The 5 Hidden Rules Behind Successful AI Products | Chris Pedregal (Granola)

I think the number one lesson is you

shouldn't work on any problems that

aren't going to be problems in the short

to medium term there are problems in

your product that might get solved by

the next model drop and then there are

other problems that are always going to

be a problem you know things that are

always going to be worthwhile no matter

how smart the models get and I think

that the easiest mistake to make is to

focus on the thing that users are

screaming about but that the next

version of the LMS will we'll just do

for you now I think as a product person

is like you talk to your users and they

complain about something like hey I

can't use granola for meetings that are

over 30 minutes right and like

everything inside of you saying that's

ridiculous grola should work for

meetings that are more than 30 minutes

this has got to be our number one

priority but something that seems like

it's really simple all of a sudden to do

well does take a bunch of time and then

like all that time would have been

wasted because the next version of of

the model had a large context window we

could just stick the whole meeting in

there and and I think this is something

that's like it's just so easy to get

this wrong also because it's hard to

predict the future right which should

you be building and investing in now so

that you know 12 months from now when

LMS can do that at a reasonable cost

Point your your product will be

fantastic all right well welcome

everyone my guest today is Chris pedig

Chris is the CEO of granola which I

think is the best AI notepad for me

meetings and I'm excited to chat with

him about his hard one lessons from

building one of the most successful and

retentive AI apps in the market so

welcome Chris thank you so much Peter

thank you for having me yeah all right

man so let's start with some spicy

Tes yeah so so you know you being a

Founder twice already right and you have

also me a formal Google PM twice so I

had to start this question like what do

you wish Google and other big company

PMS did more of you know now that you

built these successful startups what

they did more of oh you have to give me

you have to give me more context there

what do you have in mind well I mean

like how is it different being a startup

founder and being a Google pm and what

what do you wish the Google PMS or like

any other big company PM like you you

being one like what do you wish that

they did more of and what they wish they

did less of to be more efficient yeah

yeah I mean I think the reality is that

there are so many constraints in place

when you're a PM at a large company it's

just like a fundamentally it's like a

different sport you know what I mean

like like if I don't know if being a

Founder just choose a random sport is

like American football and like being a

PM coul like uh soccer you know what I

mean they're like totally you can't play

one game with the strategy or the rules

of the other game I think what I found

at Google when I was a PM is that

there's so many different types of work

that a PM does right there's like

project management type work there's

like planning there's like being a

leader there's and then part of that is

also you know product design or how

should the product work and what should

it do and my experience at Google was

that was just an extremely small

percentage of your time and that's just

the reality because there are all these

demands on your time all these

constraints all these meetings you have

to go to that there was really very

little time at least for me to do the

deep thinking on actual like product

work I I don't you can't it's just the

nature of the job I think I mean you

have you you probably have a lot of

thoughts on this Peter yeah it's almost

like you're kind of forced to do the

thinking in meetings with other people

which I guess has some benefits MH but

also just like a lot of time wasted just

like preparing like communicating

upwards like having all the meetings and

presentations and stuff right like I I

totally like I like to protect my craft

time like I I actually decline meetings

is probably not good for my career but

yeah I'm like you know I need to think

through the problem I I can't really

meet with you right now yeah I mean like

I I remember you know at Google my day

was just back toback with meetings right

so that meant that if I was actually

going to do deep product thinking I'd

have to do it on the weekends or in the

evenings you know or wake up super to do

it and and that's just the reality but

it it is kind of sad if you're a PM and

you have to like do the actual product

work on weekends you know but I think

that's just the reality of a larger or

and maybe that's why you started

granola like can you walk us through

after you left Google like why you how

did you start grola yeah so I joined

Google after my last startup Socratic

was acquired and I was I ran Socratic

for five years so I I had another

co-founder shance and I and and we ran

for 5 years when we required and I was

pretty burnt out by the time the

acquisition happened like I was you know

5 years is a long time on any project

and you know startups are intense and

when that happened I think my son was

six months old at the time so I was also

learning that whole set of skills or try

figuring out how to be a parent so I was

