GitHub CoPilot Reviews

GitHub CoPilot can be used for prompt engineering, delivering information to create a presentation, and comparing results from other AI tools, like ChatGPT or Gemini. You can use the CoPilot app while creating presentations, but we need to subscribe and pay an additional fee to use it. I'm truly considering talking to the management team to contact Microsoft to see if we can use that feature. It's a very useful feature.

The CoPilot app that you can use while creating presentations is very useful.

It would be useful if we could use the solution to create documents, not only prompts. It would also help if we could insert documents and create results in accordance with the documents inserted.

The tool has a feature that allows you to upload a voice document or a recording, and it can export the transcription for that recording. This transcription is not available in all languages. I would like to know whether the solution plans to expand the number of languages because I want to know if there's also a plan for Hebrew transcription.

There are limitations because you have to subscribe and pay more money to use the GitHub CoPilot tool.

I have been using GitHub CoPilot for a few months.

I rate the solution an eight out of ten for stability.

I rate the solution’s scalability an eight out of ten.

I've tried to contact Microsoft, but I haven't received a response. I'm not impressed with the technical support.

The solution's initial setup is pretty straightforward, but I'm not as impressed as ChatGPT and Gemini.

With GitHub CoPilot, we have more opportunities and can approach more people in less time. The solution shortens the time it takes to finish a certain task.

We have a license but need another one for the GitHub CoPilot tool.

Overall, I rate GitHub CoPilot an eight out of ten.

If I want to find things quickly and easily, I'll use it for content, but I don't cut and paste. It's like I'm checking my ideas.

If you had a Microsoft Teams environment, we could use it to create a virtual agent or something. I know the general things I can do with AI and chat engines.

I use it almost like a search engine, but it goes a step beyond. A search engine shows you many results, and you have to read everything to put it together. But with CoPilot, you ask a question, and it gives you a summary of all the websites out there. So it's faster learning.

It handle complex tasks as well. It is able to generate results that I want. 

The problem arises when a bot is not well-designed, which frustrates customers.

For example, with our local Comcast cable company, if you need to repair something, you go on the app. They ask, "What's wrong?" You say, "My power cord melted. I need a new power cord." But the bot responds, "Oh, your Internet's not working?" 

So, it doesn't recognize unusual issues. Then, they make you go through troubleshooting, saying, "Your Internet looks good, but your device isn't plugged in." It's like, "Yes, I know. I want to speak to an agent." 

And it takes another ten minutes of trying different things before you finally get to an agent.

This is an example of a poorly designed bot.

I have been using this solution for about a year.

It's the self-service type. We just use it very simply.

We just use it for the same reasons I do. We do work with other providers and program virtual agents or bots. Those are all the rage now. You put them on your website. You used to have simple ones like "I can check your deposits or cancel a check for you," but they're limited to what you program. 

But if you expand a bot like Swifter Robot with artificial intelligence and natural language processing, then it can almost be like a person. Then, you can do some really cool things with it. 

I haven't encountered any issues. When I do, I just call our IT group. I haven't had any problems with it, unlike OneDrive.

I believe it's just standard with Microsoft, so you download it with their installer.

Increased productivity and improved customer experience can count as an ROI. If customers need to know something, they'll either wait five minutes for an agent or they can just go ahead and find the answer themselves. Most will choose the latter. The problem is poorly designed bots that frustrate customers. 

We have a team that decides on the best tools, like Google Digital or other products.

I would recommend it because it's part of the Microsoft package, it's easy to use, and I haven't found any of the answers to be outrageous.

Overall, I would rate it a seven out of ten because I haven't used it enough.

I just installed the product idea in my ID extensions, as it will be handy for auto-completions and suggestions. Sometimes, I use the tool to simplify the code and for documenting the code.

I like how GitHub CoPilot analyzes individual docstrings and keeps the method context relevant. Instead of throwing random codes, GitHub CoPilot sticks to a class of more context-relevant code generation, which I like.

Speaking about the code suggestion capabilities of the product, I would say that though it is good, there is a need to develop it further. In our company, when we have more dependent classes opened, we realize that GitHub CoPilot needs to be improved. GitHub CoPilot needs to analyze the whole package and try to give more relevant codes.

If the product plans to provide more extensions, then adding Eclipse would be helpful. There are no extensions provided by the product for Eclipse.

