# Benchmark's Eric Vishria on Where is the Value in AI: Chips, Models or Apps Why Nvidia Will Not Be The Only Game in Town · The Commoditisation of Foundation Models · Which AI Apps Have Sustaining Value vs Hype and Short Term Revenue 20VC · Sep 25, 2024 · 62 min · 11,967 words Speakers: Eric Vishria, Harry Stebbings Source: https://www.996.fm/episodes/20vc--ep-ffd47406/ ## Cold open **Eric Vishria** [0:04]: Foundational models are the fastest depreciating asset in human history. I don't believe Nvidia is going be the only game in town on infrastructure. We have a major, major shift in AI, which could be bigger than any of these other shifts maybe combined. It's simultaneously the most exciting and most disorienting time in my twenty five years in technology. There's a lot of uncertainty, but we've been more active than we've been since 2010 and 2011. **Harry Stebbings** [0:29]: This is 20 VC ## Intro **Harry Stebbings** [0:31]: with me, Harry Stebbings. And today, we have Eric Vishria, general partner of Benchmark, joining me in the hot seat. Now what is amazing about Eric is the breadth of his investing success. From Benchling Amplitude to Cerebras to Confluent, these are incredible companies, but in totally uncorrelated and different industries, a once in a generation investor, a true picker, and one of the greats. ## Sponsor read **Harry Stebbings** [0:53]: But before we dive in today, all of you listening use tons of software every day. Sometimes it fills us with rage. You can't figure something out. The chatbot in the bottom right is useless. You keep getting bombarded with these useless pop ups. And for those of you who build products, no one wants their product to feel like this. Thankfully, a company exists to help users without annoying them. Command bar. It does a couple of very helpful things. First, it's a chatbot that uses AI to give users extremely personalized responses and deflect tickets. 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Plus, their flexible payment options cater to every customer's needs, making transactions smooth and hassle free. And the Squarespace AI? It's a content wizard helping you whip up text that truly resonates with your brand voice. So if you're ready to get started, head to squarespace.com for a free trial. And when you're ready to launch, go to squarespace.com/20vc and use the code 20 v c to save 10% off your first purchase of a website or domain. You have now arrived at your destination. ## Conversation **Harry Stebbings** [3:40]: Eric, I am so excited for this, man. We've been waiting like so I think it was like five or six years since our last one at least. Wow. So thank you so much for joining me today. You look older, Harry. The Botox isn't working. But I was I was just listening to you on another show, actually. Not nearly as good as mine, by the way. You said that as a CEO, you felt you fell short, and they didn't really go anywhere from there in that conversation. And I wanted to understand why as a CEO, you think you fell short as specifically as possible. **Eric Vishria** [4:11]: When I reflect on RockMelt, which was which is a startup I founded and was CEO of, my reflection is that we fell short, like far short of my hopes and dreams for the company, like my expectation for the company and my hopes and what I thought we could accomplish. We fell really, really far short of it. You know, and I think there's a few ways to think about it. One of the reflections and it's been really useful now as a venture capitalist is good teams with an interesting idea, it's not necessarily enough. The real lesson from it for me is like, hey, you can put together a great team, and I think we did. You can have an interesting or provocative idea. We were rethinking the browser, and this is circa 2010. So I think we had some of the right ideas. We had some of the right execution even, and a great team, but distribution for for a browser, brutal. But the big takeaway, the big lesson from that actually, I think, is just that, you know, startups are really hard, and I think it makes you really empathetic. It makes me really empathetic as a venture capitalist now when I meet entrepreneurs and you kind of understand, like, well, you know what? This stuff is really hard, and there's a whole bunch of stuff you can do, and there's a whole bunch of stuff you can't. **Harry Stebbings** [5:22]: But something is wrong there. If you think about that as an investor today, you're like, it's either wrong team, wrong market, wrong product, wrong time. Something is the inhibitor there. **Eric Vishria** [5:33]: Yeah. I think the question is whether it's deterministic or not. Like, it it's just like, is all of that knowable? Like, we're we're all taking calculated. Whether you're an entrepreneur or you're an investor, you're taking a calculated risk, right, of certain probabilities. And and so I I just I don't think it's deterministic. If you kind of, like, perfectly evaluate the team, the timing, the product, and everything at the beginning, you can actually determine with certainty whether it's gonna work or not. And that's just, like, that's part of it because there's too many things that change along the way. As those things change, the probability of potential outcomes changes a lot. And so, like, I I think that's the part of it that that's why startups are are are are in fun. **Harry Stebbings** [6:15]: Is there anything you would have done differently about your CEO ship? Now you've worked with some of the best CEOs, the best founders. **Eric Vishria** [6:21]: Oh, million I I do a million things differently. Like, I I and I say this to to the CEOs I work with now. Some of the big mistakes that I made were definitely not thinking about distribution enough. That's always a big thing. Two, you really there were a couple times or two people in specifically that I think about where what they wanted in comp and what I was willing to give were separate. Like, they were just off, and they were so far out of market in terms of what their ask was. I at least for one of them, I would've just broken all the rules and and thrown it out and hired them. Those are two examples. But I I think those things you know, you can get into real trouble if you kinda keep doing something like that. So you kinda it's it's always a balance. **Harry Stebbings** [7:06]: Can I ask on one, in terms of the distribution element, how do you dig into that as an investor's day evaluating whether a founder has thought that through comprehensively enough for you to get comfortable on that? **Eric Vishria** [7:16]: I'm not looking for an answer or a right answer. What I'm really looking for and trying to figure out is, has the person thought about it deeply and is constantly learning or constantly applying and adding new mental models to their framework to figure out what the right path is, and they're navigating it. It isn't like, hey, I'm a boat captain, and I'm looking and, like, this is where we're gonna go. You start going and then conditions change, and you get more information, and you have to kind of constantly change. And so what you're actually trying to evaluate isn't they're not going to have all the answers, and that's okay. You can have theories and hypotheses and then evaluate and change as as time goes on and you get more information. I think that's really what you're looking for versus this is how it's gonna work. And that that that could be bad in its own way. **Harry Stebbings** [8:06]: Speaking of, like, changing tides, being that kind of, captain of the ship and moving with the tides, you then become an investor. Very different role than being a CEO. And you said something that I very much agreed with before, but I loved it, and I wanted to dig into why. You said career investors, they're all better. They're always better. **Eric Vishria** [8:24]: They're better investors. **Harry Stebbings** [8:25]: I agree. **Eric Vishria** [8:26]: Well, also not necessarily better board members, not necessarily better