Our project, “AI Coder,” is research and development project with the aim of harnessing a diverse suite of AI technologies to their maximum potential in creating a software project. We were encouraged to delve into and chronicle their journeys with these technologies, including, but not limited to, GitHub Copilot, ChatGPT, Bard, Bing, and various iterations of GPT, as they select and develop an application or website.
Throughout this Capstone course, a notable highlight for my team and me has been our exploration into the realm of AI tools for application development—a venture into uncharted territory for all of us. It was an eye-opening revelation to discover the plethora of available AI resources: from GitHub Copilot’s coding suggestions to Code Climate’s code reviews, and CodeAI’s debugging capabilities. Our extensive use of ChatGPT from the outset has been instrumental in our progress.
Our breakthrough
A pivotal moment for us was when we initially posed a simple query to ChatGPT regarding the development of an application using MongoDB, Express, React, and Node. Remarkably, it provided us with a robust boilerplate as a starting point. While the solution wasn’t exhaustively detailed, it was profoundly impressive in its ability to generate a functional prototype swiftly. Our breakthrough is when we successfully integrated AI’s responses in various forms of details into the shape of application.
Why did it matter
The significance of AI tools in coding is significant, given their evolving sophistication and the breadth of functionalities they offer to enhance developer efficiency, accuracy, and ease of coding. These technologies have been crucial in increasing our productivity, improving code quality, and facilitating our learning experience, proving to be invaluable assets for us as developers at many levels. Most importantly, it has introduced us a new way that we never experienced before to create application.
What I learned about the technology
I’ve gathered insights into the extensive capabilities that AI brings to the table. Not only has it streamlined code consolidation and automated code reviews—thereby elevating code quality and developer productivity—but it has also promoted a learning and skill enhancement environment conducive to innovation and experimentation. The AI’s inclination to generate suggestions responsive to our prompts has been particularly encouraging.
What I learned about myself in this
This experience has taught me the importance of integrating AI into my programming learning curve. The swift and precise feedback from various AI tools exceeded my expectations. Given that AI draws upon a vast reservoir of knowledge, I realized the importance of engaging with it to tailor my learning journey, employing it to master programming languages and syntax more accurately, and leveraging it for code reviews and learning. The power of AI in transforming the coding learning process into a more interactive, personalized, and accelerated journey has been a revelation, underscoring the profound impact it can have on skill acquisition and knowledge enhancement.
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