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

0:00 Speaker 1 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. 0:18 Speaker 2 Hello, fellow Dana there. It's my guest today. My guest today is Moritz Baer Lentz. Mortz 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. 0:35 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 there you just raised another 320 million or Series A, which is pretty awesome. 0:51 He recently left Lightspeed Ventures where he was a partner and head of gaming. He also serves as a senior advisor to McKinsey Open AI, TPG, and does a whole bunch of other stuff. Morts, welcome to summation. 1:03 Speaker 1 Thank you. Thank you. 1:05 Speaker 2 All right, before we get into it, OK, 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 Mart. 1:15 Speaker 1 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 spent the majority of my time, I would call that about 80%, you know, investing my own capital now and then advising the founders that I work with quite closely. 1:35 I would say that most portfolio companies and most founders I invest in, I'm really in touch with daily. And it absent flows where like in certain months, I think with some portfolio companies, I've spent as much as 100 hours in, in a given month. 1:51 Now that typically is during fundraising or kind of like the PR and marketing push that comes after it. So, so they're certainly like peak times and down times. 2:02 Speaker 2 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? 2:13 Speaker 1 That's true every Wednesday, Yeah. I mean, just to just to finish the, the first question, the, the, the investing, the solo investing and advising founders specifically and startups, that's really 80% of my time. And then the other 20% are, are those senior advisor roles that you called out where between Open AI, McKinsey and TPGI help those three from specifically with their foray into gaming and interactive media. 2:38 And I think also increasingly really with the AI transformation of the gaming and and interactive media industry. So, so that's my jobs in a nutshell. AI efficiency, I would say I'm a power user of intelligence. 2:55 I'm not a power user of, of agentic use cases, at least for the time being. And we've spoken about that. I 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 as you and I also have discussed this, I'm really trying to record as much as possible. 3:19 My thesis is that once agents are good enough to, to genuinely and, 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. 3:38 Right now, I think the best thing to do is create as, 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. 3:54 It also includes recording conversations in, in my personal life, I, I use a range of tools and, and, and, you know, on, on Zoom, I really like granola. There's, there's a hardware solution for phones called plot. 4:10 And then, you know, there's, there's so much context in, in many other applications. So we talked about Google take out and, and how it's probably helpful to really have this massive, you know, markdown repository of, of digital activity. 4:27 Speaker 2 You're taking like Google take out, 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. 4:37 Speaker 1 Yeah, I think Obsidian is kind of like the yeah, the choice. And, and again, this is really right now it's a massive data repository. The the key will then obviously be connecting that to capable agents and, 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. 4:57 Speaker 2 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 you're not actually? 5:13 Are you recording like your browser use and things? 5:16 Speaker 1 No, but I mean, obviously there's browser history, right. So that's part of the the Google take out universe is, is, is your Chrome history and and I think you know, there'll be a, a great representation of your shopping behaviour and taste etcetera. 5:30 Speaker 2 And what about like emails? Are you connecting that into? 5:33 Speaker 1 All of them, yeah. All emails, all calendar events, all all physical movement on Google Maps. 5:39 Speaker 2 Everyone tells like this kind of graduation of OK, I'm willing to give this to the I'm willing to give this to AI and whatever, whatever it is, Claude or, or, or open AI or whatever it is. I'm not willing to give this other thing. Sounds like you're, you're a little bit more on the because you're willing to give like all your emails and stuff. 5:56 They're like, where do you, is there certain things? You're like, OK, 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? 6:07 Speaker 1 I mean, passwords live outside of the data that is that is flat as far as I'm concerned. I'm not engaging in any criminal activity. And so maybe others that are more hesitant have have a different answer to that question. 6:20 Speaker 2 OK, got it. So you're just like let's let's go all in because it's a great training set. Let's get as much training set as possible by. 6:27 Speaker 1 The way like for now, all of this lives locally, right? So, so part, part of my decision ultimately will also be when this is when this is ripe and ready for agentic solutions, where this goes and what of it goes into the agentic system? 6:42 Speaker 2 Now today, I assume you're already asking, you've got a big Obsidian file, you're already asking questions, all of that Obsidian file. 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? 6:56 Speaker 1 I I don't, I don't actually today. Oh, you don't? OK, No. OK. No, this is this is this, this lifts completely for the future. Time being, yeah. 7:04 Speaker 2 OK, I'll do something like I'll give me a restaurant recommendation based on all the, I've got 14 years of history restaurants, like based on what I'm doing, I'm going to be in Denver. Give me a restaurant, you know that, that type of thing. 