0:03
So, you were talking about AI native companies, and I do really understand the capabilities because it's really shocking.
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0:10
But, um how do you look at the cost efficiency?
0:13
Because nowadays AI is getting more expensive, so perhaps you might be able to do what an engineer can do uh with AI, but when when did the economics come in?
0:26
Because sometimes it can cost even more with the tokens than the engineer that gets it first time right?
0:31
>> The first answer is you should just join YC, and you'll get a million dollars of free tokens, and then office for many million dollars more.
0:37
Uh the second answer is the cost of intelligence is coming down so rapidly that even if it that is not true today, it's going to be true in 6 or 12 months.
0:45
Like it's a 10x cost reduction per year, roughly speaking, for the same intelligence.
0:48
It's something we tell our founders not to worry about too much because it will just solve itself with time.
0:54
>> I think an engineer today with a model is like yeah, 1,000x better than an engineer without AI. >> Yeah.
1:00
>> Would you Would you not use it?
1:02
>> I think a year ago it might have been reasonable to say, "Well, a given engineer for a particular task might be more cost-effective than a model."
1:09
I think that is There is no chance that is true today if you're using the absolute best intelligence.
1:15
Uh yeah, I'd probably go that far.
1:15
I just don't think there's a single programming task that a human is is more effective for a human to do than a model to do. >> Yep. Hello.
1:21
Thanks for this opportunity.
1:23
A lot of countries, especially in Eastern Europe, have underdeveloped startup stage and underdeveloped startup communities.
1:29
Do you have any on building especially a community of founders?
1:32
Like not being a founder of a startup, but being a founder of a community.
1:36
How to build that from scratch? Thanks.
1:40
>> I was going to hear you to say move to SF, but uh If you want to optimize the chance of your startup, you should probably join an existing community versus having to create it from scratch.
1:49
And if you cannot go to SF, of course that's the biggest place to build a startup, but go to London or Paris.
1:55
like there is where there is at least a critical mass of startups.
2:00
So that you can surround yourself with the great founders that are going to make you better founders.
2:07
If you are the only one in a in a city, it's very difficult because you don't have any peers to push you forward.
2:14
And like the people who don't understand your life are going to hold you back.
2:17
>> Gray and I sort of experienced this.
2:17
Um so I started a company in 2011 called GoCardless.
2:22
It did Y Combinator actually came back to London.
2:25
Um Gray was like our number two hire or something like that. Number three hire.
2:32
Um And GoCardless and a a small number, but really like less than five companies were like the the kernel of the the um London startup ecosystem.
2:46
Like you can kind of trace from GoCardless this like family tree to many many many dozens of other companies.
2:52
And TransferWise is in there, Monzo's in there, and it's like it's kind of amazing how it spreads.
2:55
But in those early days um So the direct answer is find a really great startup that embodies the startup culture and join that.
3:03
But in the the early days of any great startup, it feels like a cult.
3:09
Like it feels like you believe something that no one else believes.
3:11
And if you said it out loud outside the room, people would laugh at you almost.
3:19
But you like have these collective set of beliefs and behaviors and and ways of working that that make you extremely effective.
3:26
Um and so I just try and find that basically.
3:30
>> And the reality is there is always going to be one global hub for startups.
3:32
And that will attract the most ambitious people.
3:40
And the companies that are going after the biggest vision.
3:43
And you probably want to be there.
3:43
It doesn't stop there being other smaller regional hubs.
3:50
But for a lot of companies and for the most ambitious founders, you definitely should be considering San Francisco at the very least.
3:57
>> My question would be related to the thing you've spoken about the artifacts we should be pumping into AI.
4:02
So, we as founders should pump everything we could possibly find to AI.
4:08
Investors would be doing the same thing.
4:11
Do you think that we leave too much judgment to AI, and where is that gap where we should stop and leave our judgment to us and not outsource it to AI? Thank you. >> Yeah.
4:23
So, I mean, there are many ways to answer your question.
4:25
I think we can't answer all of it like for sure.
4:27
Like, one thing I've been arguing with with Nico during the batches how much AI should write for us, because I think there is a direct like correlation between the amount of thinking you do and how you write.
4:39
So, I've personally been writing most of the things I've been writing so that I don't delegate too much to the AI. That's one thing.
4:47
The other thing that we've been talking about is I feel like at YC, there is so much emphasis on how AI can give superpowers to partners and therefore can be shared with founders, and that's been the most mind-blowing [clears throat] thing I've experienced at YC is the speed at which this organization built tools to empower all all of the people who go there.
5:12
I think though that something that's super important for YC as an organization is to think about the thing that AI is not going to be able to replace, and there are a few things like, you know, founder well-being is incredibly important, and putting more emphasis on how can we help founders take care of themselves.
5:33
Community is also something where, you know, AI is not going to help.
5:35
Knowledge sharing is something where AI has where YC has a unique thing where you have 200 companies that are obsessing over how to make the most out of AI and there will never be content available on the latest thing you can do, but you're surrounded with people that are obsessing over this.
5:53
And so, one of the things we've been talking about is, you know, not relying not obsessing too much over what the AI can do in order to empower all of you, but also what is AI not able to do and how do you make sure that you're excellent at it because sometimes I feel like you can be blindsided if you're only looking at it in in one way.
