I Made Claude Cowork Smarter by Connecting It to NotebookLM (No Claude Code or Terminal Required)
Do more with Cowork by connecting it to NotebookLM (+3 new use cases)
This guide was written in collaboration with Gencay.
Gencay writes LearnAIWithMe, a newsletter focused on practical AI tutorials for people who’d rather replace than be replaced by AI.
In a previous guide, I showed you how to connect NotebookLM with Claude.
It worked, but there was a catch: the whole setup lived in the terminal. CLI, install commands, config. Powerful, but for most people, too technical.
This time, there’s no terminal (or Claude Code).
I found a NotebookLM skill that runs inside Claude Cowork. You only need to download it and add it to Cowork.
In this guide, you’ll learn:
How to set it up in two steps
Use case 1: Interview prep that knows a company’s last twelve months
Use case 2: A weekly language feedback loop that drills your real mistakes
Use case 3: Pre-trip destination briefings grounded in fresh sources
Use case 2 is connected to my Claude for Foreign Language Learning video course, while use case 3 is related to the AI Travel Guide I published last week.
The Claude Skill
This skill was created by Paul J Lipsky.
Download the skill clicking here. Then open Cowork and follow the steps below.
Customize → Skills → “+” → Create skill → Upload a skill → Upload the skill file
Now I can run NotebookLM through Cowork.
But I got errors the first time, because I skipped half the video.
So before you start, here is what I wish someone had told me.
How to set it up
Two steps. Skip either, and the skill will fail on first run.
Step 1: Install Claude Chrome Extension
Go here and click Add to Chrome.
Step 2: Add the NotebookLM domain to Claude in Chrome
Open the Claude desktop app. Click your name in the bottom left. Hit Settings.
In settings, scroll to Claude in Chrome (Beta). Click Add websites. Type notebooklm.google and confirm.
Without this, the skill cannot drive NotebookLM. The extension is loaded but blocked. That was my first error.
How to use it?
In any Cowork chat, type:
/notebooklm
The skill loads and asks what you want to do.
Four options come up.
Read / extract from a notebook
Add sources to a notebook
Generate a Studio output
Create a new notebook
Let’s pick Create a new notebook.
Question 1: Name
The skill asks if you want to name it yourself or let NotebookLM auto-name it. I named mine Prompt Engineering Course.
Question 2: Sources
The second question will ask you about the sources.
I clicked Yes, add sources now.
Five options: URLs, YouTube, uploaded files, copied text, or something else.
I dropped into the Anthropic prompt engineering course on YouTube:
Next, it loaded the source and took control of my Mac.
A red border appears at the top of the screen.
That is Claude debugging the browser. You watch it click, type, wait, screenshot. Same way you would do it, just faster.
It pasted the YouTube link into the source box.
NotebookLM ingested the transcript and auto-generated a summary describing the video as a roundtable with Anthropic experts on prompt engineering.
Done. Notebook live.
Audio Overview, Mind Map, Reports, Quiz, Infographic, all one click away in the Studio panel.
So here are 3 use cases I love.
Use Case 1: Weekly Job Interview Prep
The week before an interview, most people do the same thing. Open the company website, read the About page, and maybe check LinkedIn. Walk in underprepared and get caught off guard by something you should have known.
The fix is better synthesis of more sources than you can read.
Step 1. Train NotebookLM with Deep Research
In Cowork, type:
/notebooklm
Create a new notebook called “Stripe Interview”. Then run Deep Research with this prompt:
I have an interview at Stripe. Find sources that cover:
Company history, mission, and recent strategic moves
Latest product launches and roadmap signals from the last 12 months
Public statements from the CEO and senior leadership (podcasts, conferences, X)
Financial position, fundraising, or earnings if public
Competitor landscape and how Stripe positions against them
Glassdoor reviews, common interview formats, and what current employees say about culture
Prioritize sources from the last 12 months. Mix press releases, podcast transcripts, news articles, official advisories, and employee reviews.
Cowork takes over the browser. Red border on top. Opens NotebookLM, creates the notebook, clicks Discover sources, pastes the prompt, and hits run.
After some minutes, the research was done.
And the notebook is ready.
Step 2. Cowork Setup
Create a folder on your computer called interviews. Inside, one subfolder per company.
The artifacts folder holds NotebookLM outputs.
Give Cowork access to interviews.
The notebook from Step 1 holds the knowledge. The folder is the landing strip for what comes next.
Step 3. Generate Artifacts
In the same Cowork chat, type:
/notebooklm
Open the “Stripe Interview” notebook. In the Studio panel, generate:
A Briefing Doc covering company narrative, recent strategic priorities, and leadership focus areas
A Quiz with likely interview questions, each anchored in something the company has publicly said
An FAQ on common pitfalls from Glassdoor reviews and negotiation pressure points
Save all three to /interviews/stripe/artifacts/.
And generate an artifact with three tabs;
1- Briefing Doc
2- Quiz
3- FAQ for common pitfalls
And it started building.
Here is the artifact after a few adjustments.
Step 4. Schedule
Turn it into a habit. Every interview is prepped automatically.
Create a file called /interviews/upcoming.md. Drop your upcoming interviews in it like this:
- Stripe, 2026-07-15
- Anthropic, 2026-07-22
- Notion, 2026-08-03
In Cowork, open Schedule. Create a new task with this prompt:
Every morning at 9 AM, check /interviews/upcoming.md for any interview 7 days away.
For each interview 7 days out:
Create /interviews/{company}/artifacts/.
Use /notebooklm to create a notebook named “{company} Interview”.
Run Deep Research with this prompt, replacing the company name: “I have an interview at {company}. Find sources covering company history and strategy, latest product launches and roadmap from the last 12 months, public statements from leadership, financial position, competitor landscape, Glassdoor reviews, and interview formats. Prioritize the last 12 months. Mix press releases, podcasts, news, and employee reviews.”
Generate Briefing Doc, Quiz, FAQ. Save to /interviews/{company}/artifacts/.
And create an artifact with three tabs based on this briefing.
Set frequency to daily, 9 AM.
That is the whole thing.
You walk into an interview knowing the company’s last twelve months better than half the people already working there.
The next two use cases are exclusive to paid subscribers
Use Case 2 — Weekly Language Feedback Loop: turn Claude + NotebookLM into a tutor that drills your real mistakes every week. This is just one lesson from my full video course on learning a foreign language with Claude. The moment you upgrade, you’ll receive an email unlocking free access to this and other courses.
Use Case 3 — Pre-Trip Destination Companion: most AI travel advice is stale, pulled from old training data. This builds a brief from fresh sources, so you walk into any city this summer knowing what's actually true today. You’ll also get my complete guide on using AI to plan trips.
Become a paid subscriber and you get both use cases, the full language course, and the AI travel guide, everything you need to learn a language and prepare for your summer trip.
 | A guest post by
|