understanding.
• Codex Fine-Tuned for Programming: While GPT-3/GPT-4 provide the backbone, Copilot uses Codex, a version fine-tuned for understanding programming languages. Codex allows Copilot to interpret both code syntax and intent, making it more effective at suggesting code.
• Training on GitHub Code: Copilot is trained on vast amounts of publicly available code from GitHub repositories, enabling it to suggest contextually relevant solutions. It doesn’t just complete lines of code but understands the logic behind your requests, offering suggestions that match your intent.
• Context-Aware Suggestions: Copilot provides intelligent, meaningful suggestions by considering the context of the code you're writing. However, this context awareness is window-limited, meaning Copilot doesn’t have access to the entire project at once, but instead works within a limited context window.
• Continuous Learning: Copilot’s learning is session-based, not personal or real-time. While it adapts and improves its suggestions during your current session, it does not fine-tune based on your individual code or learning over time. This session-based learning ensures immediate accuracy but doesn't carry over between sessions.

In essence, what machine learning model is used by GitHub Copilot? It is powered by Codex, fine-tuned from GPT-3 and GPT-4, to deliver precise and context-aware code generation, improving its ability to understand and suggest relevant code based on the context of your project.

Also Read: Top 5 Machine Learning Models Explained For Beginners

Now that you know how GitHub Copilot aids in code generation, let’s walk through the process of getting started with this powerful tool.

How to Get Started with GitHub Copilot?

Getting started with GitHub Copilot is quick and straightforward. This process includes installing the tool, configuring it within your preferred code editor, and learning how to leverage its features to enhance your coding efficiency. 

Following are the steps highlighting how you can set it up and make the most of its capabilities:

1. Sign Up, Install and Configure the Extension

First, you’ll need to sign up for GitHub Copilot. If you don't have a GitHub account, create one at GitHub’s sign-up page. Once your account is ready, you can subscribe to GitHub Copilot.

After signing up, the next step is installing the GitHub Copilot extension. Here’s how to do it:

1. Open VS Code: GitHub Copilot works seamlessly within Visual Studio Code (VS Code). So, ensure that VS Code is installed on your computer.
2. Go to the Extensions Panel: In VS Code, click on the Extensions view icon or press Ctrl+Shift+X.
3. Search for GitHub Copilot: Type “GitHub Copilot” in the search bar and click Install.
4. Authenticate GitHub: Once installed, you’ll be asked to authenticate your GitHub account with VS Code. This will link your GitHub Copilot subscription to your editor.

With the extension installed and configured, you’re ready to start coding. GitHub Copilot will start providing suggestions as soon as you begin typing in the editor.

Once you're set up, let's look at how to effectively use GitHub Copilot in your development process.

2. Start Coding, Review Suggestions, and Provide Feedback

Now that GitHub Copilot is installed, you can start coding. Copilot will offer real-time code suggestions based on the context of the code you’re writing. It works for a variety of languages and can help you write functions, complete loops, and even generate comments. Here’s how to use Copilot effectively:

1. Write a Comment or Start a Function: Begin by writing a comment describing the functionality you need. For example:

 # Function to calculate the sum of a list

GitHub Copilot will instantly suggest the code for you.

1. Review Suggestions: As you type, Copilot will offer suggestions in grey text. If the suggestion is appropriate, press Tab to accept it. If not, simply keep typing, and Copilot will refine its suggestions.
2. Provide Feedback: GitHub Copilot lets you rate suggestions with thumbs-up or thumbs-down icons. Your feedback helps improve its accuracy over time. However, Copilot doesn’t learn in real-time or from individual users. Feedback contributes to overall model improvements but doesn’t influence immediate suggestions or adapt based on a single user’s input.
3. Manual Triggering of Suggestions: For advanced users, you can manually trigger suggestions by pressing Ctrl + Enter to prompt Copilot to provide recommendations, even when it doesn’t automatically suggest code.

Now, let’s dive deeper into the free features of GitHub Copilot and explore what you can get without having to pay a subscription.

Is GitHub Copilot Free?

If you’re wondering, “Is GitHub Copilot free?”, the answer depends on your use case. GitHub Copilot does offer a free tier with limited features, so you can try it out before deciding whether to subscribe to the premium version. 

Let’s explore what features are included in the free version and what benefits you’ll get.

• GitHub Copilot Free Features: The free version of GitHub Copilot offers essential features like in-line code suggestions, function completions, and support for multiple languages such as Python and JavaScript, helping developers streamline their workflow without any cost.
• Model Choices and Integration in VS Code and GitHub: Seamlessly integrate GitHub Copilot with VS Code and GitHub. GitHub Copilot integrates seamlessly with VS Code and GitHub, offering easy setup. While users can’t manually select models like GPT-3 or GPT-4, the system automatically chooses the best model for your context.
• 2,000 Code Completions and 50 Chat Messages Per Month: In the free version, you get up to 2,000 code completions and 50 chat messages per month, which is ideal for developers who are just starting or those working on smaller projects. This allows you to get interactive support and real-time code suggestions. So, is GitHub Copilot free in terms of usage? Yes, for up to these limits.
• Multi-File Edits and Copilot Extensions Ecosystem: The free version of GitHub Copilot supports multi-file edits, which makes it suitable for larger projects. Additionally, it grants access to the Copilot Extensions Ecosystem, offering enhanced functionality. However, true multi-file awareness remains experimental. Therefore, is GitHub Copilot free in this regard? Yes, but with some limitations on multi-file editing.
• Student/Educator Access: GitHub Copilot is also available for free to students and educators through the GitHub Student Pack, providing full access to Copilot for educational purposes.