6:17
>> In the next months, everything can be done internally.
6:19
I mean, every tool can be built internally and instantly.
6:21
What is the purpose of uh B2B products anymore?
6:26
Like, if you can build everything by yourself.
6:33
So, then everything that matters is just critical infrastructure.
6:34
So, what will happen with B2B products? >> Um yeah.
6:38
Uh So, I broadly agree with the premise of your question, but I would um reframe it more as a spectrum than a binary um one or the other.
6:54
Um and the reframe I would take is like, what's the hard bit?
6:58
Like, your startup has to have a hard bit.
7:03
And 10 years ago, writing a lot of software was in and of itself the hard bit.
7:08
That is not hard anymore.
7:08
And so, you have to have other things to be hard to to like to have any kind of durability, you have to have something that's hard.
7:18
And that might in some cases just be like brutally hard B2B sales into some industries.
7:23
Others, it might be a regulatory barrier.
7:24
Like, getting a banking license almost killed me. That's pretty hard.
7:28
Or figuring out the physics of like spaceship launch, pretty hard.
7:33
Actually, most hardware in and of itself is just like hard.
7:34
Um the the atoms are at the hard bit.
7:39
And so, I'd just be thinking like, on my spectrum of like this is very very easy versus very very hard.
7:42
I'd like I just shy away from the easier end of the spectrum and just like pick bits that are harder and more ambitious because it will make your startup more durable.
7:49
So, I would just absolutely not start something like Calendly today or Partyful or maybe Partyful actually has a network effect, but certainly Calendly or like DocuSign. Basically dead.
8:00
Like I think really pure software is just not um it's just too easy to replicate now.
8:09
So, just ask him so where's the hard bit?
8:11
>> You're recording um uh office hours, you're recording interviews, right?
8:15
Um it seems like you're trying to do like what you're trying to do is to make Y Combinator a AI-native company, right? >> Yes. Yes.
8:24
>> What happens when the AI is a better YC general partner than you are, right?
8:29
What are you going to do?
8:29
Are you going to be selling Birkin bags or what?
8:33
>> [laughter] >> I think as Matilde said, we're going to be therapists. >> Okay. >> Yeah.
8:37
So, I think there are I like first what I said I already believe in, which is there are so many things that the AI will not be able to do.
8:43
Like just so you know, um and I think Nico Kukcan tell the story as well as uh there is a new feature that's being experimented right now with YC where you can book an office hour with a virtual partner.
8:54
So, you can literally like Nico was able to do an office hour with himself.
9:00
Currently it was really weird. >> awkward.
9:02
>> Um so, I think there is a part of it which is like, you know, therapist, community builders, like blah blah.
9:06
But there is also uh Garry Tan wrote an excellent post a few weeks ago about about the power of witnessing, which is the fact that you have someone in the room with you that acknowledges what that what you're going through is something that's normal is incredibly powerful.
9:25
It's an incredibly lonely job and a robot doing this isn't as helpful.
9:31
So, it's not just like, you know, the human uh community and well-being and all this.
9:36
I also think that uh there is a power of witnessing.
9:39
And I also think one of probably a misconception I have, you know, new eyes on this because I was a recent partner is you might think that at the scale YC has, a lot of advice is advice they give to everyone.
9:54
The reality is I feel like partners go really deep in understanding specifically your business, your market, etc.
10:02
so that they can give tailored advice.
10:04
And so even if you have a database of 7,000 companies, there is still so much that we don't know about your company specifically and that partners need to do a good job at understanding.
10:16
>> That's always fun to get like a fresh eyes on our what our job.
10:20
Maybe one last uh last one last thing on that, all the partners at YC are past successful founders themselves who actually did YC.
10:30
Uh and there is that maybe that's the witnessing.
10:32
We know what you are going through.
10:34
Because we did it ourselves.
10:36
And that's a huge difference with a lot of investors out there who have never been founders before, who don't know what you're living.
10:44
I think that piece is never going to disappear and cannot be replaced by AI.
10:48
>> So, thank you for for your thoughts.
10:48
My question was regarding a research in AI startups because in my personal case I've built a startup while I'm doing like a PhD, okay?
10:59
From which I research like things for improving the product and all this stuff.
11:04
So, how to um know in each moment if it's like better to focus on on the on the on research for improving this this this product uh or focusing more on business like to scale, get more clients and all this stuff.
11:22
>> I think it's an abstract question that don't have uh like right answer.
11:25
Like the reality is what you want to do is always confront yourself to the market in the fastest possible way.
11:33
I was sharing this with one of the groups.
11:37
The The biggest regrets that YC founders have after the batch is not having launched soon enough.
11:44
So, I think just know that you'll always have a tendency to research more, to build more before selling more, and this is a tendency you need to go against.
11:54
And the more you can actually talk to users, confront yourself to the market, and learn, I think the better.
12:00
The Like one thing that we repeated over and over is just optimize for learning constantly, and usually that equates to talking to your market.
12:10
And then if you feel like people are not willing to use what you're doing and it's not something that they want, then go back to building, go back to researching.
12:19
>> The The motto of YC has never changed, like build something people want.
12:20
And to do that, it's a cycle.
12:23
Build, talk to customers.
12:26
Build, talk to customers.
