You Can Now Turn Any YouTuber Into Your Personal AI — And It’s Free

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What if you could ask questions directly to your favorite YouTuber — and get answers based on everything they’ve ever published?

In 2026, this is no longer a fantasy. With a simple browser extension and Google’s NotebookLM, it’s now possible to build a personal AI trained on any creator’s videos. The result feels like having their knowledge, style, and expertise available on demand.

Best of all, the entire process takes less than five minutes — and it’s completely free.

Why this changes how we learn online?

Most creators publish hundreds of videos over the years. Finding specific information inside that content usually takes hours of searching and watching.

This workflow solves the problem by turning an entire YouTube channel into a searchable knowledge base. Once set up, you can ask questions like:

  • “What is their best advice for beginners?”
  • “What tools do they recommend?”
  • “Summarize their strategy in simple steps.”

The AI analyzes all selected videos and generates answers based only on that creator’s content.

What you need?

No coding, no technical setup — everything works through simple copy and paste.

Step 1 — Install and configure Grabbit

Start by installing the Grabbit extension from the Chrome Web Store.

Once installed:

  1. Open the extension settings
  2. Go to the Actions section
  3. Create a new action (as shown in the setup tutorial)
  4. Save your configuration

This action will allow Grabbit to extract multiple video links quickly from YouTube pages.

Step 2 — Collect the creator’s videos

Next, go to the YouTube channel of the creator you want to learn from.

To get better results:

  • Use filters (Most popular, Latest, or specific topics)
  • Scroll to load as many videos as possible
  • Select only the content relevant to your goal

Then use the Grabbit extension to extract all the video URLs at once.

You’ll end up with a clean list of links — this will become your training dataset.

Step 3 — Build your AI notebook

Now open NotebookLM (Google’s AI research assistant).

  1. Create a new notebook
  2. Add sources
  3. Paste all the YouTube URLs collected with Grabbit
  4. Let NotebookLM process the content

Once the indexing is complete, your custom AI is ready.

Step 4 — Ask anything

This is where the magic happens.

You can now ask questions like:

  • “Explain their full business strategy”
  • “What mistakes do they say beginners make?”
  • “Summarize their mindset in 5 key ideas”
  • “Create a step-by-step plan based on their advice”

NotebookLM answers using the creator’s videos as its only source, making the responses highly relevant and consistent with their content.

Best use cases (sky is the limit)

  • Learning from a niche expert quickly
  • Studying a creator’s framework or method
  • Researching a topic without watching dozens of videos
  • Building a personal knowledge assistant
  • Analyzing competitors or industry leaders

This approach is especially powerful for entrepreneurs, marketers, developers, and creators who want to absorb expertise efficiently.

Tools like Grabbit and NotebookLM are changing how knowledge is consumed. Instead of passively watching content, users can now interact with it, question it, and extract exactly what they need.

It’s no longer about following a creator — it’s about turning their entire body of work into your personal AI mentor.

A new way to learn in the AI era

As more content moves online, the challenge isn’t access — it’s navigation. This workflow solves that problem by transforming information overload into structured, searchable knowledge.

In 2026, the smartest learners aren’t just watching videos anymore.

They’re training AI to think like the people they want to learn from.

alex morgan
I write about artificial intelligence as it shows up in real life — not in demos or press releases. I focus on how AI changes work, habits, and decision-making once it’s actually used inside tools, teams, and everyday workflows. Most of my reporting looks at second-order effects: what people stop doing, what gets automated quietly, and how responsibility shifts when software starts making decisions for us.