NotebookLM: Turn Any GitHub Repo into an AI Video Tutorial

Midjourney 7

A 2:37 AM Discovery That Changed How I Read Code

It was 2:37 in the morning. I was scrolling through GitHub searching for new NotebookLM extensions when I stumbled upon something that completely transformed how I think about documentation.

NotebookLM Pro Tree — a Chrome extension with 84 stars and a description promising to transform NotebookLM into a “robust Project Management Dashboard”. But the extension itself wasn’t what fascinated me. What fascinated me was the question that hit me:

What if I didn’t have to read lines of JavaScript code to understand how this extension works?

Three minutes later, I was watching an AI-generated video explaining the entire architecture of the extension while sipping coffee and taking notes.

The Strategy: GitHub-to-Video Transformation

Concept: Systematic conversion of any GitHub repository into a narrative video overview through a three-step process that eliminates the need for manual technical documentation reading.

Implementation:

Step 1: Transform the Repo into Documentation Open gittodoc.com in your browser. In the input field, enter the complete GitHub URL (e.g., https://github.com/benju66/Notebook-Nest). Click the orange “Create Docs” button. After a few seconds of processing, two new options appear: a green “View Documentation (Cloud)” button and an orange “Copy Documentation Link” button. Click “Copy Documentation Link” — you’ll need this link in the next step. GitToDoc has just parsed the entire repository structure and created complete, structured documentation.

Step 2: Import into NotebookLM Open NotebookLM and create a new project. Instead of uploading files, click the “Insert” option and select “Website”. Paste the link you copied from GitToDoc (it will be in the format https://gittodoc.com/user/project/...) or https://gittodoc.com/benju66/Notebook-Nest. NotebookLM automatically downloads the entire documentation and indexes it for analysis. The status bar will show “Processing source” — wait for this process to complete (usually 30–60 seconds for medium-sized projects). When you see “Source added successfully”, you’re ready for the next step.

Step 3: Generate Video Overview In the NotebookLM interface, go to the “Notebook guide” panel (usually on the right side). Click the “Generate” button next to the “Audio overview” option. Before clicking “Generate audio”, select the “Customize” option. In the customization panel, change the format from “Audio overview” to “Video overview”. Optionally, add custom instructions in the text box (e.g., “Focus on architectural decisions and explain why specific patterns were chosen”). Click “Generate” and wait 2–4 minutes. NotebookLM will create a complete video presentation with visual elements illustrating code structure, architectural decisions, and key project features.

What’s Happening Behind the Scenes?

GitToDoc doesn’t just display the README file. It parses the entire directory structure, analyzes dependencies, maps functionalities across different files, and creates comprehensive documentation that includes code snippets with context. This means NotebookLM gets a holistic view of the project, not fragmented information.

When NotebookLM generates the video, the AI doesn’t create a linear list of functions. Instead, it creates a narrative that explains the project’s evolution, architectural decisions, and relationships between different components. In the case of the NotebookLM Pro Tree extension, the video explained how the local-first architecture enables speed, why the developer chose LZ-String compression for the search index, and how the multi-window system integrates with the Chrome API.

The Neuroscience Behind It

Multimodal information processing activates different brain regions simultaneously. When you watch a video that combines narrative explanation with visual representation of code structure, your brain processes information through the auditory cortex for sound, the visual cortex for graphics, and Wernicke’s area for language comprehension. This simultaneous activation creates a more robust memory representation than any single modality.

Additionally, the narrative structure that AI generates leverages episodic memory. Instead of remembering isolated functions or variable names, you remember the story of how the developer solved the data storage problem or how they created the graceful degradation system. Stories are remembered 22 times more easily than facts.

Quantitative Results

Research shows that combining visual and auditory input can improve understanding of technical documentation by 42% compared to reading alone. For complex software projects, narrative explanation of architecture reduces the time needed for onboarding new developers by approximately 38%.

In my specific case with the NotebookLM Pro Tree extension, traditional documentation reading and code review would have taken me a minimum of 45 minutes. The video overview allowed me to understand the key concepts in 12 minutes, and then I could focus only on the parts of the code that specifically interested me.

Practical Application: The NotebookLM Pro Tree Case

When I applied this process to the NotebookLM Pro Tree repository, the video revealed fascinating details I would have easily missed through traditional reading:

The developer is a construction project manager, not a professional programmer. His documentation reflects this through pragmatic instructions and honest warnings about potential bugs. The extension uses a “graceful degradation” system that allows individual features to stop working if Google changes the NotebookLM interface, but the entire extension doesn’t crash. The local storage architecture means backup is critical because uninstalling deletes all data. The multi-window system enables a dual-monitor workflow that transforms NotebookLM into a real research station.

These insights appeared in the first minutes of the video, packaged in a coherent narrative structure that explained the “why” behind every “what”.

Limitations and Complications

GitToDoc doesn’t work for private repositories. If you’re analyzing proprietary code, you’ll need to use alternative methods or set the repository to public before analysis. Video Overview can last 8–15 minutes for large projects, which requires patience. For extremely complex projects with multiple technologies, one video might not be sufficient — you may need to create multiple NotebookLM projects organized by functional areas.

Also, video cannot replace in-depth code analysis. It provides an excellent conceptual framework, but for debugging or security audits, you still need to read the actual code.

The Future of Technical Documentation

This method opens fascinating possibilities. Imagine developer teams generating video presentations for every major feature branch before merge. Imagine an onboarding process where new developers receive personalized video overviews of only those parts of the codebase that are relevant to their teams. Imagine open source maintainers automatically generating educational content for every release.

NotebookLM’s ability to transform structured text into narrative video isn’t just a productivity hack. It’s a redefinition of how we interact with technical documentation.

TOO BUSY?

Link: https://github.com/benju66/Notebook-Nest Change to: https://gittodoc.com/benju66/Notebook-Nest Import to NotebookLM → Generate Video Overview Time: 12 minutes vs 45+ minutes of manual reading

The essence of this approach isn’t technological sophistication. The essence is recognizing that our brains evolved to understand stories, not specifications. When we transform a GitHub repo into a video narrative, we’re not changing the content — we’re changing how that content communicates with our cognitive system.

And that, in the end, makes the difference between documentation you actually use and documentation that gathers digital dust in a README.md file.

The real revolution isn’t that AI can read code for you — it’s that you can finally learn without pretending your brain works like a compiler.