YC’s no-fluff playbook for scaling past $10M ARR (with Garry Tan)

How do you compete with these bigger players?

>> We're seeing routinely YC companies with 10 or 20 people get to 10 or $20 million a year in revenue in 10 or 20 months.

That's like literally never happened before in software.

>> Talk to me about how you use AI in your video creation.

>> I took the scripts of all of the top videos that I ever made for my YouTube channel. I'd throw it at this prompt and

channel. I'd throw it at this prompt and then it would generate these beautiful threeact narratives. I could have a new

threeact narratives. I could have a new 10-minute script ready, whereas it normally would take me like several hours. How are you changing Y

hours. How are you changing Y Combinator? Let's stop competing with

Combinator? Let's stop competing with all the other VCs. Let's be their partners.

>> I'm going to ask you to do something you're uncomfortable with.

>> Oh yeah. What's up?

>> Gary Tan is the president and CEO of Y Combinator.

the next thing.

>> Why don't we start with the case tech story because I feel like there is a before AI for that story and AI experimentation and then once it took AI everything changed.

>> I worked with Jay Keller the founder of Case back in 2012 2013 when he first went through Y Combinator and that was also my first stint at YC as a partner

and they were sort of doing basically you web 2.0 I know for law. So literally

what's happening with uh case law and new legislative I mean whether it's legislation or literally judgments like all of the documents that the legal

profession throws off they would index which would help you understand the law and um that was really what they built for something like going on 10 years it

grew by SEO and Jake's both a great technologist and a great lawyer and so he was really able to go into that market and make something based on what was happening in society and in tech at

that time.

>> I think there was also like a Q&A component of this, right? So they could go and talk to other lawyers. We're

going to get into how things get better.

Why wasn't that enough?

>> Some things can become huge and drive billions or tens of billions of dollars in revenue every year. And some things really could only get to they only provide value that you and then you

multiply it out by all the people who need it. and that might only total up to

need it. and that might only total up to 10 or 20 or 50 million. Like that's you weirdly quite common. I think a lot of founders are worried about that early

but my sense is maybe it's premature worry because embedded in that is also the case text pivot that you know they got users and an understanding and a

useful corpus of data all of which turned into a tremendous moat for them literally right at the correct moment as technology itself shifted uh something that could only make you know tens of

millions a year could suddenly become something that could make hundreds to billions of dollars per year >> and >> and that was the dawn of the large language model in 2023.

>> Tell me that story of like how they came up with that.

>> The cool thing about YC was that Jake basically had access to early versions of chat GPT GPT3. These were sort of toy earlier versions of it and they were

certainly astonishing and interesting but they were not useful yet because the LLMs actually would just uh hallucinate.

they were early in the journey so there wasn't enough data um the par the number of parameters the sort of size of the models was too small and that's what

Jake found as he tried to use large language models to do a lot of the things that you and I take for granted today uh right at the dawn of this stuff it was um not that useful you know it

was sort of a horseless carriage if you will you know it was uh an oddity you could look at it and say well maybe this will work but It's mostly a toy and nobody will actually use it yet.

Possibly ever, right? I certainly when I first saw it, I'm embarrassed to say like uh even as an investor and technologist myself, it's like that's that was the consensus at the time. And

in at that moment, at the dawn of large language models, that was correct. Like

you couldn't use it for useful things yet. Jake being a great designer,

yet. Jake being a great designer, engineer, and lawyer, he tried really hard to make it work and it would hallucinate. And you know he also was

hallucinate. And you know he also was operating in an area that uh in particular really had high sensitivity to hallucination. You get one thing

to hallucination. You get one thing wrong and you're fired as a lawyer. So

you know his his particular space was fascinating to me because it particularly could not withstand any hallucination. And as technology curves

hallucination. And as technology curves and cost curves go, this was something that I think surprised everyone. Um if

you were Greg Brockman or Dario Amade uh at that moment you started internally you were talking about the scaling laws and that the loss function was going

down as log linear to the amount of uh data and compute you were putting in and that was an astonishing realization that like there was a path to potentially AGI

or ASI. Um the rest of us on the outside

or ASI. Um the rest of us on the outside had no idea and I think Jake also didn't have any idea but because he was in the YC community open AI itself was a spin

out from YC research by uh Sam Alman.

>> So then he starts adding this on once it's ready once it's ready for lawyers.

What was the original use and then how did it take off? I believe he basically started using it for um being able to

answer specific questions about legal cases. Um, and once he got access to

cases. Um, and once he got access to GPD4, he realized that if you cut down the size of the question to small enough,

>> um, and today we call that context engineering, but at that moment, he realized if you asked a very long ranging question, >> um, like is the defendant guilty or

something, you know, it's like such a big question that, uh, even GPT4, I mean, you could argue that, uh, some of the reasoning models today are actually much more capable of doing it. But back

then you didn't have multi-stage like test time compute reasoning um at that moment. Uh if you chopped it down to a

moment. Uh if you chopped it down to a bite-sized chunk like you gave it some amount of uh context that a human being given the same context and the same

prompt would answer in a certain way. He

found that he could uh you know given inputs and outputs have output that was usable, useful and reliable and not a hallucination. But it required you to

hallucination. But it required you to chop that down into um a particular small enough step. I think of Jake a little bit like the first man on the moon. like, oh, you can chop it down and

moon. like, oh, you can chop it down and then you should actually have tests for a bunch of different inputs and outputs and you should have evals that actually

um give you a sense and certainty about specific tasks. So you would sort of do

specific tasks. So you would sort of do tailored time in motion study of exactly how a lawyer might you know a lawyer often has to do a timeline for instance.

