Moritz Baier-Lentz on why the future of AI runs on video games

Moritz Baier-Lentz is one of the foremost investors in gaming, AI, and frontier technologies—including companies like OpenAI, SpaceX, Palantir, Etched, Decart, and Recursive. He founded Goldman Sachs's global gaming practice and was previously a partner, IC member, and head of gaming at Lightspeed. Moritz is part of the founding team of General Intuition, an AI research lab training agents on video game data, which has raised a $133M Seed round and a $320M Series A. He is also a senior adviso...

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Speaker 00

  I think there's only two things in life. There's work and play. I find it shocking and sad how poorly AI is received in the gaming industries. I raised over $2 billion this year with my portfolio companies. Half of that was done without a pitch deck.

• 0:18Auren Hoffman?

  Hello, fellow data nerds. My guest today is Moritz Behar Lentz. Moritz is one of the foremost investors in the gaming world. He founded Goldman Sachs's global gaming practice and is advised on gazillion dollars of transactions over the years. He's also a founding member of General Intuition, which is a research lab training AI agents on video game data. It raised $133 million seed funding, and I just found out that you just raised another $320 million Series A, which is pretty awesome. He recently left Lightspeed Ventures, where he was a partner and head of gaming. He also serves as a senior advisor to McKinsey, OpenAI, TPG, and does a whole bunch of other stuff. Moritz, welcome to Summation.

• 1:03Speaker 00

  Thank you, thank you.

• 1:05Auren Hoffman?

  All right, before we get into it, okay, like, the first question is, you have, like, I don't know, 400 jobs. Like, how do you manage all this stuff? Like, walk us through, like, a life in Moritz.

• 1:15Speaker 00

  Well, slightly less than 400, luckily, but it's probably about 15 or so right now. And, you know, since April, after leaving Lightspeed, I spend the majority of my time, I would call that about 80%,

• 1:30Speaker 00

  you know, investing my own capital now and then advising the founders that I work with quite closely. I would say that most portfolio companies and most founders I invest in, I'm really in touch with daily. And it ebbs and flows where, like, in certain months, I think, with some portfolio companies, I've spent as much as 100 hours in a given month. Now, that typically is during fundraising or kind of like the PR and marketing push that comes after it. So there are certainly, like, peak times and downtimes.

• 2:02Auren Hoffman?

  Are you using, and I know you and I have had many discussions about how to use AI, like, how are you using AI as kind of your second brain, like, to actually make all this happen? Because at some point, you do have to sleep, right?

• 2:13Speaker 00

  That's true, every Wednesday.

• 2:16Speaker 00

  Yeah, I mean, just to finish the first question, the investing, the solo investing and advising founders specifically and startups, that's really 80% of my time. And then the other 20% are those senior advisor roles that you called out, where between OpenAI, McKinsey, and TPG, I help those three firms specifically with their foray into gaming and interactive media. And I think also increasingly, really, with the AI transformation of the gaming and interactive media industry. So that's my jobs in a nutshell. AI efficiency, I would say I'm a power user of intelligence.

• 2:55Speaker 00

  I'm not a power user of agentic use cases, at least for the time being, and we've spoken about that. I personally think for anything outside of coding applications, because the domain is just so much less verifiable, it's not quite there. But what I'm doing religiously, as you and I also have discussed, is I'm really trying to record as much as possible. My thesis is that once agents are good enough to genuinely and in high quality support all the things I do on a regular basis, which excludes coding, but includes a lot of other systematic tasks that probably will get there over the course of the next, maybe, call it 12 months.

• 3:38Speaker 00

  Right now, I think the best thing to do is create as good of a context window of my own work and what I consider success for these activities. And that includes, you know, recording, obviously, like, digital conversations as they happen through Zoom. It also includes recording conversations in my personal life. I use a range of tools and, you know, on Zoom, I really like granola. There's a hardware solution for phones called Plot. And then, you know, there's so much context in many other applications. We talked about Google Takeout and how it's probably helpful to really have this massive,

• 4:21Speaker 00

  you know, markdown repository of digital activity.

• 4:27Auren Hoffman?

  You're taking, like, Google Takeout, which is like your search history and a bunch of other kind of, like, interesting things, where you went and stuff like that, and you're bringing it into, like, an Obsidian or something?

• 4:37Speaker 00

  Yeah, I think Obsidian is kind of like the, yeah, the choice. And again, this is really, right now, it's a massive data repository. The key will then obviously be connecting that to capable agents. And again, just to make that point, at least my personal opinion is that they're not quite there yet. But I also think they will be very soon.

• 4:57Auren Hoffman?

  Now, if you're doing something just like online that you don't think your agent can do for you yet, like, I don't know, buy some shoes or something, are you recording the video of, like, you doing that so that you can have that in the future, so that the agent understands your tastes and your preference? Or are you not actually, are you recording, like, your browser use and things?

• 5:16Speaker 00

  No, but I mean, obviously, there's browser history, right? So that's part of the Google Takeout universe is your Chrome history. And I think, you know, there'll be a great representation of your shopping behavior and taste, et cetera.

• 5:29Auren Hoffman?

  And what about, like, emails? Are you connecting that into?

• 5:33Speaker 00

  All of them, yeah. All emails, all calendar events, all physical movement on Google Maps.

• 5:39Auren Hoffman?

  Everyone has, like, this kind of gradation of, okay, I'm willing to give this to the, I'm willing to give this to AI and whatever, whatever it is, Claude or OpenAI or whatever it is, I'm not willing to give this other thing. Sounds like you're a little bit more on the, because you're willing to give, like, all your emails and stuff there. Like, is there certain things that are like, okay, I can't give that because there's a security problem? Because that's where I get my password resets or, you know, like, how do you think about all that?

• 6:07Speaker 00

  I mean, passwords live outside of the data that is fed.

• 6:12Speaker 00

  As far as I'm concerned, I'm not engaging in any criminal activity. And so maybe others that are more hesitant have a different answer to that question.

• 6:20Auren Hoffman?

  Okay, got it. So you're just like, let's go all in, because it's a great training set. Let's get as much training set as possible into the system.

• 6:28Speaker 00

  By the way, like, for now, all of this lives locally, right? So part of my decision ultimately will also be when this is ripe and ready for agentic solutions, where this goes and what of it goes into the agentic system.

• 6:42Auren Hoffman?

  Now, today, I assume you're already asking, you've got a big Obsidian file, you're already asking questions of that Obsidian file. I do something similar, where I'll, like, ask questions just of my Obsidian file. Like, what types of questions are you asking of that file?

• 6:56Speaker 00

  I don't, actually, today.

• 6:58Auren Hoffman?

  Oh, you don't?

• 6:58Speaker 00

  Yeah, no, no, this is, this is, this lives completely independent for the time being.

• 7:02Auren Hoffman?

  Okay.

• 7:03Speaker 00

  Yeah.

• 7:04Auren Hoffman?

