Is GitHub Copilot Right for your Development Process?

There are many tools and technologies accessible to developers that want to improve their workflows and be as productive as possible. Since its debut in 2021, GitHub Copilot has distinguished itself as a tool that not only boosts speed but also simplifies code and makes language switching more bearable.

Copilot exemplifies the growing cooperation between machine intelligence and human intuition by producing boilerplate code and assisting users with test-driven development.

The advantages of GitHub Copilot, potential drawbacks, and real-world examples of software developers using it to carry out their tasks in the current software development environment will all be covered in this article.

What is GitHub Copilot?

GitHub Copilot is a coding AI tool co-created by GitHub and OpenAI that allows developers to write code more quickly by suggesting lines of code or entire functions. Copilot is built similarly to a coding partner using the OpenAI Codex model (a version of the AI models GPT-3 and GPT-4) and was trained on a variety of coding languages and public code. 

Copilot can comprehend context from coding and suggest potentially correct coding snippets, functions, algorithms, or even entire classes or files. The AI uses comments, docstrings, or code itself, in combination, to suggest unique code.

Copilot lives as an integrated Visual Studio Code or IDE extension that allows developers to use it as part of their usual coding workflow.

How does GitHub Copilot Works?

GitHub Copilot functions utilizing a machine learning model, OpenAI Codex, to perceive the situation within the code you are working on and produce coding recommendations as you write code, without your needing to ask. Here is a simple overview of how it works:

Context Perception: GitHub Copilot looks at your code, comments, and even file names to understand the context of what you are working on and aligns itself to match your chosen language.

Code Contribution: Based on its AI training, Copilot predicts and provides helpful code completions, from simple lines of code to more complex functions or classes, in real-time to help you work with code efficiently.

IDE Utilization: Copilot works in the moment, embedded into development tools like Visual Studio Code, where it provides suggestions as you work in code, making it easier for you to apply useful code when applicable, or modify upcoming suggestions to fit your intent.

Public Code Reference: All of the code Copilot suggests is based on a wide body of public code it has been trained on, additionally Copilot can suggest the correct code, and also the popular coding patterns and solutions the community around the world uses.

Adaptation: While it does not learn from your code while you are coding, the Copilot does tailor its suggestions based on the current context and your prior interactions, in a relevant and useful manner.

Basically, GitHub Copilot is like a very well-informed coding partner that you can ask to suggest possible code completions, thus accelerating the development process and possibly exposing programmers to new patterns and practices, but it is just one of the AI tools.

GitHub Copilot Pros

GitHub Copilot provides many benefits, making it a useful AI tool to assist developers of all degrees and all sizes of projects. Some of the main advantages include the following:

Improved Productivity: By suggesting lines of code and entire functions, Copilot can save a lot of time coding, allowing developers to focus more on the higher level design and problem solving.

Wide Variety of Programming Languages and Framework Support: Because Copilot was trained on a wide variety of languages and frameworks, it can be useful for many projects using different tech stacks.

Learning and Discovery: Developers can learn new coding patterns or discover other ways to approach a problem just by looking at the suggestions from Copilot.

Better Code Quality: By pointing out areas in the code that need feedback or suggesting improvements to the original code, Copilot can directly assist in improving the overall quality of codebases.

Boilerplate Code Generation: Copilot is especially efficient at producing boilerplate code that can easily take a long time to type by hand.

Integration with well-known IDEs: Since Copilot integrates smoothly with many popular Integrated Development Environments (IDE, for example Visual Studio Code), it integrates into your workflow very well.

Available for solo developers and small teams: Those using Copilot may find it offers an extra ‘team member,’ providing suggestions and solutions someone might not have thought of.

These benefits make GitHub Copilot a very persuasive assistant for improving efficiency, reducing the time to learn, and improving code quality for many development types.

GitHub Copilot cons

Although GitHub Copilot has numerous benefits for developers, it also has its own downsides. Here are the primary drawbacks: 

Dependency Issue: Copilot can cause developers, especially novices, to establish too much dependency on it. This can erode problem-solving skills and foster over-dependence on the suggested code. 

Inconsistent Code Quality: Copilot generally writes correct code, but the suggested code is not always the best or optimized. 

Learning Curve: Copilot does has a learning curve and writing code with Copilot, and more so, using copilot in complex tasks, may take a little while to succeed at. 

Privacy: Copilot learns from public code, and there is always a risk it will suggest code that relates to some copyright or private code. 

Cost: Copilot does have a fee, and the fees are more significant for individual developers and small start-ups. 

Limited Context Understanding: Copilot can understand a certain aspect of context, but will likely not understand the full business logic, roles, or project. Sometimes the suggested code will be unrelated.

Mistakes Could Happen: Copilot can provide suggestion, but there can be errors or security issues under the surface. Developers must continue to review and test code.

Intellectual Property: Determining who owns the code generated by Copilot is still under discussion. This could affect developers specifically working as independent contractors or as part of a team building software of some kind.

More Review Needed: Code suggested by Copilot would still require a developer’s review. Developers will want to ensure that code matches the project’s ethics and standards for quality.

These all point out that Copilot is a good aide. But it does not replace human critical thinking in a developer’s work. Developers need to remain vigilant, critical, and engaged as they develop software.

GitHub Copilot: Pros and Cons Table

Is GitHub Copilot Right for your Development Process?

Understanding what GitHub Copilot provides is crucial for developers who’d like to improve their workflow and the quality of their project. GitHub Copilot makes coding faster; it frees up cognitive energy so developers can feel like they are able to examine the more creative aspects of programming. In this situation, it is possible that coding can be more enjoyable and productive.

However, the introduction of GitHub Copilot is something that deserves serious consideration. Developers need to critically utilize their expertise to evaluate whether the suggestions produced by AI are in alignment with the objectives and goals held by their project, and to ensure that coding stays in-line with project expectations. GitHub Copilot is intended to develop throughout creativity, not developed to necessarily replace a developer’s critical thinking and decision making.

When developers consider the smart integration of AI-assisted software development, they have the opportunity to elevate and innovate their approaches to coding practices and produce a higher quality of work. AI-integration tools such as GitHub Copilot combine AI capabilities with human expertise to advance the effectiveness and creativity of coding environments.