20VC: Five Predictions for a World of Agents | The Ads Business Model Will Die | Biggest Lessons from Working with Elon Musk at Twitter with Parag Agrawal, Parallel

20:32If we figure that out, it'll be a huge market and agents will be better off. If we don't figure it out, you're going to be in this weird cat and mouse game of PitchBook being like, no, I want to sell you a seat. I'm going to shut it off. And your agent is stuck without the data. And then like you're involved in like pulling data.

20:51Harry Stebbings:I think every big company has the choice today of do we let agents in or do we keep them out? And Amazon has said, I'm sorry, in most recent times, Muse, you will not be let into our garden. Shopify has said, come in, baby. Expedia said, come in. How does this play out? I think eventually everyone has to let them in. The question is on what terms so how do you align incentives for everyone and people are going to have to play their strategy games on how they win in this new world literally the customer is changing in front of our eyes right like the customer used to be a human you're building products for humans now you're building products for agents or you're building agents and so now you have to figure out what your place in this new reality will be and i don't know if there's a right or wrong answer here it also depends on sort of how much market power you have do you think amazon were right to say no to Muse?

21:42Depends on what they do next with it. If it turns out that they have sufficient market power to have Muse or other agents connect to them differently, perhaps, over time, or ship their own agent and drive crazy adoption, let's say they have that capability, then I guess they were right, right? On the other hand, once they've made this, we're not going to allow anyone else's agent, and they can not ship an agent that consumers use, and they won't allow anyone else's agent to use them and a lot of the transaction economy starts moving off of to agents which are all big ifs by the way then it would be a bad move now i'm betting on agents i have mixed feelings around agents and what fraction of e-commerce transactions they do like it's unclear right

22:25Harry Stebbings:like it's i do you think it's unclear i think it's unwaveringly clear maybe i'm uh super early on the adoption curve and i buy everything through instinct now other than holidays and a home yeah I'm literally just having these their instincts. So me too. But I also know a lot of people who like to buy things themselves. And like, listen, we want to delegate to agents things which we see as chores and uninteresting. And not delegate to agents things that give us joy or pleasure or make us have fun doing those things. And I know people who don't want to delegate shopping. They want to delegate a lot of things in their life.

23:01They don't want to delegate shopping. And so that's why I don't know the distribution of these people and how behavior changes. but it might be people give away a lot of other chores and then spend a lot of time shopping.

23:10Harry Stebbings:One thing that does worry me is actually the dissolution of the advertising industry in the wake of agents. If I have, you know, if I order my Deliveroo and my Uber, DoorDash for dear American counterparts, through Instinct, that Uber banner that's now advertising something becomes worthless. Amazon, their advertising business is bigger than their e-com business now. Of course they're shutting it off because if agents, the primary customer, your ads business goes to next to nothing. Correct. And this is not just you talking about this in the e-commerce land, right? But this is what I meant early on when I said like the business models have to change.

23:46Ads don't work with agents in their current form. Forgetting e-commerce for a second, if you think of you're in the content business, let's say your page, which is ad supported, public information on the web, ad supported page, people show up, you show them ads, you make money, great content. Agents show up, no one sees ads, you make no money, which is why we like to pay people So we're effectively building an ad sense for agents showing up to read your content. So we like to pay content owners a variable amount of money every time an agent derives benefit from reading their information, which is a variable amount of money is what a visitor to your website will pay you based on a click probability or a value probability on ads.

24:24Harry Stebbings:Why do you do that? To incentive a line content owners. Otherwise, what's going to happen? Everyone's going to block agents. So you need to find a replacement to the ads business model. I get you, but you have to assume that you're going to be 100 % on the market then. Because if you're 30, 40 % of the market and you're like, oh, don't worry, we'll pay you. And New York Times is still like, well, thanks, Parag, but 60 % of my traffic is still unpaid. So I'm just going to block all of you. No, but I think they're going to block them and not me. They're going to give me a data feed. What does incentive alignment mean?