  Okay, I'll do something like, I'll say, like, give me a restaurant recommendation based on all the, I've got 14 years of history of restaurants, like, based on what I'm doing, I'm going to be in Denver. Give me a restaurant, you know, that type of thing.

• 7:15Speaker 00

  I mean, I've found even for that kind of stuff, just using the plain tools. I think they have enough context just from the sum of interactions with them that they give me quite reasonable answers.

• 7:24Auren Hoffman?

  Yep, okay, cool. Now, you said the next, you know, billion-dollar games might not look like games at all. Like, what will they look like?

• 7:34Speaker 00

  Yeah, I mean, just to kind of take a step back, there's been this huge interest in VC funding in gaming, kind of starting around 2019, 2020, and then certainly exacerbated by the COVID and metaverse ambitions through 2020 and 21. I think this has faded quite a bit over the last two years. But from a venture perspective, it's probably always true that it was maybe less interesting to fund individual games and experiences. That's more akin to kind of movie financing. I would say that's not really in the domain of generating, you know, what ultimately turns the needle for a scaled VC fund, which is like a, you know,

• 8:17Speaker 00

  10, 20, 50, $100 billion plus outcome at this point. And so the question becomes, where can games create scaled consumer experiences that maybe resemble social networks? I think Roblox is a great example. I think Discord is a good example. So those were, I think, the kind of...

• 8:38Auren Hoffman?

  I mean, is TikTok a game? I mean, in some ways, is, you know, Instagram a game? I mean, kind of, yeah. It seems like it's a game, right?

• 8:45Speaker 00

  Yeah, but you can, I think, from a philosophical perspective, when we can get into these things, when we talk about general intuition, I think there's only two things in life. There's work and play. And so, and I think you only learn during play, and we can unpack that as well. But the more interesting stuff even about games, and I think what I'm focusing my attention now, is...

• 9:08Speaker 00

  You know, there's this narrative that gaming is a $200 billion industry and it's the largest media category and so on, and all of that is true. But 200 billion, even in the grand scheme of things, is still small. Like, it's large enough for an OpenAI to care about it, but it's not gigantic, especially when compared to the enterprise software industry. And this is also why we see attention isn't necessarily there, at least from the scaled funds. However, play and concepts of play are massively important to the to the human existence. And what we do with General Intuition, for example, is this is not, we're not building AI for games. We're actually using games to advance the state of AI across all sectors.

• 9:53Speaker 00

  General Intuition is a is a company that leverages gaming data and leverages gamer performance in virtual worlds, not to build any games at all, but to build intelligence that is more deeply rooted in space and time and basically expand the entire catalog of machine intelligence, which so far has been rather reductive and limited to language and text and symbols, you know, helped by obviously the breakthroughs of the transformer and the fact that all of this was neatly scrapable online. But if you really think about how human learning unfolds, this is very deeply rooted in space and time, like a toddler learning to walk or an animal learning to climb. And so the question in ML, and I did my undergrad in ML, and it was all about kind of reinforcement

• 10:38Speaker 00

  learning in space and time back then, and I think we're coming back to that a little bit, is can we collect human action data in a wide range of environments and measure the outcomes, but also the action and intent that led to certain activities to begin with? And can we start training these foundation models on along those lines? Like, world models is a term that's now quite popular, and I would say has entered the AI mainstream maybe about a year ago. But it's something we've been fascinated with and working on for much longer than that, and that laid the groundwork for General Intuition, for example, and other companies I'm involved with.

• 11:16Auren Hoffman?

  There can be so many, like, if you go back a history of AI all the way back, and then, you know, even recently with like DeepMind, so much was about like using the AI to play the game, learning from the game. Okay, can we go beat a grandmaster in chess? Can we go meet the grandmaster in Go? Can we do this? Can we play StarCraft really well? Can we, like, so much of these things have been based on, why is that just because it is like, it's a great kind of confined area for us to learn on?

• 11:46Speaker 00

  Yeah, I mean, first of all, also to point it out, Nvidia, the most valuable company in 2026, started as a games company, right? Making, I think part of that is games have often, and I think still are on the frontier in terms of technological necessity to to make them actually really enjoyable, interactive experiences. And games as a category has been pushing the technical boundaries to the extent that sometimes the technologies built for gaming then also found applications outside of it. And I think GPUs are the most phenomenal example of that and the story of Nvidia.

• 12:30Speaker 00

  But then, abstracting a little bit, play, you know, play, you can make the argument almost from an evolutionary perspective, is kind of nature's way of maximizing informational return while keeping the stakes low. So you create almost these alternative options and universes in your head, you act them out, you test the environment, you collect the data, and failure doesn't have severe consequences. Specifically, for example, you know, let's, then this is something we don't see only in humans, right? We see this in animals too.

• 13:15Speaker 00

  Like, why, why are we fascinated by play? Like, why, why is play fun or rewarding, right? Like, most of this can can typically be evolutionarily explained. And I think you want to know how to climb before the saber-toothed tiger comes around the corner, because you're only trying it then for the first time, you're probably going to have a rough day.

• 13:36Auren Hoffman?

  But even like the, you know, playing hide and seek when you're two, or I'm going to tickle you type of things, like, even those types of games, like, you learn a lot from those things.

• 13:46Speaker 00

  Cops messing around with each other, you know, again, like, we see this in animals, we see this in in humans. Testing boundaries also, right? Like, I mean, and sometimes playfully and joyfully. And I think you could go as far to say, as just briefly mentioned, you know, there are some theorists that proclaim that really learning happens during play and not during work. Work as a juxtaposition of kind of taking everything you learned in play, we're talking in abstract ways here, right? When I use these words, play and work, it's a little abstract, but but work then being, taking everything you learned during play and kind of quote unquote, putting it on

• 14:31Speaker 00

  the road and executing and reaping rewards, but not really trying new things and learning new things. And now, fascinatingly, this dichotomy also is represented in in many, you know, AI, machine learning paradigms, where there's always this subtle trade-off between exploration and exploitation, which you can almost take synonymous with with play and work. And so these concepts, yeah, these concepts are very innate to to human intelligence, and at least so far, they are innate to how we've built machine intelligence.

• 15:08Auren Hoffman?

  Why are sports so popular? Like, it seems like, is that just like the play to the next level?

• 15:14Speaker 00

  Amateur sports and playing sports, I think, is enjoyable because it is a form of play.

• 15:18Auren Hoffman?

  You go play tennis with your buddies, you play pickup soccer, you know, whatever it might be.

• 15:23Speaker 00

  Yeah. And then I think watching sports, to a large extent, is also kind of like, you know, remnants of tribal fantasies. But one thing specifically about video games too is, like, this this idea that we would train foundation models on on spatial-temporal data rather than like a linguistic fragments, and language is ultimately like a lossy abstraction of the real world. I think, you know, everyone would would agree with that. It's not new to say, hey, let's take human action data in the world. We have a lot of, we have a lot of world data and environment data of humans. We have plenty of recordings.

