10 AI Business Ideas From The Queen of AI ft. Sarah Guo

0:00:04 I think it is worth talking about the fact that there are ways to make a million bucks
0:00:06 and then like ways to make a million bucks that could turn into a billion bucks.
0:00:08 Right. And I think we should talk about both.
0:00:10 Are we here? Do we hit record already?
0:00:12 Yeah. That’s the intro. All right.
0:00:22 So what do you mean by that?
0:00:25 You saying there’s ways to make a million bucks
0:00:27 and then there’s ways to make a million bucks that could turn into a billion bucks.
0:00:29 You have my interest. Let’s go.
0:00:30 Okay. Okay. Let’s go.
0:00:33 So I think maybe, and I don’t mean this any dismissive way.
0:00:38 I think venture capitalists are very often accused of dismissing something
0:00:41 as like a cash flow lifestyle business or whatever. Right.
0:00:45 Which, by the way, for anyone who is not in the VC world, you go to a VC,
0:00:47 you say, I’ve got this great company.
0:00:50 I think it can make five million in profit in year eight.
0:00:52 And then after that, maybe we can grow this for another 50 years.
0:00:53 And one day it could be a thing.
0:00:57 And they say, that’s that’s a really nice lifestyle business.
0:00:59 It’s like them saying, that’s cute. Right.
0:01:00 I remember that’s cute.
0:01:02 Yeah. I remember my first time doing that.
0:01:06 Of course, the thing is, is that anyone who actually is an entrepreneur,
0:01:07 including anyone who’s a VC,
0:01:10 they know that you can oftentimes get richer and have a less stressful life
0:01:13 if you have a quote lifestyle business.
0:01:18 Yeah. So I’d say like there’s many type of valid businesses, right?
0:01:21 And then also a lot of things that have become very interesting start very small.
0:01:22 So I want to recognize that.
0:01:29 But I think a reasonable analogy is if you can figure out Internet distribution
0:01:33 and then get, you know, super powerful models getting increasingly powerful
0:01:37 to just do something useful and a niche, those two things together,
0:01:38 that’s like the new drop shipping.
0:01:41 You know how like for maybe seven or eight years,
0:01:43 I’m like too old to know what the exact timeline was.
0:01:47 But there’s a period of time where people are like, oh, you know, I’m an Internet kid.
0:01:50 I’m going to figure out some drop shipping thing and like make my first hundred thousand dollars.
0:01:51 I think this is it.
0:01:54 Yes. So basically for people who don’t don’t really know,
0:01:56 you could go on Alibaba or Aliexpress.
0:01:58 That was like the open AI in this case, right?
0:02:03 So it was like this thing exists that you didn’t have to build, but it’s magic.
0:02:04 Watch this. You could push a button.
0:02:06 You never had to make the product.
0:02:07 You never had to warehouse the product.
0:02:08 You never have to ship the product.
0:02:11 It will just magically appear at your customer’s door, you know,
0:02:14 somewhere between one and three weeks later.
0:02:18 All you have to do is the marketing bit and kind of what you’re saying is open AI
0:02:22 and the other AI companies have built this magic that basically will take
0:02:24 a piece of tax and turn it into a video or a song or whatever.
0:02:26 And if you just do the marketing bit,
0:02:30 you can actually almost like drop ship a product or a service to the customer
0:02:33 without having to make it yourself. Is that the idea?
0:02:35 That is. Thanks for explaining it.
0:02:39 And I think it’s like easier with a few examples, right?
0:02:42 Like copy editing is probably a prototypical one, right?
0:02:50 You can do not amazing, but like reasonable copy generation with these models today.
0:02:54 And so there are a series of companies where you just have some templates
0:02:58 that make it more obvious to somebody writing marketing copy,
0:03:02 how to use these models, and then you have a website with decent SEO.
0:03:05 And then like you add some stripe integration and you’re in business.
0:03:06 What’s an example?
0:03:11 Well, I think like copy AI and Jasper, these companies started this way, right?
0:03:15 And then I have several friends who shipped like AI companionship apps.
0:03:18 Just look at paid apps in the app store by charting.
0:03:22 And some of these people are generating a million dollars of cash flow for themselves.
0:03:24 It’s not because they’re deep AI people.
0:03:29 All right, let’s take a quick break to talk about our sponsor today, HubSpot.
0:03:31 With smaller budgets and sky high expectations,
0:03:33 growth is feeling pretty painful right now.
0:03:35 But HubSpot just announced more than 200 product updates
0:03:38 to make impossible growth feel impossibly easy.
0:03:41 Like Breeze, it’s a new suite of AI tools that will help you say goodbye
0:03:43 to your busy work and hello to better work.
0:03:46 Breeze Intelligence, which will give you the richest, most comprehensive picture
0:03:50 of your prospects and customers, and re-imagined marketing and content hubs
0:03:53 to attract and convert more leads and send your revenue soaring.
0:03:58 Visit HubSpot.com/spotlight to learn more.
0:04:01 >> When you say companion, you mean like a digital girlfriend?
0:04:03 >> Or boyfriend, right?
0:04:07 I think people think that is skewed toward girlfriend in a way that’s not necessarily true.
0:04:12 And you can have your own ethical points of view about whether or not that’s good for people.
0:04:14 But it’s a pretty basic human need.
0:04:15 And guess what?
0:04:19 People want all sorts of different things in terms of niche companionship
0:04:20 and how you might distribute that.
0:04:22 >> And aren’t these quietly very huge?
0:04:28 Can we do some ballpark, give people a sense of the size and scale that these have gotten to?
0:04:32 So there’s replica, I think that’s probably the most well-known one,
0:04:34 which is a digital boyfriend or girlfriend.
0:04:41 They kind of try to say friend, but I think the use case is a little bit more in the relationship side of things.
0:04:45 And I don’t remember their exact numbers, but I don’t think I would be crazy for saying
0:04:48 they’re doing like 50 million a year in revenue.
0:04:51 And I believe she had bootstrapped it for a while, at least,
0:04:53 or raised very little money to get there.
0:04:54 Is that right?
0:04:54 Tell me if I’m off base.
0:04:55 I might be wrong on some of that.
0:04:58 >> Yeah, Eugenia has built a very cash-efficient business.
0:05:00 >> Okay, is that like a code for something?
0:05:01 Are you an investor?
0:05:03 >> No, I’m not an investor.
0:05:05 >> Dude, you just said everything without saying a thing.
0:05:09 It was basically like your friends are there, you know the number, and they’re killing it.
0:05:12 >> Are they killing it from your perspective?
0:05:16 >> I think they are making a lot more revenue than most startups.
0:05:19 I don’t think it’s fair for me to give the number, it’s not my number, right?
0:05:20 >> Okay, what are the other ones that are interesting?
0:05:25 So there’s character AI that has like some absurd amount of traffic,
0:05:28 but I’ve also heard some things about like, I don’t know if this is all legit traffic or what,
0:05:31 but there’s character AI, what are the other ones that are interesting?
0:05:35 >> I want to touch on character for a second because I think like,
0:05:38 you know, when you look at consumer companies,
0:05:41 one of the things that I learned was that the behavior patterns,
0:05:47 like when something just really, really stands out from all other products in their category
0:05:49 or previous categories, that’s when you pay attention.
0:05:54 It’s like the, you know, dumbest metric, but it is really clear
0:05:56 when something has special consumer behavior around.
0:05:59 And the thing that is really interesting to me about character
0:06:05 or the companion apps that work really well is like people spend hours with them, right?
0:06:07 Like, you know, in terms of the number of products,
0:06:11 like how many products do you spend hours with every day?
0:06:13 Not a lot, like social media?
0:06:17 >> Sean, that’s like my product that I spend hours a day with.
0:06:18 >> Yeah.
0:06:20 >> You were a great luck, I think, when they invested in Discord.
0:06:23 I think the timing is there and Discord was one of those things
0:06:28 that was probably overlooked because it was like, you know, mostly teenagers
0:06:31 who play video games that were using this thing and it kind of looked like a chat room,
0:06:33 but you’re like, “Oh, well, how is it going to make money?
0:06:36 It’s not like Slack where you can charge the company.”
0:06:39 But the stat was people were spending like seven hours a day or something on Discord,
0:06:40 something ridiculous like that.
0:06:43 Just living in Discord, it was their social life.
0:06:45 And so you’re like, “Well, there’s definitely something there.”
0:06:48 And they were able to make a ton of money just even selling emojis at that point
0:06:52 because if you have that much engagement, you can’t fake that.
0:06:53 >> Yes.
0:06:55 >> By the way, I just went to Character AI
0:06:58 and there’s an option to chat with Elon Musk.
0:07:00 And the preloaded question, “Why did you buy Twitter?”
0:07:04 So I click it, so it starts a chat with Elon Musk as a character.
0:07:07 And then the first response literally goes, “You are wasting my time.
0:07:09 I literally ruled the world.”
0:07:12 >> Okay, so by the way, according to SimilarWeb,
0:07:17 which is like you multiply it by two or three and then you divide by two or three,
0:07:18 and that’s the huge range.
0:07:25 But according to SimilarWeb, it says that Character AI has 310 million monthly uniques.
0:07:27 Are you kidding me?
0:07:29 >> I mean, that’s more than the Wall Street Journal.
