
From Idea to App in Hours: Vibe-Coding My Way to a YouTube Knowledge Base with AI
Published on May 20, 2025
It’s a wild time to be a builder. The feeling of having an idea and seeing it turn into functioning software, not in weeks or months, but in a matter of hours? That’s the new reality, and it’s exhilarating. For a weekend warrior like myself, this is a game-changer. My latest adventure in this rapid-prototyping world has been crafting a personal YouTube Knowledge Base, and the journey, supercharged by tools like Cursor and the AI brilliance of Gemini 2.5 Pro and Claude Sonnet, has been as rewarding as the outcome. Pretty much, I can go from idea to functioning software in a ridiculously short amount of time.
This isn’t just about coding for coding’s sake. I’m on a mission to build my own personal knowledge empire - all part of the same desire I’ve had around Quantified Self concepts for roughly the past 10+ years. I’ve already tackled the beast of my Instapaper archives – roughly 7,000 articles read over 10+ years – and corralled them into a personal knowledge base. (You can read about that specific coding experience here). Now, I’ve set my sights on YouTube. It’s a goldmine of information, and I wanted a seamless way to capture, recall, and build upon the content I consume there. I also want a tool that is completely within my control. Lately that’s looked like exporting content to Markdown files I store locally.
My secret weapon in these endeavors? A development style commonly referred to as “vibe-coding.” It’s this incredibly fluid, almost conversational process where Cursor acts as my AI pair programmer. I bring the vision, the high-level goals, and the desire to learn; Gemini and Claude bring their vast knowledge, lightning-fast code generation, and tireless assistance. It’s less about getting bogged down in the nitty-gritty of syntax or boilerplate and more about a creative dialogue. “What if we try this?” “How can we make this more efficient?” And just like that, code flows, solutions emerge, and with every project, I’m learning something new, pushing the boundaries of what I thought I could build on my own in such a short timeframe.
So, what’s this YouTube Knowledge Base project all about? At its heart, it’s a Node.js pipeline. It ingests a simple JSON manifest of YouTube URLs. From there, it automatically fetches full transcripts and detailed video metadata. Then, the really cool part: it uses AI – via OpenAI in this case – to generate concise summaries, complete with a “TL;DR” and “Key Points” in Markdown. Finally, it emits these organized insights as Markdown files, neatly tucked into transcripts/
and summaries/
directories, all with clean YAML front-matter.
The real kicker for this project, and a perfect example of the new things I learn each time, is the automation we’ve baked in using GitHub Actions. Now, all I have to do is add a new video URL to my videos.json
file and commit it to the repository. That’s it. GitHub Actions take over, triggering the entire pipeline automatically – fetching, summarizing, and committing the new knowledge back to the repo. It’s the kind of hands-off, elegant solution that makes personal software so satisfying. And if the GitHub workflow fails for some reason, I can always git fetch
or git pull
the latest state of the project and run the Node pipeline locally.
This project, like the Instapaper one before it, was a masterclass in itself. It reinforced the power of diving in, even when you don’t have all the answers upfront. With these powerful tools like Cursor, with Gemini and Claude as my co-pilots, the learning curve isn’t just managed; it’s dramatically compressed. That initial feeling of ‘I’m not sure how this will work’ quickly morphs into an exhilarating ‘Wow, look what we just built!’ This ability to learn as fast as I can and leverage new tools as quickly as possible is precisely what makes this era of software development so much fun.
What else makes this exciting? It’s the sheer pace of learning and adoption that these AI tools enable. I’m constantly on the lookout for new tools and techniques, and AI assistants have become an indispensable part of that. It’s about embracing the new, experimenting, and not being afraid to jump in. This rapid iteration cycle – idea, build, learn, repeat – is incredibly addictive and fulfilling.
So, the YouTube Knowledge Base is up and running, another piece of my personal digital brain falling into place. But more than the specific project, it’s this empowering new way of creating that has me truly excited. If you’ve got ideas simmering, personal projects you’ve always wanted to tackle, there’s never been a better time to dive in. The tools are here, the learning is accelerated, and the ability to turn thought into reality is, quite literally, at your fingertips.
What will you build next?
The Vibe-Coding Anthem
To capture the spirit of this rapid, AI-assisted development journey, I prompted an AI to create a song in the style of a 1920s radio hit. Give “That Vibe-Coding Swing!” a listen:
"That Vibe-Coding Swing!" - an AI-generated 1920s style tune
Categories: Web Development
Tags: AI , Gemini , Claude , Cursor IDE , YouTube , Knowledge Management , Automation , GitHub Actions , Node.js , OpenAI , Rapid Prototyping