I wish the context window gets expanded, as it would be good for the product, especially since I am currently using some custom packages and custom classes. GitHub CoPilot needs to give some generic code generation instead of analyzing my classes and giving relevant codes. Apart from the aforementioned area, there are no major challenges in the tool.

I have been using GitHub CoPilot for ten months. I am a customer of the tool.

There are no stability issues with the product.

I don't know how to comment about the scalability feature of the product since it is just used as an extension.

I have not worked with other solutions, and I believe that GitHub CoPilot has a monopoly in the market because there is no other free tier version of other products in the market variable that meets my expectations.

The product's initial setup phase is easy.

The solution can be deployed in five minutes if you have activated a GitHub CoPilot account.

I have definitely experienced an ROI from using the product. It saved my company 30 percent on costs and time.

The pricing is reasonable. I think it is 10 USD per user.

The AI integration in the product is good.

If you are new to coding and you want to save some time by not writing a course from scratch, then you can definitely use GitHub CoPilot, as it saves a lot of time in the initial stages of development but not in the more advanced production-ready stages.

I rate the tool an eight out of ten.

Whenever I need to write test cases for my development code, I just give the command to Copilot, and it automatically helps me write them. Then I just need to review them. It also really helps me write the skeleton of the basic design. It won't give me a 100% solution, but it gives me a 75% solution. Then I just need to review it, make some cosmetic changes, and it's ready. 

Overall, where I used to spend a whole day on test-related activities, now I just need to spend two to three hours, and I can complete my job.

It's helped reduce engineering effort. If I can complete my job in half a day, then all the engineers can complete their jobs in half a day. Ultimately, it saves cost and optimizes performance. 

From the company perspective, if we needed to spend a million dollars, we can now reduce it to at least a hundred thousand dollars.

Copilot's code review, test case generation, and chat features are most valuable to me. When I write code, I feel like I have someone sitting with me to help me. Wherever I'm stuck, I just ask a question, and it provides guidance that I can use.

In a few cases, the results aren't correct, so that needs improvement. Also, it would be great if the results could be presented in different formats, not just text. As engineers, it takes time to read through text-based results. 

If they could provide diagrams or basic design architectures, it would be easier to understand and take less time to review. So, as of now, image functionality is not provided by GitHub Copilot, and it would be great if they could add that.

So, I would like to see improvements in the result generation, more results, different result formats, and image functionality.

I have been using this solution for four months. I work with the latest version.

I would rate the stability a nine out of ten. It is a stable product. Copilot is a good thing when you're writing code. It assists you wherever you need it. 

On the other hand, there are a lot of benefits to this feature, like suggesting code before you write it and suggesting the optimal way to write it, which is really helpful. 

Apart from that, it helps with writing test cases and suggestions for heavy algorithms where you need to put in a lot of brainpower. So, it makes things easier.

On the other hand, the negative points, Copilot still hasn't reached a point where we can trust it 100%. Sometimes, when we raise a query, it stops working intermittently. So, at that moment, we need to look for other options. It's not, as of now, 100% reliable. Sometimes, it stops working; sometimes, the output has issues. So, we need to be careful with information.

I would rate the scalability an eight out of ten. Sometimes, we face high traffic on Copilot, and it stops responding to our queries. It's happened a few times, maybe three or four times out of a hundred.

It's not 100% reliable. Sometimes, we stop receiving responses. We have around 500 end users in our company. It is used on a daily basis. 

The customer service and support are okay. 

Positive

We switched to GitHub because it's more appropriate and saves me time. On Google, I need to spend time searching for something, typing it in, and then getting a bunch of solutions out of which I need to pick the best one. 

Copilot, on the other hand, gives me the best answer out of all the possibilities with just one query. That's a big benefit.

I would rate my experience with the initial setup of this product a seven out of ten, where one is difficult, and ten is easy to set up. 

It is not complex. I gave it a seven because there were a few minor technical challenges with the initial login. It wasn't as smooth as logging in to Gmail or Microsoft Outlook, but I was able to log in after a few tries. 

So, it is a bit tricky. These are just minor challenges, not completely smooth. 

We use the licensed version, not a cloud version. We purchased a license and installed it.

We did everything ourselves. I was able to do it alone; it didn't require much effort. So, one person can manage both the deployment and maintenance.

It took only one day to deploy it. It's not really a deployment in the traditional sense. We requested a license key from Microsoft, and then we used that key to log in from our laptops. We configure it with our development environment, and it works smoothly.

