Speaker 1: I'm trying to turn one video into a whole bunch of social media content. Pretty ambitious, right? To kick things off, I decided to build a no-code YouTube tool in just 24 hours. First up, automating those annoying tasks like creating subtitles, writing descriptions and adding chapter markers. I figured, how hard can it be? Well, things got interesting fast when I started working on the video transcript. Whisper.ai, the tool I planned to use, it has this 25 megabytes file size limit. No big deal for most videos, but for raw YouTube videos, it's a major problem. Usually, we'd use some third-party service to shrink the video, but I wanted to keep everything under my control. So with the clock ticking, I decided to put my coding skills to use. Yeah, I know, so much for the no-code rule. But sometimes you gotta bend the rules and that's when things got really interesting. So I ended up writing a Python script. This wasn't just a quick fix, it turns out to be a game changer. The script doesn't just downsize the video to fit the limits, it goes beyond that. It also creates subtitles, it analyzes the audio for silent parts and repetitions, and even generates a simple human readable report. What started as a roadblock, turned into the foundation of something even better than I had originally planned. Using Cloud Station, I deploy three essential tools. NSN for workflow management, MinIO for file storage, and NoCodeDB for data organization. These three components work together to process our video efficiently. Let me show you how it all comes together. Let's start by uploading a new video file to our MinIO storage. We'll wait for the upload to complete. This might take a moment depending on the file size. Let's check our email inbox. We should have received a notification email about our process video, including links to all the generated content in MinIO, plus I can download the report and subtitles directly from the email, which is super convenient. Let's head over to NoCodeDB. We can see a new entry for our video here, complete with the generated chapters and description. Let's upload our test video. Now let's head over to NoCodeDB to grab our AI generated content. I'll copy the description from NoCodeDB and pass it into YouTube Studio. Now let's grab those chapter markers and add them at the bottom of our description. Time for our subtitles. We'll check our email for the subtitle file link, download it and then upload it to the YouTube Studio. With everything in place, we're ready to publish the video. Let's open our freshly published video on YouTube to see the results. Check it out. Our subtitles are perfectly synced with the video. And look how easy it is to navigate through the video using our AI generated chapter markers. So even though I had to step in with some code, the good news is that I was able to do it. So even though I had to step in with some code, the good news is you won't have to. I've packaged the script into a Docker image that anyone can use. And in my next video, I guide you through the process step by step, showing you how to do it all with NoCode tools. Now that I've tackled this part of the plan, I'm ready to move on to the next phase, scaling my content creation. With this automation in place, I'll soon be able to turn a single video into an entire ecosystem of content. From blog posts to tweets and more. All generated automatically. If you're ready to learn how to build this automation tool yourself and want to see how I'll be 10x in my content, don't miss my next video. It's going to take content creation to the next level.