0:07:31 It’s more than like a bunch of…
0:07:32 >> That’s insane.
0:07:34 Is this company really that big?
0:07:38 >> I think people want companions.
0:07:42 This is why I’m saying that the engagement characteristics around this stuff is real.
0:07:46 And so for anybody starting a new business,
0:07:49 one person company shipping AI companion up to a niche,
0:07:52 like generating a million dollars of cash flow for themselves.
0:07:54 >> So do you know how these things grow?
0:07:57 So, I mean, 300 million monthly visits is no joke.
0:08:01 What’s the growth channel for something like this?
0:08:05 >> Well, I think that’s going to be like an advantage in the future.
0:08:08 I do think one of the weird things about these AI capabilities
0:08:13 is they are so novel and unique that they do drive word of mouth.
0:08:17 For example, with Character, you can make new characters and people share them, right?
0:08:20 So there’s inbuilt virality there.
0:08:24 But like maybe I’ll give you like two other examples of just like when I say
0:08:26 the capabilities are just really new
0:08:28 and they’re powerful and people want to talk about them.
0:08:31 Like, I don’t think you can engineer that,
0:08:32 but it’s just characteristic of these companies.
0:08:36 Okay, so one example is I am an investor in a company called Hagen.
0:08:38 You can make a video avatar of yourself.
0:08:40 You cannot tell the difference.
0:08:44 And reaching that bar of quality is new as of this past year.
0:08:47 And like people create content that is unbelievable and they share it.
0:08:50 And so like now Hagen is in tens of millions of revenue.
0:08:53 Great. They’ve never spent a dollar on like paid marketing.
0:08:55 Sam, have you seen this thing before, by the way, Hagen?
0:08:58 This is one of those products that I’m seeing all over the place.
0:09:01 But it felt like it was just like people younger than me talking about it.
0:09:02 So I felt embarrassed.
0:09:06 Well, this is not like like the character AI was like, you know,
0:09:07 that’s like teenagers kind of sharing stuff.
0:09:09 Some more like Wattpad or something.
0:09:11 This is a corporate use case.
0:09:16 So this is basically using like I make a digital AI of me or of a or or just
0:09:18 like a fake character altogether.
0:09:20 And then it can be used in training videos.
0:09:23 It can be used in intro videos with customers, things like that.
0:09:27 So you could basically create a you don’t have to actually set up a camera,
0:09:30 film a video, have it edited and then post it in order to send a video
0:09:34 to a prospect or send a video internally to an in a training system
0:09:35 or educational product.
0:09:37 And so that’s what this is.
0:09:40 And that’s why they just as it says at the top raised 60 million in funding.
0:09:42 But I think the chart I saw was pretty absurd that, you know,
0:09:46 they basically raised 20 million in ARR very, very fast.
0:09:48 Holy crap.
0:09:51 Some of the usage actually also, yes, it’s a business use case,
0:09:55 but it’s like all kinds of businesses, like creators, SMBs, like high end
0:09:56 enterprise advertisers.
0:09:59 And so like for you guys to be like, OK, well, like actually,
0:10:04 I bet there’s a lot more demand for Sean and Sam talking than the amount.
0:10:07 I’m sure you’re hanging out on the pot a lot, but like then even each
0:10:10 of you can contribute.
0:10:15 And so if the marginal cost of more time of Sam talking is free,
0:10:17 like you probably do more with it, right?
0:10:19 I think that’s just what people are discovering.
0:10:20 Have you guys used this?
0:10:23 Is it the landing page makes it look amazing?
0:10:26 Like is it amazing or is it still up and coming?
0:10:27 No, it’s like pretty good.
0:10:33 This this cross this one crosses the line, I would say of usable in real life
0:10:35 versus cool demo, which is the hard thing with AI.
0:10:36 You get a lot of cool demos.
0:10:38 Then you go in and you’re trying to use it for your use case.
0:10:40 And you’re like, how come the tweet had such a good output?
0:10:44 But mine is kind of whack every single time or like, well, this is good,
0:10:46 but it won’t let me change the text on it,
0:10:49 which is what I would need to use it in my real thing.
0:10:52 I would say this one is definitely production ready.
0:10:53 They wouldn’t have, you know, tens of millions in revenue
0:10:56 if they weren’t actually usable like customers.
0:10:59 Well, and they just did like a public campaign with McDonald’s, right?
0:10:59 Like an advertising.
0:11:00 But there’s some good limits, right?
0:11:02 Like you can’t be like moving around.
0:11:04 It’s like a face on camera.
0:11:06 At least that’s what it used to be when I tried it like six months ago.
0:11:07 Yeah, there’s some new stuff.
0:11:10 You should try like, you know, you can be walking around now.
0:11:11 Oh, okay.
0:11:13 I stand corrected.
0:11:15 All right, Amber back.
0:11:17 Can they just, can we just upload our YouTube page
0:11:20 or do we have to stand in front of it and film?
0:11:25 You have to stand in front of your web or phone camera for two minutes and film.
0:11:28 And it’s more of a safety thing than anything else
0:11:32 because they don’t want people being able to take your YouTube and make you.
0:11:35 If that makes sense, like they want, they want you saying specific words
0:11:39 about like, I, Sam Parr, say it’s okay to make this avatar.
0:11:42 And you said that you started the podcast by saying there’s like a lot of,
0:11:44 you had a really, the line you said was awesome,
0:11:46 which is like, there’s a bunch of ways to make a million dollars
0:11:47 that could eventually become a billion.
0:11:50 Is this one of those companies where it started that way?
0:11:54 I think, I mean, I think the market for this company is very deep
0:11:57 because people like, they want a lot of video.
0:12:01 And I think more like, if you just think about the domain of making video,
0:12:02 you guys know much more about this than me.
0:12:06 But like people want a lot of control, right?
0:12:07 They want quality.
0:12:11 They want specific expression and brand and motions
0:12:15 and they want like one person, two people, three people, like person walking around,
0:12:17 product, whatever it is.
0:12:21 And so I think there’s actually a lot, like there’s a lot we still cannot do
0:12:24 with research and the company wants to continually pull,
0:12:27 like push the bounds of what you can do.
0:12:29 And so I think this is a good example of like,
0:12:32 I think there’s a billion dollars of video generation revenue
0:12:34 for them or for others.
0:12:38 But like, you know, you actually have to invest in the product pretty deeply,
0:12:44 but it doesn’t mean that your wedge can’t be really powerful across a single use case.
0:12:49 Sam, have you seen the ones that do this for DTC products?
0:12:51 The AI for DTC product ads?
0:12:54 So go to icon.me.
0:12:56 If you scroll down, you can watch the video.
0:13:00 So see the video of the Asian dude who’s holding like a college in peptides thing.
0:13:03 So that’s an AI generated video.
0:13:05 It’s the product in his hand.
0:13:07 That’s not actually in his hand with a script that was written.
0:13:09 He never recorded it.
0:13:13 And now you have a UGC very authentic looking ad for an influencer.
0:13:14 You go to the next one.
0:13:15 Look, he’s holding a different product.
0:13:17 That’s because he didn’t reshoot it.
0:13:20 They just put a different product in his hand and it looks super fucking real.
0:13:21 Am I right?
0:13:22 What?
0:13:23 Isn’t this wild?
0:13:25 This is amazing.
0:13:27 And so he’s got another one with ramen.
0:13:28 And so what he’s doing is interesting.
0:13:32 What he’s doing is he’s letting actual and so these are not AI generated people.
0:13:33 This is a real person.
0:13:36 This is like an Instagram guy who’s got like whatever hundreds of thousands of dollars.
0:13:40 So he’s letting popular Instagram people say, hmm, okay, I’ll do it.
0:13:46 I’ll create my digital twin that will be able to do my brand like my brand of content.
0:13:50 So a brand can come in request from a listening Instagrammer with a million
0:13:52 followers and say, I want you to sponsor this video.
0:13:53 Here’s the script.
0:13:54 Here’s my product.
0:13:57 And if I click yes, then it will AI generate that video.
0:14:01 I never needed to like open up a package, grab a thing, you know, take take 20
0:14:05 minutes, set up my tripod, record an ad, send it to the brand, ask them if it’s
0:14:07 okay, then they say yes.
0:14:09 And then I get paid instead of this case.
0:14:10 It’s basically like, I just approved the brand.
0:14:12 He uses my digital twin to make the ad.
0:14:15 If I’m cool with the ad, I get paid.
0:14:16 And that’s it.
0:14:17 And so that’s what he’s doing.
0:14:18 Our cad’s is the same thing.
0:14:20 If you go to our cad’s, it’s like pretty fucking wild.
0:14:22 And in their case, these are fake actors.
0:14:26 So these women that you see on the thing that are like promoting stuff.
0:14:28 These people do not exist.
0:14:33 This is an AI generated woman who looks like a real person that is promoting some
0:14:36 product and you script it and you can, you know, get these made.
0:14:41 I these are the or it might be like a real person, but they’ve said like license
0:14:41 to the company.
0:14:42 You can do whatever you want with it.
0:14:43 Yeah, exactly.
0:14:46 I think in this case, they might have started with a couple of those.
0:14:49 Like I think they found one of the girls from this like on five or something.