advisors, not necessarily a better bunch of things, but definitely better investors. **Harry Stebbings** [8:34]: Why do you think they are better investors? **Eric Vishria** [8:37]: Practice and reps matter. And so if you're kind of if you take somebody who's fifteen years into their career as an example and they were an operator on that time, they may have seen three to five companies that they worked on and know them really deeply and know the ins and outs of them. If you're a career investor, over fifteen years, you will have seen 30 or 35 companies and hundreds and hundreds, thousands of pitches. And then of those pitches, you'll be thinking about, well, I saw this one and this is what it looked like then, and fifteen years from now, ten years later or five years later, you've run this very long term longitudinal experiment and you have data and mental models around that. And so I think that's really helpful. It can actually hold people back too, but I think that's really helpful for investors. And so that's why I think the career investors tend to be really better investors. Why are they not the best board members? They haven't actually done these things at depth. They haven't done them themselves. They often lack empathy and understanding. I think they often think that things are more deterministic than than I think they actually are. Like, all of those things, I think, actually really can get in the way. And I was talking to my partners yesterday about a kind of we were talking about a board member who's at a different firm who is on a couple boards with us. And it's like, the challenge with that career investor is they think if a company has a plan and they miss the plan, that's because the company messed up. And if the company had a plan and they exceeded the plan, it's because the company did great. And, like, you know, or executed or management did great or management messed up. And it's just like there's about 47 other ways that could go wrong. Like, the plan could just be gobbledygook from the beginning. It could be totally wrong and messed up. The There could be external reasons for it. And like the whole job that we have is to try to figure out root cause on those things and help them figure out root cause on them and then like fix it. You're not helping your three year old fall or not fall or teach them a lesson. That isn't the job. It's quite a different actual mental model in terms of what the engagement with entrepreneur is. **Harry Stebbings** [10:54]: My question to you is you mentioned some amazing companies there that are often completely, detached in terms of, sector. There are very different companies there from Confluent, Contentful, to Cerebras. And I spoke to Bruce Dunlevie before the show, and he said that bluntly, your breadth of sector mastering is completely unparalleled as an investor. And he asked a great question, thought, which was, what is your learning process for entirely new categories, and how do you break it down and learn so fast? **Eric Vishria** [11:28]: I am not a sector specialist, and nobody at Benchmark is. And I think the fundamental idea with Benchmark is there's a small group of people, a small group of partners who are all equal, and right now it's five of us, but sometimes it's four, sometimes it's six, but it's basically four to six, who cover technology. And the challenge with that, if you kind of think about it, is we can't be sector specialists. The sectors that have the most disruption and things are changing the fastest, like, are changing. That part's constantly changing. So you have to be as a group of investors, you to be moving. You have to be looking at new stuff because that's where the disruption's happening. And so then the question is, like, I can't be a sector specialist. I can't be a semiconductor specialist, or I can't be an open source specialist. Of course, we each have preferences and things that we like and don't and lessons that we can apply, but it's not a specialty model. And I think about this lot, we should talk about it in the context of AI, but can't have it. So then the question is, well, what can you evaluate on? And I think this is it for me, which is you can say, hey, this is an extraordinary entrepreneur. That's an evaluation that you can try to make. There's a second thing, which is this entrepreneur has a very interesting and unique insight. That's a really important thing for me. And then you can say, this market can sustain a big company. Those are three things which I think even coming without sector specialists, without being a sector specialist, you can try to come to a belief or a probability distribution for each of those things. And I think if you have those things and then you add on top of all of it, I have chemistry or want to work with this company or want to work on this mission or whatever, then I think you have the basis for an investment. Think one of the maybe contrarian things around that is think that a lot of venture capital in the SaaS era and certainly a lot of growth venture capital, got to be like a very spreadsheet y investor bankery type of approach, which is like, it's kind of the model's figured out. We plug these things in and we kind of know and we figured it out that way. And I think that doesn't work. I think there was a period of time where it might have worked for a bit, but I think it largely doesn't work. I think the AI stuff is going to wipe out that breed of venture capitalists. It's going be really challenging because you really have to make these other kind of fundamental assessments. **Harry Stebbings** [14:02]: Can I pose an alternative to you there, which is actually those are generally vertical SaaS companies with deep data reserves, which will then be able to leverage foundation models that are relatively commoditized to build much better vertically specific apps and become stronger? **Eric Vishria** [14:18]: Could be. That's possible, but I would tell you this. We were talking about a company yesterday and it has every possibility that you just said. The entrepreneur in that case is one of the challenges with these platform shifts is some form, some variant of the innovator's dilemma. It's not quite the innovator's dilemma as Christensen articulated it, but it's some form of the innovator's dilemma, which is like you have to make the platform shift. And in order to make the platform shift for a company like what you're articulating, you have to kind of be willing to burn down the existing business, at least in short order. There's a whole bunch of entrepreneurs who don't do that. And so like this this is why I just go back to you. If you have a learning entrepreneur who is constantly rethinking how they're navigating the ship, then that makes a really, really big difference in the probability of outcome as you're working through a platform shift. **Harry Stebbings** [15:11]: I've gotta take this one by one because otherwise, I'm just gonna go all over the place. You said, like, the insight development. I agree, I love that. I actually ask it. Mike Maple's always taught me to ask, like, what is your insight development? How do you view the world in a way that others don't agree? Yeah. I asked Pat Grady on the show, who says hi, by the way. But I asked Pat Grady on the show, and I said, do you have to be contrarian and right? What if an a founder says, I think that actually the world is moving to cloud, duh, and I'm gonna facilitate that much quicker. There's not really an insight. Does that matter? Do you have to be contrarian and right in your insight? **Eric Vishria** [15:48]: You know, there there are levels to it. Like, yeah, it you know, you can say, like, hey, we're going to cloud and we're doing this. But normally, there's an insight. I would say, like, if you look at most of the successful companies, there's an insight. There can be an insight underneath that, which is like, yeah, it's going to cloud and this is the right way to attack it. Or it's going to cloud and you know, and