• 16:07Speaker 00

  I mean, any any recording of a human in any environment doing anything is a great kind of capture of the of the results or the environmental response of our innate actions and intent. But we don't often have this action and intent data, not in a very kind of precise, discrete way. How would we go and capture everyone's actions that led to the stuff that we see in the world? This is like a little bit, almost like kind of behavioral psychology. But you would have to plug everyone into a brain-computer interface and kind of like read the signals before they manifest in the world and then measure the response of the world. We're not there, and we won't be for a while.

• 16:47Speaker 00

  And so ironically, the best proxy we have for tightly coupled human actions in worlds is the sum of humans playing video games, you know, across the many thousand games. Games have other interesting features too. They they're very discrete, they're very neatly measurable, their states are very clear, the goals are typically very clear, the feedback cycles are short, and you can do things that are quote unquote, out of distribution. Playing Microsoft Flight Simulator is very different from flying a plane.

• 17:27Speaker 00

  You probably wouldn't try doing a looping in a Boeing 747, but we can figure out if it's possible or not in Microsoft Flight Simulator. And it's a very realistic and complex experience. And so ironically, and this is the big insight that led to General Intuition, the the sum of of coupled action and environment data was accumulated through the the preceding company and platform Metal, ultimately led to what is, as far as we are concerned, and kind of tested this hypothesis, even with big frontier labs, including OpenAI and DeepMind, this is the best dataset for world and action modeling. And so we're taking this.

• 18:10Speaker 00

  Not to then build games with it or build media experiences with it, which you can do. If you have action and world data, you can do two things. You can generate a world if the user gives you new actions. These are like the world models or kind of like playable movies. So like, you know, if people have seen a Deep Mind's genie, for example, was, I think, eye opening for many people. You see a screen and you, it's almost like a playable video. You press forward and it gets rendered as you go. So you generate a world given an action. However, what you can also do, and now we're talking about servicing a 200 billion TAM or whatever, kind of like games and film is combined, let's call it like 300 billion.

• 18:49Speaker 00

  However, when you have this data set, you can also do, you can also generate actions given worlds. So, so you can, for any type of embodiment, whether digital or real, for, you know, bipedal or quadrupeds or whatever, say, hey, tell me what you are, screen me where you are and tell me your goal, and I will give you back the optimal action sequence to accomplish this goal. And now then the question is, what is the TAM of problem solving and goal seeking in space and time? That is literally, that is what we do as, as humans, right?

• 19:30Auren Hoffman?

  No, so why, there are certain folks in like the gaming industry that seem like very AI forward and certain folks in the gaming industry that seem like quite hostile to AI. And I would think like, just based on the people I know, everyone would be pretty AI forward. Like, why is there this hostility?

• 19:48Speaker 00

  Yeah, I think your, your sample size is certainly skewed in a, in a, in a certain direction. But you're right, I find it, and I've said this before, and I've literally been quoted in, in headlines on this. I find it shocking and sad how poorly AI is received in the gaming industries. Specifically, I would say by game developers, less so by players, actually. And certainly at this point, not by the executives steering these companies, who are also obviously all aware that this is the future and are-

• 20:21Auren Hoffman?

  Just like, I'm worried about my job type of thing? Or is it more, is it more visceral or it's like a craft?

• 20:27Speaker 00

  I would say, and it's particular against what we just discussed, this backdrop of gaming always adopting and actually pushing and creating new technology. It's, it's quite, yeah, ironic, I think, that now there's this resistance. But I think it's the following, gaming has had a rough three, four last years. And by and large, I'm oversimplifying a little bit, but by and large, COVID was a huge boon for, for gaming and any kind of inside digital activities. There was a lot of over investing, there was a lot of over staffing, budgets ballooned, not often followed with the blockbuster successes needed to kind of warrant those investments.

• 21:09Speaker 00

  And so we've been, we're coming on four years now, I think, of record layoffs in the gaming industry. So that's an important backdrop. And, and also, you know, this is an industry that takes real pride in their creative tasks. And I think other tools maybe felt more like they were enabling you, but not infringing on your taste or, or kind of secret sauce. And this one feels different. And I think when you're in an environment where there's a lot of anxiety, there is, it's always easier to point to external factors than to maybe, maybe look, look internally. I think it's a very natural reaction.

• 21:52Speaker 00

  The other thing that's also contributing to this in gaming is unlike, because you would, you, you saw the same thing in Hollywood and, and movies. And I think actually it's turned around there. And there's no longer a debate in Hollywood and movies whether you should use AI. It's like, they all kind of have to. I mean, you can see also like how the industry is evolving, evolving here in Hollywood and, and you know, how many movies are actually still produced in Hollywood. So they get it, but they also have things to point to. You can look at AI video now and it's really damn good. And I think three years ago, everyone was doing the same. They're like, look at Will Smith eating spaghetti, if you remember those videos. It was a hot mess. And now it's beautiful in HD and like high fidelity. And you couldn't distinguish it from reality in certain cases.

• 22:38Speaker 00

  The gaming industry, interactive is harder, right? We figured everything else out. We did like text, image, audio, video, it's still all linear. Interactive is really, really, really rough because you have to really get it right. Because if you mess up even just 1% with every interaction, everything degrades to just slop and zero.

• 22:57Auren Hoffman?

  Yep.

• 22:57Speaker 00

  So it is significantly harder, but because of-

• 23:02Auren Hoffman?

  But we're gonna get there, for sure.

• 23:04Speaker 00

  We're gonna get there, but it's also easy right now, I think, for people to point to like AI games and say, oh, look at and I'm like, guys, just, just look at the conversation we had three years ago on, on, or two years ago on videos. And so, yes, we're gonna get there. The sad irony is that people are revolting and raising their pitchforks in fear of their jobs and in wanting to keep their jobs yet. And I've said this many times too, the only, the only certain way to lose your job probably, or, or increase the likelihood vastly over the next few years is to do exactly that and not experiment and adopt these new technologies.

• 23:42Auren Hoffman?

  Not, not try to use it.

• 23:43Speaker 00

  It will be a reality. AI will significantly change how games are built, not just how they are built, but even it will create previously impossible experiences that you can't even build without AI. That will become a new standard, it will become a new like player and user requirement and need that you can't even service if, if you're not an organization that is built AI native. And that transition takes time. I'm also, I'm not envying incumbents. It's very easy for me as an early stage investor.

• 24:14Auren Hoffman?

  Right.

• 24:14Speaker 00

  I'm just gonna throw my money at some cool that with high likelihood won't work. But if it does, it changes everything, right? That, that's like world models and action models and like AI NPCs or whatever. Very easy for me to say this and do this. I also don't envy the big operators that need to kind of like segue into a new reality over time and tech fully, working within the constraints of, of today, but, but being ready for quite different constraints in just a few years. So it's, this is the kind of stuff I work on with OpenAI and McKinsey, for example, which is helping the incumbents with this transition in a way that's, you know, reasonable and meaningful and practical and, and, and financially responsible.