pretty I was pretty thankful to post-

acquisition to just have a bit more

breather a breathing room but in the

back of my mind I knew I'd probably do a

startup again and after a year I was

just I was kind of counting down that

days a little bit in my mind I told it

would make sense for me to do that again

so I ended up quitting Google in I think

March of 2022 and I knew I wanted to do

a startup I knew like I by that point I

had moved to London so I knew I wanted

to do it in London I knew I wanted to do

a startup and I didn't have an idea and

I didn't have a co-founder so I started

playing around with stuff and almost

instantly I fell in love with g PT 3 at

the time like when I had been at Google

I hadn't had the time to play with it

properly so I'd kind of been like ah I

don't know about this thing and once I

had some free time I started playing

with it and it just I was like it blew

my mind I was like this is I was like

this is different from other stuff that

I've seen and I basically spent a year

building prototypes to get a feel for

the technology because the interesting

thing about LMS I think we've a lot of

us in Tech like normalized to it but

like the first time you interact with

one Le less so now cuz they're smarter

but like back then especially they'd be

like really good at something that maybe

like only a college level you know

college student level educated person

could do and really crap at stuff that

like my 5-year-old could do you know and

that was like a really confusing thing

and yeah and then ended up meeting my

co-founder Sam exploring a bunch of

different ideas and and then settled on

what ultimately became

granola and so why did you decide to

tackle the meeting problem or was that I

I guess we entered it kind of

reluctantly just because they so many

different products out there built for

the meeting space what I guess two

things kind of convinced us well I'll

tell you the great things about meetings

ready the great things about meetings

are one people have a lot of them and

there are they're scheduled on a

calendar so like sending notifications

to use your product when you have a

meeting actually feels helpful and not

annoying like most products if like

granola will like send like I don't know

like six or seven push notifications a

day for a user if they have six or

meetings that we're going make sense so

it's it's a really nice user need to

build a habit around because they're

like these natural hooks so that's one

two llms I think have a few like super

power applications right and I think we

you know one I think is cenation two I

think is like search right and another

thing that they're incredible at is

taking something super long and

unwieldly like a transcript and turning

it into something useful so I think that

was wow there really is so much value

here and then man we tried all these

different ideas and we put them in front

of people and no one people are just not

interested in all of them and their

lives their eyes lit up when we showed

them a thing of like like first version

of granola because they were like I hate

taking notes you know so it was just a

combination of things we like okay I

think alms can really I think there's a

product here to be built that really is

going to be helpful to people and I

think if we build it you know there's a

path here where we can get people to use

it and keep using it but it was like it

was a little scary because there's so

many people doing meeting relating stuff

yeah that that that's what I thinking

too right so like there's you know like

zoom and Google meet I think both offer

AI Meeting those now but I think people

just love using granola like I don't

know if you can share like how many

people come back like after first week

but like what makes people love Yeah

much well yeah it's like 70 like

basically if you use granola like 70% of

people come back the next week and then

they kind of stick around why what makes

why do they like it so much was that the

question or like what what's different

from the big ones I think I'd say over

the overarching reason is that it's

simple and convenient to use I I I

really think that's like the main one

there's not a there's not a bot that

joins your meeting you don't have to

open a special UI it's like a it's an

app on your computer right that looks

like a notepad it looks like Apple notes

and it kind of you can open it up and

use it if you want and if you don't you

do is use it you just close it and you

know you're really in control of it and

I think it kind of

integrates seamlessly into people's

lives like I think that's the main

reason I think it it sound when you say

it that way it sounds kind of silly it

took a lot of work to get to that like

we had to build a ton of things and cut

them out and we had to like figure out

like what is at the core of the product

right and and there's some insights I

can talk about there but I think

ultimately it's because it's a thing

that doesn't get in your way and that

people like spending time in okay so let

let's think a little bit more but let's

talk about it from the framing of your

top lessons from building AI products

right like you just publish this great

blog post so maybe why don't you start

by just listing what the lessons are

like what are your top four yeah sure

and I might mess them up for memory but

um I guess like the number one lesson I

think so basic I think what like the