Okay.

>> So what he would do is like chop it down into what would I do as a human being?

Well, I would start skimming each um each chunk, whether it's a sentence or a paragraph, and then I would try to score it based on whether it was uh noteworthy

or not for do I need to put it in a timeline or not. And so, you can imagine, I mean, he's like sort of very logically creating some of the first uh ways to do prompt engineering. So he's

taking this technology and he's finding a way to make it useful by thinking almost like a human being a little bit like a machine and then coming up with the answer. He now has a better tool.

the answer. He now has a better tool.

That gives me two questions. What

happened to the business? Did it

immediately go from like sales cycles of I think I saw you you say in a video a year or more to now a month or less. I

guess the really interesting thing was um you know he built the first versions it could do like let's say it could do a um it could comb through thousands of pages of documents and give you an

accurate timeline of events for instance and that's something you would hire uh a legal analyst or associate to do and it would cost thousands tens of thousands of dollars right

>> so instantly you can say I will save you this much money direct to the bottom line do you want to buy and it's a becomes an easy answer >> I think that was the feat of strength like They took the corpus of uh Enron

emails for instance. And uh I think the example Jake likes to use is you could ask questions about emails where there you know it involved like high nuance

things like you could ask it about ironic jokes that the CEO had made and it would be able to like discern like oh they made a joke about their fraud in

this particular way and it would like find the reference for you. So you that would that was sort of the demo that they would show to lawyers and it would just be so astonishing that people would

say I need to buy it right now. This is

the future. And it turned out to be very like not just a little bit correct. I

think I'm I'm still astonished dayto day especially as new model releases come out.

>> That explains why every time I see what it does I will see and it detects sarcasm. And now I get why that comes

sarcasm. And now I get why that comes up. Then the other thing that comes up

up. Then the other thing that comes up for me, Gary, is we keep hearing that maybe it's useless to create anything in this space because the big companies are

just going to take it on, right? You can

imagine a world in which ChachiPT does all this or Google's Gemini and its consumer grade products that people are using to figure out what to do with their with their weekend plans that it's natural for them to then ask the same

question for. It's not an unfamiliar

question for. It's not an unfamiliar tool. How do you when you do this, how

tool. How do you when you do this, how do you compete with with these bigger players?

>> Yeah, absolutely. I mean, I guess I have two answers. One is obviously the one

two answers. One is obviously the one that um we're you know, at Y Combinator, we uh you know, we believe in that. We

see it happen like we just see small teams of people go out into the world and create, you know, they they're obviously using these incredible frontier models, but they're adapting

them to the very specific things that real people in the economy actually need. And so they're not necessarily

need. And so they're not necessarily glamorous scenarios. uh their customer

glamorous scenarios. uh their customer support scenarios for um HVAC consultants for instance this fragmented industry but a very big industry um and

they're taking they're building soft you know there's a company called AOA that we worked with at YC they're they're doing exactly this customer support for

HVAC but V1 of it was basically Service Titan so Service Titan is a incredible public company but um they're basically

software and uh HVAC consultants and firms spend about 1% of their dollar wallet. You know, for every dollar, for

wallet. You know, for every dollar, for every $100 they bring in in revenue, they spend about a dollar on software like Service Titan, but they spend5 or $6 on actual people picking up the phone

and doing scheduling and doing all that stuff. So the wild thing that we're

stuff. So the wild thing that we're seeing is that if you like scope what you're doing and make the thing that is perfect for that set of people um there

you can't just take chat GPT and have it do this type of work yet. I mean it's entirely conceivable eventually but it hasn't happened yet. Um, and while that

is still true, people are sort of building the next Service Titans. And

then the wild thing about it is, you know, Service Titans, incredible business, but then you could have something that expand takes over that 1% and then expands like 5x or 6x bigger.

So that's sort of why we're seeing routinely YC companies with 10 or 20 people get to 10 or 20 million a year in revenue in 10 or 20 months. And that's

like literally never happened before in software. You know, the the average rate

software. You know, the the average rate at which YC companies grow their revenue during the YC batch, which is 12week process, is uh 10% per week on average.

I mean, some of the batches have been growing 15 20% a week, but it's been at least 10% a week for more than a year.

And so, there's something in the water.

Like, there's something happening. And

>> what was it before? I thought it was 10% a week through going.

>> Oh, no. You'd have one or two companies grow 10% a week. That was like the aspirational like if you could do it that would be what good looks like. And

then >> now on average everyone does that.

>> So it went from on average 1 to 2% to 10 to 20%.

>> Yeah. I I think the average was probably closer to 2 to 4% and then now it's consistently 10 to 20%.

>> And this is in revenue.

