The Fastest Path to a $100M AI Business | Anish Acharya, a16z GP

Intro

00:00I think that when the product you deliver cannot be 100x better than everything else, [music] of course distribution is what matters. And I think the lie that we have sometimes told ourselves as founders is that something that's incrementally better is 100x better.

00:13You know, I think of this as silver bullets versus lead bullets. You know, one silver bullet is a dramatic improvement. Many lead bullets are many small incremental improvements. 10 or 50 or even 100 small improvements. 10 or 50 or 100 lead bullets never equal a silver bullet.

00:29You really need that 100x value leap. Now with the models that we have access to, we are a wash in silver bullets, right? There are silver bullets everywhere. So I actually do think in this day and age with the technologies we have access to.

00:42You can win by betting by having a better product. [music] I'm Anish. I'm a general partner at Andre and Horowits. I invest out of our AI apps fund. That means consumer and enterprise. For consumer, we love to invest in companies that are weird and working.

00:54For enterprise, we love to invest in companies that are working maybe less weird, could be weird. [music] Uh, no judgment. Um, I personally am an engineer, a product person. I write a lot of code in my free time. [music] And, you know, I feel like we're living in the age of miracles.

01:07So, if you're building, I want to hear from you.

Go Deep or Go Home

01:22Yeah, I've been thinking about this for some time. You know, if you look at just the broad trend in AI in terms of how many people are first [music] trying new AI products without being paid to because I think of customer acquisition cost as a form of subsidy.

01:34You know, the customer is not motivated enough to do it on their own. The company [music] really has to push them to try the new product and the magic of organic product adoption is that the customer is excited enough to just try it with no further incentive.

01:48I [music] think the first thing that we really saw was the uptake of chat GPT and midjourney and a number of other very early AI products. All of the traffic was organic which was different from what [music] we had seen in consumer product adoption for maybe 10 years.

02:00Looking at the early data around willingness to pay. What we saw [music] was two interesting things. One was that a lot of people were willing to pay. so high number of people that were willing to pay and [music] the second that the AI companies quickly blew through what we thought were the ceilings on [music] ability to pay or the sort of amount that a customer would pay for a subscription.

02:19There's actually interesting reason for that. I' I'd love to give our AI companies credit and say it was foresight or experimentation, but the truth is the COGS for AI companies is non-trivial, right? It can actually be very very high, especially for [music] products like video generation.

02:35And because you had real costs in these businesses, they had to charge customers real money. And to deliver the very best product experiences and generations, they had to charge a lot of money. And what many of these AI companies found is that even as they raised prices, customers were willing to pay and in fact wanted to pay more.

02:50So that really [music] got me thinking about, hey, what is the extreme version of this? And I love exploring ideas in their extreme. I just think it's [music] a very useful way to extract the kind of core of your thinking. In the extreme of, you know, people being willing to pay high prices, there's two actual implications.

03:06[music] The first is that you can build a software company with real revenue scale with very few customers on a relative basis, [music] right? 41,000 for the $und00 million run rate at $200 a month. And the second is that software should subsume almost every part of a consumer spend over time.

03:23And increasingly [music] those dollars are going to be captured by AI and by software products. So I think it's [music] actually a very very optimistic prediction, one that we've seen come true, which is that more individuals will be able to build largecale AI companies and consumers will have more of their needs met through software.

03:43I would say in the world that we're living in, there are no marketing problems. There are only product problems. I don't [music] think products should have CAC today. And if you need significant customer acquisition costs, that means you haven't sufficiently delivered on the product.

03:56[music] The truth is that founders and companies and products were never able to deliver with the kind of ambition that they can deliver today. You can just go insanely deep. [music] And part of that is because the models can do things that they could never do before.

04:09You know, we had 40 [music] years of building models that enabled or extended the intellectual parts of our brain and the intellectual parts of our society, [music] right? But that was only a single sort of aspect of the human experience and really of our civilization and society that was addressable by technology.