12:26
And one thing that has really changed is the pace at which it's going today.
12:29
That's why today we have like some companies who do incredibly in just a few months.
12:35
Like never seen that back in our times, like companies doing like a million ARR in just by the end of YC.
12:39
It's kind of like unheard of before, and now it's happening because of that fast-paced fast-paced cycle.
12:46
And I think it also applies to research.
12:50
You want to make sure that what you're building is useful to someone.
12:51
Some projects take more time.
12:53
Some deep tech projects, space projects, all of these things of course have different timeline.
13:00
Um so, the advice cannot apply to everyone, but at the end of the day, you want to make sure you build something people want.
13:07
>> It's often useful to inspect your own biases on this one as well.
13:12
A lot of founders are a lot more comfortable building than they are talking to customers.
13:16
And the idea of going out to the market and trying to figure out whether or not they're actually building something that people want is terrifying because it may be that you go back to square one.
13:25
That all the work that you've done so far, you were working on the wrong thing and there's a lot of loss aversion that will dissuade you from doing that.
13:33
But if you want to build something that people want, that's the thing that you actually need to do.
13:39
So if you feel very comfortable in research, anytime that you're asking yourself this question, you should just be aware that you probably have a bias towards the like build or research part and you need to dial up the amount that you're talking to customers.
13:54
>> I get this advice like 15 times a day.
13:54
I think Greg put it more eloquently, but like basically that.
13:58
Get out of your comfort zone.
14:00
>> Uh so what do you think happens next with the US export restrictions on frontier AI models like Fable?
14:05
Uh do you think we will end up in a world where only US citizens can access those models?
14:13
>> I mean we are we don't know more than you do.
14:15
Like we see the news the same way you do.
14:19
So I hope like I mean for the those of us who have tried these models before they were blocked. Yeah, they're crazy. Crazy good.
14:26
Can't wait to be able to use them again.
14:29
>> It's a wake-up call for the rest of the world.
14:31
That it was more dependent on the United States government than it realized.
14:36
Like I think there were a lot of people that woke up to that news and were like, "Shit, I had no idea that a decision in the Oval Office would affect my ability to access these models."
14:44
Uh and that will create demand for like competitors and like sovereignty over AI and inference that it wasn't there before.
14:55
Like that's definitely created a market.
14:58
What happens specifically in the US over those models and like what time period that happens?
15:03
Yeah, we have no extra insight on that.
15:06
>> My question is like uh Sam Altman like a year ago was talking about in the next few years we're going to have like a one-person billion-dollar company.
15:16
And uh what's like the what's like the sentiment in YC about like co-founder or like going solo.
15:24
>> Um in theory, will you be able to create a billion-dollar company with one person? Like yes, probably.
15:32
But um you the way I see adding people is like um sort of marginal cost benefit.
15:43
And the marginal cost of adding one person is will be relatively speaking low compared with the benefit you get from them.
15:52
And it just seems illogical that you would unless you're trying to break the record of getting a one-person billion-dollar startup, like you'll just be more successful by adding a second person, I think.
16:01
But that ratio between the marginal cost and benefit actually changes quite dramatically as you add more people because you add coordination problems.
16:09
So adding having a co-founder, you you talk to each other.
16:12
A third, like it's Metcalfe's law, right?
16:13
It's the the the um the square of the nodes is the all the connections.
16:17
You have to maintain all of these different connections.
16:19
So by the time you get to 100 people, it's quite hard to keep everyone on the same page.
16:23
At 2,000 people, it's really, really hard.
16:25
And so I think what AI is going to be good at is compressing companies to keep them down below Dunbar's number, so 150 people, where you can like maintain relationships with everyone pretty successfully.
16:35
But I I think the I just don't think there's there's any point in trying to run a uh single-person company. And I've seen this.
16:43
We we keep funding them and you know, some do well, but statistically they do worse.
16:47
And uh we ran the six-person I ran the six-person experiment this batch.
16:51
We funded a very, very, very strong um solo founder who wanted to build basically self-improving autonomous agents.
16:56
They'd all communicate with each other.
16:57
He said, "I don't need a co-founder."
16:58
And what happened is he got sad. Right?
17:03
Like 6 weeks into the batch, he's like had a crisis of confidence.
17:05
He's like, "Is I'm not sure this is working.
17:07
Is it the right direction?"
17:08
I'm like, "Dude, I mean, I can be here for you, but like this is what a co-founder's for.
17:12
It's someone to to pick you out of the gutter when you're feeling down or like when you're hyperactive and manic, they like pull you back down to earth and they modulate you.
17:21
That's certainly what my co-founders did for me.
17:23
And so sure, theoretically I think you could do a billion-dollar startup with one person.
17:29
I don't think it makes economic sense.
17:30
I think the utility you get from adding a second person will always outweigh the cost at that level unless you're trying to break the record for some dumb reason.
17:37
And I think they're just very very very valuable.
17:40
But I do think it'll compress companies down from 2,000 to you know, 100 or 50 or something.
17:45
>> And maybe to add on what AI is actually changing on this topic is I feel like now it is possible to go from being an average engineer to being in a great engineer, not knowing how to sell to being good at selling.
17:57
And I do feel like the complementarity of skills is less important.
