GitHub is a version control system with you can write a code with Team, and manage your code. With GitHub Copilot as their name it is your Copilot which gives you a suggestion for your code. And give you title for your commits. Review collected by and hosted on G2.com.

Majority of the time GitHub Copilot gives you best suggestion for your code and title for your commits, but some times it gives you unnecessary title and code which is not useful for you. Review collected by and hosted on G2.com.

I like GitHub Copilot for its productivity improvement during day-to-day development. It can automatically generate DTOs, validation methods, login statements, and even unit tests based on naming conventions and comments. This allows developers like me to focus more on system design and complex logic rather than repetitive coding tasks. GitHub Copilot provides more context for our suggestions and offers better support for enterprise frameworks, which makes it more useful during actual development work. Review collected by and hosted on G2.com.

The suggestions are not always reliable for complex business logic or highly domain-specific implementations. For example, in enterprise consulting projects with custom frameworks, Copilot sometimes generated outdated patterns or insecure code suggestions that require careful review before use. Review collected by and hosted on G2.com.

I use GitHub Copilot mainly for code suggestions, debugging help, and speeding up repetitive coding tasks. It helps me generate boilerplate code, write functions faster, and understand APIs while working on projects in languages like Python, JavaScript, and HTML/CSS. Copilot saves time by suggesting optimized code snippets and assisting with documentation comments, especially useful during web development and automation projects, since it improves productivity and reduces manual effort. One of the GitHub Copilot's features I value the most is its real-time code suggestions because they help me complete functions and logic much faster while coding. Copilot Chat is also frequently used for debugging, explaining code, and getting quick solutions without leaving the editor. Automatic boilerplate generation during web development and scripting tasks is another time-saving feature. These features improve productivity, reduce repetitive work, and help me focus more on problem-solving instead of routine coding. Review collected by and hosted on G2.com.

While GitHub Copilot is very helpful, there are times when the code suggestions are not fully accurate or optimized for the specific project context. Sometimes it generates repetitive or outdated solutions, so the code still needs careful review and testing. In larger projects, Copilot can occasionally misunderstand the intent of complex logic or existing architecture. Another area for improvement would be better support for highly customized codebases and more precise debugging suggestions. Improving context awareness and reducing irrelevant recommendations would make the experience even better. The initial setup was not too much of an easy task. Review collected by and hosted on G2.com.

I use GitHub Copilot for my development work and creating production-ready applications by integrating it into the IntelliJ code editor. It boosts my productivity by reducing boilerplate code and helps me write small blocks of code quickly. I really like how it integrates into my editor, reducing the time needed to provide context since it already has all code access. With it integrated in the code editor, I can directly ask about anything within the editor itself, and it provides a valuable and structured response. Setting it up was easy since the editor supports it; I just logged in with the organization's GitHub account, and it worked. Review collected by and hosted on G2.com.

The answers should be concise as I use it in my code editor. I wish it provided interactive solutions, like giving architecture-related answers by clicking on each tile instead of writing everything in one place. Review collected by and hosted on G2.com.

Copilot helps to complete certain task with help of Ai intelligence and variety of useful integrations.

Different agents complete the workflow in a systematic manner. Review collected by and hosted on G2.com.

In complex tasks the copilot ai hallucinates sometimes and stuck between the files.

Also the pricing is bit high for advance/pro subscription. Review collected by and hosted on G2.com.

I mainly use GitHub Copilot as a code assistant. It helps me with code inline completions and writing code, which saves me a lot of time. I find the deep integration with VS Code very beneficial, especially with its inline suggestions that make coding much easier. It's amazing that it can even write whole custom functions according to my needs. The way it utilizes instructions and provides proper answers is commendable. Additionally, its deep integration with GitHub is very useful as it can write proper CI/CD pipelines for building, testing, and deploying code on GitHub. The initial setup was very easy, which was a bonus. I also like it's auto-pilot mode. Review collected by and hosted on G2.com.

It still falls short when solving/writing complex code with a lot of custom conditions. I was using the GitHub Pro with all model support, but recently they reduced some of the models. Now, they have another GitHub Copilot Pro+ plan, which complicates things for developers in choosing suitable plans while getting the most model support. Review collected by and hosted on G2.com.

Its strong integration with GitHub makes it a strong contender for developers already within that ecosystem. For individual developers, the Pro plan is often considered good value, paying for itself within the first week through time saved on boilerplate code, tests, and documentation. Review collected by and hosted on G2.com.

Learning how to use GitHub Copilot’s suggestions effectively and integrate them into a project can take some time, particularly when you’re working on more complex coding tasks. Review collected by and hosted on G2.com.

I mainly use GitHub Copilot inside vs code mainly when building a project or while practicing DSA. It saves my time by providing boilerplate code and common patterns along with helper functions that one needs to type in manually. Review collected by and hosted on G2.com.

Sometimes it misunderstands what I am actually trying to build. For more complex logic I still have to think through the implementation myself. Review collected by and hosted on G2.com.

GitHub Copilot excels as a strategic pair programmer, particularly within a documentation-first workflow. It’s remarkably effective at polishing technical documentation before a single line of code is written, then leveraging that context to generate highly accurate pattern recommendations. The VS Code integration is seamless, making it easy to manage the context window and keep instructions mapped to the proper memory locations for an uninterrupted flow. Onboarding was frictionless; simply logging into my licensed GitHub account integrated the tool immediately into my existing environment. Review collected by and hosted on G2.com.

I’d like a more seamless way to integrate with newer models or offline models, although I understand the security implications of allowing that kind of customization. It would also help to have clearer guidance on setting up the environment to better match my workflow style and methodologies, along with a more direct way to manage the AI’s memory, rules, and guidelines. Review collected by and hosted on G2.com.

I mainly use GitHub Copilot in VS Code, where it can read the whole repo and help me design prototypes. Review collected by and hosted on G2.com.

Recently, they started charging much more for credit usage, and that ended up being a painful dealbreaker for me. Review collected by and hosted on G2.com.