>> Yep. In revenue. So, and you know, it all goes back to the case tech story, right? Like before it's like, yeah, I

right? Like before it's like, yeah, I know I need to replace my software, you know? Oh, I'm still using SAP or I'm

know? Oh, I'm still using SAP or I'm using whatever I was using. I'm still

using spreadsheets. Like it's, you know, having better software was much more of a nice to have, like it's something that you felt like you needed to do. And then

today it's becoming um oh, like I see a demo, it's really impressive. Uh, I

could see how that would hit my bottom line or basically create a better product or service immediately.

Um, and then yeah, I need it right now.

When can you start? Right.

>> I totally feel that. I feel it in the air. Then it kind of brings me back to

air. Then it kind of brings me back to the conversation that I had recently with the founder of ReadAI. This is

David Jim. And I said, "When I do sales, I want a note takingaking app that keeps guiding me towards closing a sale or at least analyzes me afterwards based on a sale." And he said,

sale." And he said, >> "And scenario, >> great example." And he goes, "Andrew, that's not the way it's going to work in the AI world. What you're going to have is one tool, one noteaker. He'd like it to be obviously read AI that does

everything. And if you say I'm a

everything. And if you say I'm a salesperson, it'll customize some of the feedback that you get for sales. to me,

if I even have to customize it, it's an extra step. And so, I've been seeing

extra step. And so, I've been seeing this, Gary, in conversations with with builders. Some are saying AI doesn't

builders. Some are saying AI doesn't need to be customized at all. And I see you squint as I say that. So, I think that maybe you have a strong opinion here. And others are saying absolutely.

here. And others are saying absolutely.

What you are is go down to the level of HVAC.

>> Yeah. I I think that we are sort of we might be at a moment where it's too early to tell. Obviously the stakes are very high, but um if we got to a point

where AI is truly, you know, not just AGI, but ASI, it can like far exceed that what of of what humans can do. All

bets are off at that point, right? Um so

I don't know. I I feel like this is almost um like the reverse Pascal's wager for AI a little bit. He's like,

well, uh, it's entirely possible that ASI happens and, you know, what some people think will happen happens. Uh but

you know the society that we will need to live in will be reconfigured like in such a radical way that um you will there be jobs and then at that point the

hope is that um if if we have uh actually access to clean and um clean solar and wind and maybe even fusion with helon and things like that um over

a you know 30 50 year time frame like society can reconfigure into one that's really focused on abundance when you're talking about startups and competition and markets like we still live in a

market economy that is driven by you know should I buy X or Y and you know I I think it's like you certainly in some sense a flawed system on the other hand it's certainly the best system that we

have like the invisible hand I I want to know which direction you think but I'm looking at the list of companies that you at YC have helped launch just in the

fall of 2025 what I'm seeing here is there is a focus it is companies like uh where is it um market silver bullet for trade

compliance to give you an example of what I see I see another one bluma automate automating short form video ads at scale >> so you really are still saying I'm going

to be focused narrowly on a vertical am I right or am I just looking at a handful and drawing >> this is also about like making individual founders successful right I guess famously I think at some point Sam

Alman came out and was while working on OpenAI, he was, you know, sort of rethinking whether like the classic uh YC advice was correct. I hadn't I mean

obviously we're friends and we like hadn't like we had some exchanges about it. Uh you know I think that he's sort

it. Uh you know I think that he's sort of changed his tune a little bit in that he's seen now that like AI like all the startups out there using his APIs are sort of his commercialization arm and

that's not a bad thing, right? Um there

was a time when I think he said he just wasn't sure if um all of the advice around make something people want and like being lean was quite the right

thing. And then to me I think Looped had

thing. And then to me I think Looped had to be lean. You know a lot of people who start really huge companies had to start companies that were much more specific.

Elon Musk had to start Zip 2. I think

the reframe for us at YC is that we actually want people to be uh directly in control of their own destiny to the extent they can and then starting a company.

>> The thing that that was exciting for me is like I'm looking I'm holding here this is uh well told it's a mug by someone who I don't think 20 years ago could have created a mug. It's

beautiful. It's got like the city that I that I'm in. He sent me a bunch of them, Gary. One with every city that I've done

Gary. One with every city that I've done mixer G in, which has been a lot. Cool.

>> Um, >> and I think about him a lot because that kind of entrepreneur couldn't have existed before, but now they do.

>> You are a video guy. Beautiful videos.

You always had good taste in video. I

don't think you would have existed, let's say, 20 years ago, because it would have been forever to videotape, to edit, to put your spin on it. Do you

think the same thing now is going to happen with software that more people are going to be able to create it and it's going to be sustainable or it's going to give them enough money to sustain their lives?

>> Absolutely. I mean that's certainly my hope. The reverse is like too dark to uh

hope. The reverse is like too dark to uh you know I if anything like that's some of the reason why we spend a lot more time in DC.

>> But Gary even if it's the same like I I'm wondering that because of all the vibe coding apps I keep seeing vibecoded apps from people. Will they turn into something significant or is it going to be like most of the YouTube videos where

there's no business from it? It's just

fun to create or does that even matter?