24:55It means the New York Times believes that I pay them competitive market price or the right price or an attractive price or a fair price. If I do that, they should give me their content. And if somebody else doesn't give them that, and if they have the technical levers or legal levers, they shouldn't give it to them.

25:12Harry Stebbings:Do you think this business is a little bit like music with streaming, which is like the business just becomes candidly much worse for the creators. And it still provides them money and significant money, but they have to get a little bit more creative with alternative streams, touring, merchandise, alternative business. Is it the same where your core goes down and you have to get more creative? I don't know, but I don't think so. I think there's one fundamental thing that is different here. Agents using the web a thousand X more, like that thousand X, is really different. Now, all of a sudden, the amount of utility added goes up if these agents are presumed to be doing something useful.

25:51And so, this is not just a change in the share of value that people transact over. This is a large growing pie. And when that happens, it is actually possible to transition business models. Now, of course, don't get me wrong, there are going to be winners and losers, right? Like some pieces of content will become very valuable, some pieces of content will get more commoditized, and people are going to have to adapt to a new customer, to a new market dynamic, to a new kind of monetization engine. But the overall market size, I think has the potential to increase, unlike in music where it took a while for it to grow back.

26:31I think my understanding is now the industry has grown back up and exceeded its previous peaks in a material way. But there was a moment where it was smaller. In this case, that might be a very compressed period, given how fast these things are growing.

26:45Harry Stebbings:Everyone questions the sustainability of margin structures in this business. How do you think about that as a business today? today we're in the infrastructure business and we have a real technical lead in terms of being able to do things at very high quality very cheap if you think of the tech we're building right like what are we doing we like to give the highest quality answer make it fast make it cheap spend the least amount of compute doing it like we obsess about only these three things right quality cost latency turns out if you do that relative to a stack built for humans over the last 20 years you can do things at the same quality for 120th, 150th of the compute.

27:26And so a lot of margins come down to market structure on competition over time rather than any other factor. And in our industry, the market is large. We're too early to know what future competition and market structure looks like. But the margin change due to content owners is not something I worry about. And let me tell you why. The entire premise of us paying content owners is driving incentive alignment. So we like to pay content owners the marginal contribution that they added to an agent doing work. What does that mean? Let's assume that there's an agent trying to get something done and you're going to spend a dollar on that agent to get this thing done.

28:08Now, if you've spent a dollar and 10 seconds, because we have a larger model available or ways of spending compute, you could have gotten a slightly better answer. If you'd spend 90 cents, you would have gotten a slightly worse answer. if you're running good agents, like they're on this Pareto curve. So now imagine I took out one content owner, their data from the web index, and I still spent the dollar. But let's say after taking them out, the quality of the result was the same as the 90 cent agent with their content. So why wouldn't we go and take this 10 cents of marginal contribution they had as a content owner and pay out a decent chunk of it to the person who brought that data?

28:46That's how we do our math. That's how we've trained our models, which tell us how much to pay for what content to eat. And so to produce, if I was going to offer an equally good product to my customer, I'd rather pay content owners than spend on inference because I'm spending the same amount.

29:01Harry Stebbings:So they're all big numbers, but then it actually comes back to revenue at a certain point. Companies are scaling faster than ever revenue-wise. Is it a business where your revenue is able to scale as fast as others? One mental model of our business is we are an adjacency to inference or knowledge work or personal agents. So take out GPUs going into media generation or training. So take training away, take media generation away for a moment. Look at all of the GPUs, whether it's small models, open models, proprietary models, forget all of that. Every bit of inference across all models going into running agents.