the, like, core differentiation is gonna be, like, here, not here. Like, normally, there's an insight there. I think there's a couple cases where you know? And you really have to think about it. There's a couple cases where just, like, violent execution by a determined team in a hypercompetitive market where, like, nobody has an insight has worked. **Harry Stebbings** [16:28]: But even now, actually, you could argue that, say, like, in an Uber Lyft case, which is exactly what I was thinking, the insight, I think, would be that broad is better than narrow in terms of market expansion, and being everywhere is more important than honing one. **Eric Vishria** [16:42]: Yeah. I mean, I think I think you could say, that you know, that's a good case of violent violent execution by a determined team. And so I think there are insights there, as you said. There's like little execution detail insights in your point. And so it's not like it doesn't have to be some pie in the sky insight. Like, that's like, oh my god, know, AGI is coming in q three of twenty twenty five. Like, that's not the kind of insight that we're talking about. We're talking about actual things that are nuances that help build the company. So, they think they come at different levels. I would also say this is a difference, I've been fortunate to work with Pat on a board and work with the the larger SQLA team on a number of companies. And there is a difference also in stage. Right? They're growth investors, like, or at least Pat and his team are growth investors, and we're early stage. And so, like, there's also, like, a stage difference in terms of how we evaluate things. **Harry Stebbings** [17:31]: You said about markets being large enough to support massive companies. How do you think about market creation? **Eric Vishria** [17:38]: I think you have to say, and this goes back to the insight thing, if this thing, whatever the product is, accomplished what it was supposed to do and what the entrepreneur said it could do, would there be market creation there? Right? And so like you mentioned Uber. Uber is a good example of this. And this goes back to the whole, like, that professor, the, like, taxi cab analysis that was done, like, in the early days of Uber where it was like, oh, the entire market's this big. And it's like, well, if you can imagine, everybody has a smartphone in their pocket. And if you could actually request a ride instantly and pay for it easily with not with shorter wait time and much more accuracy and much less cumbersome communication, could a market be created? Yeah. And I think that was a huge part of, Gurley and the rest of the Benchmark teams at that time, which predates me. It was a huge part of their insight in terms of the investment thesis. And so when you think about a situation like that, okay, that's market create that's a good example of market creation. And we have those all over. I'll give you another one that's kind of really interesting right now, which is AI medical scribes. And so you go to the doctor and you talk to your doctor and then they have to do a bunch of notes and everything else, and so there's a bunch of these AI medical scribes. You look at it and you look at the proposition, and I've looked at it now. I've met several of these companies over the years and we haven't invested in any. But going back, I don't know, five years when I met the first one, it's like, if this exists and works, yeah, that's a better way. It is a better way. So there will be market created there. It's going to take away from actual human scribe business, but it will be a new but it is a new market in a way. And you can imagine, it's not hard to imagine that exists. We often say this when we're talking about companies, which is if you fast forward three years, is this a thing? Is it a thing? It's often a good sign when you're like, yeah, Like, that's a thing. Like, it's gonna be a thing. Like, we we believe that. **Harry Stebbings** [19:42]: I totally agree with you. But what on earth do you do in this, and we're totally switching tasks to, like, AI companies, but in this sea of AI companies, well, like, we're both in 11 together. Great. Love Hassan. Fantastic. But there's a lot of other competitors to 11x. I'm with you. I've met five medical scribe companies. I thought Nabla was the best, but there were, like, 20. And I Yeah. I don't have a freaking clue who's gonna win. So how do you filter when everyone does the same, says the same? **Eric Vishria** [20:12]: I I I think this is where we go back to where where we started. Do we have an extraordinary entrepreneur that you believe in? Do you think they have an insight that is cogent? And I would say this, maybe this is a more useful way to say it. The more competitive the market is, the higher the bar you have to hold on those two things, I think. And so in a hyper competitive market, you have to really believe in the entrepreneur and really believe in the heart of the insight and their execution ability. And In a less competitive market, it's just misery in life to work as a venture capitalist and serve on the board if you don't really love the entrepreneur and really love the area. So that's a thing for me, which is I think about a lot when I'm kind of looking at a company is like, am I going to be able to authentically help this entrepreneur close great talent? Like, am I going to be able to talk to them and tell them why this should be, like, this should be an amazing, like, this is an amazing person that I can tell somebody that this should be their life's work and help convince them to join a company. Right? Like that's the only which is a big part of what we do. And so when you look at that, I ask myself that question, and if my answer is like, you know what? I think it's a cool business. It'll probably work, but I just don't understand how I can make that pitch, then I don't do it. Like, that's my I just I don't do it. So there's this balance there, but, like, I think that's a big important part of it. And the more competitive the market, the higher the bar has to be. **Harry Stebbings** [21:56]: I I totally agree. My worry is in a lot of these cases, the quality of product does not matter as much as the existing distribution moats that incumbents have. Could be like AI medical scribe's great example. Microsoft has such large enterprise. Nuance **Eric Vishria** [22:13]: could just crush everybody. Just crush **Harry Stebbings** [22:15]: everyone. You're a and you're you're a 10% better product. Agreed. Better product, but they just crush everyone with bundled packaging. **Eric Vishria** [22:21]: Yeah. Today's incumbents are paranoid and on top of things and like, is Microsoft and Nuance gonna move slower and whatever than your average AI medical scribe company, of course? But they're not dopes and they don't have their head in the sand. And so, like, yeah, I mean, I think that is like, you do have to factor that in for sure. **Harry Stebbings** [22:39]: Harry, does AI allow companies to charge more price per seat and have better revenues, or does it merely denigrate their margins because of the increased cost of implementing AI? **Eric Vishria** [22:53]: The answer is for sure both. I would maybe tweak your question which is to say, I don't know that it's gonna be like the price per seat model, but I'll give you a simple way to look at it. Let's take the AI coding area. We've seen tremendous amount of capital go into AI coding and co pilots and AI software engineers and whatever. Let's say your fully loaded IT or software person is $200, just for argument's sake. And if you think about that $200, there is, call it, $10,000 for every one of these software engineers or IT people. There's $10,000 of tool spend. In that, I would put Jira, which is Atlassian, GitHub, ServiceNow, a computer, whatever, development environment, Git, whatever. So all that's called $10 a year roughly. On that $10 a year of spend, how many hundreds of billions of market cap has been created? Like, 300, 400, 