>> My argument would be I mean especially Vibe coding um the Claude code team apparently writes 95% of their code is written by Claude which means very

directly that each engineer working on cloud code themselves is doing the work of 20 people. a sort of direct quote from a recent like Lenny podcast with

one of the co-founders. And so

>> I think that that's actually the good news. You know, I think if you look at

news. You know, I think if you look at tech across like 10, 20, 30 years, um it's actually that like the access to good software is incredibly

inaccessible. And one argument I often

inaccessible. And one argument I often make is if you use an iPhone, you probably have hit uh bugs in Apple Calendar. And it's like very frustrating

Calendar. And it's like very frustrating because come on guys, like this is the built-in thing to Apple. The the iPhone like the iPhone is the Apple is like one of the most dominant tech companies in

the world. And yet they cannot find good

the world. And yet they cannot find good enough software engineers to fix the basic bugs that still exist in Apple calendar.

>> And so that's been true for time immemorial. Like if that's true for

immemorial. Like if that's true for Apple, how could you possibly imagine an HVAC person ever getting access to good software? And you know that's the

software? And you know that's the difference today. It's like, hey, you

difference today. It's like, hey, you can have it now and it can be customized to you. And if anything, like the

to you. And if anything, like the funniest thing is if AI and codegen gets even better than it is today, um people can like that might be one of the

vectors by which uh HVAC people like compete against each other. You might

even choose the one that has the best status and the best um the best app that like can tell you exactly when things are done. Or if

someone uses they use Replet to create software or you know or maybe there's a vertical version of Replet just for workflow for managing your workers right

like anything that you can imagine it could actually create a better product or service and then net net what this might mean is that just like everything that we get in you know our day-to-day

lives is just better faster cheaper and then more is more actually like it's actually good that um I And sometimes I to link the abstract to the specific.

I'm like a good example of this would be I would love for uh every apartment in San Francisco for instance to have dishwashers and uh washing machines,

right? like in a weird butterfly effect

right? like in a weird butterfly effect sort of way. Like if you think about um people doing better work uh more meaningful work doing it uh on time and

at the right time for a better price like the sort of that's how the market creates like higher um you basically higher standards

of living, right? And so that's sort of like the like what I hope is and what I think will happen is that as long as people can start businesses, uh they can make better choices, they can make

better products, um you this is actually a much bigger engine for making um our day-to-day better. You're imagining a

day-to-day better. You're imagining a world where instead of having HubSpot and Salesforce and Close and a couple of others that are really big, HubSpot, Salesforce,

then you got the mid, you're imagining a world where there is a CRM for podcasters like me, a CRM for HVAC, in fact, multiple of them. And so the revenue of Salesforce, I imagine, would

then be spread across a bunch of companies. And there would be a bunch of

companies. And there would be a bunch of companies whose founders are not as wealthy, but they are making a strong enough living. That's the world you see.

enough living. That's the world you see.

>> That's right. And then on the flip side, like >> even if they Well, I realize like you that's also often not how it works out. I I also wonder if

that's great for you because what you're looking for at YC is not to have a bunch of small companies where the founder can live a good life, maybe buy a second home, but where they're building the uh

the Mark Beni offsiz successes, right?

>> Yeah, that's right. I mean, I guess YC is funny because even if someone doesn't end up making the Salesforceized thing, like they often sell their bill. I mean,

that was true for uh Posterous. My my YC startup ended up selling to Twitter. my

our YC batchmate um backtype uh it was Chris Golda and Mike Montano's company they sold to Twitter and then the that team ended up creating Twitter ads I think like our our old teammates at

Posterous ended up making the tw the you know uh making the first Twitter uh Twitter mobile apps and or working on that team. So I don't know there is like

that team. So I don't know there is like a creative destruction aspect and then on a sort of day-to-day career basis like it's better for people to uh become

founders learn how to create things for other people and then either you know you manage to get product market fit and you figure out a moat so that you can be

you know as big a company as possible or even if you don't like everything about your life and career moves ahead by you five or 10 years faster than it would

have been or you know we have lots of friends who instead of starting companies they stayed at Microsoft and um it's better to be directly in the face

of real users and shipping real code and product and then learning how to support that um because that's just actually valuable and I think there are lots of other jobs out there that are uh

slowmoving bureaucratic I actually sort of wonder like I was hanging out with another investor who sits on a lot of boards. Um

and we were thinking like man there's a increasingly like a lost generation of people who work in big tech. And uh you I think um well even at YC like we are

seeing um the rate of 18 to 22 year olds at YC is up by more than 100% yearonear.

>> Um the rate of 22 year olds to 25 year olds is up about 20%. And then the rate of 25 to 30 year olds is actually down by like 10 or 20%.

>> Wow.

>> And a lot of those people started their careers actually during Zerp.

>> So they're actually sort of you know hanging on for dear life at um both startups and Fang.

>> And uh those are also like funny enough some of the people who are the biggest AI deniers like they just don't believe that um the sort of revolution is happening. You're saying they got such a

happening. You're saying they got such a good job where they were, they don't want to lose it and go and kick off and start something different. Got it.

>> Whereas the the young generation like they're incredibly hungry right now because Fang is not hiring. Like the the Zer jobs are not there.

>> And a lot of them, I think, are are playing more with this. It used to be that playing startup was fun. Then it

became playing YouTuber was fun, but playing startups felt like now you're becoming the man. But now you see lovable and cursor and all these tools and you say, "Okay, they're making it more accessible. Let's play with it."

more accessible. Let's play with it."

