Why AI Moats Still Matter (And How They've Changed)

23:00And they're finding that their ability to collect is meaningfully higher, you know, than that labor, that the kind of cost-benefit trade-off is so dramatic, the company is getting a lot of, you know, revenue from those customers who may not have had, you know, millions of dollars of IT budget historically and are now very willing to pay for a product like that, you know, given the impact on the business. And the way that we used to talk about this a long time ago is, and this almost had a pejorative slant to it, but it's like, are you building a feature, a product, or a company? And what's the difference between the three?

23:30Well, a feature is like there's an existing product and you tweak that product to make it marginally better. A product is, you know, not that. It's like some, hopefully, system of record or something that keeps track of something. And then a company is probably the most defensible of those three where you have a product and maybe you own a platform. Like the platforms tend to be the most valuable companies. But a feature is like I built a Chrome plugin and that doesn't mean, and by the way, there were a lot of Chrome plugins. Like Honey was a Chrome plugin that got bought for$4 billion. Like I wish I had done that, right?

24:07That's a good feature. But that was a feature, you know a product would be like oh I built my own browser and a company is like all right well like my own browser company actually makes money like you don't actually have a company even if you have 10 products if you don't have a sustainable path to have that company be around in 10 or 20 years and I think kind of another way of thinking about what David just said is that now the features like you know the feature was the most pejorative and seemingly small of all of those three almost obviously some of the features can be incredibly profitable because it's like wait a minute like this it feels like a feature um because it could get added to salesforce right or could get added to one of these other things but the amount of money that i can charge for my feature is like orders of magnitude more because it's like hey i'm going to be the front office receptionist for your you know orthodontic clinic like that's my job like that's my so that's that's that's the feature and it sits on top of whatever software you currently use, but the feature I can now charge$20 ,000 a year for because it is doing the job of labor.

25:10But uh-oh, will the existing product that my feature is riding on top of, will they go build those pieces of functionality? And or will another company show up that just says, hey, we're going to sell the greenfield with the new product that kind of has this feature set embedded. And, you know, feature product company, it still is out there. But I've just never seen a world where the features, if you will, can can get to revenue scale as quickly. And by the way, you kind of often have to start with the feature because a customer isn't like, think of it from the customer's perspective, the customer being the business buyer of software.

25:44It's like, I know I want to be locked into a piece of shit software company for 20 years. That's what I'm looking for as a buyer. No, it's like, oh, I have a problem to solve. My problem is I can't hire a front office receptionist for my orthodontic clinic, or I can't call people in Mandarin or Cantonese to go like repay their auto loans. Like, what do I do? Oh, something shows up and it offers that functionality. Boom, I'm a buyer. And then that functionality has to, that feature has to backfill product, backfill company as quickly as possible. So that's still true today as it was 10 or 20 or 30 years ago.

26:17But the difference again is that the feature, the revenue for the feature is just so high and the demand for it is so high because again, in many cases, you're just responding to help one of that. effectively. Yeah, and so I think the effect of that is that there's been sort of like a Cambrian explosion of interesting markets to go after. You know, I think it's unrealistic to believe that like OpenAI is going to go build, you know, the front office assistant for the, you know, the dental clinic, like as their core, you know, kind of business. They're not going to do that across every single market.

26:45I think the other dynamic is that for many of these companies, part of the product value is actually orchestrating the work across lots of different model companies. And so I think having one, you know, foundation model business, you know, going kind of up the stack, I think limits the actual impact of the application, you know, potentially as well. Well, I think that, you know, if you kind of think about this versus other platform companies, so Facebook was the preeminent platform company of Web 2.0. So call it from whenever they opened up Facebook platform, which I think was like 2007. People built their businesses on top of Facebook.

27:22Facebook would never do those particular things. So Facebook is never going to show up and say, hey, you know what? We should build a farming game. They were like, no, we're going to have a platform that allows companies like Zynga to build these farming games. But what the platform normally does, if they don't actually go compete with the underlying products, is they say, I'm going to tax it. But I'm going to tax it in ways that are kind of at my fancy. So this week it's 10 % taxes. That's my promise. Oh, wait, I changed my mind. Now it's going to be 40 % taxes. So that's why it's always dangerous to build on somebody else's platform.

