You have this innovation bazooka with these models. Why would you point it at rebuilding payroll or ERP or CRM? The general story that we're going to vibe code everything is flat wrong and the whole market is oversold software.
I'm so excited to welcome Anish Acharya, GP at a16z, where he leads consumer and fintech investing at Series A. Now, an interesting topic that's not discussed is the cost of transitioning from one SaaS provider to another going dramatically down. So, systems integration.
I don't think we're allowed to believe in luck at a16z. We have to see 100% of the deals in our domain and that we win 100% of the deals that we go after.
Ready to go.
Anish, dude, I've wanted to do this for a while. We've been going back and forth, and so I'm so glad that we can do this in person. Thank you for joining me.
Of course. Thank you for having me.
I'm diving right in. We were just chatting now and I was saying I think it's better to build in London than in SF or in other places other than SF. Talent is cheaper. It retains for longer. You don't have the promiscuity of people jumping from role to role, and you've built a company now both in Canada and in SF.
How do you reflect on what I just said?
I disagree with you. I wish it was true. I simply wish it was true and I want it to be true and maybe it will be true. That it will be, you know, the whole thing that we always love to say to ourselves around sort of talent and opportunity not being, you know, talent is equally distributed, opportunity is not. The truth is that cities are the original network effect and for technology there is a network effect for builders in SF and for this moment in technology right where so many of the secrets are these sort of things whispered down shadowy hallways, the benefit of being in SF is enormous. There's also, we just talked about this, there is a selection bias question. Do you care enough to make it happen in SF? You can make it happen anywhere. New York, London, Toronto, Tel Aviv, you name it. But there's something different about saying I'm going to give everything else up and be singular in my focus and move everything to SF to make it happen.
Are there any other locations where you think there is actually positivity associated with there being located there?
Tel Aviv. I think Tel Aviv, you can be incredibly ambitious and uncompromising on that ambition and have a really, really good reason to be there. I think the other nice thing about the Tel Aviv ecosystem is that the country is so small, it's 10 million people, that you can't possibly fool yourself into thinking that the domestic market is going to be big enough for whatever you're doing. So, you immediately go outside. Whereas, if you're in London, there's 60 million people here, okay? And you might say, well, that's actually a lot of people. And you know what? There are parts of the market like fintech where the LTVs are so high that perhaps 60 million is sufficient.
But for most mass market products, it's just not sufficient. And if you end up starting focused on the domestic market, it's often hard to actually move on to a bigger market. So there are all of these reasons that it's just, it's not that it can't be done and there are incredible counter examples like ElevenLabs. But I do think that it is just that much easier in SF and that's why that's where I focus.
You said the word sufficient there. Yes, you can build a sufficient size business, say in the UK, a $3 to 5 billion business, say as an example. Respectfully, when we look at companies being created today, 3 to 5 billion just doesn't seem like it's interesting enough. Has the world of venture changed so significantly on what is sufficient for a venture outcome?
I mean, 3 to 5 billion is an extraordinary outcome, don't get me wrong. So in no way, no way am I like minimizing that. And look, I do think that those types of venture outcomes stack to create really meaningful funds. So this is not about working backwards from venture economics. But the biggest companies in the world today are trillion dollar companies. If you want to build a trillion dollar company, if that's your intention, you've sort of got to start with a set of assumptions that can lead to that. If your intention is to build an extraordinary enterprise and you build a 3 to 5 billion enterprise, like you are one of the few people in the world.
When we say about those three to five billion companies.
Yes. Yeah, I mean, I heard a brilliant statement which is the SaaSacre, the massacre of SaaS companies that's going on in kind of the public markets today. And when we look at it, essentially investors are no longer confident that traditional enterprise revenue is sticky or durable.
Are they right to question whether traditional enterprise revenue is sticky and durable?
I think software is completely oversold. I think it's a silly story. I heard it called SaaS apocalypse today. It's very funny. Bloomberg is trying to get that to stick. Look, if you look at SaaS spend today, if you look at IT spend overall, it's 8 to 12% of enterprise spend, okay? So, even if you vibe coded your ERP and your payroll with all the kind of risks and dangers that that entails, you're going to save 8 to 12%. You have this innovation bazooka with these models. Why would you point it at rebuilding payroll or ERP or CRM, right? You're going to take it and use it to extend your core advantage as a business or you're going to take it to optimize the other 90% that you're not spending on software today. So I just think that of course there will be secular losers. There are like specific business models that are now going to be disadvantaged, but I think the general story that we're going to vibe code everything is flat wrong and the whole market is oversold software.