500, some big number of market cap has been created on $10,000 worth of spend for each of these software engineers. So if the AI if you can get AI good enough to eat much more of the the $200,000 of value attributed to your software engineer, a deep person, It just follows that there's like 20 x more value creation, and there will be giant, giant outcomes. So in this way, like and this is this is the challenge with it, which is it's simultaneously the most exciting and most disorienting time in my twenty five years in technology, because that is a really challenging situation where, in some ways, the prize is so big that you could very easily say, you can justify really ridiculous prices on any fundamentals basis. You can justify really ridiculous investment again on any fundamentals basis because it's like, well, the price is so big. So that's one one part of it. And then the other part of it's like, wait a minute. We're a little ways away from, like, from replacing the software engineer right now. We're we're we're, like, a bit away from that, and, like, we haven't actually captured that much market value yet. And really, no one's demonstrated anything close to that level quite yet, although the trajectory is, like, really quite good. And so that's the tension and challenge with it, you know, and this is the kind of thing that we have to, like, navigate through every day. **Harry Stebbings** [25:11]: Those companies in that trajectory are scaling revenues faster than ever. I remember when it was like, oh my gosh. They got to 10,000,000 ARR in such a now it's it's just completely different in terms of revenue scaling. How do you determine and think about analyzing revenue quality? I've heard you said before sugar high revenue versus sustainable revenue. **Eric Vishria** [25:32]: I I was talking to a team that had gone, like, a four person team, zero to four million in four months. Amazing. Like, just amazing kind of revenue trajectory. But I put, like, almost no value on that going 0 to 4,000,000. And I think one of their things was like, well, why are you giving me credit for that? And I was like, well, thing that I take away from that is that whatever you're selling, and this is true for a lot of these AI companies, customers want to buy. Customers want to buy it. And I think part of it is just like the products to a lot of these customers, the products are magic. They feel like magic to the customer. So the customer and ROI on those products is just tremendous. And they know that they have to experiment with it, or they have to try it, or they wanna try it because they see so much potential value in it, and they they feel it. So the demand side is like is very clear, and it's just pulling. And I think that's probably the biggest thing that we can take away with these early stage companies and their traction, which is like, okay, there is demand. And then you have to evaluate and figure out, okay, do we think that whatever the product the company is building, the entrepreneur, and we go back to the same things, has sustainable advantage over time. That's a really difficult judgment right now, but I think it's one of these things that we have to do. But I totally agree with you. The quickness of the scale is unlike it's like three, four, five years of what SaaS company, like your traditional SaaS companies were doing, we're seeing in under a year. And we have a whole portfolio of companies that are that are like this. Like, it's amazing. **Harry Stebbings** [27:06]: But this is I find it kind of paradoxical, because you got two questions here, which is the $600,000,000,000 AI question. Thanks, David Khan. The CapEx spend is so much, and the revenues are trading so far behind. And then you also have the the speed of revenue scaling is fast than ever. Oh my gosh. They almost seem at odds. I don't worry about **Eric Vishria** [27:24]: the 600,000,000,000 thing. I **Harry Stebbings** [27:26]: Do you think that's the right question to ask was really my question. **Eric Vishria** [27:28]: No, I don't. Like, I go back to my software engineer example. Like, the price is like, forget about AGI for a second. The price is so big even without AGI. Like, the price is so big. And so, like, yeah, the revenue will materialize. There's a lot to figure out. I was talking we had a dinner guest yesterday. We do these dinners as a partnership with a guest on Mondays. And one of the kind of conversations around it was we were kind of unpacking is, like, if you think about search. So search, we started first seeing the search the first search engines, call it 1995, is when you started to see the first search engines. And then Google Series A was 1998, I believe, and immediately was a better search engine and a better trap and everything else. What I think is lost in time is Google didn't figure out the monetization. Of course, they did it through an acquisition. They didn't actually figure it out themselves. They didn't figure out the monetization of search until, like, o one, I think, and so like, or late two thousand. And so we had, like, five or six years of these search engines, which anybody at that time was using them every day. There were crappy display ads all over them and all kinds of stuff that was just totally like people that had them I think sure there were paid search engines. People tried to do all kinds of things to figure out the monetization model. And so I don't know that we figured out the monetization model, but I think what we can say very clearly, customers perceive a lot of these products, not all of them, but a lot of these products as magic, which they are basically magic, and they want them. There's a bunch of monetization that needs to be figured out, but I kind of don't worry about it. It's like we will figure it out. That's just the delay. And I feel like and the reason the parallel to search is interesting is because it's like, hey, there was a new technology that was really powerful search, web search, and it took a while to figure out monetization and we have a new technology, alums, that are really, really powerful and we've got to figure out monetization on them and it's not going to be a $20 a month subscription. That's not the right way and it's not gonna be just like bundled API. Like, it's there's gonna be much, much more sophistication and interesting models than that. **Harry Stebbings** [29:40]: How do you think about value in the stack? When we think about where value in the stack is today, it's obviously in compute. Nvidia has seen that. It's also in models with OpenAI. Everett, you know, your partner Sarah wrote that models are the fastest commoditizing technology ever, which is a great statement. Yeah. I've used it a couple of times in shows. How do you think about where value accrues in the stack and where you need to spend most time aligned to that? **Eric Vishria** [30:03]: The foundational models are the fastest depreciating asset in human history. I think it's turned out to be largely true. Does **Harry Stebbings** [30:10]: that mean there's still great value in OpenAI? **Eric Vishria** [30:12]: I think that's a good question that is really interesting because if you think about OpenAI, Anthropic, Meta and Google, and then there's a whole bunch of others coming, xAI and Mistral and so forth, SSI now. I think the foundational model war benefits us all in a way. It's really, really good for consumers and people around it because it's just like they're pushing the state of the art so much. In terms of value accrual, for Benchmark, we have no foundational model investments, and then two, we have a set of infrastructure investments, which I think are really interesting. So we have Cerebras, which is a semiconductor and systems company for AI that we invested in and led their Series A in 2016. We've working on it for eight years. We have companies like Fireworks, which are an inference service and others kind of off that infrastructure software layer. And I think those, again, they're growing