You’re Using Google All Wrong

What if Google could not only search but think for you? Imagine an AI research assistant that doesn’t just summarize documents but turns them into podcasts, finds contradictions, builds study guides, and even chats with you—about your own content. Welcome to the future of productivity with Google’s mind-blowing AI tool, Notebook LM—and in this podcast, we go deep.

We’ve pulled insights from the top 20 tutorials, cross-analyzed them with AI, uncovered hidden features most people miss, and even exposed some game-changing use cases—from Spotify's secret use of Notebook LM to how job seekers and students are quietly getting ahead with it.

You’ll hear real-world examples, smart strategies, and even the latest secret updates Google quietly rolled out. Plus, we’ll show you how to create an AI-generated audio summary of your own documents—perfect for learning while commuting or multitasking.

Whether you're a researcher, entrepreneur, student, or just an AI-curious explorer, this podcast is packed with tools and techniques that could 10x your efficiency overnight.

But here’s the kicker: by the end, you’ll wonder how you ever worked without it. Hit play now—your smarter workflow starts here.

I gathered the top 20 YouTube tutorials on how to use Notebook LM

I asked Notebook LM to provide me with a categorized list of tutorial elements that are taught across all of these different topics. Give me the most common topics up front and the less common topics down below. And I also want you to keep the individual unique ideas separately and finally identify any gaps and opportunities that other tutorials should offer.

My second step was to ask the Notebook LM to help me customize the audio overview that explains the most common covered aspects of using Notebook LM. It also includes the most important of the unique ideas but also includes the gaps and opportunities that were mentioned. So the LM created a really great podcast outline.

It's fantastic and I turned it into a note and then I turned that note into a resource as well.

And then the final step in creating the podcast that follows was to direct the LM to create an audio overview, but to do it following the audio overview guide that I had created.

And as I did the editing for this podcast, it's a great presentation.

I'm so glad I pulled this all together.

All the Resources Are Ready—And You Can Access

I saved both the tutorial content overview and the audio overview guide as separate PDFs, and I've also downloaded the podcast as a separate file as well. And I've made those available inside my AI Business Plans community where you can go into the course into the blueprints and you can scroll down and get access to everything.

I really want this to be accessible to everyone.

So, I always have a 7-day free trial where you can access the PDFs that I talk about in the video, but you also get access to the full stack of make automation blueprints and all the tutorials that come along with it, as well as the community to help you get automated.

Yesterday I announced this new video format and today I'm researching how to use Google NotebookLM.

How I'm Researching the Best AI Tutorials with AI Help

I am going a bit meta here and I'm stepping back and I'm doing studies about what are the best tutorials out there so that I can select which ones are going to be the best for my projects.

And I'm focused on using NotebookLM to pull everything together into a PDF guide that I can use for each day's research, plus the podcast that explains everything so that we can listen and find out if that's what we want and then use the PDF to follow along step by step.

Let's jump in and learn all about the best ways to use Google Notebook LM.

Overwhelmed by Info? Here’s How Notebook LM Fixes That

Welcome to another AI business plan deep dive.

Today we're jumping into Google's Notebook LM.

Yeah, it's a really interesting tool. Kind of an AI-powered research partner. Exactly. Imagine having something that can sift through all your documents, your notes, even web pages and help you make sense of it all. That's the idea.

It's built to tackle that feeling of information overload we all seem to face. Right. So, we've gathered a bunch of info from different places to really understand what Notebook LM is, how it actually works, and importantly, how you might use it. Uh-huh. We're thinking research, maybe even business planning, learning new things.

We'll cover the key features, definitely look at some real-world examples people are sharing, and talk about what kinds of sources it likes, what it can handle, plus some maybe advanced tips and recent updates because these things change fast. Absolutely. The goal today is to give you the essential info so you can figure out if and maybe how Notebook LM could, you know, streamline things for you, help you understand complex stuff better. Sounds good.