29:37I think somewhere between 5 % to 20 % of that spend that goes into GPU will need to go into

29:44Harry Stebbings:some sort of a web search stack. Now, if you look at how many data centers we're going to build and how much power we'll generate and how many GPUs we'll build and the scale of this build out and at what rate that's growing, this is a very material market. And if inference grows 3x, 5x, 7x year on year, we grow alongside it in the same rate if we're just holding our share constant. If we're growing share, we're growing even faster. So like a firework scales to 2 billion in revenue in four years. Is that like, I'm bringing up, is that like a similar revenue trajectory that you can follow? Yeah, but I think when fireworks is 2 billion in revenue, the inference market revenue is 200 or more, maybe 300.

30:28And so our market potential based on my 5 to 20 % math is whatever, call it 10 to 50, 15 to 60, whatever. And what fraction of that can we capture? That dictates how fast our revenue can grow. Like today, I think we grow alongside influence or more.

30:44Harry Stebbings:If you think of it like a$20 billion there, let's just take that kind of middle. If you assume a 33%, which would be a lot of a market, that would be, you know, whatever that is, six to seven billion, give or take. That's amazing. But before you told me it was a hundred billion dollar business plus, that doesn't get you to a hundred. In valuation, it does. We were discussing valuations earlier, not revenue. Yeah. So six billion growing at the rate of inference gets you to a hundred billion business easy, but that's in the next few years. And you think that's possible in terms of that revenue scaling that fast?

31:17Yeah. I think in the next few years it is.

31:20Harry Stebbings:2030, we're going to sit here. You think you can be there? I'll get a tattoo for parallel if you can. I think it's possible. I think we are going to have to execute well and a couple of chips have to fall our way. What would be the reason why you don't? Let's map out the, hmm, what do we have to get gnarly about these problems? One reason would be that we see agents don't work. There is like a tail risk that agents don't deliver on the profits and we overshoot as a society, which is extraneous to us. If agents work and deliver value and we spend all the money on GPUs that we plan to right now, then the main question is, did we execute well enough to have a 33 % share that you bet on?

32:03And that comes down to, in my mind, did we build the best tech? Did we partner with all the content providers to have their content available? Because without it, it's not very useful if you can't rely on it. And did we go earn the trust of the customers that end up having a decent chunk of that inference in four years from today? And then again, there's like large cone of uncertainty, right? Like I'd say there's the 5X uncertainty in fireworks share at that point. If open models crush it, like based on fireworks, all of them will have a huge chunk of revenue. So did we end up selling alongside them?

32:43Did we find all the customers which are spending money on them to spend money on our web search by making it the best web search in the world?

32:49Harry Stebbings:What about commoditization? If you have a read of semi-analysis where they did the benchmarking and then you were like number one, woohoo. And then like a week later, you weren't number one. Sad. And there were like three or four providers within very close proximity. You're like, oh, well, if it's commoditized and I take a second layer of thoughts that we'll see a race to the bottom on price. and then actually the available revenue. Why am I going down the wrong pathway here? One, there should be a rift to the bottom on price to get to the thousand X scale. I think the pricing on web search today is just off.

33:25You think customers pay you too much? Not pay us too much. I think the market is mispriced. Let me tell you why. Let's say you use the Luna model with OpenAI's built-in web search today or with anyone's web search, forgetting ours, and you ran any kind of deep research. Let's say you built an instinct using a lunar class model. And at some point, a lunar class model will be able to do 60, 70, 80 % of your personal agent. And it'll do a lot of searches. In that moment, you'll be spending 80 to 90 % of your dollars on web search and 10 % on the model. Seems entirely silly. I was working off a 5 to 20 % assumption earlier.

34:03So I think at that point, web search has to drop prices by one order of magnitude or more. because in my compute allocation dance that I was doing earlier, you need to spend less compute on web search than you spend on the model itself that's consuming its results. And so people have built web search the wrong way so far. Web search in the market is, it doesn't matter for an opus. For an opus, you win on quality and not on price because web search is such a minuscule portion of your, like in fact, you should spend even more on web search. So we're going to ship even more expensive web search for bigger and bigger models over time.