very, very quickly, astoundingly quickly and doing really cool things. But at the same time, you kind of have to ask, like, okay, what are the foundational models gonna do, and how are they gonna move up the stack? And so this is again where I go back to, you need great entrepreneurs who are, like, constantly updating their mental models and re navigating. And and Linux fireworks. Do you not **Harry Stebbings** [31:29]: think we just see all the foundation model companies just get acquired by the big players? We've seen character inflection adapt. **Eric Vishria** [31:36]: I don't think all the foundation model companies will get acquired by the big players. **Harry Stebbings** [31:40]: Some may, but If you are not, how can you fund survival? **Eric Vishria** [31:44]: Well, I I think this is a question. Right? And they're gonna do it, but I think there's a set of people who certainly believe in the size of the prize, and so they continue to be able to raise really tremendous amounts of capital to train bigger and bigger models. Just to put it in perspective, like, a 100,000,000,000 even for the oil state companies of technology, you know, doing a $100,000,000,000 acquisition is is unprecedented. **Harry Stebbings** [32:07]: But doing a 30,000,000,000 is not, and you only need to acquire the LickPref. **Eric Vishria** [32:11]: Yes. I mean, I think well, I think there's two things, which is, like, if $30,000,000,000 acquisitions are not unprecedented, and maybe you could say, like, in this world, you know, therefore a 100 also is not, like, that big of a stretch. Like, that isn't that huge multiple, but it does feel like a big number to me. It would also never **Harry Stebbings** [32:28]: get through antitrust. **Eric Vishria** [32:29]: Well, I think the antitrust thing is a big is a big question. **Harry Stebbings** [32:32]: Does AI today to AI rounds break the benchmark model? And I don't I mean that slightly deliberately provocatively, but your fund sizes are very disciplined. You are hailed as the boutique provider of venture, very tailored for ASAN. But these rounds are often you mentioned some of the, you know, software creation AI companies. These rounds are, 50,000,000 starting price. **Eric Vishria** [32:54]: I don't think so, and I don't think so for two reasons. One is through thirty years of performance, I think we have unprecedented flexibility in what we do, so if we want to write a $50,000,000 check, we can write a $50,000,000 check, and we have. If we want to write $150,000,000 check, we can write $150,000,000 check. If we deploy a fund in eighteen months or a year, it's fine. We can do whatever we want. The fund thing is almost irrelevant artifact of history in accounting, and so I don't worry about it there. So that's one part of it. The second part of it is Does it not just your decision Does **Harry Stebbings** [33:32]: it not just impact your decision making? I totally get you. Of course you could. Like, every LP wants to be in Benchmark. It's the one fund that every LP is like, oh, I want Benchmark. I totally get it. Of course, they do. But if you have a 500 fund, you're just not as likely to write a 50 or a $75,000,000 check. **Eric Vishria** [33:47]: You know, I think one of the things that we maybe think about almost not at all is we almost never think about, like, fund cycle or fund timing or anything else, and we almost never think about or talk about portfolio construction or anything else. Like, we it does not come up. It's really interesting because when I talk to other venture capitalists, they're like, well, how do you think about the portfolio construction and how do you think about check diversity in company and just, like, never ever talk about it. And so it isn't a thing. Genuinely isn't a thing. That's a bunch of inherited goodness and flexibility. I think there's this amazing Munger quote, and he said, you know what? Finding good investment ideas is hard enough. Finding great companies is hard enough. Let's not over constrain it, basically. Let's not over constrain it. Let's not add a bunch of things to it. So what I say back is, in the benchmark view and approach, what we're looking for is these exceptional opportunities led by these exceptional people that can turn into something extraordinary if things work. Like, that combination is hard enough. **Harry Stebbings** [34:52]: Do you not think it helps provide a lens of focus to narrow your examination of where to spend time? **Eric Vishria** [34:59]: You know, we very, very openly and regularly talk about things that are just, hey, that's way off. Like, that's a $50,000,000 check for 10% ownership. It's not That's not the core model, obviously, but the flip side is I look at you mentioned 11x. That's an amazing company we're super lucky to be part of. I think about Brett Taylor, Sierra. I think about Llins, Fireworks. You know, I go through and I like to look at these companies and I'm like, I like that AI portfolio. It's a bunch of infrastructure software companies. It's a semiconductor company in Cerebras. It's a few application companies as well. And like, the foundational model rounds and some of those things have gotten, like, really, really large, but you kind of look at some of the things that are happening on the ground in the early stage in AI, and it's like, yeah, it's totally doable, totally manageable. **Harry Stebbings** [35:45]: Do you think that you always need to play the game on the field? Bill Gurdy, your partner, said that once, and Yeah. I oscillate. **Eric Vishria** [35:52]: I mean, to some extent, you always have to play the game on the field or you always have to maybe maybe a different way to say it is, like, you always have to be aware and cognizant of the game on the field. So, like, that it's the game is the game. You can always choose to play more or less. You can choose to to play more or less. So I'll give you a really concrete example. 2021 was SaaS craziness, everything craziness. Right? Like, everything was running and everything else. In 2021, we made, like, three new investments as a firm. Three. That was the game on the field and just saying, that's okay. I'm okay not playing that game. And that's great, and I have no regrets on that at all. I think that is fabulous. This year, 2024, the game on the field is we have a major, major shift in AI, which could be bigger than any of these other shifts, maybe combined. It's really big. There's a lot of interesting work happening. There's a lot of uncertainty, without a doubt, but we've been more active than we've been since 2010 and 2011. What was happening in 2010, 2011? Mobile shift. To **Harry Stebbings** [36:54]: what do stand with AI? Do you think we are overestimating what we can do in one year and we're all getting ahead of our skis? **Eric Vishria** [37:00]: One of the beauties of this in our model, like, think about if I go back to 2010 and 2011 for a second. You know, in that time timeline, that's when Snapchat, Uber, Twitter, Instagram, that's when we did the series a's. In Instagram, Snapchat, Uber, whatever, a weird round in Twitter. The round that Peter led in Twitter at that time was, like, technically a series c or series d at, like, 200 pre because the company had its history, right, with audio and everything else. And so it was a rule breaking round. It's a good example of exactly what we were talking about earlier. Yeah. You kind of have your, like, norms, and then every once in a while, you just have to be like, throw it all out and just do it. And that was a good example. But if you think about that body of work, was obviously tremendous towards a returns perspective. Fast forward to today, you're looking at the game on the field here. We have to kind of ask ourselves like, hey, are there extraordinary opportunities and extraordinary companies getting built here? And if so, like, you just gotta do it. **Harry Stebbings** [38:01]: I heard you say once when it came to Cerebras that Peter's role as your partner was to help enhance