Okay. And so we are actually overly negative and we are being too critical on these companies. How do we think about then the continuing negative growth that we've seen in a lot of these companies, the continuing seat contractions in a lot of your say CRM providers or Mondays of the world?
Well, I don't know if that's what we're seeing across the board. Like I looked at the data this morning and if you look at SaaS, public market SaaS companies, 75% have raised prices since ChatGPT was released. 75%, and they've raised prices meaningfully. The mean is 8 to 12%, but there's a large group that have raised at 25% or more.
Is that not because they have to because they're not growing seat count and so they have to grow revenue count?
Price is a measure of product market fit, right? And if you have enormous competitive pressure, you are not raising prices, you're typically cutting prices. So I think one, you've got this sort of, you know, this dissonant fact that prices are going up, right? Two, if you look at the incumbents today, like ServiceNow is not IBM, they're a highly capable incumbent, they just went public and they raised guidance. So I think it's very easy to look at these things and say incumbents, incumbents, incumbents. Like again, like they're not seers, they're very, very capable and I think they actually have a right to win and deploy technology in the context of these workflows. Now, will there be disruption? Of course, we've talked a bunch about, you know, companies that can now, that were once priced on seats which are now going to be priced on outcomes and like that is going to be a big drag. But I think for the majority of SaaS, it has so little upside in being rewritten and vibe coded and so much downside, why would you do it? Now, an interesting topic that's not discussed is the cost of transitioning from one SaaS provider to another going dramatically down. So systems integration. If you and Alex said this funny thing and I know you laughed and I laughed too, which is that like some companies have hostages, not customers.
Yeah, I love this statement.
I love it too. And if you actually have, you know, an SAP system, you are a hostage of SAP and they need to do nothing after they win you as a customer except the bare minimum. If you want to switch to Oracle, oh my god, that's like a multi-year high-risk. It's probably going to fail and you're probably going to get fired. It doesn't happen. But now with coding agents, the complexity of transitioning from SAP to Oracle is dramatically lower. The speed, the risk. So that is how I think coding agents shows up in enterprise software, especially amongst public names. Decrease switching costs, more customers, less hostages, which is a positive incentive for the entire ecosystem.
You mentioned Alex Rampell. I actually, sounds super weird, I actually think about Alex every day. Um, yeah, well, there we go. Um, because he says the most brilliant thing which is, and I'm going to butcher it slightly, but you know, will the incumbent acquire innovation before the startup acquires distribution?
How do you think about who wins in this world? The public SaaS company who has distribution, be it a HubSpot or a Salesforce who has millions of customers, or is it actually the startup who has speed, agility and incredible engineers?
So if history is any guide, and you know, to reference Alex, he would say that it often is, you know, those who have actually studied history tend to do better than those who have not. And what I would say is that when you have this product cycle and you have a capable incumbent, what happens is they usually make their product better for their existing categories. So, Microsoft will make a better word processor than they've ever made. Google will make a better search engine than they've ever made. And we're actually starting to see that, some of that anyway. What you instead see is the native categories that did not exist before the product cycle being owned by startups. So, I think that's a little bit of what we're going to see. You know, if you said something like, you know, software movies or AI movie making or sort of AI assisted movies, that's just not a category in which there is an incumbent. And I'm betting that a native company will actually win that. It probably won't be Adobe. Will Adobe make a better sort of Photoshop and Illustrator than ever before? Probably. Right.
You said there about kind of native being an opportunity in terms of like kind of where opportunity sits in the stack. Why do you think the application layer will create more value than foundation models?
