GitHub Copilot significantly speeds up development by providing intelligent code suggestions directly in the editor. It’s very effective for reducing repetitive coding tasks, generating boilerplate code, and even suggesting entire functions based on context. The integration with editors like Visual Studio Code is seamless, making it easy to adopt without changing existing workflows.

I also like how it adapts to different programming languages and frameworks. It’s especially useful when working with unfamiliar code or trying out new technologies, as it can suggest patterns and examples quickly. Overall, it improves productivity and helps maintain development flow without constant context switching. Review collected by and hosted on G2.com.

While Copilot is very helpful, the suggestions are not always accurate and still require review. For more complex or critical logic, it’s important to validate the generated code carefully. Sometimes it can suggest outdated or suboptimal patterns. Additionally, over-reliance on suggestions can reduce deeper understanding if not used thoughtfully. Review collected by and hosted on G2.com.

I like Github Copilot because it reduces the time spent on repetitive coding tasks. I also like that it works smoothly inside VS Code, so I dont have to switch between browser tabs and documentation again .Its very easy to implement for beginners.The frequency of use is also high for me because I use it almost daily while coding.It helps with writing functions,fixing small mistakes and speeding up repetitive tasks which makes development smoother.It is ease of integration with tools like VS Code . Review collected by and hosted on G2.com.

One thing I dislike is that sometimes the suggestions look correct but dont fully match the requirement, so you still need to review the code carefully. Another small issue is that getting very specific help through customer support is not always instant , so sometimes you have to rely on documentation. Review collected by and hosted on G2.com.

I use GitHub Copilot regularly during backend development, mainly inside Visual Studio Code. One of the things I like most is how easy it is to start using. After installing the extension and signing in, it immediately begins suggesting code while you type, so there isn’t much setup required.

During my day-to-day work with Python APIs, Copilot helps by suggesting function structures, repetitive code, and common programming patterns. It is especially useful when writing helper functions, validation logic, or basic API endpoints. Instead of searching for syntax or examples online, I often get a useful starting point directly in the editor.

Another advantage is how well it integrates with the existing development workflow. Since I already work in VS Code with Git for version control, Copilot feels like a natural extension of the editor rather than a separate tool. I use it frequently while coding, and it helps maintain development flow and saves time on routine coding tasks. Review collected by and hosted on G2.com.

While Copilot is very helpful, the suggestions are not always perfect, especially for complex or project-specific logic. Sometimes the generated code needs to be adjusted to match the project’s structure or coding style.

Another thing to keep in mind is that developers still need to carefully review the suggested code before using it. I treat Copilot more as a coding assistant that helps speed up development rather than something that can fully replace manual coding. Even with that limitation, it is still very useful for reducing repetitive work. Review collected by and hosted on G2.com.

I use GitHub Copilot to help with coding basic things, formatting my code, and looking for errors. It's integrated into my IDE (VS Code), so I don't have to switch tabs. I appreciate that it comes with multiple LLM options like Claude, ChatGPT, and Gemini, allowing me to switch as I wish. It doesn't run out of credits and has better code handling compared to the traditional web versions. I love that I don't have to copy and paste my code because it already has access and updates it itself. Before changing my code permanently, I can see how the new version performs and the changes it made before deciding to 'keep' it. The integration of multiple AIs helps me check what each has to offer before going with one. The setup was really easy; I just got the extension and connected my GitHub account, and I was good to go. Review collected by and hosted on G2.com.

Sometimes it takes too long to generate a response and keeps meddling with the terminal instead of the actual code, but that happens rarely. Review collected by and hosted on G2.com.

What I love most about GitHub Copilot is how effortlessly it supports my day-to-day automation work. The ease of use is what hooked me from day one; it genuinely feels like having a partner who already understands my coding style and our specific Java framework. I use it constantly throughout the day, and that frequency has actually changed how I approach writing new scripts. Instead of digging through documentation for Rest Assured syntax or Selenium locators, I can just start typing and it completes what I’m trying to do. It keeps me in the flow, making the whole process feel more natural and far less like a chore.

The implementation and integration have been big pluses for me as well. Since our codebase already lives in GitHub, getting it running in my IDE was basically a one-click setup. It didn’t require complicated configuration or major changes to how we work; it simply fit into our existing Git workflow. The range of features—especially the new agent mode—has also noticeably boosted our productivity. It’s not only about basic code completion anymore; it’s about having a tool that can help me think through more complex logic or even refactor an entire page object while I’m still in the middle of a sprint.