18:02
So as Tom said, I think the fact that you have a co-founder is just as important for all the reasons you mentioned, but I wouldn't obsess over less making sure that our skills are complementary.
18:13
Instead, just make sure that when you're sad, you're very happy talking to this person and that person can bring your morale up.
18:22
>> And just to make sure it's clear, we do fund solo founders, too.
18:24
It's not we have nothing against them.
18:26
We just found that it's easier as founders to have co-founders.
18:30
Uh and so it's solo founders, the bar is higher. >> Yeah.
18:36
At risk of rambling on, I I want to give like 30 seconds on how to pick a great co-founder.
18:40
As Mathilde said, like someone who, you know, can help make you happy when you're sad is is a great start.
18:45
I would think about who is the um smartest, most determined, hardest working person you've ever worked or studied with and then add in like a integrity layer. Like do you trust them?
18:59
Are you have Do you have a line values?
19:01
And would you be If you're in a competition, would you be scared to be on the other team?
19:05
Like that's the kind of person you want to go for.
19:08
And I All the complementarity stuff, I don't actually don't matters at all.
19:11
Like, the biggest mistake I've seen is technical co-founders thinking they need a business co-founder.
19:15
I think that's almost always a massive mistake.
19:17
If you're a technical person, I would find someone who has is as deeply technical as you and who you work great with and who's like determined and smart and a high integrity, all those things.
19:26
The business stuff is actually very easy to learn, I think.
19:34
>> Hi, I have a question about the the future of VC funding.
19:35
So, that um now new employees are um less necessary than they used to be and also the opportunity cost of having investor meetings has also risen a lot.
19:49
Uh so, I'm wondering, does the old path of seed and then the the various VC rounds still uh is that still as important as it used to be or is there has there been a a change where new paths are possible?
20:01
>> You mean you can build the company without VC VC money? Uh why not?
20:05
I mean, I don't think there is a rule here.
20:07
I think for a lot of companies uh that want to grow fast, having access to capital can still help a lot uh even even software companies because when you're going to consume these tokens, it costs money.
20:18
And so, if you can um leverage uh the VC money to simply grow faster and do more, it may be worth it.
20:25
Now, if in your case you found out that you have uh enough whatever, like tokens or access to AI to move faster with less money, that's great.
20:38
And there is some tools here.
20:38
Like, I don't think founders need to raise as much today as they did 5 years ago to achieve the same thing.
20:44
Definitely not to achieve the same thing.
20:47
But, it's the same world for everyone.
20:50
>> Yeah, I would go I agree and I'd go back to the hard thing.
20:53
Like, if you are just producing the same software that people produced 5 years ago, you can absolutely do that for way less money now.
20:59
But, unfortunately, it is um much, much less durable and defensible.
21:05
And so, what I think's what AI is doing is it's enabling founders to attack harder problems.
21:11
But, as those hard problems get more and more ambitious, then you're like, "Well, I'm the capital needs to get there uh commensurately go up."
21:17
So, it's like the guy building the nuclear reactor Did I mention this?
21:21
Or is it a We funded a guy building uh small nuclear reactors, and he's going to have to raise something like $800 million next year.
21:27
And it's just like it's really hard to build nuclear reactors without tons and tons of money.
21:32
Similarly, it's hard to like launch regulated banks without tons and tons of money.
21:36
So, I think startup ambitious startup founders will just try and do harder and harder things, and that will require in a lot of not all cases, but in a lot of cases, capital.
21:44
And I That's where venture capital will come in.
21:45
And I actually think that's great for humanity because we will get solutions to harder problems, like curing all disease um and producing like infinite abundant energy.
21:56
>> Um so, I actually want to bounce back somewhat on that.
21:58
Uh you've mentioned that pure software startups are limiting in impact, and I'm sure with in YC, this is one of the main questions is like, "What are the moats that you're betting on?
22:07
And what are the moats that you disagree with internally?"
22:12
>> I mean, at the end of the day, I think YC funds people.
22:13
I think this is the biggest moat like by a wide margin.
22:15
I think it was the case before.
22:17
It's probably just even more true today, and I don't think anyone at YC disagrees with this.
22:25
I don't know what we disagree on.
22:26
>> I think every like on the disagreement Disagreement is good. That's interesting.
22:30
Like a bunch of what companies we fund, like companies I fund, if uh Tom meets them, he's going to fund them, too. But, there is a few.
22:38
There is maybe I don't know, maybe 30% whatever number that I'm going to fund, Tom would not fund them.
22:46
And so, that's the disagreement. And that's cool.
22:48
Like we all have like going to find things we like better than others, and all of that is cool. And so, that's cool.
22:56
On what we fund, honestly, it's all depends of you, like what do you apply with.
22:59
We don't dictate what you should work on.
23:02
You figure it out with a new because we think you are the right team.
23:07
And about the third of companies like last batch, a third of our company like in our in our pod pivoted.
23:14
Change their idea anyway.
23:16
And so the bet is always the founders.
23:18
>> Yeah, I mean we can give an example.
23:19
There are so many examples of this.
23:19
The Brex founders with Brex just sold for $5 billion.
23:23
The Brex founders applied when they were 19 years old and they were brilliant.
23:27
They as 15-year-olds I think 15 or 16-year-olds in Brazil they'd started a payment network and sold it for something like $50 million before they were 18.