• 24:58Speaker 00

  And then the work where I spend my 80%, like where I'm, me, me as the startup-

• 25:03Auren Hoffman?

  Yeah, being the attacker.

• 25:04Speaker 00

  Investor and founder supporter, will go all in just on the, the absolutely crazy stuff.

• 25:08Auren Hoffman?

  Perhaps like one of the most successful gaming companies, so not everyone thinks of them as a gaming company, is AppLovin. Why have they been so successful?

• 25:16Speaker 00

  AppLovin is actually one of the few scaled examples. I mean, they build a whole ad network, right? And that, that's a, that's a tough thing to do technologically. Yeah, you have to, you have to get the, the supply right. But yeah, I mean, you can call them a gaming company or gaming adjacent company. Adam is a friend, he's a, he's a smart guy. It was a long haul to get there. And, and you know, that really broke out. The building the ad network, as far as I'm concerned, wasn't always the strategy. And so, but yeah, I think a good example of the, the insight that

• 25:58Speaker 00

  it, it's always a good idea to seek novel, novel things and maybe, maybe build things that others aren't building and try and reason from first principles. Because I'm sure there were a lot of people that told them you can't just build an, an ad network. There's, there's already Google and Meta and they're doing quite fine.

• 26:18Auren Hoffman?

  What do you think other businesses can learn from this kind of like free to play gaming model?

• 26:24Speaker 00

  Free to play hasn't been necessarily like a, you know, a smooth ride and a fairy tale of, of mostly successes. I think it's, it's very, very hard to build free to play because you have to assume a certain scale to make it work through, through microtransactions. I think what's there to learn from games like Roblox and Fortnite specifically is that they have transcended to, to our earlier point, this notion of becoming games where, you know, I think many people who play these wouldn't necessarily even call them gamers today. It's just that they are social hangout spaces and the kind of like third spaces.

• 27:08Speaker 00

  I think what they really mastered is your social graph is there. And then, by the way, that's also a big, it's very difficult right now for new games and new platforms to emerge because you really have to crack through this social graph and attention ceiling to even have a shot at, at kind of building a new social graph in, in your universe and, and your experience. So they're becoming sticky. We, we see a lot of consolidation right now, especially around Roblox, which is something that Tim Sweeney at Epic has also called out. In, in a way, these are becoming, you know, pretty walled gardens, scaled walled gardens that, that make innovation in the industry somewhat harder.

• 27:52Auren Hoffman?

  When you think of these companies, the Minecrafts, the Roblox, the Fortnights, like, why have these communities been so successful and other ones, which maybe also like, looked amazing, seemed really cool, somehow they didn't hit? Like, what did they do differently? What can we learn from them?

• 28:14Speaker 00

  One thing I kind of love to mention when it comes to game design or experience design is you want to make sure that the game allows for players to be fun and makes the players more fun, rather than actually the game and the content being the fun. You'll inevitably end up in some kind of, you know, content treadmill if why people are playing this game is because of the IP and the lore and the narrative. And you look at kind of like the ones that break out the most. I mean, again, to come back to like these sandboxy

• 28:53Speaker 00

  experiences like Roblox and Minecraft certainly, but even Fortnite is kind of like this smorgasbord of where people can just go wild.

• 29:03Auren Hoffman?

  They just have a good time.

• 29:04Speaker 00

  They have all these tools for self-expression. Yeah, self-expression, social role play, those are huge. Like even GTA V, I mean, GTA is a very popular game, but you know, the most popular mode right now for GTA V, which is now many years old, is a mod that they acquired from 5M that enabled GTA to be like a multiplayer social role play experience and people just having a blast, like being a chicken on the road to crash someone else's Ferrari and then that lands on TikTok and you know, there's like proximity voice chat and all this kind of stuff. So.

• 29:41Auren Hoffman?

  But you kind of need both, right? You need like, you need like the goal of the game, because I remember like, this is like 20 plus years ago, like playing, you know, being in Second Life, if you remember Second Life, and it was like, I don't know, it was kind of boring. Like, I tried a few times and like, seemed cool, but there was like, I wasn't sure what I was supposed to do. There was no like goal of it. It is kind of important to have both in the game, right?

• 30:03Speaker 00

  Yeah, I mean, this was like, this was like the empty metaverse before the bigger empty metaverse. Yeah, you, like, games and online experience must be vessels to kind of allow players to be fun or engaging. Yeah, you're probably right. You want to make sure you feed it with content. There needs to be a reason to come, but then also it will only go mega scale because of the players and the ingenuity of the players. It will never go mega scale because you infinitely build new, fresh content as a publisher.

• 30:45Auren Hoffman?

  There are people who play a lot of games. It could be video games, board games, card games, like that kind of, there's those types of people. And then there's all these other people who don't do that. And so some people just like gravitate to playing games in some sort of way and some people don't. What is, is there like a personality trait? And when you're working with people, it seems like you're preferring more the gaming people or maybe not?

• 31:11Speaker 00

  Yeah, I think on player motivations, at least as it comes to video games, there are different player motivation types. And when you design your game, you obviously want to solve around that. There are people who strive for mastery, right? They really care. Like, that was like my whole childhood was that. Like, the thing I cared the most was trying to be the best in the world and what I was doing. And I had a blast alongside it and I loved the game. But what, that was the thing that kept me coming back every day. There are, there are people who like the social element of it. There are people who are the explorer type or like collecting achievements and kind of completeness, if

• 31:51Speaker 00

  you think about Pokemon Go, for example. So there is no one player motivation.

• 31:57Auren Hoffman?

  And some people want more novelty. Like, they're just like, like, I know people who play lots of board games, but they get like, they get bored pretty quickly of like a board game and they're always want to move to like the next new board game or something like that. And then I know people who just like, are just, they just play Settlers of Catan every night, kind of thing, you know? And they want to really get a one thing.

• 32:16Speaker 00

  I've played literally like one game so far this year, which is Rocket League. And that's now, I don't know, eight years old. So, yeah, so there's no, no one fits at all motivation. In terms of founders I work with, I mean, I've obviously been focused on the gaming and interactive media industry, at least for the last 10 years. Some of my best investments have been in Frontier and Pure Play AI. And now in my own capacity, I work with founders from a range of industries. The one thing for me that all of them have in common or where I gravitate to is I usually like to work with people who are really pursuing

• 32:57Speaker 00

  Adash's North Stars, or let's call it like Global Optima. I'm not really interested in, in something that doesn't scream N of one company, or at least kind of like is in that vein. So like someone making another game, that's not interesting by definition. Someone building another like enterprise software of this sort or that sort. And enterprise software in general is a domain where I don't spend much time. Even with AI innovations, I want things that no one else, even including the large labs are doing. General intuition and world models and action models at the time is a great example. Like, this is genuinely

• 33:39Speaker 00

  an advancement of even the catalog of foundational AI technologies. Another good example is recursive, a team that's saying like, hey, you know, people realize that these models don't use enough space and time data. That's general intuition. And Descartes were trying to like improve these models based on how human learning really unfolds. Another way in which human learning is today quite advanced compared to what we're building for the machines is continual learning and this idea of recursive self-improvement. Right now, the models are trained. And of course, like, you know, the big labs, they use their own automated coding

• 34:21Speaker 00

  solutions like Codex or Claude Code to then generate the code for the next iteration. But there's so many things in the process where this isn't really a recursive or continual process. And even the model itself doesn't learn new things once it's trained, right? So it can scrape the web and it can digest that information, but it doesn't feed back into the model and the weights and the parameters and all this kind of stuff.