27:54So I think the two things to look at are, number one, is will the platform owner compete with what I'm doing? And that's also another Goldilocks zone question, right? Because why is it, I published this graph of VisiCalc versus Lotus 1-2-3 versus Excel. So VisiCalc invented the spreadsheet in 1979, had 100 % of the market because they were the only player in town. Lotus built a better version of that. But Lotus got to, I think, 70 % market share by 1985, which was when Microsoft released Excel for a Mac. And then by 2000, Microsoft had 96 % market share. And why is it? Because they owned Windows.

28:31The platform owner normally wins. But that's because it was just such a huge— Why do I buy a computer in 1997? Because I want to use a spreadsheet. It was just so intrinsically linked. That was one of the main use cases for computers and business use. It's like using spreadsheets. So that was like a violator of Goldilocks zone. Whereas other things where it's like all you have to worry about from the platform owner is that they're going to tax you. But they might tax you in very, very bizarre ways. But part of what David was saying in terms of like there are multiple model companies, which is great.

29:00Like the problem with Windows was that it was like 95 % of the market. Like 95 % of your customers used Windows. So if I'm going to go build a competing spreadsheet, I'm just toast because the platform owner is just going to drown me. Now, there are five model companies, or, you know, more, like when you include all the Chinese models and whatnot, open source. Like, I don't have to worry about that, but I do have to worry about them saying, wow, this is so relevant. Like, why is it that OpenAI got a public company CEO to quit her job and just to become the CEO of applications at OpenAI? Maybe because they have a huge application opportunity.

29:38but this is the nice thing is that a lot of these things are so obscure but they're still big but I don't think open AI is going to go do them because it's like are they going to do like dental care management like they could but if they've done that then I would be short open AI because it's like they've run out of good stuff to do that's something that they should do in 2029 and this is I think I told you this this story before this changed my outlook on life when I pitched this guy Dan Rose at Facebook who was running business development there. I'm like, this is a huge opportunity. You should use us for payments.

30:13We're going to do this. We can make so much money for Facebook. And he was so patient and nice. And I love this guy. I'm on a board with him to this day. He was like, Alex, that's such a great idea. I was like, all right, I got the deal. Yes, he said it's a great idea, but we're not going to do it because you're pitching me a goal. Like we have gold bricks all around us. Like, and he was right. I mean, like Facebook in 2010, I mean, how much money? Facebook has grown their revenue. They have more profit every quarter today than they had revenue per year in 2010. It's just such an incredible company.

30:40And he's like, you're pitching me a gold brick that's like 100 feet away, and it's real. Like, I love that gold brick, but we have like hundreds of gold bricks where I just have to like stoop down at my feet and pick them up, so I'm just not gonna do that one right there. And that's how these big companies think. But the nice thing is that these are gold bricks. These gold bricks are bigger than they've ever been because you have software that can do the job of labor. Yeah. Which is on that note, But if you were running OpenAI and you were thinking about which gold bricks or how to even what mental model to think about sort of what are the things that you should be doing first versus things that, hey, maybe let other people do, how would you be thinking about that question?

31:16I mean, I think a lot of it is where, well, it's two things. Number one is we want to be the back end for everybody. Like the platform, I think it's two things. Number one is can we be the platform for pretty much everybody who's building anything? So we're not going to go into these obscure spaces like orthodontic care, at least not until 2045. So let's make sure that every single developer is using us. And this is part of why Microsoft crushed Apple in the 1980s, because Apple made it really hard to develop software. And what's actually kind of interesting is that both Apple and Microsoft, like Microsoft started off as a compiler company.

31:54Like their very, very first products, they were not Microsoft Office, it was not DOS. they built a basic interpreter for the programming language basic, and they had a big business. Their biggest competitor was Borland, which only made compilers. And like the early rallying cry, if you talk to any early Microsoft employee, was beat Philippe. Philippe Kahn was the CEO of Borland. So Microsoft was focused on that, made a lot of money on that. And Apple was like, we should make money on that too. And they had a product, it was called MPW, Macintosh Programmer's Workshop. I remember I used to use it in the 1980s.