23:36
Like technically brilliant, amazing at distribution marketing the business.
23:41
And the idea they applied with was virtual reality sunglasses made out of cardboard that you could build at home.
23:48
And it was like you guys can work whatever you work you can work on whatever you want.
23:51
Like those guys could literally have applied with any idea and we would fund them.
23:53
So if the founding team is strong enough like it just doesn't matter.
23:57
I think because we bet on great people to figure it out.
24:01
And if they figure out they need durable modes, great.
24:02
And if they decide that there's a really high impact software business that they should pursue, that's also great.
24:07
Um ultimately we invest in people.
24:11
>> Do you think people will be thinking about which models they want to use or do you think it will kind of just be automatic behind like this like interface with the AI?
24:20
Like people just be interacting with it not caring which model they're using underneath?
24:27
>> Very quickly it will be automatically routed for you without any perception your just be able to go down.
24:30
The big labs will do it and open source routing models will do it and it like and the time frame on that like 12 months probably is my guess.
24:40
Um you'll just type a query and it will decide what level of intelligence to route it to internally or it will like have a smart model and then spawn a bunch of uh sub agents which are like cheaper and more effective models.
24:50
>> It's already the case today most of the time except of course if Open AI is not going to use the models of Anthropic.
24:56
So if you are using ChatGPT directly, of course it's OpenAI models.
25:00
But, if you are like a business, you have your customers don't care.
25:04
>> When YC selects companies, how do you evaluate in B2B AI a real wedge from an AI wrapper?
25:14
>> I mean, AI wrapper is this like derogatory term that is kind of meaningless.
25:19
Like >> Everything is AI wrapper.
25:21
>> Everything is powered by AI.
25:21
Or like most ideas that we are funding, because it is the first time anyone has been able to attack that problem, have AI at their core.
25:34
And like whether or not they are adding a lot of value on top of the core model, like yeah, that matters.
25:40
Um and so like if it's really like that thinner layer, we're going to be looking at the team.
25:46
We're going to be looking at like how that is going to evolve, whether or not they're a team that's going to figure that out, whether or not this is a problem space where there is enough depth to go really.
25:53
It doesn't matter how deep they go.
25:56
Some people are still going to call it an AI wrapper and snicker to themselves, right? That they're so clever.
26:01
>> Some of the biggest companies today are AI wrapper. >> 100%.
26:04
>> Before then they were SQL wrappers or S3 wrappers, like >> As you've mentioned before, given the state of AI, the sort of cost of taking an existing solution and implementing it in your product has gone down.
26:16
So, in terms of founder adding value to a product, the way I see it, there's two ways of of adding a value since the cost of implementation has gone down to essentially zero.
26:26
Uh first one is actually moving state of the art in one area and building a specific technical improvement that actually helps people and gives you that margin.
26:40
And the other way is essentially selling the product better.
26:42
And has this increased capability of models and helping founders ship products uh change the ratio in which a sort of YC batches uh, change the ratio of like, for example, super technical founder working on a very specific niche technical issue in the batches and actually people trying to market their existing solution better.
27:08
>> Uh, I'm going to summarize.
27:11
Is distribution like having a deep technical wedge can be really important or distribution can be really important.
27:18
I agree on both those points.
27:18
We have We have founders in both camps.
27:21
We have this guy with a MIT PhD in nuclear physics building nuclear reactors.
27:26
We have two guys who worked at a satellite company building re-entry vehicles to continue space manufacturing.
27:32
We have guys doing radio frequency test equipment cuz they were the radio engineers on latest SpaceX launches. And on and on, right?
27:40
Like deep technical expertise.
27:41
And we have people who are self-taught vibe coders, really honestly.
27:45
So, I think that is that second group is like, it's made us re-evaluate how deeply technical do we require founders to be?
27:52
And we don't know the answer yet.
27:55
Um, we were pretty biased towards founding teams with at least one like quite deep software engineer on.
28:02
And we're testing whether that's still true.
28:04
I think you still need to be very smart and determined and like a systems thinker.
28:07
But it's possible that with AI you don't have Not all companies need someone who's deeply technical, possibly.
28:13
Having said that, we'll fund the full spectrum of, you know, the MIT nuclear PhD to the the um, the people who learned to vibe code in their bedroom.
28:22
>> Uh, so my question uh, was going to be about more like cost and stuff.
28:24
Uh, as a person that's actually wants to initiate in the startup culture and has the motivation to like go all in, basically move to San Francisco, etc.
28:34
Uh, but is from Europe and cannot do that because of visa and budget reasons. >> Wait.
28:42
Of all Of all who's from Europe on the stage?
28:47
>> For exa- For example, we talked about like open weight models and stuff.
28:49
And how can like a broke student compete with people that have like API money to actually pay for these models versus like having a lower intelligence model etc.
29:01
What would be your like >> Are you a Are you a student? >> Yes. >> Okay.
29:07
So, out of these event, you'll get 25K plus over 25K of credits.
29:14
>> Oh, I didn't even know that. >> That's great. Congratulations. Congratulations.
29:17
>> everyone here, if you are a student, I think with a valid student email >> of >> I don't know how we're going to do that.
29:22
Probably going to ask the agent.