• 34:48Auren Hoffman?

  I assume that's coming, right? Like, we should assume there's some sort of recursive business.

• 34:52Speaker 00

  You know, like, I want someone to say like, why is no one working on that? And we're quite equipped to work on that. And, or another great example is AI, new AI inference chip and cluster company called Etched. Two, two now 24-year-olds who at age 21 had the foresight three years ago that AI would probably be huge, that there would probably be an AI inference crunch and literally build a better chip for AI inference. Then Nvidia just came out of stealth with a billion in orders, can't make that up, running a team of 400 people, including like senior executives from Nvidia, Intel, Qualcomm, hired the former

• 35:37Speaker 00

  CTO of Cypress Semiconductor, legendary semiconductor company, as their CTO. And they're shipping their racks this summer. And so this is the kind of stuff I like, you know? Global Optima, reasoning from first principles, because I can tell you in the early days, and I wasn't an investor from the get-go, so I don't want to overrepresent here. But, I mean, they had to eat glass for like, two years straight. And everyone, including industry executives, told them this couldn't be done. And now they did it. I mean, it's there and it's real, right? And I think this is, this is the kind of stuff where like, 50, 100 billion

• 36:19Speaker 00

  dollar plus companies are really born. And I think, yeah, the chances of success are always small, but life's too short not to work on the things that if they work out, they can be like, you know, they should be industry changing. They shouldn't just be industry contributing.

• 36:37Auren Hoffman?

  What advice would you give to the average 18-year-old and stuff? Like, how should they be thinking about things?

• 36:44Speaker 00

  Well, obviously, like, play a lot of video games, because this is the, this is the cradle of human and machine intelligence now. Record everything. I mean, I'm really questioning at this point the traditional, you know, college education, kind of grad school model. And I was, I went through my own interesting path where I didn't actually go to a proper college, because I was afraid to go. When I graduated high school, I spent all this time playing video games and still did really well in school. My parents hadn't gone to college. They actually hadn't, they dropped out of high school. My brother dropped

• 37:27Speaker 00

  out of high school. And so I literally didn't have anyone in my closer family with a college background. And I was always irrationally afraid to go. We even got a scholarship from my school and my mom said, it's probably not something we can afford. We thought it's something we have to pay for. We didn't even understand it's something that gives you money. And so my, my first years, like, I think half through my twenties, I was on a completely different path. And I did this vocational training and, you know, later on clicked for me and ultimately applied to Stanford, technically without an undergraduate degree and an essay about Diablo 2. And from there, the resume looks quite different,

• 38:09Speaker 00

  right? Like, you know, like Stanford and Goldman and Lightspeed and a bunch of accolades and, you know, also, also like kind of part-time study experiences, some of the finest academic institutions. But when I was, when I was 18, I think my only foray into true excellence on a global scale had been the competitive Diablo 2, kind of formative years, like seven, eight years of basically playing at 10 hours a day, trying to be the best in the world. So I think there are many paths, to answer your question, I think there are many paths to excellence. I think decreasingly it will be, for someone who is now 18 through

• 38:54Speaker 00

  the traditional schooling system.

• 38:57Speaker 00

  I think the coolest thing to do from where I sit, and I'm super bubble biased, I'll probably grab two smart, capable friends and put it in an application for Y C. Try and come to the U S if you're not already there. That's definitely an advice I have. I think this is where the music plays here and it will for a long time and the music's only getting louder. Get a lot of commentary sometimes from a German friends who are like, you know, checking in with me if I'm okay in this mess, alleged mess that we find ourselves in here and I only chuckle and, you know, my response is don't worry about me.

• 39:42Speaker 00

  But, but I'm quite worried for you.

• 39:44Auren Hoffman?

  It seems like, and not just Germany, but a lot of Europe doesn't seem to be innovating at the pace that one would expect. There's all these super intelligent, amazing people there. Like, what's your kind of theory about it? And, and why would you suggest like an ambitious European move to the U S?

• 40:05Speaker 00

  The German malaise is actually, it's cultural. It's, as you rightfully point out, it's definitely not a shortage of talent. There isn't the capital available to fund these audacious projects. But I think that's a function of something even deeper, which is like the mindset and the cultural stance toward technology and risk taking. I think this is really like the foundational difference. And this, this, America is a country literally started by people who took, like, I mean, they're kind of, you know, founders, right? In the, in the true sense of the world and like went on a ship, sailed across the sea.

• 40:49Auren Hoffman?

  We call them the founding founders for a reason.

• 40:51Speaker 00

  That's the DNA. Yeah, that's the DNA and, and it matters even, even 250 years later. It's there and it's, it's, it's self-selects. I came over the, the ocean with nothing in my pockets. Now, obviously it's a very different and much more comfortable story than what, what happened like 250 years ago. But I didn't know anyone here. I had like $10,000 in my bank account, which is not, you know, a whole lot at the time. And I tried to figure it out and moved, moved to New York and, and, and just became a citizen in February. And so there's a self-selection. But there's, but going to Germany, okay. So for example, and by the way, I think Germany specifically, my theory, and you see some of this in Japan too.

• 41:37Speaker 00

  This is a country that, that, twice, big time. And I think there's real, real remnants of this like post-World War II mentality where like, all right, you rebuild yourself now with discipline and like, you know, you draw within the lines, engineering prowess, punctuality, like all the like kind of proper stuff. And you're just like, out execute and out operate and, and no more nonsense. Just like good, good, hard work. You know, and you see this reflected in, in, in the engineering culture and kind of other cultural traits. But part of that and the downside of this is also the not trying crazy stuff. Like if you use the word vision, for example, I was talking to my mom and I told her about a project here.

• 42:22Speaker 00

  I said, my vision for this, and she starts laughing and I was like, what's going on? She's like, if you use the word vision in Germany, you typically kind of like, you know, you see a doctor. So to have it, have it cured. If you're, if you're starting a company, it means you didn't get a job.

• 42:39Auren Hoffman?

  Yep.