04:24Now with these new subjective [music] creative computers, we can address the entire nondeterministic part of human society and the human experience. [music] That is our emotions, our relationships, our desire for self-expression, [music] the creative work that we do.

04:39So this entire part, arguably a larger part of the human experience [music] is now addressable through technology. And that simply wasn't the case before. So I think that's one important point. The second is that thanks to AI code and the like collapsing costs and difficulty of making software.

04:55It it's just way easier for a small number of people to build a lot more. [music] So this simply was not possible prior and now you have founders that can do more things at an order of magnitude lower cost. And as a result you can go deep or go home instead of going big or go home.

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Narrow Startups

06:13So narrow startups are companies that build incredibly opinionated deep products, charge very high prices for a relatively small number of people. You know, the simple math is that charging 41,000 people $200 a month is a 100 million run rate business.

06:28And there's a lot of precedent for this already occurring. You know, we see Google Ultra's top [music] skew is 250 a month. Grock is 300 a month. Open AAIS is 200 a month. I believe Anthropics is 200 a month. Consumers are flocking to these products organically.

06:42They're paying high [music] prices for them. And over and over again, we're seeing them delivered the value that they expected. So the whole idea behind narrow startups is build small, go deep, [music] and charge a lot. I think specialization is a new moat.

06:56I think that you have the ability to go so much deeper with a new technology and the collapsing cost of software creation for an individual customer that you can just be so much more specialized for that customer that it's hard to compete with.

07:08You know, somebody's going to have to build 3 years of roadmap to have [music] a competitive product. So, it's simply differentiation taken to an extreme degree. I think that's an interesting and important form of a moat which is particularly relevant to narrow startup.

07:24I think the second is if you look at chat GPT they're trying to do a lot of things and if you think about areas in which there's a really rich software ecosystem that has to be built to really capture the value I don't know where that's going to fall on their priority list a great example is meeting recorders there's many products that now take notes for you by transcribing speech to text that is great but to fully capture the value you probably need to build a whole office suite you need [music] spreadsheets you need word processors you need a diary diary app

07:54and a notes app and you need all kinds of software. It's just not obvious to me that the labs are going to actually [music] get to that. So I do think that building a rich software ecosystem, a rich product ecosystem is another way to compete.

08:05Okay, I think the third thing is that there are many product categories like AI code where you benefit from using many models, right? It's better to be able to use anthropic and open AAI and Google's models. And if you're at OpenAI, you're never going to be able to build a product that also uses Google's models.

08:21[music] So being multimodel is a way to compete with elabs and big tech. The other important point is that when these products overd deliver for their customers and they can if you ask cursor to help you generate a feature with a model sometimes it's like wow this was even better than what I had hoped for or what I had imagined.

08:38So one the fact that these products can actually have those attributes and can overd deliver on the customer's expectations but the second is that they can charge for it. You know, sometimes the model has to think really hard to deliver that extraordinary outcome.

08:53And guess what? When it does, it's expensive. And that is the way that it should be. I think that when the product you deliver cannot be 100x better than everything else, of course, distribution is what matters. And I think the lie that we have sometimes told ourselves as founders is that something that's incrementally better is 100x better.

09:10You know, I think of this as silver bullets versus lead bullets. One silver bullet is a dramatic improvement. Many lead bullets are many small incremental improvements. Like 10 or 50 or even 100 small improvements, 10 or 50 or 100 lead bullets [music] never equal a silver bullet.

09:28You really need that 100x value leap. Now with the models that we have access to, [music] we are a wash in silver bullets, right? There are silver bullets everywhere. So I actually do think in this day and age with the technologies we have access to you can win by betting by having a better product.

Build for Pull, Not TAM

09:48Predicting a total but addressable market is a fool's errand. It's it's just impossible. I it's very very difficult and it's a common source of failure for investors certainly but even for founders. When I was a first-time founder I [music] had this big brain way thinking of you know products which is hey we need a big market.