29:23
>> [laughter] >> So, thanks to our gracious sponsors at various different model labs and hyperscalers, you're getting $25,000 of credits to use each. So, that should help.
29:34
>> [applause] >> So, then what would you recommend as like a European builder then? That's my question.
29:42
>> Go build something cool.
29:44
We've now solved your biggest problem.
29:45
You've got to do the rest, buddy.
29:46
>> Uh hi, my question is regarding early decision.
29:48
Like you officially state that early decision applicants are treated the same as standard ones.
29:54
But as a general partner, when you're looking through that application or that interview, do you have a sort of extra checklist or do you see something extra from them or is there anything that you expect from them?
30:05
Because for someone that's going to join the batch a year from now and he's applying right now, do you do you want to see any additional drive or additional motivation for that?
30:15
Like what is sort of that personal factor do you that you want to touch on in an interview when you're interviewing someone of that sort? Thank you. >> I don't know.
30:23
I guess all of us are different.
30:26
A year from now sounds seems too long.
30:29
But you know, we do four batches a year.
30:31
Each of us only work alternative batches.
30:34
So, I could look now at funds for fall.
30:38
Because that's the next batch I'm doing I'm going to do.
30:42
Now, the question I'm going to ask myself is that why early decision?
30:45
Like, why would I I not wait next application cycle and would I fund you today?
30:50
And so, that's kind of like that bar and there may be many answers to that.
30:54
Maybe uh maybe if you we don't fund you now, maybe you'll find a job and because you cannot afford not having a job and you have to decide now.
31:02
I don't know what's that could be.
31:04
Uh but if it's a year from now, I don't think I would fund you or maybe the bar is way higher.
31:09
>> We want to understand why you need early decision, right?
31:11
We have that question on the application.
31:13
And we read that answer, right?
31:16
Like And for some people, it'll be a very legitimate reason, like And for others, it's like, "Yeah, I'm like really excited to do a startup, but like not so excited that I want to drop out.
31:25
Like I'm saying I'm really committed, but like not committed enough that like I don't want to do another year and a half of school.
31:30
And that's going to make us question whether or not like you're going to have what it takes.
31:36
>> Thank you so much for the amazing day.
31:38
Two questions about what happens during the batch.
31:41
What are the common traits and habits of the top-ranking startups?
31:43
And second, you mentioned you've updated the user manual.
31:48
What are the non-obvious stuff except um base that are changed that have changed?
31:55
>> The most successful founders um launch early and often.
31:58
Like That is the biggest thing by far.
32:00
The The founders, for whatever reason, are too theoretical.
32:05
They're too in their heads.
32:07
They're too afraid to put something out into the world like rejection for possibly the first time in their life ever.
32:12
And so, they convince themselves that just a few more weeks of research or a few more weeks of building or whatever is like a smart thing to do.
32:20
And it's just not a smart thing to do.
32:22
Um there's a great tweet from the founder of Cursor showing all the times he launched on Hacker News.
32:29
And it's like launch zero upvotes. Launch two upvotes. Launch two upvotes.
32:34
Launch sell to X AI for 60 billion dollars.
32:38
And it's just like kind of insane that someone like him is just is willing to put himself out there again and again and again.
32:44
So, just launch early and make contact with the real world and then get data to like update your plan.
32:51
Startups the problem that very smart audience like you got you're all handpicked to be here.
32:59
Like we had many thousands of applications and we picked you to be here because of all of the impressive things you've done in your background.
33:05
The problem though is many of you have are in environments where like sitting in a library and thinking really hard about a problem is how you get the top grades.
33:17
And that translates extremely poorly to startup success.
33:19
It turns out humans are really bad at predicting the future.
33:24
And instead I think startups are like an extremely empirical exercise where you need to come up with a hypothesis very very quickly and then run a test with the real world to see if the data you get back meets your hypothesis or not.
33:36
And if not, you change approach and running that cycle is like the the key activity of an early stage startup.
33:40
It's not sitting in a library thinking really really hard.
33:43
So, basically launch early and talk to users.
33:46
It's snappy so we made a a catchphrase out of it.
33:51
>> And set really ambitious goals.
33:53
And like keep reassessing them every 2 weeks and hold yourself accountable to them.
33:58
Like and keep overwhelming the biggest actual problem that your startup faces.
34:03
Like the best founders every 2 weeks we meet them, it's a new problem because they've overwhelmed the last bottleneck.
34:10
And like you know, we chat through and we agree like okay like yeah, that's the biggest next thing that you need to go and focus on and they go and like throw everything at that and they overwhelm it and they make progress and come back and now it's another bottleneck.
34:20
So like a like tight timeline where you are constantly like reassessing what the most important thing that you need to be working on is and throwing as much of your focus at that rather than being distracted with the hundred other smaller fires that you could be thinking about.
34:37
>> Hi, you've mentioned the journey on becoming an AI native company and with some processes such as rewriting the rulebook with better advice.
34:44
How would you say you define key success metrics that you implement for AI?
34:49
Because normally for an LLM it's mostly about reading success and error about for example previous batches of advice you've given and also maybe taking this this question more generally, what would be a key advice you would give in us when we use AI as an advisor and how it could assist us successfully and define some guidelines for AI to assist us in our journey as to become a founder.