And then you you lean and create something. I told you earlier that I

something. I told you earlier that I would give you a great example of why combinators like inner access. David

Roganer, he is a guy who started out with proof, a thing that was going to help e-commerce companies. And I love after he got into Y Combinator, he goes, "What we're going to do is we're going to revolutionize e-commerce. We're going

to make every every Shopify store customized based on who the person is because we're going to have a tool that goes across all of them. I go, boy, why cominator really gets people to think beyond the tool. Before he had a little freaking widget, now he has this changing the whole thing.

>> And then suddenly he created what became Jasper and it it's because he got to see the original open AI tools and he said, "Okay, I got to pivot everything. We're

going to create an ad creation tool that uses AI." And then he changed it to

uses AI." And then he changed it to based on user needs to create a writing tool for everything. That is the inside Y combinator access. Right.

>> Absolutely.

>> What is like how how do you stay in touch with people to keep guiding them after the time that they're in the program? Oh, well I mean these days uh

program? Oh, well I mean these days uh everyone who gets into YC they have one particular primary partner and um obviously when you apply it goes into sort of this giant pool but then uh we

have 15 equal partners on the investing side who like uh are in we basically are in there trying to fish like we're you know in there with our nets and like let's uh take a look like let's watch

the video let's try the demo let's read everything about the founders what they've done and what do they know about their users. users about uh the product

their users. users about uh the product and then we try to fig figure out well who do we meet and then anyone you choose you meet and then when you meet

it's up to you uh whether or not you accept them and then when they're in like you always have one at least one person who is sort of like your investor

uh at YC and that company you're still getting on calls with them a year two years later >> that's right so you know I basically I think the bad version of thinking about YC is like, oh, it's like a summer camp

and you have a camp counselor and you never talk to them again. And then the good version of it is like, oh yeah, YC partners are, you know, actually renamed their title. It's like not group

their title. It's like not group partners anymore. It's actually general

partners anymore. It's actually general partner and we're actually investors invested in the future of the company for the life of the company, right? It's

like having your best angel investor who is there for you all the time. And then

that's for many years. So basically

>> on our end it uh the best thing we can do is like understand the business, understand where the founders are coming from, who their customers are and then just ask questions. It's like could this

be bigger? You know, what's the most

be bigger? You know, what's the most interesting thing that you've learned about your customer? What are things that uh get people promoted? What are

things that are resonating? Let's double

down on those things. Like let's be super frank about what we've tried that doesn't work. like if we're spending

doesn't work. like if we're spending money or resources or you know people time or your time on it maybe we you know we have that or set that to zero and anything that's working like let's

double down on that and then you just having someone who's outside of your day-to-day who uh could be a sounding board. I mean, there's that. And then

board. I mean, there's that. And then

honestly, the the batch itself is perfectly designed to help you have not just your partner, but dozens of other people who are all like the outcome of a one top 1% process.

>> Uh, and you they they sort of help each other honestly. I mean, that was true

other honestly. I mean, that was true for me like when I went through YC, uh, we got to know the founders of Heroku and they helped us raise our seed round and, uh, gave us a lot of advice about

scaling. And then what's funny is about

scaling. And then what's funny is about like 6 months after we went through YC they came to us with a problem which is like we were becoming one of the biggest Rails sites on the internet and uh they

were worried that they were having some sort of scale scaling issue where they thought that our codebase might not be able to run on uh on Heroku. So they

said, "Hey, would you guys, this is a big ask, would you be willing to give us your uh GitHub access and codebase?"

It's like, "Can you imagine like meeting someone at TechCrunch Disrupt and like asking them for the codebase?" Like

you'd never do it. But you know, at YC, they gave us uh so much advice and we had really become friends with them. We

said, "You know what? Like, yeah, here it is."

it is." >> Which company was it that you gave him the codebase of?

>> Heroku.

>> Uh no, which what was your company that you gave?

>> Oh, Posterous. Yeah, Posterous.

Posterous was that big?

>> Yeah, >> I'm glad to hear it. I I told you before we got started, I freaking love Posterus. I'm still like I feel like

Posterus. I'm still like I feel like that was such an elegant app. It allowed

you to post from anywhere. So, it

encouraged you to create a lot.

>> All right. Um, talk to me about how you use AI in your maybe video creation.

>> Yeah, absolutely. I mean, what one of the things that we've been learning about I mean I think a lot of it came from talking to Jake about how he thought about breaking down the problem.

Um, you know, the cool thing about prompts is that it's actually an intelligible version of fine-tuning the model. Um,

one of the things that I did recently, I took uh the script of all of the top videos that I ever made for my YouTube channel

>> and uh I just fed it in and the prompt to Gemini because it had long context at the time. I think a lot of other people

the time. I think a lot of other people have long context too, but Gemini 2. 2.5

was extra good at this. Uh you could feed in a bunch of uh a bunch of scripts and you know say help me extract the most salient features that are common

across all of these scripts.