your instincts. **Eric Vishria** [38:10]: Yeah. He did. He did. **Harry Stebbings** [38:11]: He's amazing. I have such a man crush on Peter. I haven't told him, and so it's lucky that this isn't a podcast. My question to you there is, is that not dangerous? Should a partner not be the counterbalance, not the Duracell battery to your energy? **Eric Vishria** [38:26]: Well, I think both are true. My partners have kept me out of countless companies. It's amazing. You asked this sector question earlier, we were talking about it, is like, I spend a lot of time trying to understand chemistry, my chemistry with an entrepreneur, and try to figure out, am I going to love working with this person? Do I believe this person's a learning machine or not? So I spend a lot of time on that. I spend a lot of time trying to believe, do I think that insight is cogent or not cogent? Does it hold together? I spend a lot less time on the sector specifics because I just feel like if I'm an F on a sector, with best effort I can get to a D plus, that's not good enough. And so I'd just rather not. And I actually think this is this is maybe contrarian in total aside. I think this is why the memo writing culture at a lot of firms gets you in trouble because you put a lot of information. It encourages putting a lot of information that is, like, third and fourth order stuff into document as if that is impacting your investment decision, where like most of these investments, there's really like one or two questions that really matter. All energy should go to those, and everything else is kind of like unknowable, nondeterministic, or irrelevant. So what Peter did in the case of Cerebras was, and I remember it really distinctly, I met the company first on a Wednesday, and I was like, why am I meeting a semiconductor company? This is so stupid. I shouldn't be doing this. We don't make semiconductor investments. This is maybe February, March 2016, and I came out of the meeting and was like, wow. And so the team was amazing, and then the insight was really keen and really sharp. And it's now totally accepted, but at the time, it was, like, so it was so sharp and so contrarian or so not contrarian is not the right word, actually. What it was is unique and novel. Like, that's what it was. It was unique and novel. And so I came out and I was like, this is interesting. We met again. So I I called in a bunch of partners to meet on Thursday. And so a whole bunch of us, including some of the founders, including Bruce, as you mentioned earlier, he came in because what do I know about semiconductors? Almost nothing. Well, really probably nothing. Colin Bruce, who had actually done semiconductor investments and discussions, that was on Thursday. I spent time one on one with Andrew on Friday. Bill and I had lunch with Andrew on Sunday. I'm talking to Peter about it on Sunday night. He's just totally discouraging me from doing the investment. He's like, this goes against everything I've learned in the industry. Totally discouraged. He hasn't met the company yet, just based on my articulation of it. Monday, so I bring the company in, Peter was like, was like, Just have an open mind on it. Just have an open mind. And so comes in on Monday, Andrew pitches, and he had a term sheet already, so we were running obviously. And he pitches, at the end of the pitch we're debriefing and we have a system where we talk and then the sponsoring partner basically, you can call for a vote, and Peter said, Call for the vote. He told me he was like, Call for the vote, And he pushed me. So he pushed me to call for the vote and to push her over the line after spending literally sixteen hours before trying to talk me out of it. And so the answer is, yes, my partners have kept me out of a lot of stuff, but what he was doing in that moment is he had updated his own evaluation of the opportunity and the idea and was like, yeah, it makes sense. Also, clearly really wants to do it and sees something here. And so, you know, I'm eighteen months into being a venture capitalist and I have one of the greats of all time, sixteen hours before, telling me this goes against everything. It's like, don't do it. Like, blah blah blah. And so I think that encouragement of like, hey, you saw something there, and then the rest of the group saw it and was like, yeah, there's something there. And so I go back and think about that a lot because each of us in a good partnership, each of us brings our own points of view and our own biases and baggage, but our own insights as well. And so you've got to put all that together, and if you do that well, that's these partnerships at its best, and I've seen that a whole bunch of times. **Harry Stebbings** [42:41]: In the deals where your partners have saved you, as you mentioned many times, What did they see that you did not see most often? **Eric Vishria** [42:49]: I'll give you a great example where Sarah saved me. We were looking at a company and she's like, Eric, and this goes back to your sector thing. It's just like a perfect example that ties this thing together is like, she's like, Eric, I'm telling you, you're used to looking at software companies. At this company, gross margin and these unit economics really, really matter and they suck. There isn't a path to get better and the entrepreneur is not engaged on the topic. It it was just like a great insight because, like, for us, you know, as your kind of traditional software investor and, like, doing things, it it really doesn't matter. Like, it's just like all of these things end up you know, your SaaS companies are gonna end up in between 7583% gross mark. Like, they're just gonna end up there. Like, it's fine. It works itself out. And so, like, a company that starts their, like, you know, way less than them, it's just like whatever, and you you'll fix that. But I think it was a great insight that kept me out of it because there were a ton of things that I loved about the entrepreneur and it was really a compelling individual. But I think her point on the nature of the business and the fit between the entrepreneur and the nature of that business in Pacific was spot on, and so Sarah saved my bacon. So **Harry Stebbings** [44:00]: I was talking to my partner the other day who comes out of DST, and so he's like trained on like gross margin and like real numbers guy, And he's like, oh, the gross margin at 3,000,000 in ARR. And I'm like, dude, no one gives a fuck. Irrelevant. No one gives a fuck. It's 3,000,000 in ARR. The gross margin in ten years, I have no idea what it'll be like. And even then, if it's if it's still a shit gross margin and it's go go times, we can still get a great multiple. And if it's amazing in shit times, the IPO market there's so many fucking variables. I don't have a clue. **Eric Vishria** [44:33]: I totally agree. I I I think this goes back to the spreadsheet conversation and why I think spreadsheet investors are gonna wiped out or have a really hard time in this era. And I think SaaS was such a boon and gift to the investor, bankery spreadsheet investors. Plug your stuff in and you figure it out at scale. At the early stage though, I totally agree with you. People will come in and they have a million and 0.5 and they're talking about their net dollar retention or whatever. It doesn't matter. None of that stuff and not a single company. I think I've worked on five companies that have gone from zero to more than more than 200 in revenue. And, like, in not a single case did the economics at the very early stage extrapolate all the way. Like, it's just it's just not a thing. Not even not even even the economics from when they were at 30 or 40 or 50 extrapolated to 200. Like, it just it isn't how it works. There's so much change that happens at these companies. And so, like, it just false precision around that is just dumb. And I think you can say, let's say let me take the flip side of it, which is the flip side is there are things that you can see at those stages which would tell you that this