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. You 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 never equal a silver bullet. You really need that 100x value leap. Now with the models that we have access to, we are awash 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 on having a better product.
I'm Anish. I'm a general partner at Andreessen Horowitz. 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. For enterprise, we love to invest in companies that are working, maybe less weird, could be weird. No judgment. I personally am an engineer, a product person. I write a lot of code in my free time. And, you know, I feel like we're living in the age of miracles. So, if you're building, I want to hear from you.
Yeah, 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 trying new AI products without being paid to, because I think of customer acquisition cost as a form of subsidy. You know, the customer is not motivated enough to do it on their own. The company 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. I think the first thing that we really saw was the uptake of ChatGPT and Midjourney and a number of other very early AI products. All of the traffic was organic, which was different from what we had seen in consumer product adoption for maybe 10 years. Looking at the early data around willingness to pay, what we saw was two interesting things. One was that a lot of people were willing to pay, so a high number of people that were willing to pay, and the second, that the AI companies quickly blew through what we thought were the ceilings on ability to pay or the sort of amount that a customer would pay for a subscription. There's actually an interesting reason for that. 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 products like video generation. And 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. So that really 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 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. The first is that you can build a software company with real revenue scale with very few customers on a relative basis, right? 41,000 for the $100 million run rate at $200 a month. And the second is that software should subsume almost every part of consumer spend over time. And increasingly those dollars are going to be captured by AI and by software products. So I think it's actually a very, very optimistic prediction, one that we've seen come true, which is that more individuals will be able to build large-scale AI companies and consumers will have more of their needs met through software.
I would say in the world that we're living in, there are no marketing problems. There are only product problems. I don't think products should have CAC today. And if you need significant customer acquisition costs, that means you haven't sufficiently delivered on the product. 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. And part of that is because the models can do things that they could never do before. You know, we had 40 years of building models that enabled or extended the intellectual parts of our brain and the intellectual parts of our society, 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. Now with these new subjective creative computers, we can address the entire nondeterministic part of human society and the human experience. That is our emotions, our relationships, our desire for self-expression, the creative work that we do. So this entire part, arguably a larger part of the human experience, 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, it's just way easier for a small number of people to build a lot more. 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.