>> Um and it actually extracted out like here are a bunch of the things that you did in those scripts that you can that you know uh hook hard hook fast. Have an

inner game lens. Think about what the founder and creator psychology is. um

have sort of like a sentence rhythm of like a claim, a brisk explainer and then a vivid example and then a takeaway, right? And like so these are all things

right? And like so these are all things that like you know it it just sort of figured out like this is sort of what goes into a script that performs very

very well for you. And then I took that and then I'm coming up with sort of ideas for new YouTube videos all the time. And so then I would start uh I I

time. And so then I would start uh I I took the prompt from this. The prompt is basically given a set of ideas create write a script in this format. Um, and

then I started just taking ideas, uh, you know, maybe I see it on X or I'm sitting with the founder and we're talking about, uh, you know, whether the whether to pivot or not. And I just like

could just scribble down like here's a bunch of notes. Here's like a set piece idea. Here's like a um a tweet or a

idea. Here's like a um a tweet or a video clip that I want to use. And then

I'd throw it at this prompt. And then it would generate these like beautiful threeact narratives that like look like it was almost as if I you know it would

take me normally probably like two three hours to write out like the script for at this quality and you know I would have it and when I first did it it was

like not that great. But um iteratively what I would do and this is something that anyone can do is as you use the script like you should like label it and

number it and uh I would use the prompt.

I labeled it and then I gave like what I wanted the next video to be about.

>> Um and then I would work with it. I

would like edit the, you know, I would often tell Chachi PT to use a canvas and I would go in and sort of like instruct it similar to I if I had like a junior

writer who was writing for me. And so I would like sculpt it into what I wanted.

And then uh you know, you'd have the output of an incredible script that you could have like in basically on my phone like in between on on a commute or something. I could have a new 10-minute

something. I could have a new 10-minute script ready where whereas it normally would take me like several hours of just like breaking my brain to write it out in my voice.

>> You edit this or is this like a bad first draft that you then get to go and put your spin on or are we talking about 80%?

>> Oh, it's usable. Like I mean basically Yeah. Well, I mean the initially it was

Yeah. Well, I mean the initially it was bad and then um what I would do is do this process, get the script to where I felt really good about it and then at

the last point I would say given uh what we did in this session to improve the prompt, output the next version of the prompt. And so now I've done this about

prompt. And so now I've done this about 20 or 30 times. And so now I have a thing that has all of the different tricks. Like I even, you know, it

tricks. Like I even, you know, it started off as just like here's a format, here's uh sort of specifically how a good video might work. And then

now what's crazy is because of the once the reasoning models came in, uh now I can actually give it a grabag of tricks.

Some things that um I mean what's funny is like it's not entirely the AI coming up with it. It's not entirely me coming up with it. like in the course of co-writing something like 10 or 15

scripts, like it's figured out all of these grab bag of tricks, like a a pop culture cold open, a 15 to 45 second film, TV news clip that mirrors the

thesis before the hook, like a an authority pillar. Like I love quoting

authority pillar. Like I love quoting Paul Graham or Alan Watts or Naval Ravicant. And like

Ravicant. And like >> find one of those people and maybe you've confined it to the type of people you want.

>> Yep. And

>> I'm gonna ask you to do something you're uncomfortable with.

>> Oh yeah. What's up?

>> Share this. Can we Can we give one of these sessions to our people?

>> Yeah, absolutely.

>> Okay. I'm going to follow up with you. I

would love to be able to give that out.

>> Link in the description for for uh for my prom.

>> Yeah, I'll put it up on on X on everywhere else. I love seeing how

everywhere else. I love seeing how people do it. It's so it's so interesting to see how other people have these conversations. There was a period

these conversations. There was a period where OpenAI was trying to make these more public and I get why they wouldn't.

people were revealing too many things but to see how other people prompt is a real eye openener. Um

>> yeah and what it's taught me is like I think that ultimately almost any and thing that like you rely on humans for like you could probably do better and

these things are not writing it for me like they're helping me and I'm working with it. So it's a little bit more like

with it. So it's a little bit more like a co-writer. Uh I I still think that if

a co-writer. Uh I I still think that if you just say like write me a script and you give it no direction, it's going to be bad. Like you know you you as the

be bad. Like you know you you as the writer or creator um ultimately have to inject your voice into it like and if you don't do it then then it's slop.

>> All right. One of the things that I've noticed that you've done different with Y Combinator is you added this sense of first of all video first. You're damn

good with video. Always were with visuals. you added a sense of cool. Like

visuals. you added a sense of cool. Like

I really thought once you started leading Y Combinator that you were going to dress differently and then I'm looking at you and I thought for he's not doing these videos anymore now.

Someone else is going to do the videos.

He'll hire someone. But you've got these shoes, these sneakers that are on point all the time. You always have like even for this conversation, I don't even know if you know that I'm publishing the video because in the past I didn't publish our videos. This I'm I'm

publishing but it didn't matter. You set

it up beautifully for me. What am I not seeing? This is the obviously the

seeing? This is the obviously the exterior stuff. This is an indication of

exterior stuff. This is an indication of like you modernizing the the way the Y combinator communicates, but what am I not seeing underneath the surface?

>> Yeah, I mean I guess uh I felt really really inspired and just like sort of filled with fire actually by uh one of our board members at YC is Brian Chesy

of Airbnb.