0:14:53 Um, but the idea would be, I don’t know too much about the under under the hood
0:14:54 stuff of these.
0:14:55 I just started playing with them.
0:14:59 But the idea would be that, you know, people are not going to know what
0:15:00 the hell’s real and what’s not this.
0:15:04 These look like real people in their home, giving a genuine endorsement of
0:15:08 some product that they like, and it is very simple to create.
0:15:11 I think Sarah, this is the type of idea you’re talking about where two people
0:15:16 can kind of take the existing models, you know, maybe customize them, uh, here,
0:15:19 but then it’s just in a wedge in this case.
0:15:22 It’s for e-commerce companies and they’re going to try to build a business here
0:15:26 that will do, it’ll be these, both these businesses very quick to get to, you
0:15:29 know, mid seven figures of revenue, uh, without, you know, much marketing
0:15:32 spend or much of anything, just cause the product is such a wow product.
0:15:36 And then, you know, from there, who knows if it can get, you know, really
0:15:37 enormous or not.
0:15:38 Yeah.
0:15:41 And I think a piece of it is just like for, for me, like, okay, what’s the
0:15:46 difference between like the first million and the next 999 million?
0:15:51 It is whether or not the capability exists in the company to make the
0:15:55 product deeper and keep expanding scope for what you do for your customer.
0:15:56 Right.
0:15:57 And, but there’s a ton of these wedges.
0:16:01 So it is staying with visual content.
0:16:04 Uh, you can use this category of models.
0:16:09 They’re open source to be fine tuned for different use cases that are super commercial.
0:16:09 Right.
0:16:14 So it could be models or creator videos for e-com as you described.
0:16:18 It could be renderings for like interior design or buildings.
0:16:20 I don’t know if you guys have ever looked at a floor plan.
0:16:25 Like maybe I just have terrible visual spatial reasoning, but I can’t
0:16:28 look at a floor plan with like a couple blocks and then like a fuzzy piece of
0:16:31 fabric and be like, yes, I see it.
0:16:33 I’ll put my life savings into this.
0:16:37 And our friend, Peter Lovell’s has a thing where you take a picture of
0:16:40 your home and then it does interior design for you and shows you mockups,
0:16:41 which is pretty cool.
0:16:42 Yeah.
0:16:46 But, but I’d say like those, you know, those renderings traditionally
0:16:49 generated costs like thousands of dollars, right?
0:16:51 And now if you can give it to people for very little incremental costs,
0:16:53 like that’s an interesting wedge.
0:16:58 Like there’s a handful of AI headshot companies making revenue.
0:17:01 If you guys have ever gone like a professional headshot taken.
0:17:02 Yeah, dude.
0:17:06 I so this actually, this is kind of actually interesting version of the
0:17:06 dropshipping idea.
0:17:09 So these are, this is, I bet you this would work.
0:17:11 So there was an ad I saw on Facebook.
0:17:14 I think it was a Facebook ad and basically it was a guy and he had a headshot.
0:17:16 I think of somebody who I recognize.
0:17:17 Maybe it was a VC in Silicon Valley.
0:17:21 It was basically like, if you’re in San Francisco, I take awesome headshots for
0:17:24 you, you should have a great shot for your website, for your LinkedIn, whatever.
0:17:25 It’s good for business.
0:17:26 It’s good for your career.
0:17:28 And you click a site and it’s a bunch of people in the tech industry.
0:17:31 And it was like $300 or $400.
0:17:34 And I went to some warehouses type of place in some, some little like
0:17:39 photo shoot studio in San Francisco, stood there awkwardly, got like headshots
0:17:42 made and paid this guy, you know, 350 bucks.
0:17:44 And he was running Facebook ads profitably to do that.
0:17:47 So he was able to put in and he was acquiring a customer for whatever 70
0:17:50 bucks and he was generating 350 bucks off them.
0:17:55 And now you could run that same funnel just without the San Francisco
0:17:58 studio and without the guy taking the picture and without any of the costs.
0:17:58 Right?
0:18:00 Like you just say, awesome.
0:18:02 Give me a couple of your photos and then boom, here you go.
0:18:06 And I’ve seen a couple of these go viral of like viral headshot viral your book
0:18:09 ideas, but I haven’t seen too many people just like running paid on them and
0:18:12 making them work, but I’m pretty sure that you could create a paid funnel that
0:18:16 would print cash for a period of time and maybe not forever, but an arbitrage
0:18:16 period of time.
0:18:18 Yeah, but what’s what’s an example?
0:18:23 So I’ve seen the same ones where it’s like you look like a 80s glam shot model.
0:18:27 Remember, I think the professional one people are willing to pay more, right?
0:18:29 So if it’s actually going to be for your, what’s an example of one?
0:18:30 Yeah, look, look at this.
0:18:33 Look at this company Aragon dot AI.
0:18:34 Oh dude, look at this landing page.
0:18:34 This is genius.
0:18:38 They just have a side scrolling carousel and it’s the before’s and then
0:18:42 there’s a line and then they just that same photo becomes the after that is
0:18:43 very well done.
0:18:44 How good.
0:18:48 Sarah, how hard is something like this to make?
0:18:52 So like there are a million of these wedges, right?
0:18:55 And I think that means like it’s an amazing time to, as you were saying,
0:19:00 like be good at distribution, understand like how to make a funnel and
0:19:04 how to market something and like to be an idea person, right?
0:19:07 Fundamentally, like if you run into problems all the time and you like see
0:19:10 the basic capabilities, you’re like, oh, I can think like you guys are both
0:19:13 like, oh, I can think of like five other use cases for this, right?
0:19:15 And by the way, you know, the distribution thing.
0:19:16 So this is a good example.
0:19:21 The, so I invested a little bit in Jasper and Jasper was started by guys
0:19:25 who were internet marketers first, not AI researchers, not AI, you know,
0:19:28 engineers, not, not even frankly, very good engineers.
0:19:32 Probably they were just like internet guys, internet, internet business guys.
0:19:35 And they were, I think they were doing something before this that wasn’t
0:19:38 really working very well, but they had spent a lot of time building
0:19:39 like internet marketing funnels.
0:19:44 And so when they got access to probably chat GPT three or something like
0:19:47 that, they were kind of back before, sorry, before chat GPT, just
0:19:51 when it was GPT three, they got access to the API and they built Jasper,
0:19:55 which was a took that same capability, but now made it useful for marketers.
0:19:57 So if you’re a marketer, you need a blog post written or an email
0:20:01 or you needed, you know, copy written for an ad, whatever it was.
0:20:04 They just made a standalone tool that would do that under the hood.
0:20:08 It’s, you know, the open AI model is doing 80, 90% of the work.
0:20:12 They’ve maybe customized the last, last mile of it, but they were so good
0:20:14 at internet marketing that they started running Facebook ads on this thing.
0:20:18 And it’s the fastest company I’ve ever seen get to 50 million in ARR.
0:20:22 They get to 50 million ARR in one year, which is to go from zero
0:20:26 to 50 million in revenue in one year is just absurd.
0:20:29 And the way the reason they were able to do that is because their background
0:20:32 as internet marketers as guys were like, as soon as I have anything that
0:20:35 works, I will just plow the maximum amount of cash into Facebook ads
0:20:39 as I can and I will just keep optimizing the ads until I get this thing.
0:20:42 You know, a dollar in equals a dollar 50 out or a dollar in equals $2 out.
0:20:45 And that’s why they were able to be so successful early on because
0:20:48 they had a different skill set than most of the Silicon Valley people.
0:20:50 Most people in Silicon Valley don’t ever run paid ads.
0:20:52 That’s just like a pretty crazy thing.
0:20:57 I think like if we just go to the difference then like a challenge
0:21:00 for anyone in these companies that gets this wedge and like is rare
0:21:02 to see zero to 50 in one year, that’s pretty special.
0:21:08 But even if you get like a product to hit in terms of initial adoption,
0:21:14 then I think the like the next 999 million of revenue has to be like,
0:21:19 I think more traditional modes because the problem is if it was,
0:21:23 I’m not saying the distribution piece was easy, but let’s say you were just
0:21:28 first with an idea and like you hit it on Reddit because it’s a novel
0:21:34 capability. Like I think then you need to get to traditional like reasons
0:21:37 companies get really big, product velocity, depth of product ability
0:21:40 to serve the customer or social engagement or something, right?
0:21:46 So like if you think about companions, it could be like what are the arguments
0:21:49 for like why somebody gets to dominate that business?
0:21:54 There’s a version of a companion business or any business with paid spend
0:21:58 and you know this really well, that is like just a treadmill, right?
0:22:00 Like I make money, but I have to keep putting money in.
0:22:05 It’s the opposite of compounding and if I like stop working hard
0:22:09 or other people compete with me like the treadmill gets steeper or I fall off.
0:22:14 And I think one simple answer is on companions.
0:22:16 Do you guys ever play The Sims growing up?
0:22:16 Of course.
0:22:21 Sure, like it’s very hard for me to not imagine The Sims better
0:22:27 if the characters are like smarter and like richer in interaction
0:22:31 and have like what looks like realistic video and voice.
0:22:35 And so like technically instead of it just being like I’m talking
0:22:39 to a person, it could be, you know, that person has some combination
0:22:43 of memory of me, other interactions, goals and like the media experience
0:22:45 of them is richer and we haven’t gone there yet.
