Learn 80% of NotebookLM in Under 13 Minutes!

here's a rule of thumb for using notebook LM if your use case matches the following three criteria notebook LM will perform better than other AI tools first you have a very low tolerance for hallucination second you're working with information scattered across different locations different formats like documents and slides and or across different mediums text video and audio and third you want a quick and reliable way to transform all that fragment information into a cohesive and meaningful output in the next 15 minutes I'll go over key features real world use cases and pro tips very few

people know about let's get started right off the bat it's a bit overwhelming for most users to see this when creating their first notebook there's a lot going on so I recommend pressing escape clicking the logo in the top left corner to go to the notebook LM homepage and now that we're oriented we want to bookmark this for easy reference uh in the future change to list view that's just a personal preference of mine and sort by title now let's create a new notebook and here here I'm first going to press escape again because I

want to first name this notebook Health reports 2 you'll see why in a bit and click the plus icon here to start uploading sources here I'm just going to upload my three most recent annual Health checkup reports along with a pdf version of tools of Titans by Tim Ferris and while all that's loading I'm going to add another source YouTube video and I am first going to add a video on the topic of uric acid I promise this will make sense in a little bit one more Source YouTube video and this is going to be

a video by Andrew huberman on the topic of fasting once all sources have been uploaded and processed we can now click into individual sources I'll choose my most recent Health Report um and I'm going to blur this to not overshare but ladies just know that I'm at Peak physical health and under Source guide we see that notebook LM has produced a concise summary of a dense medical report I would definitely not have read word for word on the right clicking into one of the key topics like abnormal results here actually prompts notebook LM to expand

on that topic based on all the selected sources on the left hand side even though the key topic was just from One Source right so that's the first important thing to keep in mind everything in this chat interface takes into account all selected sources meaning if we want notebook LM to ignore a source we need to First deselect it from The Source list by the way don't worry about me the only abnormal result from my health reports is my absolutely huge capacity to make dad jokes The Notebook guide feature down here is like a quick

start guide for beginners There's a summary of all the sources added to the notebook pre-created templates like FAQs and briefing docs that are very situational I'll give examples later and suggested questions here to help users get started and don't worry we'll also go over o audio overviews today all right we're going to start interacting with the notebook but since the answer take a while to generate I'll switch over to the actual Health reports notebook I've been using first I asked for the top 10 Health Trends based on my last three reports a pretty time-consuming task

even for doctors right but just after just a few seconds notebook LM just gives me a list of 10 observations one of which is a fact that I've had elevated uric acid levels over the last 3 years uh which is unfortunately true because I eat a lot of red meat and because I added a video on uric acid as a source I can now ask what are the top three things I can do to load my uric acid levels I'm told I can do these three things okay but just to be safe what exactly did

the video say clicking the inline citation brings up the video transcript and Dr Burke says uh potassium citrate can knock out uric acid pretty fast okay nice now pay attention to this next part because I got burned by this whenever you see a good output you want to refer back to click save to note if you don't do this the output disappears the next time you reload the notebook according to Google this happens because notebook LM is not trained on any of the data that we upload including our conversations meaning if we close a chat

without saving the note all that data disappears next I fast for 36 hours every week and since both the Hub video and tools of Titans talk about fasting I can ask hey does anything from my health reports suggest I shouldn't fast for 36 hours every week and again notebook Alm does a great job sharing context telling me my blood work is normal and I can continue fasting with no issues without notebook LM yes I can obviously go through the exact same information and draw my own conclusions but that's very manual very timeconsuming and I might

miss key information in contrast notebook LM is able to quickly and efficiently reference multiple sources connect the relevant dots and produce a good enough output in significantly less time finally I'm going to throw a curveball and prompt this notebook with what do the sources say about in inerting D Lo weeks into my workout routine and as expected notebook Elm says None of the sources say anything about D Lo weeks which is true but the output does mention related topics this actually illustrates a very important Point even though notbook LM and Google Gemini might use the

same underlying model notebook LM is fine-tuned to hallucinate less but as a result is also less creative whereas Google Gemini while prone to Hallucination is optim ized for Speed and creativity wrapping up this example not only can we manually add a note but we can also select multiple notes or just simply select all and choose to convert all these notes to a standalone Source Pro tip once that new source is created we can click into it select all the text here copy and paste to use somewhere else by the way if you want to cut

through all the hype and master essential AI skills you might want to check out my free AI toolkit I'll leave a link down below use case number one is something I call Focus knowledge retrieval and starting off with a simple example I have a notebook titled equipment manuals where I've added all the user manuals for all my filming equipment this allows me to ask questions like Hey how do I update the firmware for this monitor or how do I enable this one specific setting in my camera and notebook LM is able to retrieve that relevant

