How I Built a Serverless Podcast Delivery System on AWS Using Only ChatGPT — A Glimpse into the Future of Software Development

I recently had the chance to build a serverless podcast delivery system on AWS, and surprisingly, I was able to complete the entire project using ChatGPT alone. All I had to do was explain my requirements—how files arrive in S3, how the RSS feed should be generated, how CloudFront should handle distribution, and so on. ChatGPT then generated every piece of code I needed. I simply copied and pasted the output into AWS, and the system worked.

What amazed me most wasn’t just the accuracy of the code but the fact that ChatGPT also explained why each part was necessary. For example, it clarified how specific AWS services interact, what each function does, and how the entire architecture fits together. This made it far easier to understand the system as a whole rather than just pasting code blindly. It felt less like using a tool and more like learning directly from an expert developer.

Throughout the process, ChatGPT functioned as a true development partner. It pointed out potential pitfalls, suggested better approaches, and responded instantly whenever I had questions. There were moments when it felt like pair programming with a highly skilled engineer who never gets tired, never gets stuck, and is always ready with a clear explanation.

This experience made me realize that the next era of software development has already begun. Traditional development required hours of researching documentation, debugging configurations, and manually writing code. But with AI assistance, the workflow shifts dramatically. Now, we define goals, describe the architecture we want, and let the AI handle the tedious or repetitive parts. Developers can finally focus on the creative side—what we want to build, not how many lines of glue code are required to make it happen.

Looking ahead, I’m excited to explore how other AI systems, like Google’s Gemini, compare. Each platform likely has its own strengths, and I’m curious to see how they might complement or surpass what I experienced with ChatGPT. Evaluating multiple AI assistants may become the new normal, much like choosing a programming language or framework today.

Building this system with ChatGPT wasn’t just a successful project—it was a glimpse into the future. AI-assisted development is no longer a concept or a prediction. It’s already here, transforming the way we create software. And I’m looking forward to exploring this new frontier even more deeply.