The Future of Coding: GitHub AI Copilot

Mustafa Najoom
11 min readApr 17, 2023

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Introduction

Coding is the most primary and integral part of software development, which has managed to make possible incredible innovations and the deployment of cutting-edge technology in recent years, Of particular importance in the last decade is the significant surge in the development of Artificial Intelligence and machine learning algorithms that are capable of automating various coding-related activities.

GitHub is one such platform that has revolutionized the coding community by introducing the GitHub AI Copilot, a tool that can change the future of coding by introducing AI into its workflow.

The tool was created to work with a variety of programming languages and frameworks, and it is already being praised as a game changer in software development.

Gaper.io is also working towards vetting engineers for our marketplace who excel in using GitHub AI Copilot. It is not something that everyone will instantly use perfectly.

GitHub AI Copilot is an AI-powered tool developed by GitHub and OpenAI. Termed “your AI pair programmer”, the GitHub AI Copilot uses Machine Learning Algorithms and Deep Learning Algorithms to analyze the codebase and assist developers in writing faster and more efficient code. The tool can understand a developer’s coding style, predict the best possible solution to a problem, and provide intelligent code suggestions to help the developer save time and improve productivity.

Many are skeptical of developments like these. But it must be remembered that automation has the ability to transform coding by making it easier, faster, and more precise. With AI, engineers can concentrate on building software rather than writing code, while the AI handles regular coding duties.

In this article, we will delve deep into the future of coding and how GitHub AI Copilot can make a significant impact on the evolution of software development.

GitHub AI Copilot: A Revolution in Coding

The GitHub AI Copilot is a new advanced programming tool that can change the way software applications are created. The tool is based on the GPT-3 and OpenAI language models, which enables it to understand and analyze the context of the code written by a developer. It uses an advanced natural language processing algorithm that can learn a developer’s programming style and provide code suggestions based on that style.

The GitHub AI Copilot saves a developer’s time and effort by providing intelligent code completion suggestions for the developer.

This feature can significantly improve productivity, reduce coding errors, and help developers to deliver high-quality software applications. The tool allows developers to focus on the logic and architecture of the code rather than worrying about syntax and formatting.

Will human programmers be replaced? This image was generated using DALL-E.

Features of GitHub AI Copilot

GitHub AI Copilot is designed to be the perfect assistant for developers. It comes equipped with advanced features that truly make a programmer’s work easier and faster. Some of the key features of GitHub AI Copilot include:

  • Code Completion: GitHub AI Copilot can complete code snippets automatically based on a developer’s code style. It can understand different programming languages, including Python, JavaScript, TypeScript, Ruby, and others, and provide appropriate suggestions for each.
  • Error Rectification: The tool can identify coding errors in real-time and provide suggestions to rectify the errors. This can help developers find and fix errors quickly, avoid redundant code, and improve the overall quality of the application being developed.
  • Semantic Code Suggestion: The tool can provide semantic suggestions based on the context and meaning of the code. This can help developers to identify the intentions of the code and develop efficient solutions accordingly.
  • Integrated Git Support: GitHub AI Copilot is integrated with Git, which is the most popular version control system. The tool can suggest meaningful commit messages, track changes, and provide insights into the code history to assist developers in their workflow.

GitHub AI Copilot costs $10/month (or $100/year) for individuals and $19/month for every user for businesses.

Click here for a demo of GitHub Copilot.

Impact of GitHub AI Copilot on the Future of Coding

A strong AI-based tool called GitHub AI Copilot helps programmers write code by offering autocomplete options and suggestions. It has the potential to revolutionize the way software engineers write code and is based on OpenAI’s GPT (Generative Pre-trained Transformer) language model.

The following excerpts are comments made by Harvard students about their views on GitHub AI Copilot.

Manuel Llano: “This is a very impactful application of AI/ML and one that I did not expect — I always thought AI would come for the real economy first, but this is a clear disruption of the digital economy. My biggest concern regarding the growth and application of Copilot in the medium to long term is…data privacy and IP. Data privacy and IP issues will limit the availability of training data tremendously, and tech companies like Microsoft/GitHub will need to get creative to fill in the gap. Perhaps synthetic data is the solution?”