32:25and it was like$2 ,000, I think, in 1980s money to buy this, you know, IDE or, you know, programming thing. And it's like, how do you afford that? So, like, but it was like, we have to make money on that. Microsoft's making money on this. And then, lo and behold, there were like 10 ,000 times more, you know, DOS and Windows software products than there were Macintosh software products. And, of course, Apple corrected that mistake when the iPhone came out. When they did now, like, Xcode, which is the way that you build products for Mac products or Macintosh and iPhone, iOS, it's free. So like they kind of corrected that mistake.

33:01But I'd say two things to answer your question. Number one is, can we be the biggest consumer brand in the world? So ChatGPT has 800 million weekly active users, like get that to 5 billion, right? Like even if Gemini 3 came out today, it might be five times better, but are people that are using ChatGPT just as consumers, are they going to switch? like maybe, but it's unlikely just because they kind of make that their default and then be the back end for everybody who's building anything and that way it's like kind of all the gold bricks kind of come to you. I think the other thing that we should anticipate, we're already beginning to see from some of these big model companies are like, what are the big horizontal applications that they can likely sell to every large enterprise?

33:43And I think you saw today with Google's anti-gravity launch, like the IDE is going to be one of those things. I think like that You know, if there's like product market fit for, for LMS, like, you know, coding is definitely, you know, one of the top categories. So I think that, you know, thinking about what are the big horizontal kind of applications in the enterprise. I think there's also to some degree, and, you know, I think this has been earlier to sort of play out. It's sort of the Palantir opportunity. I think we're still very early in sort of the proliferation of this technology into large enterprise.

34:13At the same time, unlike prior product cycles like the cloud, if I'm the CEO of a large public company and I'm asking myself, do I need to be in the cloud? It was sort of an esoteric idea. Today, I can plug a prompt into any one of these models and intuitively understand the impact that it could have on my business. The efficiency gains in my customer support organization, in my engineering organization, in all of my back office functions, at the same time, many of them don't know where to start. And so I think you will see sort of this consultative, sort of forward deployed, Palantir-esque sort of sale into very large enterprise from some of these, you know, big model companies.

34:52Again, I think we're early in that, but you've heard inklings of this with, you know, with Anthropik talking about wanting to build into financial services in other markets. So, you know, I agree. I think the biggest opportunities are the one that Alex is describing, but I think you will see them selectively, you know, try to build kind of applications that cut across every one of those. and then they'll probably choose a few sort of like lighthouse customers to build largely bespoke kind of custom integrations into these bigger enterprises. But where the ACBs just really make sense. In Web2, there was a lot of winner take most.

35:28You were talking about one of the benefits in AI is that there's multiple winners. To what extent is consolidation inevitable or how do you think sort of this plays out? Well, I think if you have 20 companies that are all doing the same thing, what has historically happened is that it's a bad market if there are 20 companies doing it. But then, I don't know, the bottom 15 just go bankrupt. And then maybe there's some consolidation where number one buys number two, number two buys number three. And assuming that we have a functional FTC and whatnot, it's like all of this is approved because it's not like you're taking – this is like orthodontic clinic answering software or something.

36:08And then what was a bad market becomes a good market. And this kind of goes back to why momentum is important, because if you have 20 companies that are all at the exact same scale, then it's actually great for the customer, which is like the prices go to zero, or they converge on the price of electricity. whereas if you, this is not saying you want to go build a monopoly in orthodontic answering software or something, but rather you can charge more if you get to a certain scale because whatever the quality of the product that you're delivering at the end of the day is just higher. And you have to get to the critical scale to get there.

36:45And sometimes you just need these markets to work themselves out. I mean, like when I was running my company, TrialPay, we had, I don't know, 20 competitors. And it was tough because it's like, you know, everybody would be pricing their product at a loss. You know, this loss leader only works if you end up leading with like, you have to make money at the end. And nobody really had a plan for that because the venture capital dollars were really subsidizing everything. And that does not get a good market. What does become a good market at the end. And sometimes this is what, you know, Vista, the private equity firm would do is like, we're going to buy one as our anchor.