So, the core idea, what is Notebook LM really trying to be? At its heart, it's an AI tool from Google built for research, taking notes, summarizing things, like you said, a personalized research assistant. Okay. And how do you feed it information? What does it eat, so to speak, huh?

What Can You Feed Notebook LM? More Than You Think

Yeah, it handles quite a range. Google Docs, Slides now, too, PDFs, of course, plain text files. PDFs are huge for research.

Definitely. And website URLs, which is handy. Even YouTube URLs, as long as they're public, can have transcripts. Oh, interesting. YouTube transcripts. Yeah. And more recently audio files like MP3s. Wow. Okay.

So it can listen now too. Sort of. It processes the audio content. There are limits though. Currently it's up to 50 source documents per notebook.

50 sources. Is that usually enough? For most focused projects probably. And each source can be pretty large, up to half a million words. That's substantial. And the YouTube videos need transcripts. Yep.

Here’s What Notebook LM Actually Gives You

Public videos with available transcripts. And you need a Google account. Naturally. You get up to 100 notebooks per account, right? Makes sense. So, you put your stuff in. What does it give you back? What are the key outputs?

Well, summaries are a big one. Comprehensive summaries of what you uploaded. Okay. Standard AI stuff.

What else? It gets more interesting. It can analyze across different documents. So, it highlights connections between sources or maybe points where they disagree. Uh, synthesis, that's more advanced. Finding contradictions, that's useful.

Totally. It can also generate things like FAQs based on your docs, study guides, briefing documents.

Mind Maps, Timelines, and Even Podcasts—Yes, Really

Study guides. I can see students liking that for sure. Mind maps, timelines of events if your sources describe a sequence. And a really cool one, audio overviews. Audio overviews. Tell me more about that.

Like an AI podcast. Pretty much. It can generate an audio discussion like two AI voices talking about the key points in your sources.

You can listen on your commute, for example. Okay, that is cool. We should definitely dig into that audio feature more later. Agreed. It also has this notebook guide thing. It gives you like quick start templates or suggested questions to ask your sources.

Helps you get going. Kind of nudges you on how to interact with it. Exactly. And there's the main chat interface where you just ask questions about your uploaded material. And crucially, it answers based only on those sources. Right. It's grounded.

Grounded AI: Why Notebook LM Stands Out

Yes, that's a key design principle. It tries very hard not to hallucinate or make things up. It grounds its answers in the text you provided, which is a major differentiator from some other large language models. Big time.

And often when it gives you an answer, it shows you where in your sources it found the information. It even highlights the relevant text. Sometimes that citation or source linking feature is vital for trust and verification.

Absolutely. And if the AI generates something useful in the chat, like a good summary or an interesting connection, you need to save it, right? Chat history doesn't stick around automatically. Correct.

There's a save to note feature. You have to actively save the bits you want to keep. Good to know. So, you curate the important outputs. Yeah. And you can then select multiple saved notes and combine them. Maybe to build out that study guide, create an outline, or even ask the AI to suggest related ideas based on those notes.

Build, Combine, and Customize—Make It Work for You

So, it becomes iterative. You interact, save, combine, interact again. Precisely. Getting back to the audio overviews, you mentioned customizing them, right? You could tailor them, tell the AI who the audience is, maybe like explain this for an expert versus explain this for a beginner or focus it on specific aspects. Exactly.

Focus on the financial implications or summarize the technical challenges. It tries to shape the AI podcast discussion based on your instructions. That makes it much more practical than just a generic summary read aloud. Definitely.

And there's even a newer interactive audio feature rolling out. Interactive. How does that work? The idea is you can actually interact with the AI podcast while it's playing.

Ask questions, maybe guide the discussion a bit. Whoa. So you're listening, something sparks a question and you can just ask it. That's the concept. It makes it more dynamic, less passive. Feature rollout might vary, but it's a really interesting direction. Sounds very cutting edge. Yeah.

Find New Sources Automatically with Discover Mode

One more feature to mention, the discover sources feature. Ah, yes. Finding new information related to your topic, right? You can tell it a topic you're interested in and it will search for relevant articles, YouTube videos, web sources. You can then import directly into your notebook.