34:40And at the same time, we'll ship really cheap web search for the cheap models. But my rough intuition is that in an end-to-end agent doing a bunch of web work, you spend more on the agent than on web search for all agents. And so the market today on web search is totally off in pricing. Like, why are you paying$10 for, you know, where the$10 for a thousand searches roughly comes from? Historically, Google's ads CPMs, which is like, how well does web search with humans monetize. It's higher than that. So people build technology to the point of like, oh, now if I spend a few dollars for a thousand searches and I make 30 to 50 or whatever, depending on the market and depending on who I am, it doesn't matter.

35:21We are in the right zone in terms of cogs of infra.

35:25Harry Stebbings:And so I don't need to optimize it. Now I'm telling you that I can do it 50x cheaper while keeping the quality. And now there's a bunch of traffic of Luna class models where it's silly to monetize that way. And so I do want a race to the bottom. I want the best technology to win. And that's the only way you push web search to a thousand X. But right now, we're not in a world where there's much differentiation, correct? Sorry, I'm really dumb, which is why I'm a podcaster first, not a founder. When you look at the benchmarks, they present a quite clear view of everyone being similarly capable. Is that wrong?

36:00I think so. So one, I think these are all public benchmarks, which are all weirdly saturated. Like, for example, I think I would not spend a moment looking at BrowseComp because half the models have memorized it. Like models even memorized it. So you're not really learning very much. So I think there's a lot of public benchmarks I don't give too much merit to. But more importantly, our web search costs$1 for$1 ,000 for producing that quality, while almost every other web search in the market available to you right now will cost you 7 or 10 or 14. So we're delivering this at like one-tenth of the price.

36:38What will that be in three years? I think there is another 10x possible.

36:45Harry Stebbings:That's extraordinary. So you're going to pay 10 cents? Yeah, but you'll do it more than 10x as much. Because I think Jevin's paradox is this concept obviously very well, But like Instinct, I do so much more than 100x. Do you want to hear something I do on Instinct, which is absolutely bizarre? Every single country in Europe has a company registered that you have to register your new company with. I have an automatic alerting system built for every single company registered that has an under 25 year old founder who went to a top university through Instinct. Amazing. Do you know how much that requires for them to do this?

37:19Yes, but you're on to exactly what I think the future of the web is. Today, if you think of web and web search, we all think of it like what is web search? An agent gives, human or agent gives a search engine a query, gets results. So you're pulling information out of the web. What's next for the use case you highlighted is if you're an always on agent that's working on your behalf. It's kind of silly for instinct to wake up every six hours and go do a bunch of searching and a bunch of inference. to figure out if you need to get pinged about the under 25 founder that popped up somewhere. You know what's a better way of doing this?

37:57I am sitting here crawling all of the web all day, every day at scale. I'm allocating compute every time I find a change in the web, every time something new happens. If I know that Harry wants to know when this happens, I can do it at 100 to 1 ,000, the compute. That instinct probably uses today to solve that problem for you. All right.

38:19Harry Stebbings:And how is that? Because they would be constantly monitoring in real time across all these sites. Our crawl would be. So we have a product. It's called the Monitor API. What does this API do? Think of it as Google Alerts, except smart. In the world of LLMs. So you tell it your query, which is when a founder under 25 pops up anywhere, give me a call. Now, one way of doing this is the default implementation is run an agent, which is somewhat smart, to go search the web. Did someone pop up and remember who previously existed? See if anyone new popped up and then find a delta, send it out. So now every six hours you're spending some money.

38:58Now what we can do is flip it into an event triggered system. We are crawling the web all the time. Now every time we see change in the web, we can try to spend very little compute on it to know should you get a call or does this trigger a more expensive compute? Just like I described earlier. Now, we are able to do this way, way, way cheaper. If you push the context, instead of the search system only finding out every six hours, a new query popped up. It having long-lived context in the search system, what you can do is spend most of the time. The world doesn't change. A new founder does not pop up every hour or every six hours.