defining these are hard earned lessons

so these are like mistakes we we made

and kind of learned from I think the

defining characteristic of building an

AI is that the underlying technology the

models are evolving so quickly

that it's a and that affects the entire

environment so I think the number one

lesson is you shouldn't work on any

problems that aren't going to be

problems in the short to medium term and

and by that basically there's there are

problems in your product right that

might get solved by the next model Drop

Like GPT five or six or what have you

and then there are other problems that

are always going to be a problem you

know things that are always going to be

worthwhile no matter how smart the

models get and I think the the easiest

mistake to make is to focus on the thing

that users are screaming about but that

the next version of the LMS will will'll

just do for you naturally and we have a

bunch of examples there language support

is one like context window like you can

only use granola on like short meetings

at first so like that's one big lesson

do do you want me to go to the next one

Peter do you want want talk no let's go

a little bit deeper in that one so okay

so like as an example you mean like like

users are like why doesn't work for

longer meetings but your point is like

you know the next model will have a

bigger context wayd though so it will

work yeah exactly and like so and what's

weird about that I think as a product

person is like you talk to your users

and they're they complain about

something like hey I can't use granola

for meetings that are over 30 minutes

right and like every everything inside

of you is saying that's ridiculous grola

should work for meetings that are more

than 30 minutes this has got to be our

number one priority but you know the way

to do that at that time it like sounds

easy but actually it's like okay now you

need to chunk up like the meeting into

several chunks and summarize different

chunks right that but now you need to

reconcile the summaries right and

something that seems like it's really

simple all of a sudden to do well does

take a bunch of time and then yeah all

that time would have been wasted because

the next version of of the model had a

large context window we could just stick

the whole meeting in there and and I

think this is something that's like it's

just so easy to get this wrong also

because it's hard to predict the future

right like like what like llms are I

mean I still think of them as primarily

text based right with that's wrong right

LMS are going to take any kind of input

then you're already seeing that with I

mean obviously voice but photos and

video soon and like when an L1 can take

all that context in real time like

what's that mean for products what

should you be building and investing in

now so that you know 12 months from now

when LMS can do that at a reasonable

cost Point your you know your product

will be fantastic well what's something

that you mentioned that like your

5-year-old can do that an LM can't do

like something that actually is

important to solve now yeah well I mean

that was so that was a reference to like

when I started like two years ago was

like basic like math you I mean like

like basic math stuff was like really

weird or just also just like you know

like the classic like positional stuff

you know what I mean it's like Sy go on

top of this thing or whatever like like

they've gotten a lot smarter now but

that was the kind of stuff I had in mind

got it in terms of predicting what Al

can do in the future like I I guess you

can look at a few broad trends like

hopefully the cost of inference will

come down it's going to become

multimodal bigger context maybe they

they can do more work like more agent

flows as opposed to you prompting them

all the time

those are kind of the big trends right

yeah yeah exactly I think there's two

things you can do I think the simple

thing to do is basically look at what is

the what can the most cuttingedge

expensive model do today right and then

just assume that will be cheap and

accessible in not too much time and

build for that and I think everyone

should be doing that right so I think we

should be you should be everyone should

be preparing for a world where you can

feed like like live video into an llm

and that's like doable and cost

effective I think if you try to predict

past that it gets really tough right I

think it gets that gets into like sci-fi

territory if you're like okay like what

does you know like what will the next

generation of like Cutting Edge models

do I think that's a lot harder to

imagine got it let's go to your uh next

principle like okay you have this

principle called go narrow and go deep

and I I love that cuz it's about like

focus and prioritization so we we talk a

little bit more about that too yeah I I

think obviously General advice is really

hard so this is all grounded my

experience with granola but like general

purpose tools like Claude and chbt are

really good you know like surprisingly

good at a whole swath of tasks so I

think if you are building a startup you

need to be 10x better than that right at

least 5x better than that and I think

the only way you can really do that is

by choosing a narrow use case a narrow

path and trying to make that experience

really great and I think when you do

that something that's interesting that