0:22:48 But I think like there’s a version of that company that’s somewhere
0:22:51 between like a companion and a game world that will be very big.
0:22:53 It’s kind of an interesting exercise.
0:22:56 Well, if I could just get to a million, then I’ve increased
0:22:59 my likelihood and then maybe I can get that to 10 and then a hundred
0:23:00 and then a billion.
0:23:04 I actually firmly believe that if something can scale to 10 million
0:23:08 there, it may take a while, but if it can get to 10, it can almost
0:23:09 always get to a hundred.
0:23:12 Like there’s enough people in the world to make that work.
0:23:15 But it’s actually an interesting exercise to think of all the things
0:23:17 that you need to do in order to make those jumps.
0:23:21 Now getting it to a billion I’ve actually that’s been that’s been hard
0:23:22 for me to figure out how to do that.
0:23:24 But that’s a fun exercise to think.
0:23:26 Well, if I just get to a million, I bet you I can get to 10.
0:23:28 And if I get to 10, I know for a fact I can get to a hundred.
0:23:30 Yeah.
0:23:33 By the way, the Sims lifetime sales five billion dollars.
0:23:37 So without AI, the Sims was able to get to five billion in sales.
0:23:40 If you made it more engaging by by AI powering all those characters,
0:23:42 that’s going to be even stickier.
0:23:44 It’s going to be a big business, right?
0:23:46 Hey, Sarah, why?
0:23:49 Dude, you’re like pretty in the know.
0:23:50 Fuck this fun thing.
0:23:52 Like why don’t you just go do this?
0:23:54 Go make one of these go make one.
0:23:56 This sounds way more fun than investing in it.
0:24:02 I get to I like really like doing the zero to one thing repeatedly.
0:24:03 Right.
0:24:07 And so I think you just have to figure out what you’re motivated by.
0:24:12 I am really motivated by working with people that are entrepreneurs
0:24:14 that I like and respect and I think are super special.
0:24:19 And I do not like working with people that that I don’t have as
0:24:21 much enthusiasm about, right?
0:24:24 That’s like a very specific personality trait and like law of large
0:24:28 numbers, as soon as you manage very large teams, not everybody is going
0:24:29 to be at the same level.
0:24:35 And so like doing investing and making being able to contribute to other
0:24:38 people being successful that are really special and then the competitive
0:24:42 nature of be right with skin in the game and then know what is happening.
0:24:46 Like I like all of that, but I never say never.
0:24:50 I think we we incubate companies where like it’s essentially like,
0:24:52 uh, I see it, I see it, I see it.
0:24:56 And then there’s frustration that like the right, you know, a set of
0:24:59 people you’re really excited to back just hasn’t come together around a
0:24:59 certain idea.
0:25:03 Sean, you are more technical than me, but you’re still not technical.
0:25:06 I would say, but you’re more than me.
0:25:08 But Sam Park classic compliment.
0:25:09 Thank you very much.
0:25:10 You’re not tech.
0:25:12 You’re more technical than me, but you’re not technical.
0:25:13 You’re also not technical.
0:25:14 You’re almost good looking.
0:25:19 You’re harder than me, but I’m a one year at three.
0:25:24 Uh, did you, uh, when you’re, I know you’ve been like studying this stuff.
0:25:28 When you like, this seems like a really fun weekend thing just to play with.
0:25:31 Are these actually, would it be really hard for me to learn how to do this?
0:25:33 Would it be hard to build one of these?
0:25:35 Just like a really simple project.
0:25:38 Cause I know she’s, Sarah’s getting me all hyped on this show.
0:25:40 I’m like, this looks really fun to mess around with.
0:25:40 Yeah.
0:25:41 I mean, I think it’s like anything else.
0:25:41 You got it.
0:25:43 You’d have to have a partner to speed you up.
0:25:47 Like you learning to code to be able to do these things.
0:25:51 It would be the slow way of doing it versus the easy way is you find an engineer
0:25:54 who’s excited about this and doesn’t have clarity of vision around it.
0:25:57 Maybe doesn’t have a, doesn’t want to run the business side of things.
0:25:59 And you say, great, hey, let’s, let’s build X together.
0:26:01 I have a clear idea that X will work and I’ll handle the marketing side.
0:26:04 You got to make this product do, do this.
0:26:06 And, um, that’s not so hard.
0:26:07 That’s, that’s pretty easy.
0:26:08 This is exciting.
0:26:10 Uh, you can see a lot of cool shit.
0:26:13 Let’s, uh, let’s do some of your like specific kind of thesis.
0:26:15 So you have this website, conviction.com.
0:26:16 Good website.
0:26:17 By the way, how’d you get that domain?
0:26:19 I’m an internet person.
0:26:20 Yeah.
0:26:20 Okay.
0:26:21 Did you see her website?
0:26:26 She has a website for her, uh, I think it’s the incubator where you got to like
0:26:28 code in order to get access to it.
0:26:30 You don’t really code, but like the menu is set up like that.
0:26:32 It’s a little, it’s like, yeah, it’s a little CLI.
0:26:34 What’s, what’s that URL?
0:26:36 Um, I think it was called commit.
0:26:40 It was like our program for like hackathons, college students, et cetera.
0:26:40 Yeah.
0:26:42 It’s commit.conviction.com.
0:26:44 Sean, it’s a pretty cool website actually.
0:26:44 Oh, you open up.
0:26:45 It’s a terminal.
0:26:46 Yeah.
0:26:47 Oh God.
0:26:48 Uh, let me see.
0:26:49 Let me try to do this.
0:26:50 So run.
0:26:56 No, uh, type, type in help.
0:26:59 So if you type in help, it like gives you the menu anyway.
0:27:01 It’s flash is like a folder.
0:27:01 I don’t know.
0:27:02 I don’t know how to do this.
0:27:03 Um, all right.
0:27:07 So you have a website with a bunch of basically like request for startups or,
0:27:11 you know, things that you think are going to, going to be built in, in, uh, in AI.
0:27:12 So let’s run through some of these.
0:27:15 Cause I, that’s actually why I initially was like, we got to have her on the
0:27:18 pod to, to kind of, um, to talk some of these out.
0:27:21 So let’s do one that’s you call your personal seller.
0:27:22 Do you remember this?
0:27:24 He might have wrote this a while, a while back, but your personal seller.
0:27:28 It might have been one, like my partner, front of readys or something,
0:27:29 but we can certainly talk about it.
0:27:29 Yeah.
0:27:30 Okay.
0:27:31 I’ll give you the summary.
0:27:34 So the summary is, uh, your personal seller.
0:27:38 I think the idea here is that there’s a bunch of places online to sell stuff at
0:27:41 C and eBay and Amazon and a bunch of different places to sell things.
0:27:45 Um, but actually like doing that is a bunch of work.
0:27:49 Like creating the store listings, changing prices, writing the copy, all of that.
0:27:54 And I think what you’re saying is somebody should be able to just like have a
0:27:59 product and then the AI should be able to like do the actual econ management of
0:28:02 this, of the sell of the, of setting up the shop and running it.
0:28:03 Is that what that means?
0:28:04 Yeah.
0:28:08 I think like, um, it’s probably it, it matches like a larger theme that I really
0:28:14 think is exciting about AI, which is like, because all of these skills and it
0:28:19 could be, um, run a basic like social marketing campaign, right?
0:28:25 Or like send email to your customers that are likely to be repeat customers or
0:28:28 improve your website for indexing.
0:28:33 Like there are a bunch of things that, um, are probably not related to let’s say
0:28:38 it’s a, let’s say it’s a Shopify drop shipping store for like a particular
0:28:41 type of sock and you love socks as an entrepreneur.
0:28:45 It’s not like related to the merchandising decision or the design decision of like,
0:28:47 what is the sock I want to give the world?
0:28:47 Right.
0:28:52 And like that’s kind of the essence of like why, like sometimes people become
0:28:53 entrepreneurs.
0:28:57 And so can you, can you take a bunch of these tasks that require skills and all
0:29:03 these different domains and just automate them at least at a basic level?
0:29:04 Like, I think you can now, right?
0:29:10 And I think like that they’re the platforms, um, Shopify and Square, etc.
0:29:14 They’re, they like, you know, they now have native assistant products that help
0:29:16 you use the platforms better.
0:29:23 But I think across the spectrum of how to be a good internet entrepreneur, like in
0:29:26 the e-commerce sense, I think there’s more opportunity there.
0:29:27 Um,
0:29:29 How do companies do that now?
0:29:32 So let’s just say you’re a company with 10,000 SKUs.
0:29:36 Um, how do you get accurate descriptions for all of them?
0:29:40 Well, usually if you have 10,000 SKUs, you have like, it’s a, you have like,
0:29:43 you don’t have 10,000 unique, uh, totally variant.
0:29:44 Yeah.
0:29:47 But you could have color, size variants, things like that.
0:29:50 So like, I’ll give you, uh, I’ll tell you in our case, right?
0:29:56 So I have an e-com store and we have, we spend, uh, let’s see, probably like five
0:30:00 or six grand a month on just Shopify plus or whatever, like the enterprise
0:30:01 Shopify thing.
0:30:03 So that’s just the Shopify costs on top of that.
