GitHub Developer Survey Reports That 92% of Programmers Utilize AI Tools.

In the not-so-distant past, leveraging artificial intelligence (AI) for coding was nothing more than a concept straight out of a sci-fi movie. Fast forward to the summer of 2022, and we saw the birth of GitHub Copilot, Microsoft’s AI-powered coding companion. 

Later on, in November 2022, the release of ChatGPT 3.5 stirred the tech scene, amplifying the buzz around AI, which isn’t news to you. 

A recent GitHub survey revealed that a whopping 92% of developers in the U.S. are now utilizing AI-assisted coding tools in their professional and personal projects.

So, Let’s Dig Deeper Into This Matter.

According to this new GitHub survey conducted among American developers, it was found that 92% of participants are actively using AI-based coding tools at work and for personal projects. This data suggests a swift adoption of such generative AI tools in corporate settings, particularly among the tech-savvy workforce.

GitHub, a subsidiary of Microsoft, has developed one of the most sought-after tools of this type, dubbed GitHub Copilot. This tool acts as a coding partner, interpreting code, offering suggestions, and fixing bugs, all powered by OpenAI’s GPT-4 model. 

However, competition in the AI coding tool market is growing, with Google unveiling its contender to GitHub Copilot at the I/O developer conference in May. Several similar tools exist, like Amazon’s CodeWhisperer, Tabnine, and the web-based platform Replit.

In partnership with Wakefield Research, GitHub surveyed 500 developers residing in the U.S. and working for large enterprises. The majority of these respondents were male, aged between 30 and 40, working at companies with over 1,000 employees, as reported by Gergely Orosz, author of the Pragmatic Engineer Newsletter.

The survey results indicated that 70% of developers believe AI contributes positively to their coding work. They stated that AI coding tools aid them in maintaining and surpassing performance benchmarks through superior code quality, quicker results, and reduce incidents at the production level.

This usage isn’t confined to open-source projects or hobbyist tinkering. Just 6% of developers reported using these tools strictly outside of work, meaning that AI-powered coding tools are now an integral part of corporate IT operations.

But Why Has This Shift Happened so Quickly?

It boils down to productivity and efficiency. Developers affirm that AI tools assist them in achieving their performance goals, boosting code quality, speeding up outputs, and reducing incidents. More lines of code can be produced this way.

Inbal Shani, GitHub’s Chief Product Officer, said, “Engineering leaders must reconsider if gauging code volume is still the best measure of productivity and output. To foster innovation at a large scale, it’s essential to enhance developers’ productivity, increase their job satisfaction, and empower them to deliver their best work daily.”

Many developers noted that these tools enabled them to work more effectively. Christopher Harrison, Senior Enterprise Advocate at GitHub, stated that “They feel more accomplished as they can focus more on meaningful work – the reason they became developers in the first place.”

Is There Any Drawback to Using Such Tools? 

However, the growing use of AI tools raises some concerns among managers.

A study from November 2022 by Stanford University’s computer scientists found that those using AI code assistants wrote less secure code than those who didn’t use such tools. However, the former group believed their code was more secure. 

The researchers were optimistic, however, that further improvements in these tools could result in greater productivity and additional benefits, like breaking down entry barriers and promoting accessibility in software development. GitHub advises that businesses establish guidelines for using AI tools to ensure their ethical and effective use.

How Can ChatGpt Rewrite And Improve Your Existing Code? 

Artificial Intelligence has pervasively infiltrated every aspect of our lives, enhancing efficiency and productivity and making significant inroads into software development. 

A stellar example is ChatGPT, a sophisticated language model developed by OpenAI, which is a powerful tool to rewrite, improve, and even write code from scratch. It is also a powerful ally in creating applications. 

Similarly, ChatGPT can be an incredible companion in software development, even when working with existing code. It is designed to understand the context of the input provided, enabling it to rewrite and improve your code.

Improvements include code efficiency, readability, and adherence to the best coding practices. By providing your existing code as input, you can ask ChatGPT to offer a more optimized version or simply ask it to refactor the code to make it more readable. 

ChatGPT’s understanding of multiple programming languages makes it versatile, allowing you to rewrite and improve code in languages ranging from Python and Java to JavaScript and C#.

How to Use ChatGPT to Write Code?

ChatGPT shines as a tool to assist with writing code. Start by providing it with a clear and concise description of the functionality you want to implement. 

This could be as simple as “write a Python function to sort a list of numbers” or more complex tasks like “create a RESTful API endpoint in Node.js.” ChatGPT generates snippets of code that align with your instructions.

To get the most accurate results, be specific with your instructions. If you’re coding in a specific language, specify this. While ChatGPT is remarkably powerful, it’s not infallible, so always review and test the generated code before incorporating it into your project.

How to Use ChatGpt to Create an App?

ChatGPT can be an invaluable asset in application development. It can help generate code snippets for specific functionalities, create boilerplate code, and even design the application’s architecture based on your descriptions.

For example, if you’re building a web app, you might tell ChatGPT, “Generate a basic React application with a homepage, about page, and a contact form.” The model will generate the necessary JSX, CSS, and JavaScript for these components. 

Similarly, if you’re creating a mobile app, you might instruct it to “generate a basic Flutter app with a navigation drawer and three screens.”

Remember to break your instructions down into smaller tasks for the best results. If you’re designing a complex app with numerous functionalities, tackle each functionality individually.