NotebookLM In 30 Minutes

I learned how to use Notebook LM for you. So, here's the Cliffnotes version to save you the hours and hours that I've spent deep diving into this extremely powerful tool for both working and learning. It is honestly one of my favorite tools, and it's crazy how much value you get from the free version. So, in this video, I'm going to show you the core features of Notebook Outlook, including things like distilling and summarizing information and how to make it even more powerful in combination with other tools to even do things like automating workflows and building AI products. As per usual, it is not enough for you just to listen to me talk about stuff. So throughout this video, I will have little assessments which if you can answer these questions, then congratulations. You would be educated on using Notebook LM. Now, without further ado, let's go. A portion of this video is sponsored by Augen Code. Let's

start off with first answering the question, what is Notebook LM for? Well, if you go to the landing page for Notebook LM, there in big massive letters, it says understand anything. The core kind of concept of notebook LM is that in our information age, the problem is not the lack of knowledge. It's our ability to understand and make sense of it. And that is what notebook LM is here to do. It allows you to take a lot of different types of information from sources, synthesize them together, and help you understand them deeply. I'll go through each feature of Notebook LM in detail in just a little bit, but first I want to explain the overarching workflow for Notebook Lab. When you first go into Notebook LM and you click create a new notebook, step number one is to upload your sources. You can drag and drop all sorts of different files and also link from your Google Drive, different links including websites and YouTube links and copy text as well. You can also click to discover sources tab and be able to search other external sources too. You can then chat with your sources in this chat window asking you to do things like summarizing or analyzing. But that's not all. What really makes Notebook LM stand out are these specialized sources here under studio to help you dive deeper into the content and to understand it better, including things like generating an audio overview, generating an AI podcast. — Today, we're diving headirst into something — which is what first made Notebook LM go viral, and also do video overviews, mind maps, and all sorts of reports. I'll be showing you examples of these all in a bit, and it is really, really cool. As its name suggests, Notebook LM is also a note-taking application. So, it allows you to add a note and include your own notes. And finally, there are sharing features and analytics features which are paid pro features. But like 90% of notebookm is completely free. This primary workflow is already extremely powerful. But if you combine it together with other applications like Google AI studio or Firebase Studio, which are also both free Google products, you can make it even more powerful to build entire workflows and apps. And you don't even need to know how to code. All right. Now you have a good general overview of the setup for Notebook LM. Let's now cover each of these features