I don't know if it'll create more value, but I think that it is under discussed how much value it's going to create, right? If you think of what the models are. So if we lived in a world, and you know, we were actually thinking about this a lot in 2022 and late early 2023, which is if you had a single foundation model company, which at the time was OpenAI, which was a whole generation ahead, right? Then they essentially were this unique supplier to everybody downstream in the innovation ecosystem and they could do what you would do if you, for example, you know, controlled the Beatles and you're the only record label that had the Beatles. Like it's like, do you want the Beatles or not? You can charge 99% of your customer's gross margin and you do, and you actually tend to charge 100 or 110%. So that actually was a big risk to the ecosystem. What has instead happened is we have all these foundation model providers. They're all innovating roughly in lockstep. 80% of what they do, I think that they're actually substitutes for, and then there's the open source models which also do the same things. And then in the 20%, which arguably is where a lot of the value is, they are all specialists. So because you live in this world of multimodel where for some use cases they're substitutes, for some use cases they're actually specialists, there's a lot of value in having an aggregation layer and that is the apps companies. So let me tell you two categories specifically. One is coding. I think that if you actually look at coding, you might know that Gemini is great for front end, Codex is great for backend, right? If you're vibe coding your project, you probably want to use both and you don't want to switch between two CLIs all the time, it's just a pain. So being able to use Cursor as a single way to orchestrate all the models is valuable. Similarly for creative tools, right? We're seeing this specialization, fragmentation, specialization. Midjourney and Crea with their Crea1 model. These are the most aesthetically opinionated models, right? They create this incredible beautiful imagery. Conversely, if you look at Ideogram, Ideogram is often used by graphic designers. It is intentionally not opinionated from an aesthetic perspective. If you're somebody who's working as a creative at a big company, sometimes you're doing graphic design and sometimes you're just doing beautiful photography for print ads, you want to actually have access to both. And to do that, you use an apps company.
So, I think we massively overestimate the durability of revenue of AI companies more broadly as well. I think there's a chance that Cursor loses half of their revenue this year with the cannibalization of them by Claude Code. I don't know anyone who's not moved to Claude Code. Like when I hear that someone's still on Cursor, I'm like, wow.
Yeah. I think the thing that we are underappreciating is that we assume, you know, efficiency is increasing but ambition and number of customers is staying fixed. And I think this is one of the incorrect assumptions that keeps getting made around AI. It's like, well, what are all the people going to do? Where will all the jobs be? You know, it's like our ability to be ambitious for wanting more things always grows so much faster than our means. And in the same way, if you look at software, the desire and demand for software, both to make it and to consume it, is dramatically more than the supply that we have today. And I think there is a developer and developer adjacent archetype for whom Cursor is going to be perfect. Codex as an app, Codex as a CLI, Claude Code, like all of these products are going to find market fit and all grow. And if you look at any of the other markets like creative tools, they're going to specialize and fragment in their own directions.
So when you think about market composition for that market in the kind of developer tooling space, does that look more like cloud or does that look more like Uber and Lyft?
I don't think it looks like Uber and Lyft, right? I think Uber and Lyft are, to my mind, the most extreme examples of pure substitutes and a lot of the sort of price has been competed away. You look at cloud, you sort of have this oligopoly where they all actually have pretty reasonable margins, right? And you know, you can squint and say, of course, they have their specializations, but they're roughly substitutes and yet they've all done well. I think the foundation model companies look a little bit like that. And I think in the apps layer, you're just going to have people that want to consume the code they generate through a rich IDE and those that want to be closer to the metal. And that's probably closer to AWS, Google Cloud than it is Uber, Lyft.
So when we think about that, I think how do you think about competitive investing? Like it seems to me like it doesn't matter anymore. What about when I started, it was a big problem. You didn't invest in competitors. Now everyone is investing in competitors. Are we in a world where that no longer matters?
I mean, when you think about a firm that's organized the way we are, which is we actually do stuff for our companies, it becomes very difficult to invest in directly competing companies because then you've got, you know, the same resources, the same sort of Fortune 500 buyer, the same engineer that both companies want to hire. And I just like, I don't think we can run our business by investing in directly competing companies. Now with that said, I think we're in a part of the market where companies are diverging very rapidly. So even companies that appear to be directly competing today tend to be not competing in, you know, 12 months, 18 months.
Going back just before to what you said about kind of the opportunity in the apps layer, when we think about that, one threat that's often posed to the apps layer is the models themselves providing products. Whether it's OpenAI focusing on health now a lot or whether it's Claude Code or actually I saw Anthropic do, you know, some Claude attachment to legal yesterday. To what extent is models invading the apps layer a credible threat to the verticalization of apps?
Yeah. So this is such an interesting topic. So Granola, which we're not investors in, but I admire them a great deal. It's a great company. They've built a really interesting thing and they were first of course to live meeting recording and transcription, which is awesome. They have been copied to the moon. Right now, everybody has a meeting transcription feature. OpenAI released one within ChatGPT. Very cool. The thing about Granola, and I assume this is true, is that their vision is not to be a meeting transcription product. I assume it's to be a productivity suite, right? They're going to build Word and Docs and spreadsheet and all of these other products around that core primitive. Does OpenAI have the sort of prioritization, the resources and the ambition in that direction to build all the feature surface around the primitive? So I think the models will often actually recreate the primitive and even do product marketing, which I think the Claude legal stuff was. But if you have a market that demands a lot of feature surface, I just think the model companies are less set up to prioritize it.