35:16
>> I think the one of the biggest mistake you could do is just to use AI and just look at the result and move on.
35:22
Either you use it or you are not satisfied with the result and you move on.
35:27
I think a big thing you know what Tom presented was that cycle. Self-learning cycle.
35:33
And I think that's one thing people like when people hear like, you know, everyone says like AI is putting so much slope. It's true.
35:39
Like the vast majority of AI output is bad.
35:44
But once you start having that self like that loop that feedback loop once you start having an harness that actually memorize everything it tells it, that changes, that adapts to skills, once you start investing in that in building that the results are completely incredible.
36:01
Like in a matter of weeks it's can become game-changing for your company.
36:08
>> Hey Tom, this question is for you.
36:10
You have did an amazing presentation. So that was great.
36:12
I have a question that I think most people in this room have about the AI native company.
36:16
I fully understand and I think everyone understood because of your presentation.
36:23
However, how can you actually practically start and building the structure to build that AI native company.
36:30
Like do you go on Claude code and tell him exactly everything that you told us because we understand the idea, the concept, but in terms of how do you actually do it? Um so, thank you. >> Thanks.
36:44
[snorts] Um I'd pick a single loop, basically.
36:45
So, I Presumably your company is small if you started a company. >> Yeah.
36:50
I mean, I have a company and I want to apply what you said and that's why I'm asking this. >> Cool.
36:55
Yeah, I'd I'd pick one part.
36:55
I wouldn't try to do it all.
36:57
Like So, first of all, try to make all the information legible, readable, right?
37:03
So, like it's your emails, it's your Google Drive or whatever, your customer support tickets.
37:07
I'd try to make that like queryable to the agent and you can use something like Obsidian or G Brain or there are a bunch of other tools you can use.
37:16
And then I would basically pick a single narrow um process and that might be like after every sales call, I should send a follow-up email to the customer with the key points that we discussed and the follow-up.
37:30
That's like a dumb example, right?
37:33
Um a more sophisticated example might be like during every sales call, I want it transcribed and any um product ideas, I want an agent in the background to build me a prototype of that thing so that by the end of the call, I can demo it to my customer.
37:48
So, I basically pick something really, really narrow.
37:52
Try to implement it, see if you like it, see if it's good and if not, just improve it.
37:55
Just But pick a narrowest possible implementation where you can see value. >> That was perfect. Thank you. >> Hey guys.
38:02
Uh let's say you guys are restarting your startup from scratch.
38:06
So, looking back in the days and restarting an AI native company, what is the last thing you guys would automate or what would you never automate at all? >> Talking to customers.
38:18
>> I think that is what kept me focused on what was important and it's the last thing that I would trust it was the thing that meant I was the person that was closing the loop and had all the context on like what it is that we should build.
38:31
Uh and I never wanted to stop having that information.
38:37
And so like delegating that's the last thing for me.
38:41
>> Even even if you are like self-serve PLG you talk to customers.
38:45
Not all of them, but you need that direct exposure.
38:50
>> I also think that you don't want to delegate talking to your co-founder.
38:53
Like this is the main reason why um companies fail during the batch. Co-founder issues.
38:58
And so just have real conversations with them. >> Uh thank you.
39:03
My question is about pivoting.
39:07
Uh I think we've consumed advice from YC that you should pivot uh go do something that is directly home.
39:14
Uh how would you update that advice now in the AI era that uh now that pivoting is way cheaper uh etc. etc.
39:21
And in and in uh more specifically even if you have revenue and users and you're profitable etc.
39:30
>> Writing software is cheaper.
39:30
Pivoting means throwing away a good chunk of like what you've built which may be the hard stuff as well.
39:36
I'm not sure that's got particularly cheaper.
39:40
It's really hard to give a like general answer to this one.
39:42
It's like one of the like primary things that we would always say, "Hey, come and speak to us directly." to YC companies.
39:50
I think about this from a like framework perspective about like having a hypothesis.
39:54
I have a hypothesis that like this is the right business to build.
39:59
The world is going to look fundamentally different in 5 years time.
40:03
And then have a load of sub hypotheses that are like this is exactly the right product to be building.
40:06
And all the information that I'm gathering from the world when somebody says, "No, I don't want your shitty thing."
40:11
is like extra data testing those hypotheses.
40:14
And it it's only when I've got real evidence that my hypothesis that the like fundamental of what I was trying to build was in fact the wrong thing that you should pivot because you have genuinely exhausted all of the options, right?
40:34
Now, normally that's not what happens.
40:36
What happens is you run out of enthusiasm.
40:39
Like you're working on something, the like kernel of a good idea is there.
40:43
It's not exactly going to sell itself because it's a long way from product market fit.
40:47
You suck at sales and you keep getting rejected and you get sad.
40:53
And as a result, you think, "Oh, like maybe this is the moment I should pivot.
40:57
Maybe it will be so much easier if I went and worked on this like totally other idea.
41:01
The grass might genuinely be greener over there."
41:05
And that generally isn't a good way to pivot.
41:07
The grass will not be greener over there, particularly if you're pivoting from something that you are deep in into something that you are super shallow in.
41:17
Because what you will find is there are a whole load of other problems that you just weren't aware of and it's also going to be really hard building something over there.