in detail. Starting off by adding some sources. I am interested in building a vertical AI agent app or learning languages. And I want notebook LM to help me figure out what I should be building, including things like analyzing industry trends, different pain points, brainstorming and validating different ideas before coming to a four set of features to build for my MVP, my minimal viable product. This is a report from OECD on the trends shaping education 2025. Um, and this is a very reputable report about the education space. So I'm going to add that as a source. I'm also going to add a couple YouTube videos. This is one from Y Combinator about how to build AI agents, how to validate startup ideas. So notebook alum can help me with that as well as an article which is very popular for startup founders. Then I will copy some text which is what I got from a deep research over here from Google Gemini that goes into a deep dive of the competitor analysis of the education space including the core SAS competitors in the space. Later in the video, I'll be going into more detail about how to use other applications like deep research in order to get really good sources. But for now, I just want to show you all the different types of sources that notebook elm can take, including this copied text information. But that's not all. I also want to click the discover button here to search for additional sources that I think will be useful in this task. To get a better understanding of customer pain points, I wrote look at a variety of UGC user generated content sources including Reddit Xora defined painoints and language learning education space. Click submit. And I'm going to add all these Reddit sources, but not this one because I'm more interested in user generated content, not academic perspectives. So I'll click import. Rename them by typing user in the beginning. So I know that these are about users pain points. I'll name these previous ones evaluate because it's for evaluating different startup ideas. And we'll call this one trends because it's about industry trends. I also want to search and add a few more sources on industry trends. Always good to take a look as well on what it comes up with. Okay, this looks legit because it's a study. And we'll add a couple more sources. Moving on to the chat interface. It already gives you a little overview over here. But I do want to dive deeper. Starting off with a better understanding of the industry trends specifically. So, I'm actually going to uncheck everything except for the industry trends and ask it to summarize the industry trends for language learning. Click enter. And it gives us a little summary talking about the language learning app market is experiencing rapid expansion influenced by several key trends, drivers, restraints and opportunities, key market insights and drivers blah blah. It also gives you the sources where it's coming from. So you can actually um very easily double check and click into this as well. This is one of the main functionalities of notebook LM because it's so grounded in the sources that it's being provided. This has much less room for hallucinations. So yeah, key market insights and drivers, market segmentation by type, by application, by language, okay, and by geography. So I want to ask some questions like what about AI first language learning apps versus traditional SAS apps cuz I want to build something that is an AI first like vertical agent um application. Who are the industry leaders here and where are the gaps? So it says in AI language learning app the market growth is largely fueled by advancements in digital education technology. So it's showing that Dualingo for example is introducing AIdriven custom lessons and realtime voice recognition. And you can see that it would actually just tell you that the provided sources do not explicitly differentiate between AI versus traditional SAS apps. So it really is grounded in the sources that you provide. But it does show you all of the different competitors that are in the market right now and gaps in the market where AI could be able to help with. Very interesting. So before we move forward, make sure that you do click save to notes because if you don't do this, all of this is actually going to disappear because notebook has a privacy policy where it doesn't actually save the chat history and it doesn't train on it as well. Okay, cool. Going to do something similar for the user pain points. Summarize the user pain points and we can see some of the key pain points including effectiveness and fluency challenge. Many language learning applications are perceived as failing to lead to true fluency, depth or mastery, motivation, engagement, constant accessibility of traditional methods, fear of mistakes, etc., etc. Also, make sure to save to note here so we don't end up losing that information. So, you should continue doing this and asking more questions and learning more from these sources. But I want to draw your attention now to the studio section where there are also other features to help you understand this content better.

This is one of my favorite ones called the audio overview. So, let's click this and it will generate an AI podcast specifically for the user pain points that we selected. That took a couple of minutes. So, it is ready. — Let's unpack this. Today, we're diving head first into something, well, something many of us have tried or maybe are trying right now — or thinking about trying. Yeah, — exactly. Learning a new language. So, for this deep dive, we've gathered quite a stack of sources. We've got stuff from Reddit, uh, real learners, teachers. — There's some really candid stuff there — and a whole heap of opinions on Dualingo. What was it from Tik Tok, actually? — Ah, Dualingo always sparks a debate, — doesn't it? Just — All right, let's skip ahead a little bit. — People repeatedly pointed out it lacks explanations — on grammar, tenses. — Exactly. Tenses, grammar, and importantly, — you can actually join this conversation as well. King the interactive mode. Hello. So I wanted to talk a little bit more. — Well, hey there. Want to share your thoughts on this? — Yeah. So I want to understand a little bit more what exactly is the primary pain point of using something like dual lane go like what is the singular um issue that people have with it? — That is such a great question to start with and it actually really gets to the core of a lot of the feedback we found. — Yeah, that's really smart to dig into that right away. If we connect this to the bigger picture, the primary pain point with Duolingo based on what we've seen isn't that it's bad per se, — right? It's more about what it isn't designed to do. — Exactly. It excels at things like drilling vocabulary and basic grammar, giving you those consistent snackable lessons, — which is great for getting started. But the singular issue, the one that keeps coming up, is that it doesn't really build conversational fluency or deep understanding of how — how would using something like AI be able to address these pain points. — That is an excellent follow-up question and it really gets to the heart of where edtech is going. — Yeah, that's exactly where we wanted to take the conversation. — So, if the pain point is the lack of conversational fluency and deeper understanding, AI has some fascinating potential there. — The sources really highlighted a few key ways. One of the biggest is enabling natural conversation practice. — Imagine having an AI you can talk to anytime. — A practice buddy, but one that's always available. — Exactly. One that gives immediate feedback on grammar, carings you gently without judgment. — Basically, a patient conversation partner available 24/7 who won't judge you. — This directly addresses that fear of looking. — Isn't that just so cool? The first time that I heard this, I was freaking mindb blown. This is two AI hosts. It's insane, isn't it? So, you can do this. I think it's a really great way of really exploring and diving deeper into all of this information, understanding everything much better. And I want to