comes out is that a lot of the work that

you need to do to make that narrow

experience really great sometimes has

nothing to do with AI sometimes a lot

around like the rapper like like

examples for us for for granola would be

we spend a ton of time so basically you

have to do people might have headphones

on they might not have headphones on

right if you don't have headphones on

the audio stream from the speakers goes

into the microphone phone so you have to

do this Echo cancellation thing and

basically like long story short like to

make that really seamless we had to like

roll our own Echo cancellation which

sounds like super silly that we'd have

to do that in like 2024 but we did and

that took a bunch of time and effort and

has nothing to do with any like the core

like note writing of the product but it

had all everything to do with granola

just being the seamless thing you don't

have to think about and I think that's

like when you go narrow you like there's

all this kind of like parallel work that

needs to be done or like that you can do

to make that core experience great how

did you approach this with did you like

map out the customer Journey for like

doing a meeting and then you kind of

like figured out the little friction

points along the way or um yeah yeah uh

we

did but we so we were in we had a closed

like a closed beta for we were in closed

beta for a year and we basically had a

small by the end it was like 100 people

that we were building with but we

started off with three and and it became

really obvious once you gave it to real

people that there are like some basic

things that you need to that you need to

do for them to trust you to take notes

for them I think it was just a lot of

like giving it to people and spending a

bunch of time getting feedback from them

and not mapping too far into the future

I think it's very interesting because

with non- a products you can you know

design something you can ship it get

feedback right but with this stuff like

the the output is like non-deterministic

so it's almost like it's almost like not

like is this good or bad it's almost

like is it good 80% of the time or like

you know there's like a threshold where

you think it's actually good enough to

to ship like has that been your

experience all right yeah I mean I think

what it makes it just it makes it harder

I find to get a handle on what the

actual user like the quality of your

user experience is right because it's

deterministic and for better for worse

it's meant we've relied more on Direct

user contact rather than quantitative

metrics on user experience quality like

I feel like you can on other more

traditional flows you might be like okay

what percentage people made it through

this flow and you know is that good or

bad or what not whereas here it's a lot

harder to actually measure that so we

end up just spending a lot of time

talking to people and let's get a sneak

peek into how this thing works so it's

it's not just like taking someone's like

transcription like you know using some

prompt to summarize it right it's

actually more than that like can you

talk a little more about that or yeah

sure so like I guess I mean I can tell

you the thinking I can to tell you how

it works now I might leave some details

out I think what we figured out is that

when we started off while we started off

like writing the prompts for for granola

the prompts were very instruction based

it was like okay if this is the case

like write notes like this or if this is

the case include this and don't do that

and what what we kind of quickly figured

out is that the reality of the world is

that it's really nuanced and complex and

these kind of like binary instructions

map very poorly to that world because

it's okay it's like you know it's like

okay if there's this type of detail like

this type of information is important to

add right don't make the notes too long

and it's like okay now how the heck do I

know which of those two are more

important right if I have these

conflicting instructions so what we

found like our mental model shifted uh

to a different one it's basically think

of the model like the llm as an intern

on their first day at work which is

basically a smart person right who has

no idea on how you do things and doesn't

have any context on on what you do and

give that intern all the context they

need to do a good job so a lot of the

the work that we put into granola is

basically like how do we give you the

intern the right context to do a great

job in this meeting so those are things

like who are you meeting with right like

who are they what companies do they work

for what jobs do they have for a meeting

like this with these type of people and

these types of roles like what are they

probably optimizing for right like

what's like what's going to get them

promoted like that you know like if you

start thinking about that way and then

you think about who you are then you can

pull in a bunch of contexts and kind of

give the model a lot of Direction on

what would actually be valuable to you

when you read those notes okay so that's

like uh I think your third principle

like context is King right yeah but

that's actually very interesting so your

context is not like oh you got to list

like three action items and like you

know five takeaways it's more like like

it's more like teach him some general

principles about how meting not work