Free vs. Paid Features

So, is GitHub Copilot free? Yes, it offers a robust set of features for individual users at no cost, with an option to upgrade for additional functionality such as unlimited code completions, private repository access, and priority access to new features.

Also Read: Top 15+ Open Source Project Repositories on GitHub to Explore in 2025

With the setup process covered, let’s discuss the benefits GitHub Copilot offers, as well as its limitations to keep in mind while using it.

What are the Benefits and Limitations of GitHub Copilot?

GitHub Copilot offers significant benefits, such as faster coding, real-time code suggestions, and seamless integration with your editor. It boosts productivity by reducing the time spent on repetitive tasks and improves code quality with its context-aware suggestions. However, it also has limitations, like potential inaccuracies in generated code or dependency on training data. 

Here's a look at the key benefits and limitations you should consider while using GitHub Copilot:

Also Read: 15+ AI Developer Tools To Enhance Your Career in 2025

After exploring the benefits and limitations, let’s now look at how GitHub Copilot is practically used across different development scenarios.

How GitHub Copilot is Used in Practical Scenarios?

GitHub Copilot is used in various practical scenarios to boost productivity and streamline coding. For instance, in web development, it can autocomplete HTML, CSS, and JavaScript code based on context, helping developers move faster. In data science, it generates Python functions or machine learning models with minimal input. 

Here’s how GitHub Copilot enhances coding in different scenarios:

Frontend Development

Copilot streamlines the development of interactive user interfaces and responsive layouts for web applications.

• Web Development: Copilot accelerates frontend development by offering code suggestions for HTML, CSS, and JavaScript. It helps with creating responsive layouts, interactive elements, and form handling. Copilot integrates well with frameworks like React, Angular, and Vue, making it easier to implement features with context-aware suggestions.
• Rapid Prototyping: For quick proof-of-concept development, Copilot can generate initial code for functions, classes, or modules. For example, creating a login system in a web app could be done in seconds with a simple comment like "Create login functionality for a web app," saving time on boilerplate code.

Backend Development

Copilot assists in backend coding by automating repetitive tasks and simplifying complex logic.

• Software Engineering: In backend development, Copilot assists by generating utilities, simplifying complex algorithms, and handling edge cases within large codebases. It reduces the time spent on repetitive tasks, allowing developers to focus on more complex engineering challenges and logic.

Data Science

Copilot enhances the data science workflow by offering suggestions tailored to machine learning and data manipulation tasks.

• Machine Learning and Data Manipulation: Copilot provides valuable suggestions for data science tasks, from building machine learning models to manipulating data. It assists with framework-specific code for libraries like TensorFlow, suggesting model structures, and for Pandas, offering DataFrame operations such as filtering, grouping, and aggregating data. This helps streamline workflows and accelerates algorithm experimentation.

DevOps

Copilot supports DevOps practices by generating automation configurations for deployment and CI/CD workflows.

• CI/CD Pipelines and Automation: Copilot is also helpful in DevOps, where it can generate configurations for Dockerfiles, GitHub Actions workflows, or CI/CD pipelines. It automates the setup for containerized applications, builds, and deployment processes, making it easier for developers to manage environments and streamline deployment pipelines.

Educational Tools

Copilot makes learning to code easier by offering real-time suggestions and helping students focus on logic rather than syntax.

• Learning and Teaching: For beginners or students, Copilot serves as an excellent tool for learning. It generates real-time code suggestions that teach coding patterns, syntax, and best practices. Students can focus more on logic than on syntax, as Copilot assists in generating functions or entire programs, simplifying coding assignments.

Open Source Contributions

Copilot aids developers in contributing to open-source projects by ensuring code consistency and adherence to standards.

• Contributing to Open Source: Copilot offers real-time suggestions when contributing to open-source projects. It helps developers navigate large, unfamiliar codebases, ensuring consistency with project style and structure. Copilot also assists with generating tests and documentation, ensuring that contributions adhere to established standards.

Also Read: Top 20 Real-Time Project Ideas for Beginners

Now that you know how GitHub Copilot enhances your coding, it’s time to become an expert with upGrad’s advanced courses. 

Become an Expert at GitHub Copilot with upGrad!

GitHub Copilot is a powerful tool for developers, and learning how to use it effectively is essential. By understanding coding best practices and incorporating AI-powered development, you can enhance your skills and take them to the next level.

upGrad offers a range of courses that help you understand GitHub Copilot. These courses also enhance your coding expertise, particularly in areas where Copilot can make a significant impact.

Here are some free upGrad courses to help you get started in your AI-powered development career.

• Learn Python Libraries: NumPy, Matplotlib & Pandas
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