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In this video, I show you how to turn Claude Code into the ultimate AI research agent by connecting it to NotebookLM — Google's free source-grounding tool powered by Gemini.

Using a custom YouTube search skill (powered by yt-dlp) and the notebooklm-py CLI, you can search YouTube for any topic, push the top videos directly into NotebookLM, have it extract all the captions and build a queryable knowledge base, run analysis across every video, and generate deliverables like infographics, slide decks, and podcasts — all from your terminal.

No vector databases, no embedding costs, no RAG infrastructure to maintain. The entire setup takes 5 minutes and replaces a research stack that would cost hundreds a month to build yourself.

⏰TIMESTAMPS:
0:00 - Intro
1:15 - Demo
4:32 - Setup
8:22 - Walkthrough
10:08 - More Resources

RESOURCES FROM THIS VIDEO:
➡️ Master Claude Code: https://www.skool.com/chase-ai
➡️ My Website: https://www.chaseai.io
➡️ Claude Code Docs: https://code.claude.com/docs/en/overview

#claudecode #notebooklm

YouTube

A workflow tutorial combining Claude Code and Google's NotebookLM to build a free research pipeline. The setup uses a custom YouTube search skill (powered by yt-dlp) to scrape video metadata, pushes those sources into NotebookLM via an unofficial Python API, and lets NotebookLM handle all RAG-based analysis and deliverable generation (infographics, slide decks, flashcards, podcasts) at no token cost. The key insight is offloading heavy analysis to Google's infrastructure for free while keeping results accessible inside the Claude Code terminal environment.

Claude Code + NotebookLM = CHEAT CODE