0:30:09 I would say we probably have another, um, three to five grand a month on Shopify
0:30:11 apps, so you need an app for search.
0:30:15 You need an app for, uh, bundles, you need an app for this, that, you know,
0:30:16 there’s like a ton of things that Shopify doesn’t provide.
0:30:20 So my all in just software costs is at least 10 grand a month, probably
0:30:23 a little bit more on top of the fees they take of every transaction.
0:30:26 Then I have an e-commerce store manager.
0:30:28 His job is just to like run the store.
0:30:31 Like we have new products coming up, make sure those launches go well,
0:30:31 move things around.
0:30:32 Oh, this is broken.
0:30:33 There’s a bug, whatever.
0:30:35 We then have a merchandiser.
0:30:38 The merchandiser goes every day, looks at the collections and says,
0:30:39 this thing is sold out.
0:30:40 It shouldn’t be at the top anymore.
0:30:43 We don’t have sizes for this or we don’t have colors for this.
0:30:46 So let me move this other thing to the top or hey, the season just ended.
0:30:48 These need to be rearranged.
0:30:49 So there’s a human being that does that.
0:30:52 There’s also apps that do that, but you kind of need the app plus the software
0:30:54 today because the app’s not quite good enough to do it by itself.
0:30:59 We then have VA’s that go in and they do all the product pages, the descriptions,
0:31:03 the templates, the tagging, so that our inventory data is correct.
0:31:05 Cause we need to be able to analyze your inventory to do that.
0:31:07 You need to tag every product accurately.
0:31:11 So there is like four or five people that are just making sure the store runs
0:31:14 in addition to five apps that make the store run.
0:31:19 That all today is shouldn’t be the lead like future state of things.
0:31:20 That’s just the current state of things.
0:31:26 And Sean, I think the future state is for entrepreneurs who cannot recruit,
0:31:30 manage, pay the five people it takes to run your store.
0:31:32 Like what do they do?
0:31:35 As Sam said, like I think it will be easier in the future.
0:31:35 Right.
0:31:35 Yeah.
0:31:41 I think it’s also kind of like similar as an idea to all of the another area
0:31:47 that we are, and I’m like personally really interested in is the voice
0:31:48 automation market.
0:31:52 I think like a lot of your listeners will have seen the GPT for O demo where
0:31:56 it’s like a voice that may or may not sound like Scar Joe talking like in real
0:31:57 time.
0:31:59 Well, we played with 11 laps.
0:32:01 No, but that’s dubbing.
0:32:05 She’s talking about just being able to like Alexa, you just talk to it and it
0:32:07 just talks back and it’ll sound like Scar Joe.
0:32:09 So just like chat GPT, but you don’t have to type.
0:32:10 Yeah.
0:32:14 Both of these things either like it could be in your voice or like some
0:32:19 spokesperson for a brand or a company, but like the ability to give reasoned,
0:32:22 you know, knowledge based responses in a human voice.
0:32:24 I think it’s just really powerful.
0:32:25 Right.
0:32:29 And I don’t think people are thinking enough about the opportunities here where
0:32:30 you mentioned 11.
0:32:34 There’s like exactly one independent voice API business and tens of millions of
0:32:35 revenue and that’s 11.
0:32:35 They’re great.
0:32:36 That’s amazing.
0:32:38 I think there are other opportunities.
0:32:42 So like there’s a company called Cartija that does like more real time voice
0:32:42 for example.
0:32:44 You think 11 is by the way 11 lab.
0:32:46 Do you think they’re at tens of millions of in revenue?
0:32:48 They are.
0:32:51 They’re definitely at, you know, a large number that is in the tens of
0:32:52 millions of revenue.
0:32:55 Hopefully I’m not surprising surprising a market with that.
0:32:59 But you know, a lot of developers will immediately gravitate like toward API
0:33:03 business, but that is not how the rest like the world is full of niches and
0:33:06 people running businesses that don’t think about API’s and won’t use them.
0:33:07 Right.
0:33:11 And so like just to just like, you know, your personal seller.
0:33:15 I think they’re going to be a bunch of interesting voice services for
0:33:20 everything from restaurants to HVAC companies to dental reception that
0:33:21 are just like answer the phone.
0:33:25 I think that’s one of the ideas we had and it could be informational.
0:33:32 Like we are open from 8am to 6pm or a lead generation business where I’m
0:33:36 like, well, like my plumbing broke and like, are you available tomorrow at
0:33:36 3pm?
0:33:40 I’m a huge believer in this huge.
0:33:43 Like and watch on this, this simple idea.
0:33:47 So you know, like when the, when the internet came out, it was like, um,
0:33:49 oh, it’s going to be so crazy.
0:33:51 But like one of the obvious things was like, Hey, every restaurant just kind
0:33:52 of needs their menu online.
0:33:55 Like you should put your, you should put your restaurant exists where it’s
0:33:57 located and then put your menu up there.
0:33:59 Even as a PDF, that’s still like value add for you.
0:34:01 It’s like, it became where every business needed a website.
0:34:04 And now what I think it’s going to have is that every business needs an agent.
0:34:07 And so what’s the agent for most small businesses?
0:34:10 So like I called pest control because we always get a little bunch of like
0:34:14 mice jumping in our pool for whatever reason and try calling pest control.
0:34:16 Nobody ever picks up the damn phone.
0:34:19 And because there’s usually, it’s usually run by like, it’s like Mike’s pest
0:34:24 control and Mike’s out in the field doing things all day, actually doing work.
0:34:25 And so he doesn’t pick up the phone.
0:34:28 And so then you leave a message and you’re like, you, and then you call 10 of
0:34:31 them because you’re not sure if Mike’s going to get back to you.
0:34:32 So then it becomes whoever gets back to you first.
0:34:35 Mike loses business because Mike doesn’t pick up the phone.
0:34:38 Mike also is not going to hire somebody to just sit there and wait for
0:34:40 the three phone calls a day that he’s going to get.
0:34:41 It just wouldn’t make sense.
0:34:46 But now you go and I built one of these in our like AI, uh, like weekly
0:34:47 tutoring session that I have.
0:34:49 Basically, I was like, I want to build one of these.
0:34:53 So we have the same problem for our offshore recruiting business.
0:34:55 So we own an offshore recruiting business called somewhere.
0:34:56 It’s like, you can fire tip.
0:34:57 You can find amazing talent.
0:34:58 They’re just somewhere out in the world.
0:34:59 You just have to find them.
0:35:01 So what somewhere does, they find you elite talent.
0:35:04 Now the big problem, if you go to somewhere.com, it’s like, you say, okay,
0:35:09 I’m looking for a designer or I need somebody who could do, who get me leads
0:35:11 for my marketing business or my real estate business, or I need somebody
0:35:12 to do data entry, right?
0:35:13 So you have all these jobs.
0:35:17 Now the button on the site is basically like, you want to start hiring?
0:35:18 Fill out this form.
0:35:21 So you fill out the form and then it’s like, awesome.
0:35:22 We will get back to you soon.
0:35:24 Or it’s like schedule a call.
0:35:26 Here’s the call tomorrow or two days from now.
0:35:32 And no matter how many sales agents we have, a call tomorrow is not as good
0:35:34 as talk to me right now about what I need.
0:35:36 Cause right now is when I’m interested.
0:35:37 Right now is when I’m on your website.
0:35:40 Right now is when I’m not thinking about other variations of how I might solve
0:35:42 this problem and you have an opportunity to sell me.
0:35:46 And so Sam, I don’t know if you’ve seen this, but like check out bland.ai.
0:35:48 This is the one I built on.
0:35:50 If the answer is, have you seen this?
0:35:53 Assume it’s no and my mind is being blown by all this stuff.
0:35:55 But basically it lets you build a phone agent for yourself.
0:35:57 So I went on here and I built a phone agent.
0:36:01 So I built a guy who can answer the phone so that when somebody goes to
0:36:03 somewhere and they want to, they want to hire somebody, it’ll be like, awesome.
0:36:04 What are you hiring for?
0:36:05 Have you ever hired overseas?
0:36:06 And you’re like, yeah, I have.
0:36:07 It’s like, cool.
0:36:09 Um, tell me what you’re looking for.
0:36:10 A couple, you know, a couple sentences.
0:36:10 Oh, great.
0:36:13 It sounds like what you’re looking for is somebody who could be a developer
0:36:14 for your Shopify store.
0:36:18 Our, our noble budget for that is 2000 a month.
0:36:19 Would that work for you?
0:36:21 Or are you looking for something a little bit more, a little bit less?
0:36:22 And then it answers it.
0:36:25 It basically does the intake, the initial sales call for you.
0:36:26 And it’s like, no problem.
0:36:30 We’ve hired this month for 85 other Shopify brands who are looking
0:36:31 for Shopify developers.
0:36:32 You’re in good hands.
0:36:34 Uh, we do this all the time.
0:36:36 We will, uh, I’m going to start looking for candidates.
0:36:38 Now I’m going to email you tomorrow with three candidates.
0:36:39 How does that sound?
0:36:40 And the person’s like, great.
0:36:44 I guess I can just like wait for that to happen or it’ll, or it’ll pull from
0:36:47 our existing database and be like, here’s an example, resume.