Whenever I’ve hit a strange glitch or had questions about recent updates, both customer support and the community have been really helpful. It’s reassuring to know the platform is well supported, especially since we rely on it so heavily for testing now. At this point, it’s become an essential part of my toolkit—I can’t really imagine going back to writing boilerplate code by hand or spending hours debugging simple typos that Copilot catches right away. It lets me focus more on the interesting parts of my job, like figuring out the best testing strategies for our products. Review collected by and hosted on G2.com.

The context window can also be a bit frustrating. In our larger automation files—especially those with hundreds of lines of API test cases—Copilot sometimes loses track of the logic I established at the top of the file. It then starts suggesting variable names or logic that doesn’t align with the rest of the script, which forces me to pause and manually correct it. It’s not a dealbreaker, but it does interrupt my momentum. Review collected by and hosted on G2.com.

The Copilot drastically increases my productivity by suggesting, in real-time, repetitive code blocks and even more complex logic. It's like having a constant partner in programming the projects at Jheytech.Ai. Review collected by and hosted on G2.com.

Sometimes, the suggestions may be based on outdated libraries, which requires a more careful manual review. Additionally, the reliance on a stable internet connection can be a limiting factor.

What problems does it solve?: "It solves the time bottleneck in writing boilerplate code and helps to learn new syntaxes more quickly, which is essential for my study flow at Uniasselvi."

Evaluation Title: "The indispensable right-hand for developers in training" Review collected by and hosted on G2.com.

I find GitHub Copilot incredibly easy to use, and I love how it integrates seamlessly with many of my editors like Visual Studio Code and IntelliJ. That's definitely a great point about it. It plays a very important role in my day-to-day activities by helping me reduce my workload and complete tasks much quicker. The tool assists me in understanding problem statements without even writing the code, generating code, analyzing different solutions to opt for the best, and even reviewing pull requests by just selecting Copilot as the reviewer. It also provides a chat box in my editor, which allows me to push code changes, commit my code, and create pull requests or feature branches with ease. From a security perspective, GitHub Copilot also stands out positively. Review collected by and hosted on G2.com.

Sometimes the models in GitHub Copilot hallucinate or they're not able to capture the context or maintain the history. If that can be improved, it would be great. Review collected by and hosted on G2.com.

GitHub Copilot has significantly improved my coding productivity. It suggests intelligent code completions and entire functions that often match what I was planning to write. Copilot excels at routine tasks like boilerplate setup, loops, and standard patterns, which saves me a lot of time and helps me focus on the more complex parts of development. It’s like having a second pair of hands in my editor — especially useful for jumpstarting new files or unfamiliar APIs. Review collected by and hosted on G2.com.

Context awareness: Sometimes suggestions don’t fully understand the bigger picture of the current project or custom business logic, leading to irrelevant code.

Accuracy in complex logic: For advanced architecture or deeply specific requirements, suggestions can miss the mark and require careful editing.

Security awareness: Occasionally suggests patterns that might not follow best security practices, so you must Review collected by and hosted on G2.com.

I use GitHub Copilot to help me code, and it reviews my code during PRs. I like how it goes straight into solving my problems and understands what I'm asking. It gives me more than one answer, allowing me to decide what's best for my application. The initial setup was super easy; I just had to link my proxy and log in. Review collected by and hosted on G2.com.

Sometimes I feel like GPT isn't as effective as Claude, so maybe allow all the AI Agents to be equally knowledgeable. I think it might be better if it doesn't just suggest downloading plugins and instead explains things before doing them. Sometimes it just goes straight into asking to download instead of explaining why this solution might be best for me. Review collected by and hosted on G2.com.

There are lots of models, but honestly the best thing for us has been the quotas. On our enterprise plan, we’ve only hit the quota and been put in a timeout once. We also really enjoy the breadth of models available, how easy it is to use in VS Code, and the amount of quota we receive as well—it’s been great. Review collected by and hosted on G2.com.

I think the flexibility of the models is really hard to get a handle on. For example, things like tool calling and enabling web search are pretty hidden behind the Co-Pilot interface. Another example is the 1m context token with the Claude models: you really can’t make many changes or decisions around that. Review collected by and hosted on G2.com.