7:15 Speaker 1 I mean, I found even for that kind of stuff, just just just using the plain tools, I think they have enough context just from from the sum of interactions with them that they give me quite reasonable answers. 7:24 Speaker 2 Yeah, OK, cool. Now you said the next, you know, billion dollar games might not look like games at all. Like what? What will they look like? 7:34 Speaker 1 Yeah. I mean, just to kind of take a step back, there's been this huge interest in VC funding and gaming kind of starting around 2019-2020 and then certainly exacerbated by the the the COVID and metaverse ambitions through 2020 and 21. 7:52 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, and experiences That's more akin to kind of movie financing. 8:08 I 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, 1020, fifty $100 billion plus outcome at at this point. And so the the question becomes where can games create scaled consumer experiences that maybe resemble social networks? 8:32 I think Roblox is a great example. I think Discord is a good example. So those were I think I mean is. 8:38 Speaker 2 Tick tock a game. I mean, in some ways is, you know, kind of, yeah. It seems like it's a game. 8:45 Speaker 1 Right, yeah, but you can. I think my 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 learned 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, you know, there's this narrative that gaming is a $200 billion industry and it's the largest media category and so on. 9:14 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 open AI 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 like the the scaled funds. 9:33 However, play and concepts of play are, are massively important to the to the human existence. And what we do with General Intuition, for example, is this is not that we're not building AI for games. We're actually using games to advance the state of AI across all sectors. 9:52 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. 10:18 You know, helped by obviously the breakthroughs of the Transformer and, and, 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, in ML, and I did my undergrad in, in ML and, and it was all about kind of reinforcement learning in space and time back then. 10:40 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? 10:59 Like world models is a term that's now quite popular and I would say has has entered the, the AI mainstream maybe about a year ago, but it's something we've been fascinated with and working on for, for for much longer than that. And and that laid the groundwork for general intuition, for example and other companies I'm involved with. 11:16 Speaker 2 Making so many like if you go like 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. OK, can we go beat a grandmaster in chess? 11:33 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. 11:46 Speaker 1 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, 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. 12:12 And games as a 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 GPU's are the most phenomenal example of that and and the story of NVIDIA. 12:30 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. 12:54 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? 13:13 We see this in animals too. Like why, why are we fascinated? Why by play? Like why, 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 tooth tiger comes around the corner because you're only trying it then for the first time, you're probably going to have a a rough day. 13:37 Speaker 2 It's even like the, you know, playing hide and seek when you're 2 or I'm going to tickle you type of things. Like even those types of games, Like do you learn a lot from those things? 13:45 Speaker 1 Cops messing around with each other, you know, again, like we see this in animals. We see this in in, in humans testing boundaries also, right? Like, I mean, and 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 that proclaim that really learning happens during play and, and, and not during work. 14:15 Work as a juxtaposition of kind of taking everything you learned in play. And we're, we're talking in abstract ways here, right? When I use these words, play it and work, it's a little abstract, but but work then being taking everything you learned during play and kind of quote UN quote, putting it on the road and executing and reaping rewards, but not really trying new things and learning new things. 14:37 And now fascinatingly, this dichotomy also is represented in, 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. 14:57 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. 15:08 Speaker 2 Why are sports so popular? Like it seems like that's just like the the play to the next level. 15:14 Speaker 1 Amateur sports and playing sports I think is enjoyable because it is a form of play. 15:19 Speaker 2 You go play tennis with your buddies, you play pick up soccer or, you know, whatever it might be, Yeah. 15:23 Speaker 1 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 I 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. 15:51 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. 16:07 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, and intent. But we don't often have this action and intent data, not in a very kind of precise, discreet way. 16:25 How would we go and, 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 behavioural psychology, but you would have to plug everyone into a brain computer interface and kind of like read the signals before they manifest in, in, in the world and then measure the response of the world. 16:44 We're not there and we won't be for a while. 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, the, the many thousand games. 17:03 Games have other interesting features too. They they're very discreet, they're very neatly measurable. The states are very clear. The goals are typically very clear. The feedback cycles are short and you can do things that are quote UN quote out of distribution. 