Coding is hard. One tiny error in punctuation can render hundreds of lines of code moot. There are so many coding languages to keep track of, there are the nuances that come with writing front-end or back-end code, and all of it with looming deadlines.
A tool that can help both experienced and new coders navigate the tricky waters of coding while helping to hit deadlines and speed along the process would be extremely valuable. Enter GitHub Copilot.
By combining the power of OpenAI’s generative AI LLM (large language model) ChatGPT with the publicly available coding found in all of GitHub’s public repositories, Copilot serves as an artificial pair programmer—offering autofill suggestions and responses to natural language prompts as you code.
Copilot for GitHub is a hot topic in coding circles because of its sky-high potential to assist coders of all experience levels in their efforts to create solutions for problems and inefficiencies faced by their organizations.
So how does it work? What are the GitHub Copilot pros and cons? And how can you best use this new technology?
As previously stated, Copilot is a generative AI program designed to help programmers save time and find solutions to coding issues. It was developed as part of a collaboration between GitHub, OpenAI, and Microsoft.
The idea of GitHub Copilot is that it will attempt to serve as a pair programmer for the human writing code. Copilot automatically suggests code to complete the commands and sequences the coder is writing.
Additionally, if a coder has an issue that must be solved, they can type in a prompt in plain language and Copilot will then produce code to accomplish the goal stated in the prompt. This is done thanks to the natural language recognition capabilities found in other OpenAI products.
The reason coding with Copilot works is because the artificial intelligence has been trained with all the code available in GitHub’s public repositories. So, any open source code or coding that has been made publicly available on GitHub makes up Copilot’s base of knowledge.
That isn’t the only source of knowledge for Copilot, though. It also takes into account the context provided by your use of it. The suggestions you accept and the choices you make with Copilot help it better understand and address your coding needs.
GitHub Copilot brings many benefits to the coders that use it. Obviously, these benefits will vary from coder to coder. More experienced coders will get different benefits from those who have less experience in the field, but Copilot has the capability to help everyone who uses it.
This is by no means a complete list of every one of the numerous GitHub Copilot benefits, but they give a solid overview of what a high-quality AI pair programmer can do.
Coding with Copilot helps developers keep their code consistent. Because Copilot takes into account the context of your coding, its autosuggestions become more consistent with how you code.
The first few suggestions that are presented to a developer may not totally fit with exactly what the coder is trying to do, but as more code is written and more suggestions are accepted, Copilot becomes more and more consistent with each developer using it.
Increased productivity and reduced development time are two GitHub Copilot features that go hand in hand. Large projects with tight deadlines are not uncommon in the world of software development, and Copilot has been designed to help in those situations.
Instead of searching libraries for boilerplate code that would generally be copied and pasted anyway, GitHub Copilot can find appropriate code based on a search prompt or offer an autosuggestion for your boilerplate based on context and previous searches.
Copilot helps improve productivity and development speed beyond boilerplate code as well, but considering how much time searching out boilerplate code or writing it out by hand consumes in a development project, just that functionality shows how valuable Copilot can be.
Another benefit of GitHub Copilot is the ability to find solutions to problems you may not have encountered before. Remember: Copilot has access to every single piece of code from all of GitHub’s public repositories.
That means that if any developer that supplied code to a public repository worked on a situation that you aren’t familiar with, Copilot can find that solution for you in an instant. This can improve your code without potentially putting you behind schedule.
And that ties into the ability of Copilot to reduce the barriers faced by newer developers as they attempt to break into the industry. By providing suggestions and facilitating searches for solutions, Copilot helps provide a hands-on way for newer coders to learn and improve.
Generative AI is a relatively new technology. That means that, despite the huge potential upside of programs like Copilot, there are still pitfalls that must be avoided. As time goes by, these pitfalls will be less and less of an issue. But for now, these are some of the things you should be aware of before relying too heavily on Copilot.
As with any generative AI, Copilot is limited to finding existing solutions—it cannot create a unique or truly innovative solution all on its own. Copilot has a massive library of existing code to search through, but it is limited to existing patterns.
So if, for example, a less experienced developer is over-reliant on Copilot, that could mean that they will be stymied if a unique problem arises. It’s important that a coder keeps their skills sharp. Relying too heavily on Copilot could limit their growth and weaken their code writing skills.
The biggest potential pitfall, and one that every major generative AI platform is currently dealing with, is intellectual property issues and matters of copyright. Many companies want to own all the code that their developers write—but will they own that code if it is partially generated from someone else’s work?
Also, do the people who have developed open source code have any recourse to take legal action against a company that is charging people to use an AI program that pulls solutions from that open source code? Probably not, but it is something to be aware of.
Another potential pitfall of GitHub Copilot is that the code it suggests can be inelegant or even outright broken. When developing solutions, keeping code as simple and elegant as possible reduces potential trouble spots and makes maintaining and testing that code easier.
Because Copilot pulls from public repositories, the code it pulls up is not always streamlined. It can even contain punctuation or characters that were necessary to the original developer’s code that could break the code that you are working on.
So when using Copilot, it is imperative that you keep your eye on the suggestions that you accept.
Along that line of thinking, you need to verify that the code you accept from Copilot will be compatible with your security protocols. You don’t want to put some code into your project that may accidentally make your organization vulnerable.
Considering all the potential benefits and drawbacks of GitHub Copilot, the best way to use it is as a tool—not a crutch. It exists to augment a developer’s work. Copilot is not meant to replace the work of a developer.
As previously stated, Copilot is meant as an AI pair programmer. That means it exists to offer suggestions and help answer questions while the primary coder actually does the work of putting the code together.
The great thing about Copilot is how it compliments a human developer’s skills. But without a human that is able to discern correct suggestions from overly complicated or erroneous suggestions, it can cause as many problems as it solves.
GitHub Copilot is an incredible tool with massive potential to make coding more accessible to new developers and more efficient for experienced developers, but it is still just a tool. So, it is important to remember to use it as such.
To best take advantage of the benefits of GitHub Copilot while avoiding the pitfalls, the best strategy an organization can implement is to work with people who understand custom development and how GitHub works within enterprise systems.
TEAM IM has a long and fruitful history of implementing platforms to facilitate custom application and software development. Our experts have collective decades of experience with GitHub and both artificial intelligence and machine learning.
GitHub Copilot can improve your development team’s productivity and ability to hit important deadlines. TEAM IM can help your developers take advantage of Copilot’s capabilities thanks to our experience with all parties involved in Copilot’s development.
So don’t wait. See how a copilot can assist you today!
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