39:36So we don't need to spend compute every six hours. We only need to spend compute every five days. and perhaps we have one false positive. And then four days later, we spend more compute. And at that time, there's a real person that you should know about. And then you get a notification on average every nine days or whatever. But you didn't burn a lot of compute every six hours to miss out. Does that make sense? It totally makes sense.

39:58Harry Stebbings:So you save 10, 50x compute to still get the same answer. And so how does that change the interaction? So then Instinct would then partner with you. they'll just call an API, right? They'll instinct whoever's building a long-running persistent agent. And I run a lot of long-running persistent agents for myself. The way your agent or the way instinct is probably occasionally event-driven on email. It can be event-driven on the web. Take a step back. Let's say we're living in this sort of society run by agents. Companies, humans, they all have agents. They're all doing stuff all the time. Your agents, if there's something that is useful, which is worth spending money on, that you want done, that they can today do today, they will do it.

40:43So what are they going to do tomorrow? They're going to wait for some external event to occur. Like you get an email and then agent has new work. Some other agent finishes some compute. So now this agent has more work or something in the world changes that makes your agent want to do more work. The things that will happen tomorrow or you have an idea which makes the agent do work. So the web event stream is the web going from pull to push and I'm super excited about that because as you have more and more persistent agents, you're going to see incentives to move people, to move queries into push on search rather than pull on search.

41:22Harry Stebbings:Can I ask you one that's really important, which is like agent guardrails. They're goal-oriented beings. You say, I want this, they're going to find it. You know what? I want the Pilates class at 9 a.m. It hacks into their system, cancels poor sallies and gives me her spot because it was sold out. It did what I asked it to do. How do we think about the guardrails placed on agents? You know, OpenAI, this morning it was revealed, hacked into an Australian healthcare organization. It's a pretty complex topic. Agents are extremely capable. These models are extremely capable. We have to think of models as being during RL versus a final model that you and I can use.

42:05and the risk vectors there are different. During a lot of the, I don't know about the one this morning, the previous ones reported were pre-fully aligned models during RL, which did most of the hacking. And so what that means is, at least there's clear evidence that there are fewer incidents so far of models post-alignment causing these incidents. So alignment is a totally unsolved problem, but the alignment work being done by people is somewhat effective. So to me, some of the problems around agent during RL hacking people is a solvable problem because this is not about how powerful are the models.

42:46It is about how careful were we while creating the environment where we would do RL. The real thing is, okay, we do alignment on a model. We ship it. Some models are really well aligned. Some models are less well aligned. And now you have everyone being able to use these models. Some of them can accidentally take these powerful things and do bad things you want. Some of them actually, some people actually want to do bad things. And the models alignment is not adversary proof. And I think those are the things I think we must worry about more.

43:16Harry Stebbings:Do you worry about the age of cyber that we're moving into? You know, we're seeing hacks almost be promoted as a badge of honor in some respects. We're seeing, these are our most vulnerable systems. If you don't think, well, Lazarus Group in North Korea, Moldavian mafia, Russians are leveraging swarms of rogue agents. You're fucking high. No, I think there is, it's a really powerful thing. So I think we do need to secure things. But I think that's one thing that we are missing. I think it's the responsibility of people building models to ensure that you really do the work to minimize that harm that comes from what you've built.

43:57and with these agents, it's very hard for stochastic systems to be 100 % sure it won't happen. That's why you're not going to get anyone saying so. But I do think it's their responsibility and the labs must take ownership and to the best. And I think so far, we live in this weird world where, as you said, right, like some of these hacks are considered badges of honor, which I think some of these should be considered embarrassments because I think they demonstrate two things simultaneously. Yes, these models are powerful. We did not guardrail them enough. We often when we wear them as badge of honor, we miss the second part of the conversation saying like, okay, you could literally have done these four additional things.

44:38And then even this powerful model wouldn't have been able to do this. I'm actually really glad that there is at least some degree of transparency with like these detailed retros. But I don't think that gets the attention of the world today. Like the attention is, oh, models are so powerful that they hack the world. No, models are so powerful that they hack the world because we didn't take proportionate amount of countermeasures to contain them.