Do you not think if bundled into an existing solution with 80% of the features, the majority of people just go, 'Ah, fuck it.'?
Perhaps. I just think that the model companies have ambitions in so many directions that it's hard for them to prioritize building opinionated UIs for the legal community. I also think in many of these categories again being multimodel is important and OpenAI is only going to ever give you OpenAI models, right? Anthropic is only going to give you their models. Same with Google. So if you are multimodel, rich feature surface, I think being an apps company is better.
'Boring wins' is a statement that you said to me before when we were talking about kind of apps layers and where value will accrue. What do you mean by boring wins? And how does that translate to the next generation of iconic companies?
Oh, did I say boring wins?
Oh, well, let me make the sort of exact opposite case. I think weird wins.
Yeah. So, I mean, here is something that's actually very interesting, which is the nature of these models is very different than the nature of any technology we've had before. I'd say a lot of the technology we've had before, it's quantitative, it's sort of clinical, it can do incredible things, but it's sort of bounded in the range of, you know, feelings that it can sort of capture. Now, we have this wild, non-predictable, emotional, very human technology and sometimes it gets pointed in these directions that are very human but perhaps uncomfortable to a big corporation. Right? What is the human experience? That often involves disagreement, persuasion, sexuality, and we see that mirrored in some of these AI products. Yet, if you're Google or Apple, you have a thousand committees that are explicitly designed to ensure there's never any persuasion, disagreement, or sexuality expressed in your products. So, I think that there is a pocket that startups can really thrive in, which is building these weird products that really touch on many core aspects of humanity that the models can reflect, but the big corporations are uncomfortable.
I mean everything in companionship, right? Every product in companionship has been, you know, both well received by customers and a little uncomfortable for the labs to build.
Perhaps Midjourney, Grok. I'm sorry, when you say companionship, you're saying like...
Character, but also Janitor, right? There's a ton of products that are there for, you know, Replika, which is probably the, you know, one of the most like healthy and nourishing forms of companionship. But all of these products are there and they're there to facilitate friendships between people and technology and a lot of that stuff is just uncomfortable for big tech to do.
Would you encourage your children to use them?
Absolutely. In fact, one of the products that I would love to exist, my request for startup is what I call a contextual companion for my son who plays Minecraft. My son plays Minecraft. He plays it online. He absolutely loves it. You know, the other kids playing Minecraft may or may not be the best influence, often not the best influence. I'd love to actually have an AI companion play Minecraft with him so there's a context in which they interact and I don't know, just sort of models pro-social behaviors and is still cool and chill. I think there's a lot of room for teaching through these types of relationships and technology can help provide that.
Do you not think that it engenders or removes the ability to interact with other humans and makes people even more withdrawn or used to building a relationship with technology than we already have?
I think it does the exact opposite. I think people are able to be more self-reflective and explore aspects of themselves and human relationships that they often just don't have another person to explore these things with. And I think, you know, if you're wealthy and perhaps educated, you know, maybe you're interested in therapy and that's like an outlet for it. Or if you are like you and I and you've got this embarrassment of social riches and you have all these people that want to hang out with you and you go to these dinners where you stay up late having all these philosophical conversations. Or perhaps if you're one of the relative minority today that is spiritual or religious some way and it's very, you know, emotionally nourishing to you, like there are directions in which we can explore these things, but I think for the majority of our society today they just don't have an outlet and I do think technology can be that outlet.
I like the idea. I also like it especially when you think about the amount of old people who are alone and you think about the companionship there.
Yes, and by the way, I think the whole thing is that there's got to be a level of indirection. This is why I think contextual companions are very powerful because I think for a senior citizen, like, you know, it's important they have a big sense of self-respect. So, if an AI calls them every night to like check in on them, well, they're going to be like, 'Well, hold on. I don't need that. You know, I don't need to be babysat.' But if instead the AI called to, you know, check to see if they'd taken their medicine, ask them how their day was, maybe lightly flirt with them, talk about World War II, I don't know, like suddenly they've got a context in which they're interacting. There's a level of indirection, but the thing that's actually delivering is sort of spiritual nourishment.
How do you... the shittest question ever, but you know after 10 years I'm not embarrassed to ask fucking questions. Which, go for it. How does the UI paradigm change in the world of AI? Like everyone's like now we're just all going to be voice. Do you agree with like just all voice?