yeah it's general principles but it can

be specific to the people so so like a

good example there is there are let's

take I don't know like let's take in

like VCS like investors right like they

do a lot of startup pitches right there

are a set of things that are really

important to investors to make sure that

their notes capture when a startup

pitches them right and that's very kind

of like specific to that use case so we

don't like actually tell you say exactly

hey write these things but we do

articulate okay like you need to make an

investment decision right these are the

types of things that are important when

you're making an investment decision

like write the notes to match so it it's

basically you have to give it the

context of what's valuable for those

people but you don't have to be too

prescriptive on specifically what to

write got it got it and in in doing this

what's a day in a life like is it just

like you're like constantly up to your

prompt and or maybe you're using

retrieval or something and then do you

have like an eval process going or you

just kind of relying on user feedback

yeah we have a very to be perfectly

transparent we have a very manual evil

process

going that we're you know we're

systematizing I think that you can

having automated eval or like we're

actually taking the same approach to our

eval process as we do with granola which

is we want our eval framework to make it

much easier and faster for humans to

eval things as opposed to fully automate

the human and the reason for that is

like there's just so much Nuance there's

so so so much Nuance in whether like

notes are important because like notes

are basically it it's kind of like it's

like stack ranking of like all this

information what's the most important

information for you that's like an

extremely hard problem so yeah so our

internal tooling is is very human-

centered and aiming at making our humans

faster yeah I I always have like some

doubts about those like synthetic eval

stuff or like you know they get the

other LM to give the LM a score like who

knows if the score is like made up or

got this stuff yeah so that goes into

well okay I want to finish covering your

principles so you have another principle

called your cost is my opportunity yeah

can you talk about that yeah so like as

I was like you know since I've like

become conscious or like aware of the

internet and you know started hacking on

stuff like the principle of the internet

has always felt so crazy and so powerful

was that if you built something online

you put up a website like millions of

people could go to that website right

it's like yeah it would cost more take a

little bit more energy but like the

marginal cost of an of serving an

additional user was you know BAS

basically zero or close to zero right

and that's amazing right because that

means if you build something good you

know it can scale to tons of people but

it also means that if yeah it just means

that like the flip side of that is like

you know if if a Google or Microsoft

build something then like you know scale

to millions of people in AI because of

the cost of like these models are so

expensive to run still right that it

doesn't work that way right like the the

the marginal cost of every user is is

constant so like for granola basically

we pay money every time we generate

meeting notes right so yeah our

transcription and our bills map linearly

to you know one to one to how many users

we have right so the interesting thing

there is that as a tiny startup you

probably don't have that many users so

it's actually possible to use really

like Cutting Edge models like and

whereas you know my my friends at Google

who like that I worked with before I

left you know if you're on Google Drive

you have so many users and so much data

and if you actually want to roll out a

like a Cutting Edge feature to all those

users it's just not feasible it's not

feasible from a financial standpoint or

from a compute standpoint so basically

you're saying that you can build like

you can use the best models even though

it cost a lot to deliver like the Best

in Class experience to a small group of

users and they expand from there is that

yeah because like I think you know best

case scenario as a startup your user

base grows exponentially right and and

if you like if you look at the cost

basically the cost of insurance like say

like oh models haven't gotten cheaper no

no models have gotten smarter right over

time but if you keep the level of

intelligence fixed like what it costs to

like run like I don't know

gpt3 level intelligence today is nothing

compared to what it was three years ago

right so hopefully as your startup

scales if even if you're growing

exponentially the your inference costs

should decrease exponentially and you

kind of hope the math works out in the

long term got it that makes sense okay

so let's talk about your I'm not sure it

there a principle but I I really like

like it it's you should build products

that feel like they have a soul what is

a soul like what do you mean by have a

soul yeah it's a good it's a good

question and I think soul is basically

this does a product give you a sense of

cohesiveness when you use it and that's

one of those things where it's like if

something is kind of frankensteined

together you know by a lot of like

different people then when you use it

you don't necessarily know what the