thing is like going into a wall or is gonna have to undergo a major transformation or, like like, I think there are problems that you can see, but I think the positives are not really knowable that way. **Harry Stebbings** [45:54]: Can I ask you? In terms of, like, how you spend your time, I spoke to Victor on your team, and he said Eric is so unlike most other VCs. He spends, like, 70% of his time with his portfolio. **Eric Vishria** [46:04]: Yeah. At least. **Harry Stebbings** [46:06]: I would love to understand how you think about the makeup of your time between sourcing, picking, and doing diligence and doing references and and then servicing, helping portfolio. What does that look like? **Eric Vishria** [46:18]: At this point, I'm probably 80 or 85% on working on the portfolio. I mean, it's a lot. And part of that's because, whatever, I'm on 12 or 13 boards, I can't remember, but a huge part of it is that is our model. That is the Benchmark model in a sense. The Benchmark model is a concentrated portfolio of very high conviction commitments. Like, we're making commitments to entrepreneurs. It's like it's very high concentration and very high conviction. That that is the nature of our model, and I think that is Are you on too many boards? **Harry Stebbings** [46:51]: Twelve, thirteen is nuts. **Eric Vishria** [46:52]: It is a lot, but I I I think they're all at different stages, so it it isn't as nuts as you it kind of seems on the surface because four or five of them are really young companies that are in their very early days. And like you said, I spend 80%, 85% of my time on them. So it's not like I'm If I spent 60% of my time looking for new companies, then of course you wouldn't be able to spend that much time on your portfolio. **Harry Stebbings** [47:18]: Final one for you. You said about cool the vote. What does the vote look like? **Eric Vishria** [47:23]: Our vote system, which is somewhat irrelevant but it's a way to kind of quantify people's feedback. So a company comes in, we all talk about it. At this point in time, most of the time like, there's only five of us, right? So at this point in time, we would have chatted about the company and at least two or three partners would have met typically. And so there's a decent amount of institutional knowledge about the company. And then at the end, you kind of quantify your feedback, and so it's a way for partners to quantify their feedback to others. And so our voting system is you vote one to 10, you can't vote five. Six and above is yes, four and below is no, and it's kind of strength of conviction. Right? If get a bunch of tens, amazing, that I've never seen that happen. If you get a four, like partner's telling you they didn't really like it but it's not, whatever. If you give a two, your partner's telling you they're really discouraging you from doing it. **Harry Stebbings** [48:16]: Have you ever had a one? **Eric Vishria** [48:17]: I don't know. If you're gonna if your next question is what happens if you don't have the vote and you still wanna do it, I have no idea. I don't know what happens. **Harry Stebbings** [48:23]: Does that not go against being nonconsensus, seeing the beauty which others don't? They're not **Eric Vishria** [48:29]: necessarily, dude. I I think they're **Harry Stebbings** [48:31]: Because you have to get a quorum, so you need to get three out of the five. **Eric Vishria** [48:35]: I don't know that you have to get three out of five. Like I said, I I don't know what hap this is a it's a very Benchmark is a very high trust, like, high confidence in each other model and structure. Right? Is it always five five people saying yes? No. I'm I'm just saying nobody knows what the votes are except the sponsoring partner. And if a partner wants to do something, I think they can do it. You're getting feedback from your partners who you trust and have confidence in. Why do the voter tool? I think it is actually useful to quantify things. You get all this you get all of this feedback. Right? And and anybody who votes a six on an investment does it apologetically. They have to be truly conflicting. It's there's nothing strategic. That's managing politics. That's not managing making the best investment decisions. **Harry Stebbings** [49:21]: Do you not think it's about kind of being all in or like hell no? **Eric Vishria** [49:24]: Well, I think the sponsor your sponsoring partner, the the kind of advocate probably needs to be that. But your other partners who are looking at it and trying to help you make a decision, I don't know that they have to be that way. They they, you know, they have less information necessarily, and so having their strength and conviction doesn't need to match yours. **Harry Stebbings** [49:44]: Okay. We're gonna do two types of quickfire. One's a short quickfire. One's a slightly longer one. Quickfire on people, you've got one takeaway from working with Gurley, Fenton, and Matt Cola. Okay. I just chose them because they're my favorites. So what's the biggest takeaway from working with Gurley? **Eric Vishria** [50:01]: Even great companies can be overvalued. One of the things that Bill is really good at is is, like, thinking about fundamentals. Right? He he came from public marketing investing way, way, way back when, at the beginning of his career. He has that mindset, that analytical mindset, and so he thinks through that and says, Hey, on a fundamentals basis, you will trade sometime at under 30 times free cash flow. And so that's a thing. Right? We're all you and I were talking about what's the ARR number or the revenue and all this stuff. But ultimately, you talked about the four areas, which is sourcing, picking, winning, helping build. Right? There's a really important fifth stage that nobody talks about and not every venture capitalist gets to you, which is exiting. And ultimately, our job is to return money back to our investment partners. So when you kind of think through that, you do have to ultimately, hopefully, everyone gets to a place where they're thinking about this like fifth step, not everyone does. And in that place, do have to kind of think about these fundamentals. And so occasionally, you have an amazing company, that you really believe in, but it can be overvalued too. Okay. Fenton, what's the takeaway from Peter? The insights around people and motivations that Peter has are unparalleled. I've described this before, Peter and Bill, one of the things that's amazing about the two of them is they're very, very different style investors, like almost diametrically opposite in a bunch of ways. And obviously, they have a lot of common ground, which is how their partnership was so effective for so long. Peter is very much like people first. Bill is very much, I would say, like market first. It's a different mental model in looking at these things. **Harry Stebbings** [51:44]: Totally agree with you. I remember Peter once told me price is a mental trap. **Eric Vishria** [51:47]: He he told me a version of that on one of the first investments I looked at at Benchmark in 2014, summer of twenty fourteen. The discussion was like, well, could you do it at 40 or 60 or whatever? It's like some price. I was like, well, I'd do it at 40 and not 60. And he's like, no, no, that doesn't work. No, it can't do that. I've said this now subsequently to new partners who've joined in my own way where like, yeah, that's not you can't not allowed to make that claim. **Harry Stebbings** [52:15]: I remember also when I was debating whether I should get more operating experience before becoming an investor. He was like, do you wanna be an investor? And I said, yeah. He's like, then invest. **Eric Vishria** [52:24]: Then be an investor. Yeah. Yeah. **Harry Stebbings** [52:27]: Final one, cola. What have you learned from Matt? **Eric Vishria** [52:29]: Matt is the best at understanding the insight and the depth of an entrepreneur's insight. That is Matt's superpower, understanding the depth of the insight. Is the insight