17:22 Playing Microsoft Flight Simulator is very different from flying a plane. You probably wouldn't try doing a looping and a Boeing 747, but we can figure out if it's possible or not in in Microsoft Flight Simulator. And it's a very realistic and and complex experience. 17:39 And so ironically, and this is the big insight that led to general intuition, the the sum of 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 lapse and including open AI and DeepMind, this is the best data set for world and action modelling. 18:08 And so we're taking this 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 2 things. You can generate a world if the user gives you new actions. These are like the world models are kind of like playable movies or like you know, if people have seen a deep minds Genie for example, was I think eye opening for many people. 18:31 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, and film is combined, let's call it like 300 billion. 18:49 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. 19:19 And now then the question is, what is the term of problem solving and goal seeking in space and time? That is literally that is what we do as as humans, right? 19:30 Speaker 2 So what? No. So why there 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. 19:46 Like why is there this hostility? 19:48 Speaker 1 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, in headlines on this. I find it shocking and sad. 20:03 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 executive steering these companies who are also obviously all aware that this is the future and aren't. 20:21 Speaker 2 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? 20:27 Speaker 1 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. 20:43 Gaming has had a rough 34 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 overstaffing. 21:01 Budgets ballooned, not often followed with the blockbuster successes needed to kind of warrant those investments. And so we've been, we're coming on four years now, I think of record layoffs in the gaming industry. 21:16 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, or, or kind of secret sauce. 21:35 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. 21:52 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, 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 a is like they all kind of have to. 22:09 I mean, you can see also like how the industry is involving evolving here in Hollywood and, and you know how many movies are actually still produced in, 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 3 years ago everyone was doing the same. 22:26 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, the gaming industry, interactive is harder, right? We figured everything else out. 22:42 We did like text, image, audio, Video is 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 0. 22:57 So it is significantly harder, but because we're. 23:02 Speaker 2 Going to get there for. 23:03 Speaker 1 Sure, we're going to get there, but it's also easy right now I think for people to point to like AI games to 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 going to get there. 23:19 The sad irony is that people are revolting and raising their pitchforks in fear of their jobs and in 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. 23:41 Speaker 2 Technologies not try to use it. 23:43 Speaker 1 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. There will become a new standard. There 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 has built AI native. 24:07 And that transition takes time. I'm also I'm not envying and comments. It's very easy for me as an early stage investor, right? I'm just going to 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 AINPCS or whatever. 24:25 Very easy for me to say this and do this. I also don't envy the big operators that need to kind of like Segway into a new reality over time and tactfully working within the constraints of of today, but but being ready for quite different constraints in just a few years. 24:42 So it's that this is the kind of stuff I work on with open AI and, and McKinsey, for example, which is helping the incumbents with this transition in a way that's, you know, reasonable and, and meaningful and practical and, and, and, and, and, and financially responsible. 24:58 And then the work where I spend my 80% like where I'm me me as to start. 25:03 Speaker 2 Up being the investor. 25:04 Speaker 1 And conda supporter would go all in just on the the absolutely crazy stuff. 25:08 Speaker 2 Perhaps like one of the most successful gaming companies. So not everyone thinks of them as a gaming company is app love. And why have they been so successful? 25:16 Speaker 1 App Lovin 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. Yeah, you have to, you have to get the the supply right. But yeah, I mean, you can call them an, a gaming company or gaming adjacent company. 25:36 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. They're building the at network as far as I'm concerned, wasn't always the strategy. And so. 25:51 Well, yeah, I think a good example of the the the insight that it, it's always a good idea to seek novel, novel things and and maybe maybe build things that others aren't building and and try and reason from first principles. 26:10 Because I'm sure there were a lot of people that told them you can't just build and, and that network there's, there's already Google and, and Meta and they're doing quite fine. 26:18 Speaker 2 What do you think other businesses can learn from this kind of like free to play gaming model? 26:24 Speaker 1 Free to play hasn't been necessarily like a, you know, a smooth ride and, and a fairy tale of, 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. 