37:18We're going to go lowball and put the other five out of their misery and now we end up with actually a pretty good product at the end or a pretty good business at the end, pretty good company at the end. So I think that will probably play out the same way here because you just can't have a market where you have everybody lost leading and nobody's big enough to get any kind of scale effects. Is there going to be a world where the 19th player survives? I mean, Jack Welch would always say you have to be number one or number two and there's no value being number three through 100. I don't think that's changed.

37:52Right. Even in the model provider example. And I'm also curious if prices go down. Yeah, I don't see how, like, there actually are, I mean, people know XAI, Anthropic, OpenAI, Gemini, like, they know, or Quinn, they know the big ones. But there are actually, there's a long tale of things that people haven't heard of, where it's like they've raised lots of money. It's just like not, it works fine. but how can you serve, like the model company is the most cutthroat because like unless you're state, if you're state of the art minus, minus, minus and you're trying to earn a living, it's just like that's just not gonna work.

38:29So that game is super cutthroat. I think the one area where that may have diverged and Martine talks about this a lot, is like when markets are growing so quickly, you end up having specialization. And so I think in other kind of modalities, in some of the creative tools or people have specialized to serve the up market, You know, like I'm producing, you know, movies. Okay, I want to create sort of like social, you know, quality content. Like these are different, you know, markets that the models can kind of specialize in. Time will tell, you know, how sort of, you know, defensible those become over time.

39:02But maybe that's the optimistic take that like, you know, early on everything looks, you know, overlapping and competitive. But we're still so, you know, the market is growing that everything can kind of expand and people can kind of specialize over time. earlier when you were talking about the feature versus product. Didn't Steve Jobs once tell Drew Houston that Dropbox was just a feature? Yeah, that's why it's always been this pejorative thing. But that's kind of the point that I was getting to is that nobody wants to like, oh, I need this company. No, it's like, I need this feature. Every now and then you see a product that is not a feature because it's just like so far out of left field.

39:36Like nobody was anticipating ChatGPT dominating their daily workflow in 2022 in October. But then once it came out, it was this like, holy crap, this is incredible. And that's not a feature. You could argue it's a feature on top of your iPhone, but no, the iPhone is the delivery mechanism. That's a product. And they've obviously turned that into a company. Whereas other things, it kind of is like, you know, why is there antivirus software? That almost doesn't make any sense. Like, shouldn't the operating system stop you from getting viruses? Like, why do you need a third-party tool to do synchronization between devices?

40:09But it turns out, like, the reason why Dropbox has survived and thrived since Steve Jobs made that comment is like, it's really hard to do well. And there's a lot of other things. Like once you've built that feature, you can backfill with all sorts of other product, which is what Dropbox has done a pretty good job of. But it is hard because this is the danger of building on somebody else's platform is that, you know, I'm going to build this thing that they should have had, right? If they had the foresight. And if it doesn't operate in the Goldilocks zone, right? it's like, wow, this will like triple Apple's profits.

40:45Let's just say that Dropbox would have tripled Apple's profits. Would they have dropped everything? Would they have focused on building that versus the iPad or something, whatever like Steve's last gizmo was? Like, sure. But if it's kind of in this like Goldilocks zone of irrelevance, like janitorial services, it's like, yeah, they should do that. But, you know, platform owners get lazy. This is why like, you know, half the things on my iPhone don't really work if they're built by Apple. Try like any parent that's listening to this, if they've tried screen time, it's just like an embarrassment upon humanity.

41:17And because they don't have to go sell as a, it's like they don't have to compete on feature. They compete on the fact, they don't even compete. They just like, they're the platform. They roll it out, it's gonna be bad. And that does create an opportunity for somebody to come up with a feature and actually out-compete the platform. But like, you have to be careful because it's like, obviously the platform owner is gonna go compete with you. And that's why often what I find very compelling about entrepreneurs when they know this, like they've studied how is it that from every single platform shift from like, you know, we were talking about AC versus DC current, like there have always been these battles for like who's going to be the underlying, you know, layer.