So, it helps you build your source collection, not just analyze what you already have. Yep. And you can refine those searches like asking specifically for journal articles or just videos. Handy for research. Yeah.

Okay. That covers a lot of the what it does. How are people actually using this in the real world? Any cool examples?

Real-World Success Stories Using Notebook LM

Yeah, lots are popping up for learning and research. One user mentioned uploading four PDFs about an investment. Okay. And Notebook LM generated that AI podcast, the audio overview, which they listened to on their commute, made complex info digestible on the go.

That's a perfect use case for the audio feature. Students must love it, too. Oh, for sure. Uploading articles, book chapters, lecture notes, then asking specific questions, generating quizzes, study guides, those podcasts. Again, I could see it being great for dense material like technical papers. Mhm.

Analyzing security white papers. Maybe someone did exactly that. Fed in multiple sources, listened to the overview first to get the gist, then dove in with detailed questions in the chat. Efficient. What about languages?

Another interesting one—understanding foreign language documents. Upload them and you can ask the AI to explain the content in English or even generate the audio overview with English-speaking AI hosts. That's powerful for global teams or researchers dealing with international sources.

Big Business and Small Wins—How Companies Are Leveraging It

Let's shift to business use cases. Any big names using it? Well, apparently Spotify uses Notebook LM to help power Spotify Wrapped. Really? For analyzing listening data and trends. Maybe the specifics aren't totally public, but yeah, suggests it's capable of handling complex data analysis for business insights. Interesting.

What about more day-to-day business tasks? Analyzing legal documents seems common. Someone used it for trip insurance guidelines, finding specific clauses quickly instead of reading the whole dense thing. Cutting through the jargon. I like it.

Job seekers are using it, too. Upload your resume, upload a few job descriptions, and ask it to find the matches. Highlight relevant experience. Exactly. Or even help draft sections of a cover letter tailored to that specific job description based on your resume. Smart. Saves a lot of time tailoring applications.

Project managers are finding uses, too. Feeding it meeting notes, project plans to get what? Briefing docs, timelines. Yep. Generate briefing documents for stakeholders, timelines of key milestones, FAQs for the project team. Helps keep everyone aligned.

Okay, that makes sense. Distilling long reports, brainstorming. Yeah. Or organizing research notes, outlining complex narratives. If you're writing something long, even analyzing presentation slides, you can upload Google Slides now. Right. You mentioned slide support.

Personal Use Cases You Didn't Expect

What about personal uses, not just work or study? People are getting creative. Organizing family history documents, maybe asking questions about ancestors based on uploaded letters or records. Huh. Genealogy assistant, kind of.

Or helping with decision-making. Someone mentioned analyzing their own journal entries to find patterns or reflect on choices. That's quite personal. Using AI for self-reflection. And simpler things like planning trips—uploading hotel confirmations, flight details, maybe some articles about the destination and asking what's my flight number or summarize the check-in process for the hotel.

Precisely. Quick access to your own info. Even technical fields are seeing use like analyzing complex codebases or summarizing software projects. So, it's pretty versatile. Learning, business, personal, technical. Seems like it.

Pro Tips to Get the Most Out of Notebook LM

Now, let's talk tips for getting the most out of it. Any advanced strategies? Well, source selection is key. If you want really focused answers, don't just dump everything in. Select only the most relevant sources for that specific task or question.

Garbage in, garbage out still applies, even with smart AI. Absolutely. A practical tip: if you're looking for PDF versions of things online, using type:pdf in your Google search can help find them easily for uploading. Good one.

What if a website you want to use as a source is blocked, maybe a paywall, or just doesn't scrape well? The workaround is often just good old copy and paste. Copy the text content you need and paste it directly into Notebook LM as a text source. Simple, but effective.

What about that 50 source limit? If you have say 70 relevant articles, you might need to combine some. If you have several short related documents, maybe merge them into a single PDF or text file before uploading. Stay within the limit that way. Okay. Consolidate sources if needed.