41:26
There is another good version of pivoting, which is that through working on something that turns out to be really hard, you are exposed to an even better idea.
41:36
You're working this kind of, you know, what happened with GoCardless, right?
41:40
Like you're working on like collecting payments for sports teams and sports teams turns out don't really want this.
41:46
The problem is not acute enough.
41:46
But the core of what you're building about getting access to collecting payments, you get a bunch of users that say, "Well, I I kind of would like this for my business, just not for my sports team."
41:58
And there's a much bigger idea that you've been exposed to and like that's the one that you want to run after.
42:04
But those pivots where your customers pull the pivot out of you tend to be easier ones to make the decision about making.
42:11
Normally we're talking to founders that have that are getting sad and and the question is like, does this founder need a pep talk or have they genuinely exhausted either themselves or all of the options in terms of like turning this into a successful company? >> Okay. No pressure.
42:26
So, this is a question for Tom and I suppose that the other people on stage might share a similar view as well.
42:33
It's about how um in the future all the gains from AI will accrue to a small number of high agency people.
42:41
Do you feel like Do you think high agency is a trait you can really build as a muscle you can build or is it just you're born with it or not?
42:48
>> I think high agency is basically a belief that your actions are going to produce output.
42:54
Like you actually going to have impact. Right?
42:57
Like um and if I were trying to develop that in myself or try to teach like a child to do that, I think I would point them towards projects where they could like that seemed hard enough to push them but like tractable enough that they could actually like like see some output and then just like continually make that harder and harder and harder.
43:22
So, I just like pick something that seems quite difficult and try it.
43:28
And that might be a side project and to keep yourself going I would probably try and find a co-founder.
43:31
And at some point this would look like doing a startup. Right?
43:34
Like find a friend who thinks really really smart and determined and together see what come up with an idea of a side project to build that seems like quite difficult but probably not totally totally impossible.
43:47
And then do that and see how it went.
43:49
And then just like if that succeeds, do another one and another one and eventually like you end up building rocket ships to Mars.
43:53
And that's sort of how it goes.
43:55
Like no one actually realistically starts by building rocket ships to Mars. Right?
43:59
They build Zip2 and then they build PayPal and then they build Tesla and then eventually they build the really big thing.
44:02
So, I think that's in the abstract how I would approach that problem.
44:09
>> Yeah, I was going to say I think you I don't think you can teach it, but I think you can get better at it.
44:15
That's pretty much what you describe.
44:15
If you have the kernel there and you some small core from which you can expand, you can train yourself. >> Uh >> It's all good. >> Yes, uh Lukasz here.
44:27
Um so, I see this strange phenomenon in SF recently that every billboard and every plane and every [clears throat] uh balloon Brex um is a tech company nowadays.
44:41
And since building everything became so easy, there's this funny thing that companies just try to gather traction regardless of what they do.
44:54
Um so, I'm just curious, how do you think about standing out in the crowd when you build companies cuz way more companies are being built at least at the early stages nowadays.
45:04
>> We had a nice talk from uh the Brex CEO where he was saying that so Brex in SF, if you've been in SF, uh I don't know, 6 years ago or something, SF was covered with Brex ads.
45:18
And he was basically saying the reason at the point they just bought all the billboards in San Francisco.
45:21
And the way he was justifying it was no one was doing it, so just want to stand apart.
45:27
In order to stand apart, we're going to buy billboards.
45:30
And clearly now billboards are not the thing that can make you stand apart.
45:32
And so, the job of a founder every time is to think about how you can differentiate.
45:38
And if the answer was obvious, then everyone would do it.
45:42
And so, I you know, this is what you need to obsess over, and you'll always have an answer that's better for your company specifically.
45:49
Um I think it's an issue this every billboard in SF is about AI.
45:53
>> During my time, all the billboards were about tech already.
45:55
It's always always been the case in SF. In Boston, >> town.
46:00
You go to LA, every single billboard is about a TV show or movie.
46:03
Just the US has industry towns in a way that Europe doesn't so much.
46:05
But I I really like Matilda down south, which is like you have distribution matters more than ever.
46:11
Like that's clearly true.
46:11
And there the way to get distribution, like the meta game, is evolving so quickly.
46:17
You've just got to figure something out for yourself.
46:19
I mean, the Clue founder found a a way to get reach and distribution, right?
46:24
Like I do agree that distribution is is more and more and more important than it ever was.
46:29
Because it's one of the hard things.
46:30
Like software no longer is the hard thing about building a company.
46:33
Distribution can be one of the hard things.
46:36
>> But remember what mini game you're playing now.
46:39
If you're at the like very early stage, you are playing the mini game of like getting towards product market fit, right?
46:45
Like finding some first customers and figuring out from them what they need and building that.
46:50
And then getting to the point where you need to like put fuel on that fire and like scale it.
46:53
And so when you're looking at those billboards and how companies that have product market fit are getting their customers, remember they're playing a completely different game.
47:04
The way that you stand out from them to an individual customer is by giving them like real like white glove service, by like turning up in person, spending an inordinate amount of time for what is like a small contract, and building something that exactly fits their needs.
47:19
That's the like unscalable thing that allows you to compete with somebody that's putting up a billboard on the highway in San Francisco. >> Thanks, everyone. >> Yeah, thank you. >> [applause]