• 42:40Speaker 00

  And even in the language, we say venture capital. Sounds cool, you know? Take my hand to the promised land, like, let's see where this thing goes. It's like adventure capital. Germany, we call it risiko kapital. So before, before you get to capital, before you get to capital, you already cover the fact that it's a very risky endeavor and the linguistic focus is on the downside. And in America, the linguistic focus on the upside. And I think this stuff matters.

• 43:08Auren Hoffman?

  Interesting.

• 43:08Speaker 00

  And, and so, you know, it then becomes this thing of like, well, this will most likely fail. And you know what? I know, like, we know, you know? Lightspeed knows, like, I mean, we have, we have more data on this than, than.

• 43:24Auren Hoffman?

  Right, we know it's gonna most likely fail.

• 43:26Speaker 00

  Most institutions in the world, like, yeah, we can confidently say most of these fail.

• 43:29Auren Hoffman?

  It's the famous Jeff Bezos, he gave himself like a 10% chance of succeeding or something or whatever.

• 43:35Speaker 00

  Yeah, in terms of what ultimately matters for the fund, it's less than 10% of companies, certainly.

• 43:41Speaker 00

  And so this is just a wrong way of looking at this and we're, and technologic, technology compounds exponentially. And by the way, also another, another pet peeve of mine, like in Germany, like the retirement system, like no one owns stocks. The, the retirement system is not invested in equities. The, and, and on a personal level, people don't own, most people, I mean, we'll have to check, fact check me here, but most people won't touch equities, the vast majority.

• 44:11Auren Hoffman?

  Well, maybe there's a good, I mean, you don't want to be, if you're in the German market, the last 30 years, it has been terrible.

• 44:17Speaker 00

  At all, at all, like U S equities, anything.

• 44:19Auren Hoffman?

  Yeah, but like, I mean, usually, like, usually you invest where you live. And so if you were in the German stock market, like the entire German stock market is like, I don't know, 50% of Nvidia or something.

• 44:30Speaker 00

  You go to the bank, you go to the bank, you ask them how to invest your money and they say, let's just put it in your, your savings account. Well, you, you get your hard earned like 0.2% every year. And then by the way, we'll, we'll, in the meantime, use it to make real returns.

• 44:44Auren Hoffman?

  Outside of S A P, you can't even like, it's like hard to even think of like, and that, that was like a 50 year old, that's a 50 year old company. Now it's hard to even think of like a super successful German tech company. That's, I'm sure there are some, but there, there's not a lot, yeah.

• 44:57Speaker 00

  Even the German car makers kind of slept through the electromobility transition for the longest time.

• 45:03Auren Hoffman?

  I personally think German cars are, I'm not against Germany, but I personally think their, their German cars are terrible now. Like that they, they, 20 years ago, they were like the highest. I'm just saying, it's true. Like you drive a BMW, you drive a Porsche, you drive a Mercedes today. And the, the, the relative difference between them and all the other cars, it used, like 20 years ago, was like really big. And it was like the manufacturing was better, the cars are better. And then today, in many cases, there, it's the inferior vehicle. It's not as good as an American car, it's not as good as a Japanese car, it's not as good as a Chinese car in many, many, many different dimensions that's out there. So even there, I feel like it's like, it's, they kind of lost the edge.

• 45:46Auren Hoffman?

  Obviously still amazing cars, but just kind of lost that edge that they, they once had there. I don't know why that is.

• 45:53Speaker 00

  The tricky thing right now is that missing the future and not adequately investing and not adequately taking risks into a possible technological future has never been as costly

• 46:09Speaker 00

  than today. And also today is the cheapest day ever, right? Because this stuff moves exponentially and everything else moves linearly, getting it wrong will be worse and worse and worse. And getting it wrong right now, from my perspective, and the jury is in doubt on this also. But I think that the mistake is under investing, under investing, not just financially.

• 46:35Auren Hoffman?

  It's okay to get it wrong.

• 46:37Speaker 00

  Culturally, culturally under investing.

• 46:38Auren Hoffman?

  You have to try a few different things and you're going to get some things wrong, right? It's a, you, you just have to assume you're going to get a lot of things wrong. But not doing anything at all guarantees you'll get a rug.

• 46:49Speaker 00

  There's so few things that move the needle. And then you basically, I mean, there's so, in the grand scheme of things, there's so few companies and technologies and people who really push the world forward. And by not investing in these crazy projects, you're just basically burying a nation from having exposure to, to, to a chance of, of having one of these people or technologies or, or companies.

• 47:19Auren Hoffman?

  Now, it seems like somehow, it seems like if you just think of like Sweden, Estonia, like it seems like there is a lot of tech innovation happening in some parts of Europe. Why, why have they been so successful?

• 47:32Speaker 00

  Yeah, I, I, again, I think it's, I think there is a difference in mindset. I think the German mindset is specifically risk averse. And I do think it comes back to kind of losing to world wars, right? I'm not, I'm not an anthropologist, but I, it just strikes me as, as playing a role.

• 47:48Auren Hoffman?

  But it doesn't seem like there's that much more innovation happening in France than there is in Germany or something, or that much more innovation happening in Belgium or, or, you know.

• 47:56Speaker 00

  I think France, I think France is ahead of Germany, certainly.

• 47:59Auren Hoffman?

  Sure, sure. France is definitely ahead of Germany, I a hundred percent agree with you.

• 48:03Speaker 00

  Israel. So, so there are these European, I would say, innovation clusters.

• 48:09Auren Hoffman?

  There's something about like attracting ambition somehow. Like if you're an ambitious French person or ambitious German, there's a very high likelihood you move to the U S. There's almost no ambitious American who moves to Germany or France.

• 48:26Speaker 00

  Yeah, I think that's true.

• 48:27Auren Hoffman?

  Going the other way. So you kind of know by the way people are moving, where the ambition, it's almost like you're going to, you move to France to like, have a good life and retire or something, but you're not, you're not, and have some great croissants. But you're not moving to like change the world.

• 48:42Speaker 00

  They do have better croissants.

• 48:44Auren Hoffman?

  Yeah, that's for sure. Yeah, it's beautiful and wonderful and great to visit.

• 48:50Auren Hoffman?

  What, what, how else are you using A I in your personal life? Like what else are you doing to like, I don't know, just make your life better right now?

• 48:58Speaker 00

  What personal life?

• 49:00Auren Hoffman?

  You're married, right? You got, you know, you, you, you got other types of things you're doing. You're, I don't know, you're, what else are you doing to enhance, whether it's your own personal productivity? Your, your, your, I don't know, any type of life, you know, et cetera.

• 49:13Speaker 00

  Yeah. The real trick is to go into your spouse's master prompt and, and, and put a general statement for their model use that, that the husband or the wife, in whatever case, is always right. So.

• 49:28Auren Hoffman?

  Okay. So you like, you surreptitiously go in there and say, oh, I'm having a, I'm having an argument with my husband. It's like, hey, like, take, take your husband's side all this thing. I like it.

• 49:38Speaker 00

  Yeah. This is like the, the, the highest valued, most practical takeaway for the listeners on, on, on this.