26:42 I think what's there to learn from games like Roblox and and Fortnite specifically is that they have transcended to to our earlier point, this notion of becoming games where you know anything, many people who who play these wouldn't necessarily even call them gamers today. 27:03 It's just that their social hangout spaces in the kind of like third spaces. I think what they really massive 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 in your experience. 27:30 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 has also called out in in in a way these are becoming, you know, pretty walled gardens, a scaled walled gardens that that make innovation in the industry somewhat harder. 27:52 Speaker 2 When when you think of these companies, the Minecrafts, the roadblocks, the fortnights, like why? Why have these these communities been so successful? And other ones which maybe also like looked amazing, seemed really cool. 28:08 Somehow they didn't they didn't hit like what? What did they do differently? What can we learn from them? 28:14 Speaker 1 One thing I kind of love to mention when it comes to to game design or experience design is you want to make sure that that the game allows for players to be fun and makes the players more fun rather than actually be the game and the content being the fun. 28:35 You'll inevitably end up in some kind of, you know, content treadmill if why people are playing this game is because of the, the, 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 these sandboxy experiences like Roblox and and Minecraft, certainly, but even Fortnite is kind of like this, this smorgasbord of where people can just go wild and and they just have a. 29:04 Speaker 2 Good time. And they have all these trust and sell costumes. Yeah. 29:08 Speaker 1 Self expressions. Social role play, those are huge like even GTA5, I mean GTA is a very popular game, but you know the the most popular mode right now for GTA5, which is now many years old is is a mod that they acquired from 5 M 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 elses Ferrari. 29:35 And then that lands on TikTok and, and, and you know, there's like proximity voice chat and, and all this kind of stuff, so. 29:41 Speaker 2 But you kind of meet 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's kind of boring. Like I tried a few times and like seemed cool, but there's like it wasn't sure what I was supposed to do. 29:59 There was no like goal of it. It is it is kind of important to have both in the game, right? Or? 30:03 Speaker 1 Yeah, I mean, this was like the the, the this was like the the empty metaverse before the the bigger empty metaverse. Yeah. You again like games and online experience must be, must be vessels to kind of allow players to be fun or, or engaging. 30:24 Yeah, 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 you 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 as a publisher. 30:45 Speaker 2 There are people who play a lot of games that 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. 31:02 What is, is there like a personality trait? And when you're working with people are it seems like you're preferring more of the gaming people or maybe not. 31:11 Speaker 1 Yeah, I, I think on on player motivations, at least as as it comes to video games, they're different player motivation types. And 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. 31:27 That was like my whole childhood was, 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 kept me coming back every day. There are there are people who like the social element of it. 31:45 There are people who are the explorer type or like collecting achievements and then kind of completeness if you think about Pokémon Go, for example. So there is no one player motivation. 31:57 Speaker 2 And some people want more novelty, like they're just like, like I know people who play lots of board games, but they, they get like, they get bored pretty quickly of like a board game. And I 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're just play Settlers of Catan every night kind of thing, you know, And they, they want to really get at one thing. 32:16 Speaker 1 I've played literally like one game so far this year, which is, which is Rocket League and, and, and and that's now, I don't know, 8 years old. So, 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, and interactive media industry at least for the last 10 years. 32:37 Some of my best investments have been in, in Frontier and, and pureplay AI. And now in my, my own capacity, I work with founders from a range of industries. And 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 audacious North stars or let's call it like global Optima. 33:01 I'm not really interested in, in something that that doesn't scream and 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. 33:21 And and and and enterprise software in general is is 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 are doing general intervention and and world models and action models at the time is a great example like this is genuinely an an an advancement of even the the catalog of foundational AI technologies. 33:45 Another good example is recursive A-Team that's saying like, hey, you know, people realize that these models don't don't use enough space and time data. That's general intuition and the card and we're trying to like improve these models based on how human learning really unfolds. 34:04 Another way in which human learning is today quite advanced compared to what we're building for the machines is continue learning and this idea of recursive self improvement. Right now the models are trained and and of course like we, you know, the, the big labs, they use their own automated coding solutions like like codecs or our cloud code to then generate the code for the next iteration. 