Don’t Stop at the First Output—Iterate, Expand, Refine

You mentioned iterating on notes earlier. Can you expand on that? Yeah. So, let's say you generate an FAQ list from your sources. You can then select that FAQ note and ask the AI follow-up questions about it. Like what?

Like, “Can you add some questions for beginners to this FAQ?” Or, “Expand on the answer to question three with more detail from source X.” You interact with the generated notes. So, the output isn't static. You can refine it. Exactly.

And that discover sources feature. It could be used to stay updated, set up a search for a specific field or topic, and periodically check it for the latest news or research. Right. Use it to pull in recent articles or web sources to keep your notebook and your knowledge current. Smart.

Okay, it sounds powerful, but we need to be balanced. What are the limitations or downsides? Things to watch out for.

Limitations and What to Watch Out For

Well, it's still officially labeled as experimental by Google. So, responses might sometimes be inconsistent or features might change. It's evolving. Good reminder—it's not a finished static product.

And accuracy hinges heavily on your source material. If a source is vague or poorly written, the AI is going to struggle to give you a clear answer based on it. It can't magically fix bad source info. Makes sense.

What about the website integration? You said it takes URLs. How well does that work? Initially, it seemed to focus more on just page titles and maybe summaries. Getting deep content scanning from complex websites might still be an area of improvement compared to, say, a clean PDF.

Okay, so PDFs might be more reliable for deep analysis than some websites, potentially. Also remember that chat history isn't saved automatically. You have to use that save to note button for anything important you get from the chat interaction. Crucial point. Don't lose good insights.

And while it's designed to hallucinate less, which is a big plus, it might also mean it's less creative sometimes. It sticks closely to the source text, so you might not get wildly novel ideas from it but rather synthesized insights based on it. It's a trade-off.

More grounded, perhaps slightly less imaginative than some other AI tools. Fair enough.

The Latest Updates: More Formats, More Countries, More Languages

What about recent updates? What's changed lately? Quite a bit, actually. Support for more source types was a big one. Google Slides, those website URLs we mentioned, and audio file support landed around June 2024.

Okay, so it's becoming more versatile in what it accepts. Definitely. Availability expanded massively. It was US only initially, but now it's available in over 200 countries and territories. Wow, that's a global rollout. Huge.

The interface also got a refresh. Now there are clearer separate sections for your sources, the chat area, and your saved notes and the audio overview controls. Better organization, seems like it.

And we talked about the interactive mode for audio overviews. That's a key recent addition, right? The ability to ask questions during the AI podcast. And those audio overviews are now available in over 50 languages. You can change the output language in the settings.

Fifty languages for the audio output. That's impressive accessibility. It really opens it up for international use cases.

Final Thoughts: Should You Use Notebook LM?

Okay, so wrapping this up, we've gone pretty deep into Notebook LM. It's this AI tool for research, organization, understanding your own information, acting as that personalized assistant grounded in your specific documents.

Key things that stand out are its ability to summarize, analyze across sources, find connections, generate those FAQs, study guides, and especially that customizable, now interactive audio overview feature that feels pretty unique. Yeah, the AI podcast idea is powerful.

Plus, the focus on grounding answers in your content to reduce making stuff up. That's crucial for trust, especially in research or business contexts. And the recent additions—more sources, global access, interactive audio, and multiple languages—show it's actively being developed.

So, for you listening, think about how these features might fit your workflow. Could that discover sources tool help you find new information? Could generating a briefing doc save you time? Could listening to an audio overview of those meeting notes make your commute more productive or help you understand that complex report faster?

It's really about cutting through the clutter, right? Gaining insights more efficiently, maybe exploring topics you wouldn't have had time for otherwise. Exactly.

The world of AI tools is moving incredibly fast. And Notebook LM is definitely one to watch in this knowledge management space. We definitely encourage you to check it out, experiment with it, see if it can help you become, you know, better informed and maybe just more efficient.

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