GitHub Copilot

Score8.8 out of 10

65 Reviews and Ratings

What is GitHub Copilot?

GitHub Copilot is an AI-powered developer tool that, according to the vendor, aims to assist developers in writing code more efficiently by reducing boilerplate code and improving productivity. It is designed for both individual developers and businesses of all sizes. The tool is commonly used by professionals in various industries, including software developers, web developers, mobile app developers, data scientists, and DevOps engineers.

Key Features

AI-powered coding suggestions: According to the vendor, GitHub Copilot uses AI to generate coding suggestions based on natural language prompts. It is trained on a vast amount of code to provide accurate and relevant suggestions, potentially helping developers implement solutions more efficiently.

Support for multiple languages: The vendor claims that GitHub Copilot supports dozens of programming languages, allowing developers to receive coding suggestions in their preferred language. It covers languages such as JavaScript, Python, Java, C++, Ruby, and more.

Integration with popular editors: According to the vendor, GitHub Copilot seamlessly integrates with popular code editors like Visual Studio Code, Neovim, JetBrains IDEs, and Visual Studio. It is designed to provide suggestions as developers type, potentially enhancing the coding experience.

Context-aware recommendations: The vendor states that GitHub Copilot shares recommendations based on the project's context and style conventions. It allows developers to navigate through lines of code, complete function suggestions, and make informed decisions on which suggestions to accept, reject, or modify.

Speeds up repetitive tasks: According to the vendor, GitHub Copilot helps developers save time by generating code for repetitive tasks. It reduces the need to write boilerplate code, potentially allowing developers to focus on more significant challenges.

Filters out vulnerable coding patterns: The vendor claims that GitHub Copilot includes built-in filters to identify and block common vulnerable coding patterns. This feature aims to assist developers in writing more secure code and reducing the risk of introducing security vulnerabilities.

Blocks suggestions matching public code: According to the vendor, GitHub Copilot has a feature that blocks suggestions matching public code. This is intended to ensure proper attribution and licensing, preventing developers from inadvertently reusing code without permission.

Categories & Use Cases

AI Code Generation

Vicky Negi

Lead UI/UX in Information Technology at Ideal User (11-50 employees employees)

Use Cases and Deployment Scope

GitHub Copilot is used in my company to help developers write better and structured code. We develop applications using PHP Laravel, but sometimes developers don't follow standard coding practices, which can lead to issues. They also need help understanding how to define write logics via coding terms. GitHub Copilot has been incredibly helpful to my team, enabling them to write better code and work faster.

Pros

Make code development faster and quicker.
Helps write better code standards for projects.
Provide the latest functions from the technology.
Notifies about the deprecated functions.

Cons

Copilot provides a great level of code suggestions. It works great for backend code, but can be improved for front-end code, including styling.

Return on Investment

CoPilot has saved my development time.
CoPilot has provided good-quality code to keep the client happy.

Usability

Alternatives Considered

Cursor

Other Software Used

Cursor, Anthropic Claude, Google Gemini, Azure OpenAI Service, Bolt, National Instruments Vision Builder AI

Pintu Barman View profile

Web Developer in Information Technology at Onlightenmedia (11-50 employees employees)

Use Cases and Deployment Scope

We use GitHub Copilot in our organization primarily for software development especially for code generation and code suggestion, its saves lots of time and helps us to develop our app faster with efficient code. Nowadays it become more powerful with the agent mode, now it has a capacity to perform very complex task with high success rate, if efficient prompt is provided.

Pros

Real time code suggestions are really fast and accurate I liked it.
After introduction of Agent Mode now it can handle very complex task with high accuracy.
Get better performance, if use it with MCP server.

Cons

The only issue I faced is the context token size, it can be increase.
Sometime with agent mode it takes too much time, which can be reduced but I understand it also depends on the complexity of the given task.

Return on Investment

It has very positive impact in our organization, it saves lots of time.
Helps us to build more efficient and secure Apps.
Helps in fast product development.

Usability

Alternatives Considered

Anthropic Claude

Other Software Used

Anthropic Claude

Verified User

Employee in Engineering (10,001+ employees employees)

Use Cases and Deployment Scope

We use github copilot as a coding assistant mainly. We have been using the IDE integrations of Github Copilot in both IntelliJ IDEA as well as VSCode. It has acted as a very strong coding assistant, providing valuable suggestions and feedback to the code. It also suggests code for problems that I describe, thus helping me "vibe-code" in my work. We have not yet procured the agentic capabilities for github copilot so my review is based on the non-agentic version.

Pros

Reading codebases and understanding the same.
Providing valuable code snippets for problems or tasks that I describe in English.
Also helps with other supplementary technical activities, such as, from time to time, I have asked it to suggest places where I can add logs and suggest how I can monitor those logs on Splunk via a dashboard. It has helped me with both.

Cons

Sometimes code generated by Copilot is not of the best quality, doesn't handle all the edge cases, and misses some requirements.
I have noticed that the Copilot is not the best at analyzing large monolithic codebases and placing them in their context. It has suggested to me APIs and methods from time to time that don't exist in my codebases.
I would have loved it if there were a deeper integration available with the IDEs. Although the IntelliJ IDEA extension is decent, I would have loved it if there were, say, a direct integration available of the GitHub Copilot agent with the IntelliJ Debugger.

Return on Investment

Has improved our dev velocity for simple tasks such as dependency updates or addressing SSRF vulnerabilities in our code bases by at least 50%.
Our Engineers use Copilot to even generate dashboards on Splunk. Thereby, not just helping with coding but also with observability and monitoring.
A slightly negative ROI may be that new grads into our company often blindly rely on GitHub Copilot-generated code and are not then able to demonstrate analytical and critical thinking ability. They struggle when it comes to verifying if the AI-generated code is accurate or not.

Usability

Alternatives Considered

Augment, Google Gemini, Uniqodo, Windsurf and Cursor

Other Software Used

Microsoft Visual Studio Code, GitHub, Atlassian Jira, Postman

Verified User

Team Lead in Engineering (11-50 employees employees)

Use Cases and Deployment Scope

Development teams in our organization use GitHub Copilot to improve productivity while working on .NET applications in the Visual Studio IDE. Before using GitHub Copilot, our developers depended on Google searches, AI tools, and developer forums to get help with development tasks. With GitHub Copilot now integrated into Visual Studio, they have a one-stop solution that eases their development process.

Pros

Code Completions.
Fixing Bugs in Code.
Optimizing Code.

Cons

Chat responses can be improved.
Accuracy needs improvement.
Ease of Use can be made better.

Return on Investment

Faster Development Time.
Learning Curve is Reduced.
Lowered Development Costs.

Usability

Alternatives Considered

ChatGPT, Perplexity and xAI Grok

Other Software Used

xAI Grok, Perplexity, ChatGPT, Microsoft Teams

Verified User

Engineer in Engineering (1001-5000 employees employees)

Use Cases and Deployment Scope

The department gathers all business requirements that in order to achieve them and make them real, we need to develop code. Here is where GitHub Copilot plays its role. We have Visual Studio Code and Eclipse installed in the developers local environments and we have installed the extension that helps us in developing and reviewing the code.

Pros

Review code
Answers quite good the questions I ask about the workspace configuration
Specialized agent for coding Java, Groovy

Cons

Sometimes generates nonsensical code, "hallucination," which can require additional review and correction
Sometimes can contain security vulnerabilities
It is a paid service