34:27 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, it can scrape the web and it can, it can digest that information, but it doesn't feedback into the model and the weights and the parameters and and all this kind of stuff and. 34:48 Speaker 2 So I assume that's coming, right? Like we should assume there's some sort of. 34:51 Speaker 1 Cursive, you know, like I want someone to say like why is no one working on that? And we're quite a good to work on that. And or another great example is, is AI, new AI inference chip and cluster company called Etched 2 2 now 24 year olds who at age 21 had the foresight 3 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 than NVIDIA just came out of stealth with a billion in orders and can't make that up. 35:30 Running a team of 400 people, including like senior executives from NVIDIA, Intel, Qualcomm hired the former CTO of Cyprus semiconductor legendary semiconductor company as their CTO and, and they're shipping their racks this summer. 35:46 And, and, and so, 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 from the get go. So I don't want to over represent here, but I mean, they had to eat glass for like 2 years straight and and everyone, including industry executives told them this couldn't be done. 36:08 And now they did it. I mean, it's, it's there and it's real, right? And I, I think this is, this is the kind of stuff where like fifty $100 billion plus companies are really born. And I think, yeah, the the chances of success are always small, but life's too short not to work on the things that if they work out, that can be like, you know, they should be industry changing. 36:34 They shouldn't just be industry contributing. 36:37 Speaker 2 What? What advice would you give to the average 18 year old and stuff like how how should they be thinking about things? 36:44 Speaker 1 Well, obviously, like play a lot of video games because this is the, this is the cradle of human and machine intelligence. Now to record everything. I mean, I'm really questioning at this point the, the traditional, you know, college education kind of grad school model. 37:06 And I was I went through my own interesting path where I I didn't actually go to a proper college because because I was afraid to go when I graduated high school. I spend all this time playing video games and still did really well in in school. 37:22 My parents hadn't gone to college. They actually hadn't got they did dropped out of high school. My brother dropped out of high school. And so I literally didn't have any one 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. 37:41 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 20s, I was on a completely different path. And I, I did this vocational training and, you know, later on clicked for me and ultimately applied to, to Stanford technically without a undergraduate degree and an essay about Diablo 2. 38:06 And from there the, the resume looks quite different, right? Like in the, like Stanford and Goldman and, and lightspeed and, and a bunch of accolades and, and, and, and, you know, also also like kind of part part time study experiences, some of the finest academic institutions. 38:23 But when I was when I was 18, I think my my only foray into true excellence on a global scale had been the competitive Diablo 2 kind of formative years. So like 7-8 years of basically playing at 10 hours a day, try to be the best in the world. 38:43 So I, 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 the traditional schooling system. I think the coolest thing to do from where I sit, and I'm super bubble biased, probably grab 2 smart, capable friends and put it in an application for YC. 39:11 Try and come to the US if you're not already there. That's definitely an advice. I, I, I have, I think this is, this is where the music plays here. And I 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 OK in, in, in, in, in, in, in this mess, alleged mess that, that we find ourselves in here. 39:36 And and I only chuckle and, and you know, my response is don't worry about me, but but I'm quite worried for you. 39:44 Speaker 2 It seems like it's not just Germany, but a lot, a lot of Europe doesn't seem to be innovating at the pace that one would expect us all these super intelligent, amazing people there. Like what's your kind of theory about it? 39:59 And. And why would you suggest like an ambitious European move to the US? 40:05 Speaker 1 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. 40:21 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? 40:44 In the, in the, in the true sense of the, the world. And like went, went on a ship sailed across to sea. 40:49 Speaker 2 We call them the Fountain. 40:51 Speaker 1 And that's the DNA. That's the DNA and, 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 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. 41:11 I 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 move moved to New York and and and and just became a citizen in February. And so there's a self. 41:26 Speaker 2 Selection. 41:27 Speaker 1 But going to Germany, OK, so for example, and, and by the way, I think Germany specifically my theory and you see some of this in Japan too. This is a country that that that twice big time. And I think there's real, real remnants of this like post World War 2 mentality. 41:47 We're 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. 42:07 And you see this reflected in in in the engineering culture and the kind of under 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. 42:22 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 see a doctor to have it have it cured. If you're starting a company, it means you didn't get a job. 42:39 Yep. 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 it's like at venture capital Germany, we call it Riziko capital. So before, before you get to capital, before you get to capital, you already cover the fact that it's very risky endeavour and the linguistic focus is on the downside. 