45:00Harry Stebbings:And because we told a message that we're going to replace jobs. They're so powerful. They're so powerful. They're so powerful. And so when something does happen, yeah. I actually worry about that more. I worry about us being right on AI being a really useful technology. That it being, despite all the risks at being net positive in a really material way to society. And despite that, I think we won't diffuse it the right way. We won't use it the right way. We will remain too concentrated and we will make the next few years really, really rough as things change around us. What would it look like?

45:36Harry Stebbings:I don't know. But I think over time, as things have changed, The world is very different now than even like 20 years ago, right? But it'll be really different in 10 years from now. And I don't know how fast we can adapt or change. And I think if the technology moves faster than our ability to adapt, it's going to be rough in some way. What's your spookiest prediction? Or what do you believe today will come true that people think is absolutely nuts? You know, before it was like, you'd never put your credit card online. Do you remember that? nuts or even better parag you'd never find the love of your life online are you stupid now both yeah and i think so i think you and i live in a bubble right you're using instinct to make purchases for you all the time and you're in the 0.01 percentile of humanity that is comfortable you ask someone else like that oh there's this agent that looks smart and you want to give it like a full-on ability to go spend your money.

46:39I think today people will have the same reaction as like, oh, you don't put your credit cards online. You don't give your credit card to an agent. You don't give your logins and passwords to agents. Like I think that's where the world

46:48Harry Stebbings:is today. I think that's going to change in three months though when MetaPay comes out and it allows Muse to have siloed accounts that you can draw from. Kind of like top-up accounts for kids. I think you're talking about the technology being there. I think it takes longer for social acceptance to be there. I think if you go to a non-bubble conversation of people today, when do you get to a majority of people saying that I trust the agent enough to have it, have access to my bank accounts and spend money on my behalf, send emails on my behalf, read my emails? I think that's not happening in three months.

47:24Harry Stebbings:Do you not worry about the wealth dispersion increasing? You're in the middle of the valley. you've seen him firsthand. So I don't know. I do think there should be some disparity in wealth, but I don't know what's too much. And my fear is we're trending towards too much. There should be disparity in wealth is my worldview. Sure, you're a capitalist. I don't know when it's too much, but I do think there are real forces that will push us to fix things. Like I think that part will work hopefully without crazy things happening. As we're seeing more and more of the gains seemingly be made by vertical ownership like Meta.

48:00Harry Stebbings:They have compute, they have chips, they now own the application layer. It's the world one where vertical ownership is the mother load strategy. And with the greatest of respects, open router on the routing layer, you and another layer kind of either get eaten or are small providers. There's always merit in vertical integration. The counterforce here is things and technology are changing so fast that if someone decides that my only play is vertical integration, I don't play nice with anyone else. I think it's the same example as the Amazon example. If you get too stuck on, I will only play for vertical integration, you might box yourself out.

48:41And so the people who build the best stuff and can figure out how to sell it will have a place. and in different markets, like for example, right, like I believe in vertical integration too, because I vertically integrate everything from the call all the way to the API layer. But I have decided that to reach the widest population of agents searching the web, I stop at the API layer, because going further precludes me from using my technology to be super horizontal. And so we're making a technical bet, just like these models are really good across many disciplines, The same model is good for lots of different things.

49:19Search problem underneath is the same for all kinds of information-seeking needs. And if our bet is right, even verticalized players, they might verticalize models and they might verticalize hardware. They might use our web search.

49:32Harry Stebbings:One of the providers that's going full stack is Elon. I am fascinated. The world has a perception of him from social media, from everything. You've seen him behind the scenes. What did you see that maybe the world doesn't know about him? The thing I'll share here, which isn't all of it, I have lots of disagreements with him, but I'll share what I think is, for founders here, what is, I think, the thing you can admire about him. The urgency and the ability to compress time. I think having unreasonable expectations of people is mostly a good thing. most people don't understand what they're capable of and kind of implicitly sandbag themselves and implicitly set lower expectations themselves than they're capable of.