show you now my secret pro tip for how I use audio generation to learn things really, really quickly. It's how I keep up with a lot of the AI trends and things that are going on. And I'm going to use another example for this cuz let's learn about something new. But I do want you to put a bookmark on this specific example because we're not just going to end it here. I'm actually going to show you how to build out this AI application for learning languages using a combination of notebook and AI assisted coding tools like Firebase Studio, which is also a Google. But first, let's cover the core features of Notebook LM. All right, here's my pro tip. Are you ready? This is another notebook about social media's impact on youth mental health. And I generated an audio overview. We can take a listen to this. Welcome to the deep dive. We're here to sift through all the noise, pull out the crucial insights, and well, get you properly informed. Today we're diving deep into something that touches almost every family, social media and etc which is really great if you want to dive really into this um and really enjoy this process. But sometimes I just need to learn the information really really quickly and there's like a lot of fluff during these podcasts, right? So what I like to do is actually come here and download this audio and put it into Google AI Studio which is also a free tool. Then I ask it to get a transcript of this podcast and then condense it by removing all of the fluff and changing it to a single person as opposed to two people talking. And then I can download it again and play it at 2x 3x speed and get through all of that information super quick. — The provided text is the growing concern about social media impact on mental health particular. — And that my friends is my super secret tip on how to learn things really quickly. Just listen to this while you're like running around, you know, going outside, hiking, working out, whatever. And actually, did you know that when you're moving around and listening to audio, it helps you concentrate better? Anyways, going back to notebook, I want to show you guys some of the other features that you can use under the studio tab. Um, you can also generate a video overview. So, we

can have a video over here. And let's actually check it out. All right, let's talk about something that's well, it's everywhere, right? Social media, teen mental health, you see the headlines all the time. But we're going to go a little deeper, get past those headlines, and see what's really going on. And it's not just talk. The numbers really back this up. Check this out. The NYC Health Department found that 27% of teens on social media have an anxiety diagnosis. Now, compare that to teens who aren't on social media. That number plummets to just 9%. We're talking three times higher. That's a huge, huge gap. It's not just a feeling. It's something health crisis. So boom, the debate just became a fullon legal battle. And look, this whole thing didn't just happen overnight. It's been building for years. You can trace it back. — Need I say more? Crazy, right? Oh my god, it's crazy. And the graphics that are being generated, they are in fact accurate to what is being represented in the sources as well. Oh my god. Like this is such a game changer. also generate a mind map where it's a great way to visualize this information under social media and impact you know you can look at this and then you can actually click in to these different categories as well. So impact on youth mental health adolescent addressing the issue and emotional regulation you can click into all of these. So it's a really great way of like visualizing how the data flows together and then in the chat interface it would explain. You can of course also download the mind map looks like this and you can know throw it on a slide or something if you're making a presentation about it. And speaking of