43:04 And in America, the linguistic focus on the upside. And I think this stuff that's interesting. 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 and then. 43:24 Speaker 2 Right. We know it's going to go like. 43:25 Speaker 1 Most institutions in the world like, yeah, we can confidently say most of these fail. 43:29 Speaker 2 It's so famous. Jeff Bezos, he gave himself like a 10% chance of succeeding or something or whatever. Yeah. 43:35 Speaker 1 In terms of what ultimately matters for the fund, it's less than 10% of companies certainly. And so this is just a wrong way of looking at this. And we're and, and technologic technology compounds exponentially. And by the way, also another, another pet peeve of mine, like in Germany, like the the retirement system, like no one owns stocks. 43:56 The 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 and it's. 44:11 Speaker 2 Maybe. I mean, you don't want to be in if you were in the German market the last 30 years it has. 44:16 Speaker 1 Been terrible at all, at all like US equities, anything. 44:19 Speaker 2 Yeah. But like, I mean usually, like usually you invest where you live. And so if you were in the German stock market, like entire German stock market is like, I don't know, 50% of NVIDIA or something. 44:30 Speaker 1 You go to. 44:31 Speaker 2 The bank you go to. 44:32 Speaker 1 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're, you get your hard earned like 0.2% every year. And and by the way, we'll we'll in the meantime use it to make real returns. 44:44 Speaker 2 Outside of SAP, you can't even like, it's like hard to even think of like and that, 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's there's not a lot. 44:57 Speaker 1 Yeah, even the German car makers kind of slept through the Electro mobility transition for the longest time. 45:03 Speaker 2 I personally think German cars are I I'm not against Germany, but I I personally think they're they're German cars are terrible now like that they they 20 years ago. 45:11 Speaker 1 They were like the highest. 45:13 Speaker 2 I'm just saying it's true. Like you drive a BMW, you drive a Porsche, you drive a, 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 is better, the cars are better. 45:30 And then today, in many cases there, it's the inferior vehicle. It's not as good as a American car. It's not as good as a Japanese car. It's not as good as a Chinese car in on many, many, many different dimensions that's out there. So even there, I feel like it's like it's the, the kind of lost the edge, obviously still amazing cars, but just kind of lost that edge that they they once had there. 45:50 I don't know why that is. 45:53 Speaker 1 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 than today. 46:10 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 isn't out on this also, but I think that the the mistake is under investing. 46:32 Under investing, not just financially. 46:35 Speaker 2 It's OK to get. 46:36 Speaker 1 Culturally. Culturally, you just. 46:38 Speaker 2 Have to just, you have to try a few different things. You're going to get some things wrong, right? It's 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 rock. 46:49 Speaker 1 There's so few things that move the needle and then you basically, I mean, they're so in the grand scheme of things, there's so few companies and technologies and people who really push the world forward. 47:05 And by not investing in these crazy projects, you're just basically barring a nation from having exposure to, to, to a chance of, of having one of these people or technologies or, or companies. 47:19 Speaker 2 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? 47:32 Speaker 1 Yeah, 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, I do think it comes back to kind of losing to world wars, right. I, I'm not, I'm not an anthropologist, but I, it just strikes me as as playing a role. 47:48 Speaker 2 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, you know, I think France. 47:57 Speaker 1 I think France is a head of Germany, certainly. I mean, it's a lot of France. 48:00 Speaker 2 Is definitely a head of Germany. I I I 100%. 48:03 Speaker 1 Look at Israel. So, so there are these European, I would say, innovation clusters. 48:09 Speaker 2 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 US. There's almost no ambitious American who moves to Germany or France. 48:26 Speaker 1 Yeah, I think that's. 48:27 Speaker 2 True. 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. Have some great croissants, but you're not moving. They're like change the world. 48:42 Speaker 1 They do have better croissants. 48:44 Speaker 2 Yeah, that's for sure. Yeah. It's beautiful and wonderful and great to visit. What? What? How else are you using AI in your personal life? Like what else you doing to like, I don't know, just make your life better right now. 48:58 Speaker 1 What personal life? 49:00 Speaker 2 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 you doing to enhance, whether it's your own personal productivity, your, your, your, I don't know any type of life you know, etcetera. 49:13 Speaker 1 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 and whatever case is always right so. 49:28 Speaker 2 Do you like, do 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 leg I like. 49:37 Speaker 1 It yeah, this is like the the the highest value and most practical take away for the listeners on on this. Look. I mean, the truth is right now I probably spend like 100 to 120 hours on on all this kind of stuff. 49:55 Like if I think for me like like work, work and personal life, like really blend together, but it's also part of that is like, I really love the stuff I work at. I now have, I have 100% freedom to choose my, my, my projects like to point it out with what I set up in April. 