And so he was part of the selection process when they were looking at candidates for this job. And uh the second I got in the role like I mean my

board is uh Brian and obviously Paul Graham, Jessica Livingston, the original founders uh Carolyn Levy and uh Harsh Tagger is actually just joined as a

observer recently and so yeah these are sort of like the stalwarts of YC and then they basically just really enabled us to I mean think about it from first

principles like what does I feel like YC 1.0 0 was the creation of Paul and Jessica and Trevor Blackwell and Robert Morris. I mean, the original founders of

Morris. I mean, the original founders of YC really set like the the vibe and the course and like what YC is about and they built it up. And then the second

decade, you know, was really with Sam and Jeff. And Sam created he took Google

and Jeff. And Sam created he took Google and turned it into Alphabet. And it was, you know, a lot of different competing things that all like sort of raised the

um ambition level of what YC was, >> meaning like the nonprofit aspect and all those things, these different research um you know, working on continuity as a separate fund. like all

of these things basically broadened the aperture of like what YC was. Um, and

then >> in full transparency, I feel like when I came back, like we explicitly decided as a board and as like the sort of steering body of what YC was supposed to be, we

said, you know what, like Alphabet is great, but we're going to go back to being Google. And uh, it's easier. It's

being Google. And uh, it's easier. It's

like a thousand times easier to be Google than to make Alphabet work. What

was one of the hard things to cut back on?

>> Obviously, what's great is like all the people sort of involved in continuity are working on their own funds and they're doing great and uh we think the world of them. Um but yeah, that was

probably the hardest thing. you have a great team that's executing on a strategy and then at some point we we realized actually like YC should be

about the the initial batch and like rather than treat like group partners as kind of like camp counselors it's like oh no no those people are actually the partnership like we're an equal

investing partnership similar to Benchmark but we have 15 people like that's actually the core of what YC is and then we also have incredible staff we have the world's best media team we

have world's best software team and um those are sort of like the pillars of YC and then it's just so much simpler. It's

just like let's do what we uniquely do the absolute best. Let's stop competing with all the other VCs in you know let's be their partners actually.

>> What was the problem with competing when you say competing with other VCs? You

mean uh founders would raise money from Y Combinator and then you'd say okay and we can also give you the next round from Y Combinator's >> and then what does it mean if you don't get it and >> that was always an issue if you don't

get it that was always like a a negative signal potentially what other problems were there with keeping that on because otherwise it seemed like it made sense as the one thing to keep >> yeah I mean some of it is uh you know

partners really you just didn't have the expectation that you would stay in touch with uh founders and then as a result there was sort of like a throw it over to the other team.

>> Why are these two connected? Whether

you're investing with the continuity, >> whether you're getting continuity investment or not, why shouldn't you continue with the partner that you were working with in your batch?

>> I mean, I that was just like a different vibe. You know, when you have a

vibe. You know, when you have a compartmentalization, >> I see the bureaucracy might come along and just say, well, like your time is for month zero to month four, and after

demo day, it's someone else's job. And

you know, it's actually easier to do it that way, but I don't I think it's less fun. And then it certainly doesn't allow

fun. And then it certainly doesn't allow us to support founders the way that I really want us to cuz being a founder is so hard. And um the the most important

so hard. And um the the most important thing actually is that uh you don't really know who to trust. And so if you have at least one person at YC who you

know has taken an oath to look out for you and take care of you for the life of the company that's actually I mean that's better than I think 90% of people who start startups period.

>> I'm thinking about something like Whisper Flow. It's on my computer. Do

Whisper Flow. It's on my computer. Do

you know what it like lets you dictate into your computer?

>> Absolutely.

>> Like what other rappers if I were to pick a a bad phrase? What other rappers are there that would develop or could develop into >> I I think there's like infinity um sort

of off thebeaten path like underserved verticals like HVAC is just one of like I think like accounting compliance audit like T I mean there's like infinity

things that um I think are just where there's brass there's gold and so that's sort of the most obvious the thing that I think is still non- consensus but I

hope is correct and uh now sort of the moment to start working on it is actually consumer so and you know actually it's it shouldn't be so non-conensus you know chat itself is

actually the best and most astonishing consumer launch of any product in the history of products actually and it was impelled by by AI >> but what do you see in consumer because I am always afraid of consumers they

don't make rational decisions they fall in love or they don't where with a business you know exactly how you can get to them you know exactly how you can make the message stick.

>> Yeah. I mean, apparently one of the biggest uh behavior changes in Chachi PT recently, for instance, is that people sort of treat Chachi as a counselor or

as a psychiatrist or therapist. And uh

you know, I I think that I'm pretty psyched about things like my buddy, my YC batch mate Chris Bader. He has a company called Rosebud AI, which is >> I've seen your freaking videos for it. I

I'm a paid user of it. I've got some thoughts. Go ahead.

thoughts. Go ahead.

>> I I think that that's super interesting.

on the one hand a small startup of two or three people and uh on the other hand like people are paying for it. It's very

high retention and so it's growing. You

know, I I think it has uh similar vibes to um ever like there's things like Evernote that grew um very organically for a really really long time and then

suddenly everyone's using it, right?