presentations you can also come here under reports and generate something like a briefing doc very official looking briefing document that you can send to people as an executive summary a study guide. This is pretty similar to the briefing doc in terms of the content that's being displayed. But it also has things like a quiz where it would ask you to answer each of these questions in two or three sentences. So this will help you learn things more deeply and it has the answer key as well. Some essay format questions and some glossery of key terms. Something else that you can do is that say you actually want to study this information, you can click convert to source and you can ask a specific questions for the study guide. out like for example extract three quiz questions in the study guide. Yeah. And it says like here are three quiz questions extracted from the study guide. Uh say describe two key characteristics of the adolescent brain that makes it particularly susceptible to the influence of social media. So um I can say like validate if my answer is correct with the answer key is the answer for two key characteristics. I actually don't know what it is. I'm just going to like guess here. Uh maybe it's still developing uh decision-m capabilities to differentiate what is real or false. Um is susceptible to emotional deregulation. I don't know. See that's correct. Uh it does not fully allow the specific key characteristic pride in answer guide. Okay, my bad. Rapid growing and is highly plastic. Uh, and yeah, okay. Well, seems like I need to study more on this subject. But yeah, you can see how this can be extremely powerful if you are actually learning things and want to test yourself. Man, if I had notebook when I was still in college, I really think I just could have like cut my study time down by 80% probably. So jealous of you guys who are still in school. The timeline feature under reports is also quite useful. If for some reason you're interested in learning about the complex world of bananas, you can generate a timeline of the banana development. Very fascinating. Prehistory ancient time of banana all the way to the modern banana. Wow. Amazing. Another little pro tip, you can go to Gemini, click canvas, copy this detail timeline, and write create an interactive visualization. Wow, you have an interactive web application dashboard about the banana timeline. Amazing. Gemini doesn't have the best like formatting. It's not the most visually appealing one. So, if you do have Claude, copy this. Go to Claude and type create and interactive of this banana timeline. Yay! Amazing. The great banana timeline. Wow. From ancient domestication to modern crisis. 9,000 years of banana history. Wow, so cool. So many banana activities. So, this is a notebook about my AI agents boot camp that we run. The FAQs feature is also quite handy. So, this is the Lonely Octopus AI agent boot camp, um, which looks like this. So, what is quite useful is that you can generate some FAQs that you can put onto your website.

We've already seen the add notes little button show up a few times now, but I really wanted to emphasize how powerful this button actually is. So, here is a midterm performance review for Bobby Adams, who is a product manager. We're going to paste in some other people's feedback for Bobby as well. And we are actually going to generate notes um as we're going through some of this. So, Laya is a note-taking app. So maybe you know you're looking through Bobby's report and then you're generating notes like needs to improve communication skills um is improving technical skill set and completed goals for Q2 whatever it is that you want to do like OKRs are completed feedback from manager is relative and consider for promotion. So yeah, like as you're going through um some of these sources and learning more about it, you can actually add these notes like evaluate, we can hear in the chat as well, evaluate Bobby Adam's performance regarding signal sync B2. Uh so we're seeing ah like great, you know, all of this is great as well. So you can save this as a note. It's generating more information. So what was a key accomplishment? Save that to notes. We can generate a timeline of Bobby's. So you see that generate cast characters, timeline of main events. Save that to notes too. And then what you can do is so you convert everything to source. So now there's additional sources that we can draw from. Then you can ask it like should we consider Bobby promotion based upon all that information. I hope you can kind of tell like this um loop between adding different things like summarizing different things together and then different user input as well. Converting that back into a source. There's like this loop between adding notes and then putting it back into source. um that can really help you refine and iterate upon whatever it is that you're trying to understand and dive deeper into. Yes. So, we should consider Bobby Adam promotion. If you're a developer and interested in building apps 10 times faster, I highly recommend that you check out Augment Code. It's built for real engineering work, including debugging, writing tests, refactoring, and navigating complex systems. Augments Context Engine feeds models exactly what they need from your codebase and can handle code bases with 10 million plus lines of code and over 10,000 files. So no matter how big or old that your app is, you can still ship incredibly fast with Augment. You can even launch cloud agents to refactor or fix tests while your laptop is closed. It runs in your IDE including VS Code, Jet Brains, Vim, and Cursor. And it's secure. Augment is ISO and SOCK 2 certified. And there's no training on customer code ever. You can try it out 7 days for free at the link in the description. Thank you so much Augment Code for sponsoring this portion of the video. Now back to the video. All right, before I show you how to combine Notebook LM with other applications to make it even more powerful, I just want

