This tutorial demonstrates combining Claude Code with Notebook LM to automate YouTube research workflows. In minutes you can scrape video captions, import sources into a RAG-style notebook, run offloaded analysis, and produce deliverables (infographics, slide decks, flashcards) without paying token costs. The video covers setup, tools, and a live demo.
– Automated scraping: Use a custom YouTube search skill in Claude Code to collect titles, captions, views, and metadata, then push URLs to Notebook LM.
– Offloaded analysis: Notebook LM ingests sources into a RAG-style notebook to extract top skills, trends, and cited captions while minimizing local token usage.
– Deliverables & exports: Automatically generate infographics, slide decks, flashcards, audio summaries, and batch exports from analyzed video sources.
– Setup & integration: Step-by-step walkthrough of the Notebook LM-PI repo installation, authentication, and wiring the Claude Code skill for a terminal-first workflow.
Quotes:
Claude Code might be the most powerful research agent on the planet.
With just five minutes of setup, we could create workflows that scrape YouTube and push them to a RAG system.
All the thinking is done by Google and they’re paying for it.
Statistics
| Upload date: | 2026-03-02 |
|---|---|
| Likes: | 4421 |
| Comments: | 110 |
| Fan Rate: | 5.02% |
| Statistics updated: | 2026-04-01 |