I think so. Voice is amazing for enterprise. I think that one, dynamic UIs and two, chat UIs are overstated in consumer. And the best thinker on this is actually Eugenia who founded Replika and now Wabi. She's great on this. And what she would tell you if she was here is that look, most people don't want to save time, they want to spend time, okay? And the products are designed by the most high agency people in the world, like Sam and Elon are the most high agency people in the world. For them, the optimal UI is a chat box where you say exactly what you want and like voila, there it is. But for many people, they are again looking to waste time, spend time. They want a browse-based interface. They're not quite sure what they want. They can't always articulate it. So, I think that in a world where we have intent-based and browse-based, browse-based largely stays the same. And perhaps the future of intent-based is chat, I'm still a little skeptical.
I think people are consistently concerned by, we mentioned it earlier, but defensibility, switching costs, durability. When we think about moats and Alex's statement of hostages not customers in a new world of AI, do we just accept that there's no defensibility or are new moats created?
I think defensibility still exists and still matters. Like networks are the gold standard and they still are. You know, a network effect product is incredibly powerful. Now look, you might argue that something like Moltbook is a new type of synthetic network that perhaps means there are certain types of networks that are less defensible than they were, you know, once were. But something like an Airbnb, you know, you can have all the vibe coding in the world. Like their network effect is incredibly powerful. So one, I think defensibility matters. Traditional moats still do matter. I do think that within moats like systems of record, there will be some who are more or less prone to disruption. So, if you're an on-prem database and there's no engagement layer and there's not a lot of human workflows built around the so-called system of record, I think that you actually are at some risk. If you're the core system for a bank, you've got thousands of transactions per second. You've got hundreds of humans that interact with you. You have this incredible demand for accuracy. I still think that you're sort of as good as gold in terms of defensibility.
Is there any forms of defensibility which were very prominent in the prior 10 years which are no longer as prominent?
Yeah, I'll give you the opposite. I was always skeptical of the sort of data network effect. You know, that was like this thing that got thrown out a lot when you couldn't think of what moat to say. But today if you look at companies that have proprietary data sets and not just proprietary, OpenEvidence is a good example of this, but live proprietary, and live is a very, very powerful moat where you...
When you say live, what do you mean?
Like your health data for example, right? That's our sort of live and ever-changing source of data. Now there's a question of how proprietary can that be. But once you actually have data like that or perhaps live data about a product that's running, now you can put a relatively commodity model in front of it and get much better results than the most cutting edge model that does not have access to the proprietary or live data.
Okay. So we have actually relatively the same forms of defensibility that have existed before that will continue to make... I'm always trying to understand, I feel very kind of insecure right now as an investor because I'm trying to understand what holds true from the prior decade and what doesn't and I need to change my mind on, you know, when the facts change I change my mind. When we think about a lot of the forms of vanity remaining true. I was always taught that margins matter. I walk with my mother around London, poor woman, and I'm always like, 'Mom, margins matter.'
Yes. I can imagine holding your hand. Poor mom, handheld. Yes.
Jesus. No wonder she wants to finish the walk. My question to you is, do margins matter as much in a world of AI and are we entering a new way that we should be thinking about margins?
Yeah. So, here is actually where I think there's nuance in the margin conversation that's important. Okay. So, if you look back at anytime you've gotten, we should talk about, you know, the bubble that doesn't exist or perhaps there is some sort of subsidization and distortion that's happening in the market. For the record, I don't believe we're in that period. But I do think that anytime you have this sort of superheated markets, you have some distortion. Okay, if you look at the distortion from 2021, you essentially had this indirect subsidy of Google and Facebook. So you would invest in a fintech company, you would give them $10 million, they would go spend $8 million on Google ads and Facebook ads. So there's a subsidy that was happening that were sort of these empty calories for the startup. If instead you look at the form of subsidy that happens today, what it typically means is zero margin or negative gross margin credits for the user to try the product. So these things tend to be a drag but these are actually very healthy calories for the companies because out of that you get conversion into high-paying users and many of whom are actual power users. So I do think that the blended margin story for AI native companies tends to be worse. But if you look at the overall sort of form of distortion that's happening, it's a much better one than we had five years ago.
Does that make sense?
Yeah, it does. Jason Lin is a very good friend of mine from SaaS and he said to me yesterday, I said a brilliant statement. He said for the best companies, influence is the new sales and marketing.