0:36:49 This is the type of person we’d be looking for with this person.
0:36:50 Fit your needs.
0:36:50 Yes or no.
0:36:54 So then the human sales person will come into work and see a ticket.
0:37:00 That’s like the AI agent did the initial sales call and found the customer’s
0:37:03 requirements and kind of already warmed the sale up and told the customer what
0:37:06 they needed to know the things you repeat every time on the phone.
0:37:10 And now you could follow up with the more bespoke answer for that person.
0:37:11 That’s the future that I see.
0:37:12 I wasn’t able to fully build that.
0:37:17 I did like a prototype of it, but that’s what I think websites, even like ours,
0:37:20 which is an internet business should have, which means that every plumbing
0:37:24 and pest control and restaurant, they’re going to have their version of that.
0:37:27 This is 100% way better than having a call center.
0:37:30 Or it might, or it will be when it is long, so long as it works as good.
0:37:32 But this is absolutely the way to go.
0:37:32 All right.
0:37:33 Let’s do some more.
0:37:35 So you have another one on here.
0:37:36 That’s, I think an easy one.
0:37:37 That’s cool.
0:37:39 Next gen auto complete.
0:37:43 And I think the idea here is you do a Chrome extension or a browser extension
0:37:48 that not just like auto complete helps you fill in the next word.
0:37:50 It thinks you’re going to say or how to spell a word.
0:37:53 But what you have here is that it starts to learn your voice so it can write
0:37:57 your, it can help you write your emails or your blog posts in your voice,
0:38:00 which is kind of like the next level up from auto complete next level up from
0:38:01 Grammarly.
0:38:05 It doesn’t just kind of correct or spell check your stuff, but it actually
0:38:08 writes the way you write because it has watched the way you write.
0:38:09 Is that the thesis here?
0:38:10 Yeah.
0:38:10 Yeah.
0:38:11 Absolutely.
0:38:15 And I think it can be, you know, lots of different types of business communication,
0:38:17 but especially like email.
0:38:21 So I don’t know if this is, this is actually my friend, Mike Vernals idea.
0:38:22 I think he suffers from the same thing.
0:38:27 I do that might be true for you, which is like I’m an incredibly picky writer.
0:38:33 And so I will use the models today for generation of basic content,
0:38:37 or I’ll ask my amazing EA to like draft emails for me.
0:38:40 And then I will go rewrite the whole thing because I don’t like the tone
0:38:43 because it doesn’t sound like me or because it’s not tight enough or because
0:38:44 I want to use a certain phrase.
0:38:49 And I think the next level of like value and impact is definitely going to be
0:38:51 fine tuning to specific voice.
0:38:54 And nobody wants to write like chappy GPT.
0:38:56 Like nobody wants to be the generic AI either.
0:38:59 So what everybody wants is the thing in between.
0:39:01 This shit’s all wild to me.
0:39:03 Is there anyone right now doing that that you like?
0:39:05 Because I would like to use this today.
0:39:09 I mean, superhuman has like really interesting AI features, but I think
0:39:11 though the unlock is going to be the personalization.
0:39:15 And what’s your overarching investment thesis?
0:39:19 So you have this thing called software 3.0, which by the way, most VC thing to do
0:39:23 to be like, Oh, software 3.0, web 3.0, you’ve done it.
0:39:25 You have you have gone full VC.
0:39:26 What is software 3.0?
0:39:27 Yeah.
0:39:28 Okay.
0:39:33 So the seed for that phrase software 3.0, it comes from actually
0:39:37 an essay that Andre Karpathy wrote years ago about software 2.0.
0:39:43 And the base premise here is that like you had to write a lot of software
0:39:47 by hand in a prior generation before machine learning.
0:39:51 And then software 2.0 Andre, you know, worked at Tesla was working
0:39:55 on autopilot was really about data set labeling.
0:39:56 Right.
0:40:02 You are teaching a machine learning model by the data you choose to
0:40:06 put into the pipeline, how to do new tasks.
0:40:10 Software 3.0 is the idea that the next generation of software, a lot of it
0:40:14 is about manipulating foundation models and they’re called foundation models
0:40:17 because they have a lot of capability out of the box.
0:40:20 You don’t need to train them from scratch.
0:40:24 You just need to give them like guidance, reinforcement, the information
0:40:26 specific to your business.
0:40:30 And so an example would be like Sean was talking about for his lead capture
0:40:34 intake form voice bot, like he doesn’t need to go train a model.
0:40:38 He doesn’t need to go like collect data for that software application.
0:40:40 Like the voice agent is a software application.
0:40:45 He just needs to like make sure it’s plugged into his scheduling system
0:40:51 and his database of candidates and be able to retrieve the right
0:40:55 information about the business and like, you know, respond consistently
0:40:57 to customers in a certain tone.
0:40:57 Right.
0:41:01 And so that’s more about like manipulating a bunch of this base work
0:41:04 that people like labs have already done for you.
0:41:08 And the premise here is like that last mile of getting a foundation
0:41:12 model to be like something that serves all these use cases in the real
0:41:15 world that, you know, maybe the research labs think of as niches.
0:41:18 Like the world is composed of very large niches.
0:41:21 And so I think it’s a thing is really big opportunity for entrepreneurs
0:41:22 and for us.
0:41:26 So here’s the deal.
0:41:30 I made most of my money from a newsletter business.
0:41:33 It was called the hustle and it’s a daily newsletter at scale to millions
0:41:36 of subscribers and it was the greatest business on earth.
0:41:41 The problem with it was that I had close to 40 employees and only three
0:41:43 of them were actually doing any writing.
0:41:45 The other employees were growing the newsletter, building out the
0:41:47 tech for the platform and selling ads.
0:41:50 And honestly, it was a huge pain in the butt.
0:41:53 Today’s episode is brought to you by Beehive.
0:41:56 They are a platform that is built exactly for this.
0:41:59 If you want to grow your newsletter, if you want to monetize a newsletter,
0:42:03 they do all of the stuff that I had to hire dozens of employees to do.
0:42:05 So check it out beehive.com.
0:42:09 That’s B-E-H-I-I-V.com.
0:42:16 What are some of your like hot takes or maybe your contrarian takes?
0:42:20 Anything that you think that might be counter to what the most people say,
0:42:22 most people do, most people are betting on.
0:42:25 Do you have anything that is against the grain?
0:42:28 You know, I’m going to give a like a somewhat arrogant answer,
0:42:31 which is I don’t spend a lot of time trying to figure out what the entire
0:42:33 market thinks actually.
0:42:34 So I’m like, I don’t know which of these things are contrarian.
0:42:39 I can tell you where like my opinion has changed dramatically.
0:42:42 Like, let me give you one example for many years in including,
0:42:44 you know, the tenure of my investing at Greylock.
0:42:46 I was one of several people who were like, okay,
0:42:48 we’re going to go understand healthcare and digital health.
0:42:50 And I was like, oh, healthcare sucks.
0:42:50 Right.
0:42:52 It’s a quarter of the economy.
0:42:53 It’s really important.
0:42:54 How could you not want to work on this mission?
0:42:59 But it is so slow and the incentives are so screwed up that like trying to enter
0:43:04 that market with technology or the speed of entrepreneurship that,
0:43:08 you know, Silicon Valley entrepreneurs are seeking is like not a good idea.
0:43:13 And we just did a healthcare administration automation company.
0:43:15 So I’m like, oops, like changed my mind.
0:43:16 Real hypocrite here.
0:43:20 And like one of the reasons being, I’m like, well, if you think about the
0:43:26 mind numbing work that happens in healthcare administration, like billing,
0:43:31 authorization, coding, claims, processing, like all like even not even mind
0:43:34 numbing, but just like expensive and manual like patient support.
0:43:37 It’s actually really fertile for an AI company.
0:43:40 And, you know, we back something that’s like growing really quickly in one of
0:43:41 those domains.
0:43:41 Right.
0:43:46 And so I just say like, I guess I’ve changed my point of view on healthcare.
0:43:48 I went to the pediatrician yesterday.
0:43:53 My doctor is with my baby there and I’m sitting there and she’s got her iPad on
0:43:57 like a table and there’s a video like there.
0:44:00 And I’m like, who the fuck is that guy?
0:44:03 And they’re like, oh, that’s just like my scribe.
0:44:07 I, uh, he’s just listening in and he’s, and he’s taking notes, but she was like,
0:44:11 I used to stay up until three AM taking notes on all of my patients.
0:44:12 They just do it for me.
0:44:14 And obviously the wheels are turning in my head.
0:44:18 I’m like, yeah, that, that job is going to be unnecessary in a few years.
0:44:20 But it was amazing to have a medical scribe.
0:44:21 I’ve never seen such a thing.
0:44:23 And she’s like, oh, this has been around for a long time.
0:44:24 I was like, I’ve never seen that.
0:44:25 Yeah.
0:44:29 I do think one framework for like your listeners, like thinking about different
0:44:35 ideas is like what parts of work have been outsourced services already?
0:44:36 Right?
0:44:39 Because like it used to be the doctor taking the notes and they’re like, wow,
0:44:43 we pay this person a lot and like they should see more patients and think
0:44:44 about their patients more.
0:44:48 Like let us outsource that to a cheaper tech in our office.
0:44:52 Let us like outsource that tech to India or the Philippines.