If you invest some amount, it will definitely reduce your production cost. I would rate the ROI an eight out of ten, where one is low ROI and ten is high ROI. 

I would rate the pricing a five out of ten, where one is very cheap and ten is very expensive. So it's affordable.

There are no additional costs to the standard license. So the price is fixed.

This is the first time I've used a tool like this that assists with code writing. Before that, I used a simple Google search. 

Moreover, Google has recently launched its feature, but it's not as mature as Copilot's. They're in the very early phase.

Developers, testers, front-end, back-end, any developer can use it. It's really beneficial for them. On the other hand, testers can also explore test cases with Copilot. It'll help them, too.

Overall, I would rate the solution an eight out of ten. 

I use the solution in my company since, as a data engineer, I also work with Python. For writing a code or for reviewing the code, I'm using code on it.

The most valuable features of the solution stem from the fact that it gives you suggestions when you start typing.

I have not used the product much to be able to comment on what needs improvement in it. With the passage of time, I believe that there will be improvements in its prompt response, like ChatGPT, considering that GitHub will get more data. With time, the product will mature.

The product's price is an area of concern where improvements are required. ChatGPT is free, and people would rather prefer it over GitHub CoPilot.

Considering the way GitHub CoPilot works, it can improve its connection with technologies like SQL. Right now, I can't write an AWS Glue job in GitHub CoPilot. In the future, if the tool can improve and include multiple technologies and languages, I see that they have a scope to offer better scalability.

I have been using GitHub CoPilot for less than a month. I am just a consumer of the tool.

Sometimes, when the product doesn't function properly because of some network issue, I prefer to use ChatGPT. In ChatGPT, you can ask any general question.

Scalability-wise, I rate the solution a seven out of ten.

Before GitHub CoPilot, I worked on ChatGPT, so I had to give the prompt to get what I wanted. ChatGPT is also a very helpful tool.

I currently work with GitHub CoPilot and ChatGPT.

ChatGPT gives the wrong output at times, after which you need to correct it. GitHub CoPilot gives correct codes since it always works on the existing codes in GitHub. GitHub CoPilot gives a correct output.

The product's initial setup phase is easy, but sometimes, if your company has firewall issues, it gives errors.

There is a need to pay around 10 USD to be able to use the solution.

I am planning to use this AWS Bedrock and another tool from AWS for its AI-based features. I have not decided on the tool I plan to use. I want to learn and see what AWS is doing with its products.

GitHub CoPilot improved my code efficiency by helping me save time. The tool gives me ready-made codes, which I review and then implement.

Speaking about GitHub CoPilot's ability in terms of context and syntax suggestions, the tool is helpful.

The product is easy to integrate.

I recommend the product to developers who plan to use it. It is not a free tool forever, meaning it is only free for a month.

I rate the tool a six to seven out of ten.

The primary focus has been on leveraging its capabilities for increased ease of use and productivity. The main goal is to accelerate application development, allowing us to build applications more efficiently.

The most valuable aspects in terms of features, revolve around its code generation capabilities. Firstly, the functionality for generating test cases based on existing code and application logic has been invaluable. Secondly, the code explanation feature has emerged as another essential tool. Beyond these, the primary function of facilitating the development of new code or additions to existing code remains a key focus.

There's room for improvement to ensure that suggestions align more precisely with the context of what I'm seeking, minimizing instances of unrelated or inaccurate code suggestions. It could benefit from enhancements in several key areas. Firstly, there's a need for improved integration across different Integrated Development Environments to ensure a consistent user experience. Secondly, providing users with more granular control over when Copilot is active, preferably on a per-project basis, would enhance flexibility. Also, broadening Copilot's contextual awareness beyond open files to consider the entire project or codebase context could lead to more accurate and relevant suggestions, particularly in scenarios where opening all files is impractical. The current state lacks maturity, and reporting is not readily available out of the box. Users have to request specific reports, involving collaboration with the data team, indicating a need for more streamlined and accessible reporting features.

I experimented with the technical preview version when it was initially launched last year, taking advantage of the free access provided at that time. However, in a professional context, I have been utilizing it for real-time database work over the past three and a half months.

The stability is generally satisfactory. The tool itself operates smoothly, but potential challenges may arise, especially in larger enterprises utilizing proxies. It's crucial to adhere to the documentation on operating with proxies to avoid glitches.