41:56The best entrepreneurs have studied this and they have a plan. They're like, I know I have a feature. Like Drew knew this. He's like, I know that like there's this stupid comment on Hacker News. It's like, oh, this is just like our sync with this, that, and the other thing. It's like, yeah, of course Drew knows that. But he built this into a$10 billion company because like he had a plan. And the best entrepreneurs, they often like, okay, I know it's not this naivete. I was like, oh, I'm going to build this. There's no way that they're going to build it because they're too dumb and stupid. It's like, no, they're not.

42:22Like these companies, if they get their act together, they will marshal a lot of resources to go compete with you. It might take them five years, but they will 100 % do it. You have to backfill your feature with a product and you have to have a moat for that product as opposed to like, oh yeah, like the big company will never figure this out. It's like, that's not true. I think what's also unique, I wrote this piece a while ago called the messy inbox problem. And it was sort of a wedge strategy that we've been observing across lots of different industries. And it's just this idea that you hook into a bunch of your different unstructured data sources.

42:53Could be email, could be fax, could be phone. You know, Tenor, as an example, has trained a model to be able to extract all the relevant patient information from those data sources to plug it downstream into some system of record, in their case, in EHR. But this exists in a CRM, an ERP, what have you. And I think that that wedge for that feature is interesting in large part because it lives up funnel from software, right? You're replacing the kind of human level judgment of the individual. Like often that, you know, the secretary is sort of like collecting the physical facts and then plugging it into the HR.

43:25And so now a bunch of AI companies can kind of, you know, wedge in and then eat away at all the downstream workflows that might have been other point solution software companies. And so, you know, Tenor is no longer just doing, you know, the messy inbox. They're now doing scheduling and prior, you know, prior auth and eligibility and benefits. And they've used that wedge to try to become, you know, kind of the end-to-end platform. Eventually, maybe they become the system of record. But again, because you can kind of replace the human labor now with software, I think it's creating opportunities for these, you know, features to actually become products.

43:59And, you know, in their case, I think become, you know, whole companies. Well, I think this is the thing that in my mind is very dramatically different than every other platform shift is that it is just so consensus. Like cloud was not consensus. Mobile was not consensus. And that's why the incumbents kind of screwed up. And then sometimes it was just like completely, I'll use the Silicon Valley term, orthogonal to their business model. Because it's like I sell$5 million a year products. And wait a minute, I'm going to charge$100 ,000 a month? Like, that's just hard. Like, how do I pay my salespeople?

44:34How do I make my quarterly numbers? So that's why, like, you know, Workday beat PeopleSoft. Or that's why, you know, Salesforce beat Siebel. So all of these things played out. But behind it was this concept of it's like that new thing, that iPhone is stupid. Like there's no version of the famous Steve Ballmer clip of like him saying this, nobody's going to buy an$800 phone with no keyboard. There's no version of that for AI. It's like, how do you find a big CEO or even a small CEO? It's like, nobody will use that tool that makes you a hundred times more productive. Of course. And this is why it's kind of a bonanza for most of the incumbents as well, because anybody who has a system of record will add a button or a feature to use our parlance that will make them more money.

45:20So, like, they're just kind of gold bricks everywhere. And the challenge, though, is that there isn't this kind of white space to occupy in the same way that there was for cloud or for mobile or for a lot of the Web 2.0 things where it's like you just, like, the incumbents screwed up. They weren't paying attention. They scoff at this new technology. Like, nobody's scoffing at this new technology. Like, everybody's just trying to embrace it. But, you know, the opportunity often exists where a lot of the areas that just seem too small, they don't have an incumbent at all. Like those actually might turn out to be like, you know, trillions of dollars of value.

45:56And that's kind of what makes it much more exciting than like last gen where it's like, oh, I'm just going to copy everything that was on prem and make it, you know, recurring billing cloud. And I'm going to do that at a time when like the big guys say that's stupid and I don't get it. So some argue that mobile was ultimately sustaining in that although there were net new companies and use cases that were$100 billion like Uber and Airbnb, etc., that the incumbents, some of them became trillion dollar companies, helped guide by mobile. When we look at the business impact of the AI era, what's your mental model for thinking about sort of the incumbent startup or kind of net new company in terms of value capture?

