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