• 49:47Speaker 00

  Look, I mean, the truth is, right now, I probably spend like a hundred to a hundred twenty hours on, on all this kind of stuff. Like, I think for me, like, um, uh, like work and personal life, like, really blend together. But it's also part of that is like, I really [bleep] love the stuff I work at. I now have, um, I have a hundred percent freedom to choose my, my, my projects, like, to point it out with what I set up in April. I, I have no employees. I, I don't even, I don't have an EA or, or anything. I really try and do everything myself. I file my own FINRA filings. I do my own taxes, actually, also.

• 50:28Auren Hoffman?

  Why? Why do you do your own taxes and, and do your own FINRA filings?

• 50:33Speaker 00

  I just think I do it better because I just know myself better. And like, I, I feel like, yeah, I can answer a ton of questions someone else might, might ask me. But as long as I understand the system fully, which doesn't take as much work as everyone thinks, then.

• 50:50Auren Hoffman?

  Walk me, because I, I imagine you have an extremely complicated tax situation. I would never even like think of, of, of filing my own taxes. Like, walk me through, like, you know, walk me through it. Like, how, how does that even work? Like, I don't even know how to file my own taxes.

• 51:07Speaker 00

  I'm still, I'm still like, I'm still on like TurboTax. I'm just literally maxing out what you could do so far. This might actually change. It might change this year, uh, to be honest. But like, um, you know, I, I, I really like the, the full freedom of the, the current endeavor. And also, um, you know, I don't, I, I invest my own capital exclusively. So I'm not running a fund in, in the sense that I'm pooling other people's capital. I have no LPs.

• 51:34Auren Hoffman?

  You are your own LP, essentially.

• 51:36Speaker 00

  Yeah. I, I have no customers. And in a sense, really, the only customers I have are the founders I, I, I work with, right? Which is your typical VC answer. But if you're being honest, if you're running a, an VC firm, your customers are your LPs. Your customers are not your founders, right? And if you don't have LPs, you don't really have customers. And so, um, I work really hard. I try and be available like all the time. I, I think my average response time to people is like over email or WhatsApp is like, you know, about a minute or, or so. And, and I like it that way. And I kind of expect the same thing.

• 52:08Auren Hoffman?

  I would say the more successful the person is that I email or WhatsApp or whatever, I would say the faster the response time is.

• 52:18Speaker 00

  Yeah. I think this is a strong signal also for founders. Like, if someone takes, uh, an hour or two hours to respond, always, I think it's a huge, uh, it's a huge turn off.

• 52:28Auren Hoffman?

  Like Sam Altman, he, he, he emails back within an hour. Like, it's unbelievable. Like, the guy is super busy. Like, why?

• 52:35Speaker 00

  Yeah, or like send a text message. Yeah, a text message, say, sorry, I'm so busy. And I'm like, dude, I, I know.

• 52:43Auren Hoffman?

  I mean, like, how do these, I don't even understand how these people do it.

• 52:47Speaker 00

  Extremely generous with his time, uh, by the way, right?

• 52:51Auren Hoffman?

  He's incredible. Yeah. Yeah. When I was in college, I, I emailed Steve Jobs and I was like a college student. And I got an email, you know, I emailed him back, you know, I emailed him in like 2:00 AM when I was in like the lab. And I got, you know, I checked my email in the morning. He had already emailed me back. Like, it was, I didn't even know how, why he'd even reply to a college student. Like, it's just crazy that these people do this.

• 53:12Speaker 00

  I think some people are just kind of wired differently. And at least I really enjoy self-selecting and hanging out with these people. A lot of the founders I work with are in, uh, their twenties even and, and, or early thirties. And I get a lot of energy from that. Like, it makes me work.

• 53:33Auren Hoffman?

  You just turned forty, right? So now you're like, you know, you're like an old guy around all these people.

• 53:38Speaker 00

  That's right. Yeah. Uh, you know, that's okay. Um, I'm trying to keep up, but I really, I really self-select for, um, energy. And I think it's important. I mean, like, how are you gonna do crazy things if you are not hyper energetic? How are you gonna build like a 500-person team out of rock stars that are all [bleep] energy bundles? Like, I mean, you gotta.

• 54:01Auren Hoffman?

  How do you see the, when you're, when you're talking to people, how do you like see the energy? Is it like you see just like the fifty-two cans of Diet Coke in the background?

• 54:11Speaker 00

  Hopefully not. I mean, we need it to be sustainable, right? I would say the, the best founders, um, what are some traits that I, I really like, maybe also beyond this?

• 54:25Speaker 00

  I would say they're all, um, they all have typically unique insights that they're pursuing for, for some, for some reason, like learned probably through prior experiences, that, um, they have this hypothesis that is original. And, and they're kind of, they're, they're like, uh, obsessed with, with, uh, proving the world that this works. And it's kind of like this, you know, unique insight that if, if it's really true, it, it can have profound impact or it will have industry-changing impact. And, and I think that's, you can look at, I mean, pretty much all the companies I invest in,

• 55:05Speaker 00

  they're, they're built on a thesis that is original and, um, and if right, quite consequential.

• 55:14Auren Hoffman?

  Yeah.

• 55:14Speaker 00

  I really like that. I mean, this, this is maybe a terrible thing to say on the, on a podcast, but I think it's, it's highly unlikely that any of these things, uh, these, these kind of projects are successfully built by people over, frankly, like, the age of like thirty-five at founding, you know, oftentimes below thirty at, at founding.

• 55:34Auren Hoffman?

  Just because like, it takes a, somebody who's just thinking differently. And once you're a certain age, it's just hard to think in a very different way.

• 55:45Speaker 00

  Experience simply doesn't matter as, as much as, as people think. And it can be a detractor too. And by the way, experience is quite easy to hire for. What you do is you just get a few adults in the room.

• 55:57Auren Hoffman?

  By the way, you can even rent them. You don't even need to, you don't need to hire them. You can, you can, because, because experienced people are happy to be your advisors or be your consultants, right?

• 56:06Speaker 00

  Yeah. You need like a judgment caller or an intuition here or there. And then you can still choose to ignore it if you have a strong argument from first principles, reasoning from first principles. Again, so, so unique insight that if, if true is profound. I want people who pursue global optimal. What that means is like, I don't want them to look left or right. And it's like, it's like anything that's like, we want to be the Uber of this. Like, you know, like the Airbnb, that list is just like, it kind of actually is a bit of a turn off. Also, by the way, every time I see like, especially in gaming, like people like to do this, like, we're a team of veterans that like, I'm like, oh, man, like, you know, it's just like, you know, I mean, my, my, my daughter likes dinosaurs too. You know, it's like, I think it's a huge turn off.

• 56:47Speaker 00

  I'd rather have you have no experience and just be absolutely like, kind of artistically smart, uh, and, and audacious.