The scalability is impressive. It accommodates growth seamlessly; as you acquire more licenses, the tool scales accordingly to meet the increasing demand. As of now, we have successfully onboarded and currently have approximately three hundred and fifty active users.

We have engaged with the support team for feature requests, particularly in terms of porting, and have found the response to be somewhat delayed. It's worth noting that GitHub and Microsoft teams have communicated that they are actively addressing these concerns in private.

The initial setup is straightforward.

The initial setup operates on a license-based model, providing flexibility as you can allocate licenses to a GitHub team. While the implementation itself is straightforward and requires minimal ongoing maintenance, a significant challenge has emerged in terms of documentation, especially concerning security documentation. The current lack of comprehensive documentation raises concerns, particularly for larger enterprises. When activating Copilot, you are prompted to provide essential information, such as the location of your Azure instance where suggestions will be processed. Once you input this information, the installation proceeds seamlessly.

While it's premature for a comprehensive ROI analysis, we have observed a positive trend with users expressing satisfaction.

A personal license is priced at ten dollars per month, while a professional or enterprise license costs nineteen dollars per user, and these rates are consistent for all users.

While we have explored various options within the Microsoft ecosystem, such as the solution offered, we haven't actively employed any other AI tools at the enterprise level.

It's essential to perceive it as a supplementary tool, not the primary driver. Caution should be exercised in blindly accepting suggestions to avoid unexpected challenges. The time invested in reviewing suggestions is crucial, and the tool's effectiveness depends on the user's domain knowledge. While it can be ideal for bridging domain and technical aspects for those with expertise, users with less experience may overlook potential issues, necessitating careful consideration. Overall, I would rate it seven out of ten.

I am evaluating the tool to understand how useful it is for development. I'm evaluating how smart it is.

The solution makes our work easier. If we use a particular coding style, the solution can identify our coding style. The solution increases coding efficiency. It tries to judge our coding and logging style and imitates it. It automatically suggests copy-paste functions. It saves us time.

If we try to do something that involves two to three files and functions, the tool gets confused. It gives us advice that does not work. The suggestions are not well evaluated. We need to put more effort into debugging. The tool miserably fails when multiple files are involved. The tool must improve its ability to work with multiple files.

The first suggestion provided by the product must work. Whenever the product provides a suggestion, it must validate it. It will be helpful for the users. If the first suggestion is good, we can use it. If the first suggestion is wrong, the product will not solve the problem even if we ask it multiple times.

I have been using the solution for the last one and a half months.

The tool is stable. It gives us an answer, whether accurate or not.

I rate the product’s scalability a five out of ten. It does not work well in complex coding scenarios.

The initial setup is easy. I am using the latest enterprise version.

The solution is costly. It is not reasonably priced.

I have also used ChatGPT. GitHub CoPilot is built into coding. If we are working on coding, GitHub CoPilot is a better choice. ChatGPT is a better choice if we want to understand the concepts.

Overall, I rate the solution a five out of ten.

GitHub CoPilot helps its users summarize documents. GitHub CoPilot has an AI capability that allows it to give its users a summary of documents that it has received from them. GitHub CoPilot also provides meeting summaries and suggestions on how and when you are supposed to send reports or emails. GitHub CoPilot establishes a total baseline of its users' activities so that it can later recommend to its users how to structure their day.

GitHub CoPilot's stability is an area of concern where improvements are required.

I have been using GitHub CoPilot for three or four months. I have experience with the preview version of the product. Though I am not sure about it, I think that GitHub CoPilot is not yet released in the market.

Stability-wise, I rate the solution a seven out of ten.

I will not be able to comment on the scalability part of the solution since my company has not undertaken a full-fledged deployment process across our organization's users.

All the people in my company use GitHub CoPilot in one form or the other.

The product's initial setup is straightforward because it's pushed through the updates. The product's updates are allowed automatically, so the setup process is not something one needs to get involved in deeply.

The solution can deployed in less than a minute since it is done through the automatic updates provided by GitHub.

No technical people are required to take care of the deployment and maintenance of the solution since it gets automatically pushed as an update from GitHub CoPilot.

The solution's deployment part was managed with the help of one of our company's in-house teams.

GitHub CoPilot comes readily available for enterprise customers, so it's a free add-on if you already have GitHub's enterprise license.

I recommend the solution to those who plan to use it.

As it is a new product in the market, I rate the overall tool an eight to nine out of ten.