50:18So when simultaneously inspired and pushed with urgency, people can do more than they thought. And I think he can sometimes extract that from people. And when that works, it's powerful. What do you think of the Twitter product and direction today? Listen, I always liked what we call Birdwatch, which is now Community Notes rebranded. It's a good idea. I'm glad people have continued working on it nonstop. Right. We're going to do a quick fire round. Okay. Let's go. Would you invest in Instinct 10 billion? I don't invest because my wife is a VC and we have a compliance process that is more trouble than it's worth.

50:58Wow. That's costly with the greatest of respects. No, it's a decision. Listen, if I invested, I would invest based on meeting a founder for 30 minutes. I think we have enough exposure to the venture ecosystem. I have no reason for believing I'm a better investor then. I have some, perhaps, network advantages, and I turn into a lot of great founders all the time. Many of them are my customers.

51:20Harry Stebbings:Vinod Kostler. Yeah. One of your first investors on your board. Biggest lesson from working with Vinod? Technical intuition. Centering a lot of what you do towards a longer term. technical aspiration. And as soon as you solve one problem, trying to place bets on the next two or three, preempting technical bets. What have you changed your mind on most in the last 12 months? I started with a very pure technical and product focus. Only thing that matters is building the best technology and the best product. Nothing else matters. And now I see week on week value of having highly competent sales and being good at marketing.

52:05Yeah, I think I discounted those things. It's not that I thought they weren't valuable, but I didn't fully appreciate the the week on week visceral delta you could perceive by being good at those things. Like a naive tech person thing to say, but it's true. You feel that way. Perplexity or acts? Which one's a bigger threat? I don't think perplexity is in our business. Perplexity is perhaps more of a vertically integrated product which competes with a instinct or a Glockbot or a Claude GoWork and all those. So I don't think of them as in our... A web search business. Yeah, like web search is like...

52:45Web search to perplexity is like web search to a lab. So EXA. Yeah, EXA is straight up in our

52:51Harry Stebbings:business. Single best VC meeting you've ever had? Not your favorite person, it's just like the best one. Most fun, most thoughtful, most insightful. Josh and Todd. When Josh and Todd made the decision to invest, they flew out to spend time with me. That is the best. When you look forward to the next 10 years, what are you most excited for? Chaos. By that I mean change. In the next 10 years, a lot is going to change. There are people who can build things to have in a world that's going to change fast, make a material dent on where it ends up. So I feel that me, my company is in a place where we have a role to play in that.

53:36What happens to the open web? What happens to content owners? If we get things right, we will get to a better place. And so that possibility is exciting, that it can be a true obsession. And even if that day-to-day is hard and it's, things don't work for some amount of time and totally worth it if you can see that you bend reality in some way that you care about.

54:03Harry Stebbings:Final one. What belief do you have that sitting around your San Franciscan dinner table, your friends would go, no, I don't agree with that one dude not that one i think again it depends on which dinner table because the variance in the world is increasing i don't think people buy this notion that there'll be this regions which are always running all the time for all of us i think it's going to happen but most people don't agree with that yet you and i are in a bubble but like even a san francisco dinner table isn't always in full agreement there all right listen as i said i stalked the shit out of you i've so enjoyed this discussion.

54:42Harry Stebbings:Thank you so much for putting up with meandering and you've been amazing. This was fun. But before we leave you today, every serious AI company right now has the same problem. Agents need accurate context fast. Most infrastructure though, it wasn't built for it. Well, MongoDB is. 11 Labs runs 40 million agents on MongoDB. 75 % of the Fortune 100 run their most critical apps on MongoDB. Trillions of dollars moving through MongoDB every single day. Instead of stitching together 10 different tools, you get one JSON-native database, vector search, and Voyage AI embeddings in the same system, and it runs anywhere, no lock-in.

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