Amy Eginton: “I used to refer to GitHub when I had to code for engineering classes and I find it fascinating that there is a potential to auto-complete code using natural language prompts. The flywheel that Copilot would generate for GitHub would be fantastic and it would also offer users what many of them are looking for — a quick, easy solution to their coding challenges. I am interested to see where these capabilities land in the next couple years!

In general, a platform like this could bring the following changes to coding work:

Productivity gains: By using AI Copilot, engineers may create code more accurately and quickly while spending less time on repetitive activities. Their time will be freed up to work on more challenging issues and innovate more swiftly as a result.

It can make developers much more productive by giving them smart code suggestions that reduce the amount of manual coding they have to do. This can help software development companies optimize the cost and time required to deliver software applications.

Saving time: AI Copilot can examine the codebase and provide suitable code snippets, saving developers’ time and energy. This can be very helpful for intricate projects that contain a lot of code.

Better code quality: AI Copilot can help developers find and correct errors, enhance the written code, and lessen the risk of bugs and vulnerabilities.

GitHub AI Copilot can help beginners learn and understand programming concepts more easily. The tool can give suggestions for structured coding and code snippets that show how programming concepts work in the real world

Leveling the playing field: AI Copilot can assist programmers of various experience levels in writing code more effectively, leveling the playing field and enabling less experienced programmers to advance their skills more quickly.

Coding democratization: AI Copilot can assist close the knowledge gap between seasoned engineers and newbies, democratizing the coding process. It can help folks who are just starting out learn and develop their abilities more quickly by offering advice and suggestions.

Reduced cognitive load: AI Copilot helps lighten developers’ cognitive loads by producing recommendations and finishing code snippets, which can help developers concentrate and make mistakes less likely.

Integration with GitHub: One of the most well-liked software development platforms, GitHub, is integrated with AI Copilot. This can speed up the development process because developers can use the tool immediately within the GitHub environment.

Increased collaboration: Collaboration amongst developers can be improved thanks to AI Copilot, which offers a platform and common language for coding discussions. This will hasten the development process and boost output in general.

The tool can enhance the code quality by identifying and rectifying coding errors in real-time. GitHub AI Copilot can also help ensure that the code being written is correct and follows best practices which can significantly reduce debugging efforts and help developers to deliver high-quality, reliable, and robust software applications.

Evolving job roles: The position of a software developer may change when AI Copilot is more fully integrated into the development cycle. They might need to concentrate more on high-level design and problem-solving, leaving the more basic coding tasks to AI Copilot.

Is GitHub’s AI Copilot Perfect?

There are some concerns about the implications of using AI in coding. One of the foremost of these is the possibility of job losses for developers. The introduction of AI in coding is feared to lead to a reduction in the demand for developers, as AI solutions can automate coding activities. This can lead to a loss of jobs, especially in industries where software development is the primary source of employment.

However, they explicitly state that “GitHub Copilot does not write perfect code.” It takes into account (to a limited extent) the context and offers suggestions for the best code possible. It does not test this suggested code and might offer outdated uses of libraries and languages. GitHub Copilot may even fail to use functions that are already defined in your project or file.

GitHub states that code suggested by GitHub Copilot should always be tested, reviewed, and vetted.

This leads us to safely conclude that no, AI has not replaced human developers and engineers. The human is always in charge. Such AI-driven tools will only augment the skills of humans and make workflows more efficient and productive.

In fact, rather than replacing humans, tools like GitHub AI Copilot can actually attract more individuals into entering the coding arena by lowering the (often daunting) barriers to entry in this competitive field.

Drawbacks and Weaknesses of GitHub AI Copilot

Because GitHub Copilot is trained on code that is publicly available, it does not have a lot to offer for new libraries, frameworks, or APIs, as it doesn’t have much to learn from. Thus, it is also unable to offer code suggestions for anything newly released.

Secondly, the public code that GitHub Copilot uses to synthesize code recommendations can be marred by “insecure coding patterns, bugs, or references to outdated APIs or idioms”. The code it suggests can therefore also contain such problematic features, which would have to be corrected by a developer.