to briefly cover the additional features that you can get if you do have the paid version of Notebook LM. As I said earlier, you really already get so much just from the free version alone. But there are like a few perks. So there's three different levels. There's the free tier, DC pro tier, and then there's the enterprise tier. And some of the things that you do get on the pro tier is that here you get 300 sources. Uh while on the free tier you only get 50 different sources that you can add. On the pro tier you can also have a configure chat section where you can define your conversational style like change that a little bit and also change your response length. You can customize these a little bit more. You can also customize these different outputs a little bit more as well. like for example on the audio overview defining what the length of the um audio is and what things that the AI host should focus on. Honestly, these are nice to have, but I find that it doesn't really make too big of a difference, I would say. Um yeah, I don't think it really makes too big of a difference. Anyways, you do also have the share tab over here. So, this is when you can add other people um into this notebook and you can share them with them. You can also add a little welcome note like for example like hello check out you know something like that and you can give a different access like between full notebook and chat only and copy link and just paste the link to them. You also get analytics. Um so here I don't have any analytics because you need to share with at least four other users to see what the uh chat activity is but you would be able to see analytics across different users as well. And finally, there is enterprise level as well where you pretty much get all these features, but you just get more security like privacy and security guarantees from it. So, in terms of the actual pricing models, it seems like you don't really purchase it um by itself. You really just purchase it based upon the package of which Google product that you have. So, in my case, I get the pro um version because I have Google Workspace for business. Okay, let's now talk about Notebook LM in combination with other applications. One of my favorite combinations is

between Notebook LM and deep research. So using deep research, I would generate something that is of deep dive into a specific topic and then I would add that as a source into Notebook LM. For example, looking at very specific market trends for electric vehicles in Malaysia between a time of 2020 to 2025. I would just add that as a source in addition to all the other sources because after all you know with all the different bells and whistles that notebook LM has really the key thing like everything that is grounded with is the sources. So if you are able to curate better sources for notebook LM the output that you're going to get is also going to be much better and deep research is the number one way that I use in order to generate highquality sources. We also really like

the combination of notebook LM plus cla which I think I showed you already previously. Um whenever I have something and I want to change that into a dashboard or a visualization I just throw it into claude and have it generate a dashboard. You can also do this like using Gemini or chatbt as well but I find that with claude it comes up with the best dashboards. Notebook plus

manis is also a really powerful combination because you can use notebook to distill down information and then use manis to actually implement it. For example generating slide decks. Notebook LM is really good at generating the content of the slide deck and then you can throw it into Madness to actually create the slide decks yourself. Madness is also great if you're implementing something like a design guide that you generated from Notebook LM and you want to actually implement that into your landing page. Now, finally, going back to that bookmark, remember we were doing the research for building an AI app for language learning.