0:44:55 And now there are a number of scribe businesses in, um, medicine that are
0:44:59 growing really fast, like a bridge, Nabla freed, like it is happening.
0:45:02 And so I think that will happen in a bunch of different areas where like
0:45:07 basically if you can create separation of that work already to outsource it,
0:45:10 then maybe you can outsource it to a machine as well.
0:45:10 Yeah.
0:45:12 Sam Moment had a good thing.
0:45:14 He was like, everybody worries about AI taking your job.
0:45:16 You have a, that’s not the right way to think about it.
0:45:18 It’s AI will take your tasks.
0:45:22 Uh, like you have to think about it not at a job level, but at a task level.
0:45:24 There are certain tasks it can do really well.
0:45:25 There’s certain tasks that can’t do really well.
0:45:26 There’s certain tasks today.
0:45:28 It can’t do that in the future.
0:45:28 It can do.
0:45:32 And so eventually a job becomes a bundle of tasks.
0:45:36 Um, but, but for now it’s you can’t think of the whole bundle because it
0:45:40 can’t replace the whole job, but it can replace specific tasks, which might
0:45:43 be just the way it works in the long run is that there’s a huge slew of tasks
0:45:45 that can be, that can be done by AI.
0:45:47 And then there’s people that bundle those tasks together to make
0:45:49 sure that they’re getting done well or at the right time.
0:45:53 I think that’s like approximately right, but to be intellectually honest,
0:45:58 like that there was a scribe in that outsourced BPO that had that job.
0:46:02 And so it’s not taking the doctor’s job, but it’s taking the piece of the job
0:46:06 that like the doctor’s job that already got separated out the task that they
0:46:09 didn’t like, but that became a job of its own.
0:46:12 Yeah, the job goes back to being a task basically in this case.
0:46:12 Yes.
0:46:13 Yeah.
0:46:13 Yeah.
0:46:14 It’s a good framework.
0:46:19 Sarah, are you, are you investing exclusively in AI related businesses?
0:46:21 I am a technology investor.
0:46:22 I’m not a machine learning researcher.
0:46:25 I’ve been working on this stuff for a handful of years and I really believe
0:46:28 it, I think it’s like the most important thing to happen in technology in a long
0:46:33 time, but I’d say like I’m also here to just invest in great tech companies.
0:46:35 And so you’re also here to get paid.
0:46:38 I am also here to work on things that will work that are important, right?
0:46:43 And so like if a, if an entrepreneur that I think super highly of or like
0:46:46 that I’ve worked with before or whatever comes to me and says like,
0:46:49 I have a great idea, nothing to do with AI.
0:46:51 I’m still definitely going to be really interested in that.
0:46:55 If you ask me like, what are the ideas that we think about or hunting?
0:46:56 It is all in AI.
0:47:01 I do want to put one more thing out there, which is definitely not a idea
0:47:03 that just anyone can go after.
0:47:10 It’s kind of the opposite of the like easy wedge idea in terms of how can
0:47:16 I put distribution around like one functionality for a niche on a model
0:47:19 like a AI headshot application or something.
0:47:21 But I do really want to hear from anyone who has a point of view on what
0:47:25 happens to the like NVIDIA compute monopoly and overall what’s changing
0:47:26 in the data center.
0:47:29 I don’t know if this is a hot take to your former question, but like,
0:47:33 I think a lot of people intellect in technology really the intellectual
0:47:39 like are like, oh, yes, of course, workloads are changing from not AI to AI,
0:47:43 but they don’t actually think about like what that means in terms of scale
0:47:44 and market cap.
0:47:48 Like that means like chips, memory bandwidth, networking, energy,
0:47:50 storage, optimized system design.
0:47:55 Like that was a lot of technology company market cap before.
0:47:58 And so like, if that’s true, there’s going to be a bunch of different like new
0:48:02 specialized solutions and it’s trillions of dollars of value at stake.
0:48:06 And it’s not just like single direct attack on NVIDIA.
0:48:08 That is like the opportunity.
0:48:09 What else would be in that category?
0:48:12 If it’s not just like, hey, our chip is better than NVIDIA chip.
0:48:13 What else is what is that?
0:48:16 What’s another shape of a company that could be in that space?
0:48:21 So I guess an example would be like, well, what are other bottlenecks?
0:48:23 Like memory bandwidth?
0:48:26 What like, what if you design storage to be specific for AI data centers?
0:48:29 What if you like, you could do cooling systems or like there are,
0:48:35 if you just reimagine the entire data center around like big AI inference,
0:48:38 I think you end up with like totally different needs.
0:48:41 The New York Times had this article the other day.
0:48:44 And I don’t remember the stat entirely, but it was something like the amount
0:48:49 of AI capacity or in chips like currently created right now.
0:48:54 We need to create like another like four trillion dollars in market cap
0:48:58 in order to satisfy like the amount of capacity that we have.
0:49:02 And they were sort of running it in a way of like, I don’t know
0:49:03 if we’re going to be able to do that.
0:49:07 But then when you think about it the other way around where you think
0:49:10 about, well, in 1998, if you said like, you know, what, how big is the
0:49:15 internet going to be? I’m sure it went far beyond virtually 100% of
0:49:18 the expert’s opinion as to how big it will get.
0:49:21 And I remember reading this article the other day and I was like,
0:49:23 that’s just absolutely astounding that we’re in one of these moments.
0:49:27 Sequoia, Sequoia came out with a sort of blog post or I don’t know,
0:49:28 PDF or something like that about this.
0:49:31 The thing they called it the $600 billion hole or something.
0:49:34 It was basically saying, well, we’ve invested this much or we’re
0:49:36 investing this much in capex.
0:49:40 So if you invest that much in capex, what do you need to get out to make
0:49:43 that, you know, return, you know, that’s a VC saying that, which is,
0:49:46 which is not just like some journalist who doesn’t get it.
0:49:46 Who doesn’t get tech?
0:49:49 Sarah, what was your reaction to that and what’s your take on that?
0:49:53 I think it is a lot of capex.
0:49:59 I think if you put it in context of like, how does it compare to
0:50:03 other big capex spends in the past?
0:50:06 Let’s say like the broadband build out, like, well, we wanted the internet,
0:50:09 you know, like we spent about $2 trillion on broadband to date.
0:50:12 Like we’re not there yet, right?
0:50:13 That was worth it.
0:50:17 And so what I would say is yes, like it’s a totally valid question.
0:50:18 We’re spending a lot of money.
0:50:19 What are we going to get out of it?
0:50:20 I think we’re going to get a lot of value.
0:50:23 We had Darmash on the Darmash founded HubSpot.
0:50:24 Darmash is amazing.
0:50:28 Yeah, he’s really wise and he’s tends to be right more than he’s wrong.
0:50:31 And I think he said something great when I asked him, I’m like, man,
0:50:34 I’m a little nervous about a lot of the stuff where the world is going to go.
0:50:36 And he’s like, well, I’m fairly educated.
0:50:39 And I think that it’s not going to be as good or bad.
0:50:40 As you think it’s going to be.
0:50:43 Do you agree with that sentiment?
0:50:45 No, I think I think it’s actually pretty bimodal.
0:50:48 I think it could be like bad or it’s like it could be much, much better.
0:50:51 So it’s the opposite.
0:50:53 It’s either going to be much worse or much better.
0:50:54 It’s kind of your take.
0:50:56 Well, what’s the bad?
0:51:00 Like what’s the bad situation look like where like, like, for example,
0:51:02 I think the bad situation and I’m fairly uneducated.
0:51:04 So take it with a great assault.
0:51:06 The very bad situation is that there’s just going to be this massive gap
0:51:07 between the haves and the haves not.
0:51:11 And like, if you have money now, that’s going to grow and you’re going to be awesome.
0:51:13 A bad situation is AI kills us all, right?
0:51:15 That’s the doom situation.
0:51:16 That’s a bad situation.
0:51:19 But then they’re in route to that.
0:51:21 There is just this massive separation of the haves and haves.
0:51:22 Not you have not.
0:51:23 You know what I’m saying?
0:51:24 That kind of freaks me out.
0:51:28 What’s your what’s your where do you see the bad situation going going towards?
0:51:35 So I think it is not necessarily that correlated that your your resources
0:51:40 or your capital today mean that you most take advantage
0:51:43 of the of the AI revolution, right?
0:51:46 I actually think people have a lot of agency in this, right?
0:51:48 Then go start these businesses, make a million dollars.
0:51:50 That’s such a small group of people.
0:51:52 Why does it have to be because of human nature?
0:51:53 How many people know about this shit?
0:51:56 You go to your well, your parents are tech entrepreneurs,
0:51:58 but go ask Sean’s mom and dad.
0:52:00 I go ask my parents, go ask my brother and sister.
0:52:02 Like, yeah, most people are not entrepreneurial.
0:52:06 Even if this widens the number of people who could be successfully entrepreneurial,
0:52:09 it’s not going to like it’s going to go from point one percent or whatever one
0:52:13 percent of the population to I don’t know, not 50, right?
0:52:14 And it’s not going to go that far.
0:52:15 Yeah.
0:52:20 I don’t know if it has to express in pure entrepreneurialism versus like you will
0:52:26 get increased productivity for people in lots of different types of jobs.