bullshit? Is it authentic? Is it really deep? He's six sigma on that. Matt says very little, and it is always insightful. **Harry Stebbings** [52:49]: The normal quick fire. What do you believe that most around you disbelieve, Eric? **Eric Vishria** [52:53]: I I don't think Nvidia is going to be the only game in town. I don't believe Nvidia is gonna be the only game in town on infrastructure layer. Like, I just and I think the entire setup right now is an assumption that if AI is real and here to stay and there's real ROI, then Nvidia just continues to run at this level, and I I I don't believe that. **Harry Stebbings** [53:16]: That's a good one. Credit to you, Eric. That's fantastic. Which venture investor outside of Benchmark do you most respect? **Eric Vishria** [53:23]: There's so, so many. Good. You've got one. I've got one. You know, I think you'd have to say I I I'd have to say I'd have to say Getz and Jim Getz. And the reason I would say Jim Getz well, one, Jim is the one who first told me I should get into venture, and so I'm eternally grateful to him for that. He said that to me in 'eight. It took me six years to figure out that he was right, but I'm super grateful for him for that. But two, we talked about this, there's almost nobody who's had wins in consumer land at the scale of WhatsApp and wins in enterprise land, and he's done it over and over. So to have like Palo Alto Networks and WhatsApp is just insane. And obviously, had many, many other wins. And so he's been a spectacular, spectacular investor, and I'm eternally grateful to him. **Harry Stebbings** [54:14]: Why did you not join Sequoia? **Eric Vishria** [54:16]: I just like at that time so in o eight, when I talked to them, I really had it in my head that I wanted to be a founder, and I'm super glad I did. I had some conversations, came up with the idea for RockMelt. So Tim Howes and I, who's my cofounder, pursued RockMelt. And then five years later, you know, RockMelt went through our ups and downs. We were bought by Yahoo in 2013. And then, you know, a year later, joined Benchmark. **Harry Stebbings** [54:41]: And you didn't go back to them? **Eric Vishria** [54:43]: I did not. No. Different time. I think, you know, Sequoia, like a lot of firms, hires people quite early in their careers and, like, grows their own. Are you ready for **Harry Stebbings** [54:53]: my hardest one? **Eric Vishria** [54:55]: Okay. This **Harry Stebbings** [54:55]: is off schedule. This is, for true pros. Right. This has been so good. The heaviest things in life are not iron or gold, but unmade decisions. What unmade decision do you have that weighs on you most? I don't know. I can **Eric Vishria** [55:09]: think of several little things that I would have done, but I don't know. We had early acquisition interest in RockMelt. That was probably something that I should have leaned into more in retrospect. That's an example and that would have been a very different But in the scheme of things, looking back now, it's 2024. Would it have changed anything? Probably not. This is the whole what's that children's story about the horse rider and the soldier and the conscription? Have you heard story? No. It's a really amazing story. Summary of it is, it's like ancient China and there's a draft. The first part of it is, there's a family in rural China, and they get a horse. This kid finds a horse. The villagers are like, my god, he's so lucky, he's so lucky, he's so lucky. And the wise man is like, we'll see. And the kid's riding the horse and breaks his leg. And then the villagers are like, Oh my god, it's so unlucky. It's so unlucky. It's so unlucky. And the wise man is like, We'll see. And then there's a draft, a military draft, and the draft people come to this rural village. And they draft everyone except the kid with a broken leg because he has a broken leg. The villagers were like, We're so lucky. He's so lucky. The wise man's like, We'll see. I say that because it relates to my RockMelt experience and kind of where we started, which is founding and building a company is really, really hard and you have to have a lot of determination in order to do it and you go on these ups and downs and I certainly did. And ultimately, we didn't realize the potential of what we wanted, but did it work out or did it not? In the fullness of time, I'm like, I couldn't be happier where I'm at. And thankfully, those team members, they're at great places and great companies, a whole bunch of them work inside of the portfolio that I work on, which I'm super grateful for. And so we'll see. Reminds me of The Businessman **Harry Stebbings** [57:02]: and The Fisherman. I don't know if you've heard that one. I haven't heard it. **Eric Vishria** [57:05]: Oh, yeah, yeah. I have heard this one where it's just like, well, what would you do with all that money? Well, I'd retire in a small fishing village. Yeah. Totally. Totally. Haven't heard that one yet. **Harry Stebbings** [57:13]: Drink beer and chill. Yep. Pretty much. Yeah. An ultimate one, you can cool yourself up before the birth of your first child and say, Eric, you should know this. What would you say? **Eric Vishria** [57:25]: Man, it's hard. **Harry Stebbings** [57:30]: What's the hardest? **Eric Vishria** [57:32]: I think the the big thing in the first few years and we we went from zero to two, so it was particularly challenging, but not as challenging as people who went zero to three or zero to four. But I think the hardest thing is your time goes away. It inverts. It used to be, on a typical, for you or for me now, my kids are a little bit older, like Friday is the day you're the most tired and then you have Saturday and Sunday to recover. This totally inverts. Right? For me, like, when we had kids, at the end of the work week was that was the most rested I was gonna be, and Monday morning was the most tired I was gonna be. And, like, it just, like, completely inverted because the weekend because it's so hard with little babies. **Harry Stebbings** [58:13]: I'm so well trained then. In the week, I have venture, which is the easy part. And on the weekend, I have just back to back to back media stuff and Saturday and Sunday. So I'm knackered coming into Monday. **Eric Vishria** [58:25]: Okay. Okay. Yeah. You're you're you're in good shape then. **Harry Stebbings** [58:28]: I add kids, and I'm totally fucked. It's final one for you. When I ask you for a memorable moment from your time at Benchmark, what's the one that you tell grandchildren? **Eric Vishria** [58:37]: That one for me would be when the founders of Confluent, Jay Neha and June, called me and said they were gonna go with with Benchmark for their Series A. That was my first investment. It was three founders, you know, and the company's gone on to wild success. That was a huge huge moment for me and and really memorable. I remember where I was, and it was a big deal. Alright, dude. I've absolutely loved doing this. Thank you so much for agreeing **Harry Stebbings** [59:02]: to do it. This has been amazing. So fun. What a man. I absolutely love doing that show. If you wanna check it out on YouTube, you can by searching for 20 v c. There, you'll find all of our episodes in video. I'd love to hear your thoughts and feedback. But before we leave you today, ## Sponsor read **Harry Stebbings** [59:17]: all of you listening use tons of software every day. Sometimes it fills us with rage. You can't figure something out. The chatbot in the bottom right is useless. You keep getting bombarded with these useless pop ups. And for those of you who build products, no one wants their product to feel like this. Thankfully, a company exists to help users without annoying them. Command bar. It does a couple of very helpful things. First, it's a chatbot that uses AI to give users extremely personalized responses and deflect tickets. But it can be beyond just text. It can also co browse with the user and show them how to do things inside the UI. Magic. 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