So what we want to do now after exploring more into the content that's in these sources is to distill everything down into a set of features to create something called a product requirements document or what is common these days called a product requirements prompt that we could then put into an AI assisted coding applications something like firebase or lovable bold or like cloud code to actually build out the first version of that product. You with me? All right. So what we're going to do now is we're actually going to distill down this information and combine these sources together. So the ones that are for evaluating a startup for example, I'm going to type here summarize the ways to evaluate what is considered a good AI app idea. So it has this and what I'm going to do is save this to the note and I'm going to convert this to a source. Then I'm going to do the same thing for the trends part to summarize the trends specific to online learning u for language learning. Save that to note as well and we'll add that as a source. And finally select all of the user sources. Summarize the user pain points for online language learning. Now I'm going to select these summarized sources and write using these selected sources outline the key features for an AI agent app. So I do want it to be specifically an AI agent. And if you're not really sure what I mean by the difference between that, like what it actually means to be an agent, um I'm not going to go into too much detail here, but you can check out this video over here where I explain specifically what makes an AI agent. But yeah, I do want this to be like a vertical AI agent application specifically for language learning. So moment of truth here, we're going to see what are the key features that would be required. See, so a good AI agent app for language learning should incorporate several key features. All right. So, real-time conversational practice, role-play scenario, 247 availability, safe environment, incident detail feedback and correction, including comprehensive error analysis, explanation of mistakes, personalized reporting, hyperpersonalization, and adaptive learning path, dynamic curriculum, blah blah. Okay, there's a lot going on here. So what I'm going to say is So I'm only going to be building an MVP minimable viable product two core features that will be the most competitive and suitable for an AI agent. So it says here it would be real-time conversational practice and instant detailed feedback and correction. That seems to be what we're going to be building. And it has all these sources here as well. All right, cool. Next, we are actually going to jump into chat GPT or Gemini if you want. Doesn't actually matter which one. And we're going to input. This is a prompt that's going to guide us through the process of thinking even more deeply about the exact application that we want to be building. And we want to do this step before we jump into Firebase Studio, for example, to actually build out this application. Because the more clearly you think through what it is that you want, the more details that you have and like what text stack you, what the vibes are that you're going for, what is the customer experience, what is the user journey feel like. The more you think through these things, the better your end result is going to be. So the first question to ask is, what are you building? Can you give me a pitch? And this is where I am actually going to go back to Notebook LM and copy what it is that we just said we were going to build. Oh, and by the way, um I will be putting this product requirements prompt in the description below. So you can just copy paste that if you want to build it yourself. Anyways, so we're going to answer the rest of these questions. So what's it for? Who are your users? So I want to say like beginner to intermediate languages start with English. This is the easiest there needs. If for example you don't know like you want to have more detail you can also keep going back to notebook LM here and then ask it the questions here. All right. It's you know there's a lot of information here but it's okay. It's AI. It can take it. So what's the main user flow? Can ask that as well. What does the main user flow look like? So yeah, we can copy that. It's an art and a science here. You know, sometimes you want to get it from notebook. Sometimes you just want to use your own brain a little bit as well. So what are the must have features in your MVP? So here's a quick checklist. So for now I'm just going to write user O voice input with speech recognition real time AI conversation agent feedback system memory/personalization and push notifications. All right. Now we will copy this. Go into Firebase Studio and copy this and actually build it. I'm not going to show you the full details of me actually building and iterating through all of this entire process because I actually made a full video on Firebase Studio which I'll link over here um that goes through the process of building an entire app. which is really similar to what I did in order to end up with this application. — Hi there. Let's talk about food. What's on your mind? — I like potato. Eating potato. — Potatoes are great. Do you have a favorite way to prepare them? — I like to eat raw potato. Raw potato? That's interesting. I've never tried it that way. Is it crunchy? Great effort. Keep practicing. It seems like you repeated potato in your sentence. To make it flow better, you could say, "I like eating potatoes. " — Yay. Isn't that really, really cool? We literally just went from the very beginning to the ideation phase, analysis, research, all these different things to an actual functioning prototype. Pretty cool, huh? Yeah. So, in this example, I use Firebase Studio because it's free. It's also because it seems like we're sticking mostly to like Google products since Notebook LM is a Google product. But really, you can also use other tools as well. Uh you can have like you can use Levelable. I also made a video that goes through how to build um applications using Levelable, which I will link over here. And if you are a technical person and you're comfortable with code, you can also start building it out using claude code which I do have a video about here as well. So yeah. Okay. Thank you so much for watching until the end of this video. I really hope this was helpful for you in learning more about Notebook LM and just realizing how crazy powerful it is, right? Uh so as promised, here is a

little assessment. Please answer these questions and put them in the comments so you can actually retain all the information that we covered today. Thank you so much and I will see you guys in the next video or live stream.