essence is or what this thing is like

it's a little bit like I don't know I

think we think of I think on some level

we interact with products the same way

we interact with people right you kind

of attribute attributes and and you have

like a relationship with it so I think

that's anyway yeah I'll pause there no

so so it's like well I mean you talking

about Frankenstein like you know that's

pretty typical at larger companies you

have different ORS trying to build on

the same surface and you just like the

like what was the point of the surface

like there's like five different things

that you can do on the surface right so

so you see kind of like being focused

and like actually solving

like solving a problem or having that

emotional connection yeah I I think it's

maybe a way to put it is sometimes you

use a product and you can kind of feel

the person who designed it like you can

feel the people on the other end who

made that product and you can kind of

hear what they're saying or what they

felt or what they wanted you to feel and

other times you don't feel that at all

right it's like a that feeling is absent

and I think it's like one of those

things you don't you know if you stop

and and you pick up an an object you'll

kind of you'll know if you think about

it but like you know it's like one of

those subconscious things like I I I

like I don't know like early Mac

products always felt like that like I

always felt like I could feel like the

people behind like in copertino probably

working their butts off right and like

what they they're trying to pour a lot

of themselves into this thing and it

felt very like they're humans on the

other end of that I also with my last

startup I was building for high school

students and like early versions of

Snapchat also really felt that way you

know completely different you know

product UI but like they there was a

real like point of view on the world you

know and you could tell that they're

like again there's something that

they're like really like pouring

themselves into it whereas most products

you you interact with you don't get that

you don't get that or maybe you feel

people talking about like hey we got to

hit this metric this quarter so gotta

put this big banner here yeah how do you

balance between listening to customer

feedback and your own product intuition

like like do you think the two kind of

feed off each other or do you think no

yeah I think I think there's a few

different schools of thought here I I

basically think like on one end there's

I'm an artist right I'm going to go off

and I'm going to come up with like the

perfect design and it doesn't really

matter what people think right I'm just

going to like understand this problem

that's one end and I think on the other

end there is extremely customer feedback

driven right just listen like the

customer is always right like listen to

what they say and what they want and

like my view is that I think for a

product to have soul it needs to be

designed with cohesion so I think it's

very important to design based on your

intuitions and your instincts and for

that to come from you as opposed to like

I said Frankenstein from a different you

know and you need have like a consistent

worldview but I think the problem is

that it's extremely hard as a human to

put yourself in someone else's shoes so

you need to constantly be getting the

context of what other people are

thinking so so like our view at granolas

is not actually like to make a list of

here are the product requests or the the

pieces of feedback that people give us

and therefore we're going to build x

what we do is we inundate ourselves with

product feedback right like we try to do

I try to do a user call a day every day

we have a screen that will Flash the

feedback that users uh send us like real

time on the wall we get these Dodges so

basically it's like I want us to be

immersed everyone on the team to be

immersed with what customers are saying

but then when we go design kind of from

first principles of like how we think a

thing should work yeah I I love that

it's uh it's kind of it's kind of like a

prompting LM right you want to have the

context like yeah cuz you want to put

yourself the customer shoes at the end

of the day like and like some of it

might not be like what they're saying

but like actually watching them try to

use the product or something you know

yeah yeah 100% And I think like you you

want it to be as like I think our brains

are really good at filtering information

right so it's like if you're constantly

immerse in what users are saying or

thinking or feeling then you don't have

to analytically say oh okay well there

you know 15 reports of this and there

are 50 reports of this and therefore you

know it's like you'll feel it you'll be

like no clearly this is more important

you know like like I can feel it it's

like an emotional thing like it hurts

exactly dude that that resonates me so

much man like I that that is also why I

started this interview with the big

company thing cuz like you just don't

have time to be immersed man like you

just have so many other meetings with

internal stakeholders it's so hard to be

immersed some big companies like yeah

yeah so yeah and the other thing that's

that's maybe not talked about a lot is

like it takes a lot of like

infrastructure and tooling to to be

immersed right so like like so my last

startup was cratic right and it was a it