• 56:56Speaker 00

  But yeah, I, I, so, so pursuing this global optimal, I think first principles reasoning is super important. I mean, the person that does it the best, I think, is Elon. And, and, and I mean, he's literally built so many things that people said weren't possible in a way where the thesis was articulated and then just executed. And sometimes over ten or fifteen years, uh, you know, um, when I was at, when I was at Goldman, um, SpaceX was actually one of my early clients. Ironically, the, the two things no one wanted to work at, uh, at Goldman as a banker in, uh, 2016, seventeen was gaming, which led me to start the, the gaming practice. But the other two things that no one wanted to work on were space and AI.

• 57:38Speaker 00

  Okay? So, so, so, so Palantir, I grabbed, uh, together, actually, with, uh, with senior leadership there. But SpaceX, it was really hard for me to even get like NMD or VP to the SpaceX meetings, including for meetings that were bake-offs with banks, uh, to help them with financings. I remember distinctly one situation where literally the Goldman team was me and the summer intern. And I was a senior associate at the time. And that was the Goldman setup. And this was, this was at a time where this was already like a sixteen, seventeen billion dollar company. And now, of course, ten years later, they do the IPO and like, you know, I see, I see them post like, our longstanding relationship with SpaceX.

• 58:19Speaker 00

  And like, when I'm thinking to myself, man, just ten years ago, I, I couldn't even get anyone over the age of like thirty-five to come with me to this meeting. But yeah.

• 58:32Speaker 00

  You know, but, but, but back then we, we kind of wrote out for, for debt financing, actually, a hundred twenty page memo of SpaceX and the SpaceX plan. And, and this was a time where rockets were basically exploding half of the time and, and returning maybe thirty percent of the time. And, um, you know, there was no satellite constellation, there was no Starlink, there was an idea of Starship, which, uh, back then was called BFR, Big Rocket. But it was all written down as kind of like the successive plan of taking payloads to space initially, then because you can do that cheaper than anyone else, launching a satellite

• 59:15Speaker 00

  constellation to become the world's largest telco provider. I actually don't, I don't think they're the world's largest right now, but like it's certainly, certainly commercially very viable. And to help fund the real thing, which is, and I remember this distinctly, is, uh, putting people on Mars. And Elon corrected me and said, no, no, yes, on Mars, but then also you need to leave the solar system because a lot of the things, and then the reasons why we're doing this is to really kind of like the continuity of the, the, the human species, right? In light of extraterrestrial adverse events, many of them, you will still have on Mars, uh, just like on Earth, like solar flares or things that affect the solar system. So ultimately you'll also have to, to leave the solar system.

• 59:59Speaker 00

  So you went out of this way to like, the language was a multi-planetary species or something like that. And I read that as one, ten years later, it rhymes a lot, right? It's become a lot more sober. Now, now I think like in their, in their TAM chart, I think it was funny that like the biggest opportunity is like, after all was enterprise software or whatever, right? So, but, but man, I mean, it kind of did just unfold in, in that way. And I think this is the kind of stuff that, uh, this is the kind of stuff where you just knock it out of the park. And that's what venture capital is all about. I don't really care about like, no, the, the certainty of not losing my money. Like that's, that's trivial.

• 1:00:42Speaker 00

  I, I, I want enough reasonable probability shots on target to, to, to get an audaciously large outcome.

• 1:00:51Auren Hoffman?

  Our last question we ask all of our guests, what's conventional wisdom or advice do you think is generally bad advice?

• 1:00:57Speaker 00

  This is the part where, where I enter the podcast unprepared. Um, well, I, I, you know, a lot of people that, that are listening maybe are also founders. And the one thing that founders always care about is raising more money. And I think some, some wisdom for fundraising, maybe, and kind of like some pet peeves on, on, on my end, uh, I would not underestimate how much even, um, among the top firms, uh, social proof matters. And I think social proof is probably the most powerful thing to think about when you're running a, a fundraise. I raised over, actually over $2 billion this year with my portfolio companies, which is like a ridiculous amount, if you, if you, if you think about it.

• 1:01:42Speaker 00

  And I think maybe half of that was done without a pitch deck, right? You can play this the traditional way and you'd like create your pitch deck, do all these like data room and, and like diligence. And I, I know some founders who are like very diligent and very nice and answer all the questions, but like ultimately I think people, even, even, even, even the, the, the very sophisticated investors are still humans and kind of social creatures. And, and more so than urgency, because founders also sometimes like to play with urgency, like, hey, you know, like, or we got preempted or this and that. And that can, that can sometimes be a turn off, honestly.

• 1:02:23Speaker 00

  Like you have to be able to do the work, but I think the one thing that gets investors going more than absolutely anything else is social proof.

• 1:02:31Auren Hoffman?

  That's true for almost everything in life.

• 1:02:33Speaker 00

  So many things.

• 1:02:34Auren Hoffman?

  It's true for, you know, what, it's true for trends, it's true for, um, you know, hiring, it's true for, uh, dating in some ways, it's true for so much of life.

• 1:02:45Speaker 00

  Is, um, you know, when, when, like, if you, if you, if you look at like how to raise money, you'll find like, maybe, maybe like this, like, uh, there's this like famous Sequoia pitch deck, the order of like what you, what should your pitch deck have? And like, hey, ask your, ask your advisors for like warm intros. By the way, I read all my emails and I think most, most good investors, but coming back to our point, like Sam Altman, like these people, they actually look at everything that lands in, in, in their inbox. And, and I, I maintain my inbox religiously. Uh, so, so I see everything, I just respond to very few things.

• 1:03:21Auren Hoffman?

  Yeah, exactly.

• 1:03:22Speaker 00

  And, and so, you know, warm intro or not, slightly less interesting, but how to manufacture social proof? Um, are there specific angels that can support you in your, your, your journey? What can you say and how do you want to say it to someone? And what can you point to credibly, um, that, that evokes the sensation of proof from people that the people you're trying to raise money from would care about? Well, it doesn't necessarily have to be other investors, you know? It can be professors, this can be interesting angels, it can be, um, you know, interesting things you've done. So I would basically design my entire fundraiser around the idea and the notion of, of social proof first and foremost. That's the most important thing.

• 1:04:06Speaker 00

  Whether you have a pitch deck or not, you know, sometimes doesn't even matter that much.

• 1:04:12Auren Hoffman?

  All right, this has been amazing. I knew it'd be great. This has been incredible. Thank you, Mort, for joining us on Summation. I hope, uh, everyone like comes away from as like excited from this as I did, but I really appreciate you being on, uh, on the show.

• 1:04:26Speaker 00

  Thank you so much.

• 1:04:27Auren Hoffman?

  One more thing before we go. I read a blog called Summation. It's the same as this podcast. The blog is about non-obvious idea sharing on business, talent, data, longevity, and random contrarian takes. If you like the conversations on this show, you'll probably like the blog. It's free, new content comes out twice a month. You could subscribe at orin.substack.com. That's orin.substack.com.