10:04It has a needs to have a big TAM. I wasn't even quite sure what TAM [music] meant, but it seemed important and I know you needed a big one. A big one is better than a small one. And that's why a lot of my early thinking was in markets like healthcare and you know disease management and I just didn't know anything about those markets nor did I have energy for those markets.

10:20You know how I built a successful product was building something that I wanted to see exist and I was personally [music] passionate about which was sort of social graphs and mobile games. And that's what me and my founder built. Look, when when the iPhone app store was released, there were 6 million iPhones in the world.

10:36Like, [music] that's not much of a TAM, but we built there because it felt like it was growing quickly and we had a lot of energy for the market and we bet on, you know, perhaps not even thinking about the TAM and we were right. So, I don't think about TAM very much at all.

10:49I do think about value delivered to the customer and [music] the, you know, price they're willing to pay. Okay. So, I think the most useful prompt for a founder right now is what is the $1,000 a month skew of our [music] product, right? That is the direction we need to be thinking about like what is the extraordinarily expensive?

11:06What would the product need to do? Does [music] it do it today? Would people be willing to pay? Have we tested it? So, I think if you find customers that are be willing to pay dramatic prices for your product, you're probably on the right track.

11:16[music] You know, conversely, if you have a free product that you have to pay customers to try, you're probably on the wrong track. [music] It's a much more useful signal for builders than thinking about concepts like TAM. If people are paying for it, they're getting value typically.

11:28Of course, what is like upstream of that? [music] Things like retention and things like customer acquisition cost. So these things can be measured, but this is why it's so useful to build in an area in which you have great intuition cuz you just [music] you feel the feelings, you know it, you talk to the customer, you've perhaps you're the customer yourself or you've got great intuition around their pain [music] points.

11:46The customer has more ideas for your road map than you have. Like there are a lot of qualitative signals. The most overriding signal is you simply can't keep up with everything that is happening as a result. Like that's how you know you have product market fit.

11:59As Mark famously said, the market is [music] pulling the product out of you often violently. That is the experience of it. I mean I think there there's many psychological traps from being a founder. I can tell you a few of the ones that I fell [music] prey to and experienced as a founder.

12:13So one is trying to talk yourself into having product market fit. like [music] if you have to talk yourself into it, you don't have it. I think that's incredibly important. I think the second is, and perhaps a related point, you know, you're looking for metrics [music] that will justify this fact that you have market fit and you go crazy looking to calibrate on what's [music] good retention, what's good.

12:34Those are often not productive. Ultimately, a business has [music] physics and if you're losing 90% of your customers at the end of year one, like [music] even if that's bestin-class for the category, it's very difficult to build something that's working.

12:48So, [music] I think thinking about the sort of business health and first principles rather than frameworks is often more productive. I think the final trap that you can often fall into is the power user trap. Power users are power users and that's great that they're getting that much value out of the product, but if you're not able to capture the value that they're getting, you know, they still only count as one dot on your growth chart.

13:09So, you really do have to either build for power users and [music] capture the value you're creating, which is the narrow startups idea, or you need to build for a mass market and not, you know, tell yourself that having some really happy power users is a substitute for having broad market fit.

13:28The most important piece of advice is that there is no marketing problems. There are only product problems. Be insanely ambitious on product. Raise prices. Adjust based on what you hear from the customer. And don't worry so much about business books, frameworks.

13:42Just build for a small number of people. Charge a lot. Go insanely deep. And you know, more likely than not, you'll find your way to success. Like this is not a 20, 30, 50year idea. This is like a 3 [music] 57year idea. That's what the abundance agenda means.

13:54And it's coming now because there's both abundant capital and [music] dramatic consumer interest in these new products. You know, if you were ever going to start a company, start it now. Like, there are better and worse times. [music] And this is the best time I've seen in my entire career by a long shot.