was an AI tutor it was like a mobile app

right you stuck on a homework problem

you could take a photo try to teach it

how to do your homework problem getting

immersed and feedback there was was

incredibly hard it took us a lot like it

took us like I think a year and a half

to figure it out eventually what what we

did was so we were based in Manhattan so

every Tuesday we had a class of high

school kids come into our office and

just hang out in our office for three

hours so they'd come in after school and

they'd hang out do homework do whatever

and on Tuesday it was always the same

kids so it was the high school down the

block and and the idea there is like we

get to know them we get to see their

Journey they'd get to trust us and then

on Thursdays every week we'd have a

different set of kids we've never met

before right and we could do that in New

York because like you know Manhattan St

there are lots of kids and once it's

like it's a ton of effort to put that in

place right you have to Source the kids

you have to get them signed disclaimers

they're all minors like it's a huge pain

in the butt right but like once that

machine was churning oh man the whole

team like we would ask them questions

about everything right like like we

would show them prototypes we would like

just shoot the [ __ ] you know and talk

about stuff and that like immersion like

helped the team tremendously but it it

took a ton of time and effort to get it

I do that through you know like Discord

communities or online communities and

yeah you have something to go through a

bunch of internal approvals but it's

totally worth it because you can just

like randomly ask some questions

throughout the day yeah that's great

like you know you know like my my

product development feedback loop now is

like there's three circles there's like

internal stakeholder feedback there's

customer feedback through my community

and then there's AI feedback like I also

ask all my questions yeah that's

interesting how's that what have you

found the AI to be helpful with versus

not so helpful with when you're asking

question it's pretty good for like

obviously it's very good at summarizing

stuff but like in terms of asking

questions it's like you have to give it

a ton of context like you have like

pasting like entire slack threads or

like you know my entire document and

then I start asking questions then it's

a lot better if you just randomly ask a

questions it's probably not very good

yeah yeah yeah but like it's never going

to you you can ask any any dumb question

you want yeah yeah yeah yeah yeah yeah I

have this so I have this go link I don't

know is go link does everyone know what

a go link is or is that just like a

Google like a big tech company thing do

you guys have go like a short link right

it's like a short yeah it's just like

you can like a mini URL you know like

and I have one for a Claud project that

has a ton of context about like granola

and my job at granola right and what I'm

trying to do and like who I work with

and like what our Tech stack is and like

all these things so that when I'm asking

a question at least it has all that like

that General context otherwise it'll

just you know might just go off totally

in the wrong direction and I I find that

it helps a lot some of the time and

other times it just you know it over

indexes on that on the context awesome

so let's kind of wrap up by I would love

to hear about what's next for canola you

know I've been using it it's it's pretty

awesome no cing app I I love how it

combines my notes with the AI notes I

kind of wish it let me or maybe it

already does this like does it let me

upload my own temp templates yeah for

format does it's just really hard to

find okay so you can yeah after a

meeting has happened you can select from

there a few templates and but you can

also create your own but it's really

indisc discoverable right now so we're

definitely going to make that better

that might be because like with my

prompts like the more examples I give it

of stuff that I want the better it

becomes that might be an interesting

idea ping a bunch of past meeting notes

yeah yeah absolutely yeah so you're like

where we're headed and and what we're

going to focus on yeah yeah yeah I I

think um

I think right now gral is really focused

on giving you good notes right and

having those notes feel like they're

your notes and you mentioned this I

actually don't know if we explain it

basically I think what the big

difference I think about granola from

all the other like AI note taking apps

out there is that it's a text editor

right and you can still take notes and

then when the meeting ends it'll flesh

out your notes but it really anchors on

what you've written and like I think big

picture A lot of the value that granola

is g to provide in the future isn't

going to be on the Note helping you get

good notes it's going to be on the okay

now the meeting's over what's all the

work you have to do as a result of this

meeting and kind of helping you do that

work because the the reality is again we

were talking about the importance of

context you know the context from the

meeting and maybe the series of meetings

that you've had like on that project

leading up to that meeting like that

context is super important and I'm I'm a

big believer that a lot of the work like

action items like all the stuff that

comes off of like the the back of a