>> Here's what I love about Rosebud. My

therapist actually said, "Go sign up for Rose Bud." So, I signed up. It is like

Rose Bud." So, I signed up. It is like it remembers what you've done before.

And so it's actually this is actually a really good indication of the kinds of consumer products that could make sense because it's replacing a more expensive thing which is a therapist and doing it in many ways better because it's more

accessible. I can call up my therapist

accessible. I can call up my therapist at any minute and say come sign up. It's

David Coats by the way who's uh one of the cons one of the advisers of the app.

The the thought that I have on it is it doesn't have the Gary Tan design magic.

Look at the text and the way that you read it. It doesn't look beautiful. Look

read it. It doesn't look beautiful. Look

at the voice interaction with it. It

doesn't sound like an 11 Labs voice. It

sounds like it's thinking for a moment and then it's talking to you like a robot and then you talk back to it. I

need the Gary Tan magic. Like the fact that you would wear sneakers in a freaking podcast that no one could see and they're laced just right. That level

of detail to design needs to be applied there cuz the brains are good. That's

>> Well, I think Chris Bader's got it.

That's actually fantastic feedback for him.

I mean, that's the great thing. It's

like, uh, that could be fixed tomorrow.

>> I asked someone for a business coach.

They go into 11 Labs and they created a, um, an agent. This is a guy named Jeff Shank. He said, "Okay, let me show you

Shank. He said, "Okay, let me show you how I can do it. I can create a business coach for you." He did it overnight. It

is good. He's making it better by adjusting it to me. Do you think one of these tools can that's built on using let's say 11 Labs agent feature? Do you

think they could become a business that eventually ends up on Y Combinator? Are

we looking at stuff that's always going to be too small?

>> I mean, honestly, uh we we would I I think that even founders who uh have access to a lot more capital or better resources. Um we've been working with a

resources. Um we've been working with a lot more alums in the batch now. Daniel

Khan, for instance, who create co co-founder of Cruise Automation, he's in the batch. And uh I'm pretty excited

the batch. And uh I'm pretty excited about it because whether it's like your first time or your fifth time, like being next to a bunch of people who are moving extremely fast, like that that's

probably the biggest thing that second time or multi-time founders maybe struggle with is that like the next time you have plenty of resources, but the one thing that's actually the most

important is time. And so there there's almost the only thing that matters up front is like can you speed up? And then

I I do think it takes a village to actually properly speed up.

>> I I do admire that that's always been a Y Combinator thing that startups equal fast growing companies and that's the that's the difference. But Gary, what I mean is can these apps that are essentially rappers that are essentially

built on something else turn into real businesses? I guess in in your recent

businesses? I guess in in your recent podcast, someone made the point point that these are basically MVPs. And once

you get the proof that this works, you have to really have real engineers and maybe they're using cursors, so they're much more advanced without than they would be without, but they it's not enough to just build these simple tools.

>> Ideally, the founders themselves are actually really correct engineers and then, you know, you you basically 20x yourself by um being able to use these

tools. But if you actually learn how to

tools. But if you actually learn how to prompt and you learn, you know, it you would literally be a 100x engineer, right? You'd be a 200x engineer. You

right? You'd be a 200x engineer. You

take your 10 and drop a 20 on top of that and you're 200x. And that's like the most powerful thing in the world is to be able to do so much more with way, way less. Um, and then that's why this

way less. Um, and then that's why this is sort of the golden age to be trying to create products for other people.

like I you know I think it's like astonishing and then it's sort of it's yeah it's it's sort of like there's there was an earthquake you know you're

walking around in the in San Francisco and there's a skyscraper chopped in half and like all the water manes are busted and then everyone's walking around and they're just like oh wow weird like why

is that happening and it's like guys there was a 7.5 you know earthquake that just happened like and people are acting like it didn't happen. Um, so yeah, I I

I think it's strange. I mean, it's 2025 now. Um, and then I don't know, like the

now. Um, and then I don't know, like the the majority of things in our lives dayto-day, you could still argue are like not quite touched by any of that stuff. And that just means that

stuff. And that just means that literally anywhere you go, like you could do something that is better. And

so this is by far the best time in the history of startups to be starting one.

>> That really is true. actually you're

really seeing more and more people getting into it. I was starting to get Gary a little like down on startups because people the the energy was not on it and now I feel like the energy is so

on it and I still want people to do this right and to not end up with these with these products that people don't want to use the Y combinator phrase.

>> Yeah.

>> All right. Thanks so much for doing this. I I love that you're more and more

this. I I love that you're more and more public. I wish that on Twitter I I love

public. I wish that on Twitter I I love that you care about San Francisco. I

wish on Twitter you would talk more about this type of stuff.

>> Absolutely. I will. I appreciate the feedback.

>> I like your thinking. I love, by the way, I love as someone who lived in San Francisco for a decade and and just felt like I moved out because nobody loved about loved it. I feel like it needs the love that you have and a few other people have. But I like your insight a

people have. But I like your insight a lot. Um, bring it in to other places.

lot. Um, bring it in to other places.

Thank you.

>> Thank you so much. I appreciate that.

>> Hell yeah. I'm looking. Thanks for

having me.

>> Thanks. Bye everyone.