Yeah, I love that. 100% correct. Yes. Yes. I also think that power users are so much more powerful than they ever have been. Like Andrew Chen used to say pre-AI and I love this, like power users are just users and it was true because even if they got 100x more value they typically didn't pay 100x more. Like you look at Spotify, great European company, the very best Spotify SKU with the highest bitrate music, totally lossless, all the pods, all the videos, family plan, everything was $20, $25 a month. So there was a belief that the price ceiling for consumer products mass market was $20 to $25 a month. You look at Grok Heavy, it's $300 a month. ChatGPT, $200 a month. Gemini Ultra, $250 a month. So we're seeing 10x higher prices paid. And you have consumption revenue on top of it. So for the power users, they're paying incredibly high subscription rates plus consumption revenue. So the S&M costs of acquiring those users are very wisely invested. And I think this is an important point that's changed.
But you're telling me then for my team when I'm looking at margins with the investing team that we should have the same high bar that we carried or we should have greater elasticity to lower margins.
So first of all it's typically a lot of organic traffic. One, I would look at your M1, you know, your sort of month one as traffic, not truly acquired users because it's organic and it's free to acquire. And then second, I would take a look at the sort of margin cost of those users, free trials and sort of just say, hey, that's CAC and that's okay. And then look at the margin profile of people who convert and say that's a sort of durable margin profile of the product and the business. Does that make sense? So you're sort of unbundling the CAC oriented margin spend versus the durable margin which is what's associated with your power and paying users.
It totally does. The challenge becomes if you're trying to work out a CAC to LTV metric that you can kind of oscillate around. It's very difficult to get an accurate sense of LTV in such a changing landscape where you're not sure of the durability.
Is the LTV 12 months or is it 46, 48 months?
Yeah. Well, I think that retention really matters and if you take a look at the best AI products, you know, even if you look at M2 as the new M1, right? Because again, you're getting a lot of sort of tourists who come in at M1. You're not paying anything for them.
And so M1 means month one.
Month one. That's correct. If you look at M2 sort of as your first month for some of these products that are acquiring a ton of top of funnel traffic, then you apply the same high retention bar you ever apply to them. You know...
What's an M12 that would make you very excited?
I mean, like the bigger the better, but certainly 50% is solid, right? And if you're 60, 70%, I mean, we're very, very happy.
Okay. So, we have that in terms of margins. I do want to touch on you said bubble. No, I'm not in that camp. I like to attack things while I'm there. Why are you not in that camp?
Well, and there's a little quip that I like to use, which is like it's not a bubble, and it's good that it is. And I'll tell you why. Look, this is not my area of focus or expertise, but one, you look at OpenAI's recent investment announcement, sorry, which is that they're at $20 billion of top line. And the way that they got there is they 3x'd capacity and they 3x'd top line. So every time they bring on capacity, all of that supply, that inference supply is 100% spoken for. And we're seeing that story happen over and over again. Whereas in previous, you know, sort of so-called bubble periods, you saw this incredible buildout of supply far ahead of demand. So so far we're not seeing that, right? Two, if you actually look at the prices that customers are paying, they're going up. So you're not seeing the sort of price compression that you would get from a typical overbuild of supply, right? And then three, as I said previously, even if there is subsidization, there's always going to be some distortion subsidization, it's a sort of intelligent subsidization that's mostly being paid for by big tech and the labs and it benefits consumers and startups. Like, God bless. I'm all for that.
I do a show with Jason Lemkin, Rory O'Driscoll. And Rory said something brilliant, I think, which is like this will all work out if we see the transition of spend from the 12% SaaS budgets that we operate in today transition from that budget to the human labor budget. Do you think we will see that transition?
I mean, we're already seeing it. I think DG was on the show talking about CH Robinson, right? Like we're seeing a lot of companies start to see the productivity improvement from this new technology. I mean, how can they not, right? It's not just coding agents in which this is showing up. You talked about voice. Voice is the wedge into the enterprise. Voice agents are so powerful. And by the way, I think that the near-term story of a lot of voice, I know we talked about support, you talked about sort of customer support. That's interesting. But the more interesting thing is why is support an isolated function. Why is it? And let's go through it. It's you typically have had sales, support, operations, and collections. You know, who is the person that's really good at customer support, empathetic, they're a listener, they really understand the product well. Who is really good at sales? They're more of a yapper. They're a talker. They're high energy. They're very charismatic. You know, they're sort of good at the upsell. They're always in a good mood. You've got these two different human archetypes for these two different roles. We've typically organized the enterprise around these two archetypes, right? But now the models can be either of those people at any time. So the most sophisticated companies are starting to take support, sales, collections, operations, bundle them all together with one broad goal like CAC improvement. And I think that is going to be the 10x on productivity more than saying, 'Hey, we're just going to take cost out of customer support.'