GitHub AI Copilot also has a language barrier, especially when it comes to non-English languages. GitHub reports performance disparities in code converted from non-English languages (relative to that converted from English). Similarly, it also tends to perform better for the more popular programming languages (e.g., Python, JavaScript, TypeScript, and Go) than others.

Interestingly, and in complete contrast to the fears fostered in the AI-will-replace-humans camp, a potential downside of GitHub AI Copilot is actually that the tool could make developers lazy or complacent. If developers become too reliant on the tool, they may not take the time to truly understand the code they are writing or to think critically about the best way to approach a particular coding problem. This could lead to suboptimal code and a lack of innovation in the coding process.

Conclusion

The GitHub AI Copilot is a game-changer in the world of coding. It has the potential to transform the way software development is conducted, bringing efficiency, speed, and accuracy to the process. The integration of AI in coding can help developers to save time, identify programming errors, and focus on the logic and architecture of the code. It can also help beginners to learn programming concepts more easily and help companies to save time and cost during software development.

Such tools should also put to rest the fear of AI replacing humans. They are meant to be used as an assistant of sorts to improve workflow and offer suggestions based on existing code. It is not capable of developing, or even testing, a full-fledged application on its own.

Let’s do a final overview of the future of coding with tools like GitHub AI Copilot. Here are a few possibilities:

  • More efficient coding processes: As GitHub AI Copilot and other AI-powered coding tools become more advanced, we can expect to see developers become more efficient in their coding processes. With the ability to suggest code snippets and complete code in real-time, developers will be able to write code more quickly and accurately than ever before.
  • Increased collaboration: GitHub AI Copilot has the potential to increase collaboration between developers by making it easier for them to work together on coding projects. By suggesting relevant code snippets and completing code in real-time, the tool can help to ensure that everyone on the team is on the same page and working towards the same goals.
  • Improved code quality: As AI-powered coding tools become more advanced, we can expect to see a significant improvement in code quality. By suggesting best practices and catching errors in real-time, these tools can help to ensure that code is robust, reliable, and secure.
  • Greater innovation: Although there is a concern that AI-powered coding tools could stifle innovation, it’s also possible that they could have the opposite effect. By automating repetitive coding tasks, developers will be able to spend more time on creative problem-solving and experimentation, leading to more innovative and groundbreaking code.

Overall, the GitHub AI Copilot is an excellent example of how AI can revolutionize software development, and its future development will be closely watched by the entire software development community. The future of coding is bright, and AI Copilot is only the beginning. As AI technology advances, we may expect even new breakthroughs to change the way we write code and create software applications. Automated programming, testing, and debugging tools will make developers’ jobs easier and more productive, while advances in coding education and software development models will make software development more accessible to a wider variety of consumers. Concerns have been raised regarding the impact of AI on the coding business, as with any new technology, but if used properly, AI has the ability to transform the way we produce software and improve the world for the better.

FAQs:

Q. What is GitHub AI Copilot?

GitHub AI Copilot is a tool that can change the future of coding by introducing AI into its workflow. The GitHub AI Copilot is a new advanced programming tool that can change the way software applications are created. The tool is based on the GPT-3 and OpenAI language models, which enables it to understand and analyze the context of the code written by a developer. It uses an advanced natural language processing algorithm that can learn a developer’s programming style and provide code suggestions based on that style.

Gaper.io is a marketplace where you can look for engineers who excel in GitHub AI Copilot.

Q. What is the future of GitHub AI Copilot?

A strong AI-based tool called GitHub AI Copilot helps programmers write code by offering autocomplete options and suggestions. It has the potential to revolutionize the way software engineers write code and is based on OpenAI’s GPT (Generative Pre-trained Transformer) language model.

Q. Is GitHub’s AI Copilot perfect?

There are some concerns about the implications of using AI in coding. One of the foremost of these is the possibility of job losses for developers. The introduction of AI in coding is feared to lead to a reduction in the demand for developers, as AI solutions can automate coding activities. This can lead to a loss of jobs, especially in industries where software development is the primary source of employment.

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