0:52:27 And it’s not obvious to me.
0:52:31 That’s like just the people who are already most highly paid today.
0:52:33 You’re somebody who thinks a lot about AI.
0:52:36 You spend your time in the ecosystem.
0:52:41 A lot of very smart people are actually worried about the doom scenario.
0:52:44 Ever, you know, from Elon Musk to we had Emmett Shearer on the podcast
0:52:45 and Emmett’s a smart thoughtful guy.
0:52:49 And he’s like, you know, the P doom, the probability of actual doom here
0:52:51 is it’s pretty scary.
0:52:51 It’s not zero.
0:52:54 And here’s here, you know, here’s where I think it is.
0:52:56 What do you think about that?
0:53:01 And what are the odds that AI truly is a sort of like a critically dangerous
0:53:05 thing, you know, I don’t actually spend a lot of time thinking about this
0:53:10 problem because the because it is like conjecture in the future of both
0:53:13 the objectives of these models and capabilities of these models that are
0:53:16 kind of like hand wavy, right?
0:53:21 Like I think when you talk to experts about some of the suggested scenarios
0:53:23 like here are two classic ones.
0:53:27 Oh, you know, people are going to use this to design a virus that kills us
0:53:36 all by weapons or somebody is going to make the objective for a foundation
0:53:40 model that is super powerful to be like make the most money or generate
0:53:43 the most paper clips and it’s going to take over all of the resource
0:53:44 in the world and kill us all.
0:53:46 There’s no linear path from here to there.
0:53:52 And so when when people ask me about like the doom scenario, like I am
0:53:54 much more concerned about abuses.
0:53:56 We actually do understand.
0:54:00 So for example, like what if people don’t understand what information
0:54:05 is true or not or like people are going to use this stuff for hacking and fraud
0:54:10 and lots of like bad activities today and like we should go understand
0:54:13 that and react as quickly as possible to that.
0:54:17 And as a country like probably want to stay ahead on these capabilities
0:54:18 technically.
0:54:21 Well, have you heard and what’s a wild example of how people use this
0:54:22 for hacking or for fraud?
0:54:27 Oh, I mean like for my company, we get emails from me.
0:54:28 It’s not really me.
0:54:33 And sometimes it will have or like I’ll have a link to something
0:54:34 that sounds like it’s in my voice.
0:54:37 Yeah, I think that’s the simplest example, which is.
0:54:44 Well, like what happens if you can create really authentic sounding media?
0:54:48 Like, you know, are your parents like, you know, going to not pick
0:54:51 up the phone if it’s a spoofed phone number and it sounds like you
0:54:54 when you say you need something like that’s a bad scenario.
0:54:58 And so I think we need more tools to protect against that.
0:55:00 And general education about it.
0:55:02 So I worry more about that.
0:55:07 And then I’d say like, I think of the probability of a bad scenario.
0:55:10 I said was like, it is possible.
0:55:12 I can’t see exactly how we get there.
0:55:18 And if you ask me like, what are the reasons in which broad use
0:55:20 of cheap intelligence are going to be great?
0:55:23 I can give you so many reasons, right?
0:55:27 So Andre Carpathi just started a company around education.
0:55:33 And like the, the, the fields that have been super resistant to
0:55:37 cost improvement, basically healthcare, the government and education.
0:55:43 Like, I think this will actually move the needle on some of the domains
0:55:46 that matter a lot to all of us humans.
0:55:49 And I think like when, when people talk about like the doomsday,
0:55:53 it’s really fun and scary to talk about the dystopian doom scenario.
0:55:57 But I think the opportunity costs of not exploring the ways in which like,
0:55:59 you know, you can have an economy of abundance.
0:56:02 We need to talk about that.
0:56:03 And that is really what I focus on.
0:56:05 Sam, do you know who Andre Carpathi is?
0:56:07 No, but I love his name.
0:56:10 It’s a lovely name.
0:56:15 Andre is a, is a amazingly well respected research scientist and educator
0:56:21 who’s trying to create like an experience that is AI powered in education
0:56:26 where like the most amazing expert in a domain is like a personal tutor
0:56:28 taking you through the material interactively.
0:56:32 And he’s one of like the five big thought leader type guy.
0:56:36 He ran Tesla’s AI program in terms of self-driving cars.
0:56:40 He was like one of the, let’s say, five most known and respected guys
0:56:40 about that.
0:56:42 He then went to open AI.
0:56:43 He then quit open AI.
0:56:46 It says he’s listed as a co-founder of open AI.
0:56:50 So I guess he’s the man who’s like the early, early mind behind it.
0:56:54 And at Tesla, he was basically the guy leading their entire self-driving unit.
0:56:57 I think he’s, I forgot what his title was, but he’s like, you know, chief AI guy.
0:57:00 When I lived in San Francisco, it was a fun period.
0:57:05 I lived there from 2012 to basically 2020 or 2022.
0:57:11 And back then it was like the Airbnbs of the world and Tesla or Uber.
0:57:15 And we had sidecar back then where it was like, holy crap,
0:57:17 we’re going to get into a stranger’s car.
0:57:18 And this is so exciting.
0:57:19 This is so new.
0:57:24 And, and you’d go to hackathons and people are working on like meal delivery services.
0:57:25 And that was like really cool.
0:57:30 I went recently or this was about a year ago and I was walking around the fairy building.
0:57:33 And this kid recognized me.
0:57:34 He’s like, oh, Sam, you know, I like the pod.
0:57:36 I go, what’s up, man?
0:57:40 And he said, I’m doing a hackathon right now in the fairy building upstairs.
0:57:42 Doing your wife want to come up and like see what’s going on.
0:57:44 And I was like, hell, yeah, let’s do it.
0:57:47 And so we go up there and it was so invigorating.
0:57:49 I was like, dude, we used to do these exact same thing,
0:57:53 but it was around like the sharing economy and all this stuff and stuff.
0:57:55 And they were, I was just talking to people at what they were building.
0:58:00 And I remember thinking like this is like totally, I guess it happens in San Francisco a bunch.
0:58:01 I was like, this is like the Renaissance.
0:58:05 Like there’s something really, really cool going on and everyone was doing AI stuff.
0:58:07 And I just thought it’s magical.
0:58:09 Right when I moved there, it was like mobile was the thing.
0:58:11 It was like, oh, X for mobile.
0:58:16 Everything we got to make, we got to make it work on an iPhone and an Android.
0:58:21 And then you would see like, you know, some like false flags, like front back came out.
0:58:22 It’s like, oh, shit, this is the next thing.
0:58:24 This is the next big social app.
0:58:25 And then it would kind of die.
0:58:29 But then, you know, Instagram, Snapchat, you know, they actually, they stuck.
0:58:32 And I remember the early days of Musically that now become TikTok.
0:58:35 And so mobile was like the big thing at the time.
0:58:38 Then it became crypto and it became the crypto hub.
0:58:41 But it started to lose a little bit of the steam for crypto
0:58:43 because crypto was a lot more international.
0:58:47 But now it looks like for AI, San Francisco, at least as back as the hub.
0:58:49 Sarah, are you in San Francisco?
0:58:52 Yeah, we’re in the mission in San Francisco.
0:58:58 And like, I think we really believe in the sort of like community aspect of not in the
0:59:01 like, maybe in the squishy sense of the word, too.
0:59:04 But like, if you’re thinking about looking for ideas for companies
0:59:08 and being inspired to like be committed to the grind and have the right ideas.
0:59:11 Then the right thing to do is not do it like alone in your basement.
0:59:17 What you have in San Francisco are people who are optimistic and then like work oriented.
0:59:19 They believe lots of things are possible.
0:59:20 They’re learning about what’s going on at the frontier.
0:59:24 And we actually do this grant program in bed, embed.commiction.com
0:59:27 to create that kind of community and a bunch of other stuff.
0:59:30 But it is, it is around this idea that people want to have the experience
0:59:35 that you described, Sam, which is like, well, like not all of this is going to work.
0:59:41 But what are smart people trying that is some version of the future
0:59:42 in this area of AI?
0:59:46 And like that will probably educate and inspire me and some of it will be really big.
0:59:51 Yeah, I think that like if you’re 22 and you’re young and single
0:59:54 and you’re into this shit, I would just say two words.
0:59:57 I would say go West, go West, young man.
1:00:00 By the way, people always talk about San Francisco.
1:00:02 It’s dangerous, it’s dirty, it’s lawless.
1:00:04 That’s the appeal, baby.
1:00:07 You can say you made it in the war-torn city of San Francisco.
1:00:10 You don’t want to be a billionaire who is coddled.
1:00:14 You want to be a billionaire who grew up on the mean streets of San Francisco.
1:00:17 Yeah, not that mean.
1:00:20 All right, I think we have to wrap up.
1:00:21 Tara, thanks for coming on.
1:00:24 Where should people find you and where should they follow you?
1:00:28 You can just Google Sarah Goa or conviction.com and I’m on Twitter.
1:00:30 All right, that’s it.
1:00:31 That’s the fun.
1:00:31 Thanks, guys.
1:00:34 I feel like I can rule the world.
1:00:40 I know I could be what I want to put my all in it like days on the road.
1:00:42 Let’s travel never looking back.
1:00:44 (upbeat music)