How do you think about competition within markets? I'm jumping around so much, but I'm just fascinated. You brought up customer support. I tweeted it the other day and I tweeted it before. I just can't get my head around this market. There are like 50 providers with over $50 million in funding, 10 with over $100 million. And I was, I'm very much of the Peter Thiel school of thought that, you know, competition's for losers and we want to have monopoly markets with your Decagons and your Sierras and your Intercoms and your Palos and I can go on and on.
Well, the question is how do you define market? Okay, this is an important point, right? So I would argue that in many cases what you're calling a market is actually an industry. Let's look at legal. Many great companies have been funded and there's still room for another dozen. And I think the reason for that is legal is a $500 billion. It's sort of infrastructure for capitalism broadly. Is there going to be one company that wins the entire market of infrastructure for capitalism? Of course not. That is an industry, not a market. You're going to have dozens of winners that all specialize just as in legal today. You've got dozens of specializations. So I think in many of these markets, we are talking about it as if it is one market when it is much, much bigger and all the companies will specialize in their own directions.
Well, it's a $500 billion market. If you assume that we eat their market, not we're an attach to it.
And we aren't attached to it.
I mean, that's an open question. I don't think that we're in the 8 to 12% anymore, right? $50 billion legal software traditionally. I think we're going to be somewhere between the 50 and the 500 and I think closer to the 500 than the 50.
What does that look like? That means like AI native law firms that...
Possibly. I think it means dramatic productivity increases for lawyers, dramatic productivity increases for programmers and engineers. Like I think that the difficulty of doing 100% of a job is really, really high. It's this thing of like pretty easy to get to 60, 70, 80%. So I do think that's why a 20% productivity increase so far we're seeing it show up more as, you know, a four-day work week than 20% less jobs because jobs as bundles of tasks don't set themselves up to be 100% automated so far. Right? You can do all the customer support you want, but sometimes you got to take the customer out for a steak dinner. And so far, the models are not doing that.
They're not. We mentioned like the $500 billion TAM. Do you do TAM analysis work when investing?
Here's what I think. I think we tend to consistently underestimate how big the markets are and consistently overestimate how easy it is to go from zero to one. Right? I think when you squint, you can take something that's not working and say, I can see how it will work. And that is why in my mind seed investing is, you know, it's its own sort of art. I focus very much on the Series A because I believe that having shipped something and having sold something is such a dramatic signal. To me that is actually, you know, the optimal point in terms of information provided slash entry ownership and price whereas at the seed it could be anything, very, very difficult to get something working. Once you do get something working, I believe these companies tend to be even greater and greater versions of themselves for a long time to come. And then I think the mistake that many venture capitalists have made is just not estimating the market to be as big as it is.
I'm enjoying this so much. I have really three things I want to dig into there. You said about markets and underestimating size. Our dear friend Alex at Deel. I met him at the seed round and he told me about you, Deel, and I was like, dude, you're brilliant, but payroll.
I'm sorry, brother, Deel and ElevenLabs. I'm sorry. Fuck off.
I didn't tell you earlier.
What's your next pass? Please give him a Granola. Preed.
Yeah. Yeah. Chris knows this. Chris knows this. I sent a voice note to my partner saying, 'Will someone please set up a JustGiving page for Chris because no one's going to invest.'
I will, I will send you my next pass. You know, most investors when they send you the pass, you're like, 'Wow.' Like, I look forward to your down.
Yeah. Mine you should do.
Yeah. 100%. So you said about market underestimation. I underestimated the payroll market specifically. I thought Alex was right. I didn't underestimate him, but the market I did. What market did you underestimate which you later realized you were wrong on and what did you learn?