46:36I think a lot of it is the same. Like, unless you really screw up the pricing model or like, you know, you're all per seat pricing, it's very, very hard to just get the market to adopt something that is just violently different. And you're operating in the public eye and your technology team is bad. There are a lot of ands that need to happen. I have a hard time believing that incumbents will really suffer. I mean, there probably are some things like, you know, take like one example of, and this kind of goes back to distribution versus technology. Like all of these business process outsourcing companies, these BPOs, they're the largest employers on the planet.

47:10So like Tata, Wipro, Infosys. So if I'm J.P. Morgan and I say I need a call center and this call center needs to have access to like customer records and it needs to be safe and everybody needs to be trained, like and I need to have like 100 ,000 people that can answer the phone. You know who can do that for you? Infosys, right? Or Tata. Tata has already done the integration with J.P. Morgan in this case. they might just add AI and now they don't need 100 ,000 people and they maintain that JP Morgan contract and they operate in the area of the Goldilocks zone where it's like they're going to make like 100 times more money.

47:46That's one case. That's the bull case for Tata. The bear case is like JP Morgan's like, wait a minute, like we should partner with the startup to do this or we should do this ourselves. And now like Tata loses that relationship altogether. And it could go either direction. Like I think a lot of these things are really up for grabs, But I think the default is that the incumbents probably will do well, but you can pick a lot of these cases. I mean, this is why you see the public markets kind of don't know what to do, where there is a case that is very, very bad for a lot of software companies. But there is an alternative case, which is like if you operate in the right Goldilocks zone and you're, you know, you have the right momentum to actually build these things and embrace these new technologies, like you'll maintain all of your customer relationships and you're just going to have a more profitable business.

48:33And it's not that you're going to do this. Like, the most compelling thing, I think, about AI that almost everybody gets wrong is like, oh, it's going to destroy all the jobs. Like, our beloved representative from Silicon Valley is, like, trying to, like, eliminate AI. It's just so crazy that our elected representative wants to turn us back to farmers of tangerines and whatnot in Silicon Valley. but um which which again i think is crazy but uh it's not like all the jobs will go away i actually think that's not going to happen at all what's going to happen is there a lot of things where it's like if i could hire somebody for a dollar to do this task i would 100 do that i cannot hire somebody for a dollar i've never been able to hire somebody for a dollar now i can hire software for a dollar so a lot of these tasks like you know look at how many people took taxis post uber right And it's like, did you hear people say, you probably took an Uber to get here today, right?

49:26Would you have taken a taxi 20 years ago? Like, no way, right? Because it's like, where would you find the taxi? How would you arrange the taxi? It's just like way too complicated. Whereas once you make it very, very abundant and less expensive, like everybody's going to use this. And I think that's what Rokana and his ilk are missing, which is it's not like, oh, I'm going to go and say I'm going to like eliminate all the jobs. Like think of it in that JP Morgan example that I just mentioned. It's like, wouldn't it be cool if every single customer of JPMorgan Chase could have their own personal friend that they could talk to every single day there that would help them with every single element of their financial life?

50:00Or it's like, I'm stuck downloading the app. I can't figure out how to get it set up. Oh, talk to somebody in real time that will help you about that. Why don't they do that? It's just like the cost is known. It's high. And then the value is probably low. and as soon as you can bring the cost down to zero now you're going to start hiring AI in all of these different areas that you just would never bother hiring a human for because it's just like you can't train the human you can't find the human and the human's too expensive That's a good place to wrap Guys, thanks for coming to the podcast Most don't matter Thanks for listening to this episode of the A16Z podcast If you liked this episode be sure to like, comment, subscribe leave us a rating or review and share it with your friends and family.

50:43For more episodes, go to YouTube, Apple Podcasts, and Spotify. Follow us on X at A16Z and subscribe to our Substack at a16z.substack.com. Thanks again for listening and I'll see you in the next episode. As a reminder, the content here is for informational purposes only. Should not be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security and is not directed at any investors or potential investors in any A16Z fund. Please note that A16Z and its affiliates may also maintain investments in the companies discussed in this podcast. For more details, including a link to our investments, please see A16Z.com forward slash disclosures.