I Built an AI Tool That Automates My Entire YouTube Workflow (Cursor AI Coding Project)

I finally hit a milestone on a project I've been chipping away at for months: a fully automated content pipeline that takes a raw video file and turns it into a finished, published set of content across every platform I use. No more manually writing descriptions, cutting Shorts, or copy-pasting blog posts. Here's how it works and how I built it.

Where This Tool Started

This didn't start as some grand automation system. It started as a simple script to transcribe a video and spit out a YouTube description and comment I could paste in manually. That was it. Just a small time-saver.

But once that worked, I kept asking the obvious question: what else could this handle? A few months and a lot of iteration later, it's turned into a tool that runs almost my entire post-production workflow.

What the Tool Does Now

At this point, the pipeline handles nearly everything after I finish recording. Here's the current feature set:

• Transcribes any local video file
• Generates optimized YouTube descriptions and comments
• Creates YouTube Shorts automatically from the long-form video
• Writes Facebook post content
• Generates a full blog post for the website
• Schedules everything to post automatically, including spacing out Shorts every couple hours
• Pulls the YouTube URL and embeds it directly into the blog post

My part of the process now is upload the raw video, check a few boxes, and hit "Run Full Pipeline." That's it. Everything else happens on its own while I move on to the next thing.

Why This Matters for Content Creators

If you're posting consistently, you already know the real time sink isn't recording, it's everything after. Writing descriptions, formatting posts for different platforms, cutting clips, scheduling, keeping track of what's posted where. That overhead adds up fast, and it's the kind of repetitive work that's perfect for automation.

This isn't about replacing creativity. It's about removing the repetitive, mechanical steps so I can spend more time actually building and recording instead of managing logistics.

How the Build Works

I built this using Cursor AI, and I walk through the actual interface and workflow so people can see what building with AI assistance really looks like, even if you don't come from a traditional coding background. You don't need to be a career developer to build something like this. You need to understand the problem you're solving and be willing to iterate.

In terms of time investment, this represents roughly 15 hours of total build time. That sounds like a lot until you compare it to the ongoing time savings every single time I publish a video. The math only gets better the more consistently you're creating content.

Key Takeaways

• Start small: this began as a single-purpose transcription tool
• Automation pipelines grow feature by feature, not all at once
• AI-assisted coding tools make it realistic for non-developers to build real automation
• Time invested upfront pays off fast if you publish content regularly
• The biggest wins come from automating the repetitive, non-creative parts of your workflow

What's Next

This is part of an ongoing series where I document real coding projects, AI-assisted development, and tools I'm building to solve actual problems in my own workflow. If you've got an idea for a tool you wish existed, drop it in the comments. I'm always looking for the next build, and I like hearing what kind of automation problems other people are trying to solve too.

If you want to follow along with future builds and breakdowns, subscribe and keep an eye out for the next one.