Have you ever found yourself in a position where you needed to sift through a lot of YouTube videos to learn or research about a particular topic? Watching hours and hours of videos, taking notes, and still overlooking important details is a genuine struggle.

In this article, I’ll go over the process of how I saved countless hours extracting key information from YouTube videos. I did this by building a Python workflow that makes use of large language models (LLMs) to answer any questions about the video content. This not only saved me hours, but it also boosted my productivity and enhanced my learning. As a result, I can use the extra time to create more content or take a well-deserved break.

Let me walk you through the process of how I created this YouTube AI assistant. Let’s dive in!

Why I Built This YouTube AI Assistant

Before proceeding to the technicalities, let’s explore why this project has been a game-changer for me.

At the core of what I’m doing on a daily basis in my full-time role as a developer advocate and in my part-time endeavor as a YouTuber (I run the Data Professor YouTube channel) is content research.