back

Guide to Google’s NotebookLM

A very meta in depth guide and audio example of how NotebookLM makes a guide on using Perplexity.

NotebookLM is Google’s AI-Powered Research Assistant for the Digital Age.

In today’s fast-paced digital world, staying on top of information can be overwhelming. Enter NotebookLM, Google’s innovative AI-powered tool designed to revolutionize how we interact with and process information. Whether you’re a student, researcher, professional, or simply someone who loves to learn, NotebookLM offers a unique way to organize, analyze, and explore your digital content. We like this AI app a lot.

What is NotebookLM?

NotebookLM is an AI-powered note-taking and research assistant that helps users make sense of large amounts of information quickly and efficiently. It combines the power of artificial intelligence with a user-friendly interface to create a virtual workspace where your documents, notes, and ideas can come together seamlessly.

One of NotebookLM’s standout features is its ability to work with various types of documents. You can upload Google Docs, PDFs, text files, Google Slides, Youtube URL’s and even web URLs. This versatility allows you to bring all your research materials into one place, regardless of their original format.

AI-Powered Analysis

Once you’ve added your sources, NotebookLM’s AI goes to work, analyzing and summarizing the content. It can create overviews, identify key topics, and even suggest questions to explore further1. This feature is particularly useful when dealing with complex or lengthy documents.

Intelligent Q&A

Perhaps the most impressive aspect of NotebookLM is its ability to answer questions about your sources. You can ask specific questions, and the AI will provide answers with inline citations, linking directly to relevant sections of your original documents. This makes fact-checking and deeper exploration of topics incredibly efficient.

Note-Taking and Organization

NotebookLM allows you to create, save, and organize notes alongside your source material. You can manually add notes or save AI-generated responses for later reference6. This integration of notes with source material creates a powerful tool for students, writers, and researchers.

Google’s NotebookLM has introduced a groundbreaking feature called Audio Overview, which is revolutionizing how we consume and interact with written content. This innovative tool transforms uploaded documents, web pages, and other text sources into lively, podcast-style audio discussions between two AI-generated hosts.

How Audio Overview Works

When you upload content to NotebookLM, the Audio Overview feature analyzes the material and creates a dynamic conversation that summarizes key points, makes connections between topics, and presents information in an engaging format. With just a single click, users can generate these audio discussions, which typically last between a few minutes to around 20 minutes.

The AI hosts don’t simply recite the content; they engage in a back-and-forth dialogue, complete with light banter and enthusiasm that mimics real podcast conversations. This approach helps maintain listener interest and can potentially surface new insights or connections within the material.

The Future of Information Consumption

NotebookLM’s Audio Overview represents a big step forward in how we process and interact with information. As AI continues to reshape our learning and research experiences, tools like this offer exciting possibilities for more dynamic, personalized, and efficient knowledge acquisition. As the technology evolves, we can expect improvements in accuracy, language support, and interactivity. For now, Audio Overview stands as a super cool example of how AI can transform static content into engaging, accessible, and multifaceted learning experiences.

While the feature is still experimental and has some limitations (such as occasional inaccuracies and English-only output), it represents a solid step forward for Google that has been struggling to make a friendly and cool AI app. NotebookLM gives a positive way to interact with and digest information, making learning more dynamic, efficient, and personalized

This is the audio file from NotebookLM. We had to make a video to host on Youtube. Listen to the conversation the AI’s are having about Perplexity. Pretty amazing!

Recent Blog Posts

Apr 14, 2026

Anthropic Shipped Claude Channels. Your AI Agent Can Now Text You Back.

Until very recently, every interaction with an AI agent had the same shape. You sit down. You open the tool. You give it a task. You wait. You check. You iterate. Every cycle requires your presence. Walk away and the session stalls, the output piles up unseen, or a permission prompt freezes everything until you come back. That constraint just changed. On March 20, 2026, Anthropic shipped a feature called Claude Code Channels. It lets Claude's agentic tool communicate with you through Telegram, Discord, and iMessage. You send a task from your phone. Claude does the work on your computer....

Apr 13, 2026

What Did You Do Today?

There's a saying in Jackson Hole. You hear it at the coffee shop on the square, on the chairlift at the Village, in the bars after a day on the mountain. It goes like this: It's not what you do. It's what you did today. I've been thinking about that line all weekend. Because Sam Lessin dropped a piece arguing that AI isn't just a labor crisis — it's a meaning crisis. And Goldman Sachs just published 40 years of data proving that when technology displaces workers, the damage doesn't heal. It scars. Ten percent slower earnings growth for the...

Apr 3, 2026

Claw-code Broke GitHub’s Star Record in 24 Hours. Two Engineers Did It on an Airplane. Here’s What That Means for Your Business.

Here's the number: 100,000. That's how many GitHub stars a repository called claw-code collected in roughly 24 hours. Not a year. Not a month. One day. By the time a live stream was done discussing it, the counter was climbing by a thousand stars every ten minutes. Nobody in the room could remember seeing anything grow that fast. Because nothing had. I watched it happen in real time. I'd met the two engineers behind it the weekend before at an AI hackathon in San Francisco. Within 72 hours of shaking hands, they'd built the fastest-growing repo in GitHub history —...