information from my sources to replicate this you can just Google the product you have followed by user manual type PDF side note this is also how I found the pdf version of tools of Titans and even if you can't find a pdf version of the user manual remember you can add the website directly as a source Pro tip there are some websites that actively block notebook LM from adding them as sources but we can easily get around this by adding another source um and just copy and pasting the text from that website right here moving

on to another example I have a tax and accounting notebook for my business where I've added uh documentations like tax codes from the government and audit reports from my accounts in preparation for tax season I can ask this notebook questions like what are my tax obligations last year what are some notable Trends in my financial statements and very personalized questions like hey do I qualify for offshore tax exemption since I travel a lot last example for this use case since I interview candidates as part of my full-time job I have a recruiting notebook this is

just an example where I add sources like guidelines from HR performance rubrics question Banks uh candidate rums and interview notes I can now prepare for these interviews more effectively by asking questions like hey what are the key achievements and relevant skills of this candidate based on their submitted documents or based on what we look for in product marketing managers at this level give me 10 questions to ask this candidate and what are the key strengths and areas for improvement for this candidate based on the interview notes Pro tip if you try this yourself remember to

only select the documents from the candidate you're currently interviewing or else notbook LM might incorporate information from other candidates as well next up we have the project context engine use case put simply I have a notebook for each project I'm responsible for at work and I add meeting notes project plans and documents from similar projects as sources side note project and program managers benefit massively from notebook LM because by definition their job requires them to one work with information scattered across different locations and two synthesize that information in an easy to digest format and notebook

LM is designed to do exactly that remember the suggested templates found under notebook guide well here we can take that a step further to create perhaps a high level briefing document for senior leaders um a campaign timeline to make it easy for us to create a slide to visualize those key milestones and even an FAQ document for colleagues who are unfamiliar with the project Pro tip uploading meeting transcripts from Zoom or Google meet unlocks highly accurate answers to questions like hey what are my outstanding tasks or um write a meeting recap email based on this

one specific meeting and since I've shared recap documents from previous projects I can ask notbook LM to identify learnings and strategies I can incorpor it in my next campaign Pro tip if you're struggling to get started with notebook LM I recommend uploading files you know are related in some way and then trying the suggested questions down here they're surprisingly helpful also if you just happen to be a Google workspace user you might want to join my Weekly Newsletter to receive an insanely actionable tip every week link down below next up I work in Tech and

I'm obviously interested in AI but staying current is tough there's a lot to read and honestly it's hard to connect the dots sometimes like for example what are the implications of this big meta announcement for the rest of an industry my solution was to create an earnings analysis notebook with earnings reports from tech companies along with articles from Tech analysts that have compiled in a Google Docs format you'll see why that's important in a bit now with notebook LM doing the heavy lifting I can ask very targeted questions such as what is Google's monetization strategy

with regards to Ai and I get this structured list and I can also ask broader questions like how do AI strategies differ for Google meta Amazon and apple and it's actually amazing how notebook LM first shares a one- sentence catchy summary Google enhance expand and explore meta AI for everything everywhere before expanding on their respective strategies and because I enjoy listening to podcasts during commutes and workouts I can ask notebook LM to generate a personalized podcast Episode by clicking customize audio overview and providing Specific Instructions like focus on how earnings from one company affect its

competitors and assume the listener has zero technical background it's like they're taking a page from meta's book right instead of trying to invent some whole new AI thing they're making their existing products better more powerful and more profitable yeah it shows that AI isn't always about replacing everything sometimes it's about improving what we already have and meta seems to get that Pro tip when we add a Google doc or slide as a source we can click in and then we can click here to resync the file after after changes are made so that we're always

drawing from the most upto-date information a few final thoughts I want to leave you with first although notebook LM rarely hallucinates it's not optimized for creativity so I found myself taking notebook lm's outputs and using gemini or claw to produce that final deliverable second the amount of information notebook LM can absorb is massive around 25 million words per notebook and that's compared to around 500,000 words for Gemini 100,000 for claw and 64,000 for Chach BT and even though we're capped at 20 sources per notebook we can simply combine multiple documents into one file and third

this might be an obvious point but with a tool like notebook LM the quality of the sources becomes extremely important using articles from wellestablished Publications is going to give us much better outputs than lowquality clickbaity blog posts I have a lot more use cases to share so let me know if you want more content like this in the meantime check out my AI playlist and as usual have a great one