It's such a good question about which market did we underestimate? I mean, I've made this mistake a couple of times, you know, like for example, I remember when we were acquired by Google and I remember looking at the sort of the stock price then telling my co-founder like, well, maybe this can go up 10 or 15 or 20 or 30%. How much bigger can it possibly get? So, if you look at a company like that, which was so capable, but seemed dominant in their core market, it was very hard to squint and see what they would become, and they're so much more valuable than they once were, right? I think another interesting example of this is Credit Karma. You know, free credit scores for Americans. And I know the credit score is a much bigger concept in America than it is where I grew up in Canada or even here, but I think you would sort of ask yourself if you did the back of the envelope, you would say, well, most people tend to use their credit score once or twice a year, right? And most people don't even actually need it that often. It's only when you're applying for a new financial product. And then for most people, you either have exceptional credit and you don't really need to look at it because you already know that or you have terrible credit and you just don't want to look at it and you kind of already know that. So now you've got this torso of people who infrequently need access to their credit score. Is that really a big company? And if you then look at Credit Karma, you know, it's like over 100 million Americans use it. You've got 50 million quarterly actives. You've got people logging in on average four times a month. And the reason that it works is that the credit score is actually this sort of mirror that people like to look in and see how they're doing objectively as an adult. Whether you're doing great, whether you're doing poorly, whether you're doing just okay. People really find a lot of sort of satisfaction in the feedback loop of looking at their credit score. Not something that I ever would have predicted. And as a result, Credit Karma has many opportunities to sort of inform and sell their company, their customers products. And it really, really works.
So, how do you reflect on that? Like missing that.
I think when you have a formidable founder and they're showing a lot of early momentum in a market, inertia is the best mental model. In my mind, inertia is the most powerful force in the universe. So everything that is happening today is going to default happen forever. And when you have a formidable founder making tremendous nonlinear progress, you have to tie break in the direction of them doing it forever. That has to be your underwrite.
So funny, Rory just mentioned earlier. He says, 'When a founder continuously hits target, you should bet on them continuing to continuously hit target. Don't overthink this shit. It's hard to hit target.'
Well, this is, you know, I'll tell you a funny thing. So, when I first started, I remember sitting, I spent a bunch of time with Marc and Dixon and everyone. So, I remember sitting down with Marc and saying, 'All right, Marc, what's the process?' Like, tell me exactly what the process is. And Marc said this maddening thing, which is just be right a lot. And I was like, Marc, what is, of course be right a lot, but what else? What it's like, and of course, you know, there's a bunch of things that we talked about but ultimately like having reflected on that I think his view is like your process doesn't matter as long as you're consistently winning. When I started my career at Amazon as an engineer in 2003 they had a very similar thing I think it's still a part of their kind of leadership principles which is that you're consistently right and I remember being 23 or 24 years old and just finding it to be maddening because like well why are you right how are you right but this quality of being right sort of supersedes the why or the how or all of our very intellectual mental models of how long it can sustain.
And you said like just win and the importance of winning. We said downstairs I lost to a wonderful colleague of yours, Seema, in a company, AskLeo, in Germany at the Series A. And I reflect on this a lot. A lot.
I can tell it's on my mind.
Yeah. When you reflect, what was your most painful loss and how do you reflect on that?
You've never lost a deal?
How long have you been in Andreessen?
Do you worry about that? I mean this in the nicest way. Like I asked, I asked Ran Pal about this because, you know, he lost the A of Roulette and then did the B which is great and fantastic. Well done him. Yeah, perhaps risk aperture is not high enough if you're never losing deals.
Maybe, I don't know. Like I think that there is a process by which you can be a part of most important companies that you want to be a part of. I think that there are some very difficult pre-existing conditions to overcome like somebody has a very healthy successful relationship with a past investor. You're just never going to overcome that, right? And by the way, like having been that, I think healthy and supportive past investor for many people, I would never expect those founders to go work with someone else.
What do you do in those situations when they're like, 'Listen, I love you, but like, yeah, I've known these guys for 10 years. They backed me before.' Do you like, 'Hey, we're going to be the collaborative partner and try and nestle in now' or like we'll just peace out and...
I think that there are no games to be played. And I think this is the magic of being in this business and being at Andreessen Horowitz. You know, when I started, I had this nervousness around like maybe it's a sales job, but I've realized if you just sort of show up with the right intentions and like, you know, you have to assume that they know everything, you know, of course they do. We live in this era of very, very sophisticated individuals and founders and you respect that and say like, look, I want to respect the relationship that you have. With that said, like our mission is to be a part of every important technology story that happens. If there's a way to be a part of it now, great. If not, like let us get to know each other and earn the right to be your lead investor at the next round. And sometimes that's the right thing.
How elastic will you be on ownership in order to win deals?
Not very elastic. I try to explain what our model is, but I'm very elastic on price. I should probably be careful about saying that. I mean, my mental model is that below a certain threshold, the price doesn't matter. You just have to...