meeting GR should really be able to take

away a lot of the repetitive tasks there

got it so it's like you know all obvious

just like next steps own nurse but

actually following through following up

see if they actually do their job or you

know that kind of stuff right yeah yeah

I guess this is like one of those kind

of philosophical discussions where I

think like like I think there's kind of

obviously the reality is like uh Blended

but two extreme there's do you want AI

to replace the human who's doing stuff

right or do you want AI to give the

human superpowers so it can do it so you

want like Jarvis you know from Iron Man

where it's like you're still driving

you're still in control but like now you

can do so much more than you could do

before or do you want something that's

like fully automated that goes and does

stuff for you and like we're we're at

granola we're very much a believer in

like giving people superpower so it

would be less like a go off and like do

it but it would be more like there's all

these classic examples right like

follow-up emails like that's like a

classic thing where it's like a lot of

writing a follow-up email is kind of

wrote and then there's like a few

decisions that are strategic that you

really want to make sure you get right

and like the human should be doing those

but like all the specifics of like what

was agreed upon in the meeting that that

an AI could write if does that make

sense yeah that makes a lot of sense I

mean like you know we talked about

before interview like you know I was in

a meeting and everyone else was like

furiously taking notes and I I was able

to just sit there and have granola take

my notes I put some notes there some

sometimes but like then I can actually

think about what's going on in the

meeting right so I'm just like furiously

taking notes yeah so that that already

helps a lot yeah there's uh yeah man I

think there's like it's an exciting time

to be alive right like I really think

the I really think the tools like you

know the famous saying is like it was

like we shape our tools and thereafter

our our tools shape us right and and I

think that's true and I think with AI

it's like the potential for the tools to

like shape our thinking is exponentially

higher right so I think it's like and

that's good and bad right it's like it

can oh it's like you can in kind of push

people to think a certain way or not to

think about certain stuff or that you

could really Elevate the types of the

level that people are thinking at right

like I see a future where AI is taking

care of all like the boring details and

you get to think the higher level about

like what's really that what really

matters right and then you that's where

you influence it's going it's going to

let the Google PMS operate like Founders

man that's I don't know I think there's

more structural issues there but yeah

yeah yeah so do you have any like

closing words of advice for people who

want to build AI apps or you know get

into stuff

yeah I think it is an extremely exciting

time to build like I don't know when Sam

my co-founder and I started off was kind

of pinching myself I'm like oh man I get

to be alive now like it it feels like

one of those moment like it a little bit

like if you go back to the early

Computing Pioneers in like the 50s and

60s like Eng goart and alen K and all

those guys like it feels kind of similar

now except for those guys who are

looking at the technology of the time

you know they're looking at this

computer that'll take up a whole room

right and cost like a million dollars

and be like one day everyone will have

their own computer and you have to be

super Visionary right to imagine that

whereas like we get to be like one day

you know AI is going to be able to do

this and it's like six months later can

do it you know so it's like the fact

that we get to live through that facee

is incredible I think the I don't know

any advice would be like the world's

moving quickly and I think the the right

move is to like adapt to it quickly as

opposed to like like I think it's really

hard to predict what's going to happen

right so kind of kind of roll with it

and like as every time you get a big

technical change it unearths a bunch of

opportunities and sometimes it's not

obvious what those are until you kind of

just play around with it so I think

there's like a lot of Alpha and just

playing with the latest stuff and just

kind of seeing what you know what you

discover and where the value might be

yeah I totally agree just like thinking

of stuff without any kind of goals or

you know just like spending time to

actually play through with these tools

that that's really important yeah it's

so hard to do that when you know you

have a busy job and those things you're

trying to accomplish because it's like a

different mindset right you want to be

like a kid playing with toys right and

just seeing what kind of comes out of it

just to clown the me meetings man it's

not yeah no no no and sorry and and and

uh for for for people watching this

where can they find granola where where

can they use granola yeah oh yeah yeah

so

granola.bar

speciic use case very well so congrats

to you and the team and yeah hopefully

more people play with yeah Peter thank

you so much it's been a pleasure sure

and I really appreciate you taking the

time all right

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