50:18 I, 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 filed my own FINRA filings. I do my own taxes actually also. 50:28 Speaker 2 Why? Why do you do your own taxes and and do your own FINRA filings? 50:33 Speaker 1 I just think I do it better because I just know myself better and like 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. 50:50 Speaker 2 Walking because I, I imagine you have an extremely complicated tax situation. I would never even like think of, 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 many my own taxes. 51:07 Speaker 1 I'm still, I'm still like I'm still on like TurboTax. I'm just literally maxing out what you can do so far. This might actually change. It might change this year, to be honest, but like, you know, I, I, I, I really like the, the full freedom of the, the current endeavour. 51:24 And also, 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 pulling other people's capital. I have no LP's. 51:34 Speaker 2 You are your own LP essentially, yeah. 51:36 Speaker 1 I, I have no customers and in the 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, a VC from your customers IUI PS your customers are not your founders, right? 51:51 And if you don't have a piece, you don't really have customers. And so 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 e-mail or, or WhatsApp is like, you know, about a minute or or so. And I like it that way. 52:07 And I kind of expect the same thing. 52:08 Speaker 2 I would say the more successful the person is that I e-mail or WhatsApp or whatever, I would say the faster the response time is. 52:18 Speaker 1 I think this is a strong signal also for founders like if someone takes an hour or two hours to respond always, I think it's a huge so you turn on like. 52:28 Speaker 2 Sam Altman, he, he gets he, he rolls back within an hour. Like it's unbelievable. Like the guy is super busy like. 52:35 Speaker 1 Yeah, I would like send a text message. Yeah, I would just say text message, say sorry, I'm so busy. And I'm like, yeah, dude, I, I know, yeah. 52:43 Speaker 2 I mean like how do these I don't even understand how extremely. 52:46 Speaker 1 Generous. Yeah, extremely generous with his time. 52:50 Speaker 2 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, 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 e-mail in the morning. He had already emailed me back. 53:06 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. 53:12 Speaker 1 I think some people are just kind of wired differently and at least I I really enjoy self selecting and hanging out with these people. A lot of the founders I work with are in their 20s even and, and or early 30s and I get a lot of energy from that. 53:31 Like it makes me work you. 53:33 Speaker 2 Just turn 40, right? So now you're like, you know, you're like an old guy around all these people. 53:38 Speaker 1 That's right. Yeah. You know, that's OK. I'm trying to keep up, but I really I really self select for energy and I think it's important. I mean like how are you going to do crazy things if you are not hyper energetic? 53:54 How are you going to build like a 500 person team out of rock stars that are all energy bundles? Like I mean, you got to. 54:01 Speaker 2 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 52 cans of Diet Coke in the background or how? 54:13 Speaker 1 Do you needed to be sustainable right. I would say the the best founders. What are some traits that I, I really like maybe also beyond this, I would say they're all, they all have typically unique insights that they're pursuing for, for some, for some reason, like learned probably through prior experiences that they have this hypothesis that is original. 54:44 And, and they're kind of they're, they're like obsessed with, with 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, it can have profound impact or it will have industry changing impact. 55:00 And, and I think that's, you can look at, I mean, pretty much all the companies I invest in, they're, they're built on a thesis that is original and, and if right, quite consequential. I really like that. 55:15 I mean, this, this is maybe a terrible thing to say on the on the podcast, but I think it's, it's highly unlikely that any of these things, these these kind of projects are successfully built by people over or frankly, like the age of like 35 at founding, you know, oftentimes below 30 at founding. 55:34 Speaker 2 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 well, I think it's in a very different way. 55:45 Speaker 1 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. 55:57 Speaker 2 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? 56:06 Speaker 1 Yeah, you need like a judge call 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 Optima. What that means is like, I don't want them to look left or right and looks like like anything that's like we want to be the Uber of this and like, you know, like the Airbnb of that list just like it kind of actually is a bit of a turn off. 56:33 Also, by the way, every time I see like, especially in gaming, like people like to do this, like we're be more 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. It's like, I think it's a huge start off. I'd rather have you have no experience and just be absolutely like kind of artistically smart and, and audacious. 56:56 Oh yeah. I, I, I so, so pursuing this global Optima. I think first principles reasoning is super important. And 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 execute it. 57:16 And sometimes over 10 or 15 years, you know, when I was at when I was at Goldman, SpaceX was actually one of my early clients. Ironically, the the two things no one wanted to work at at Goldman as a banker in 2016, seventeen was gaming, which led me to start the the gaming practice. 57:34 But the other two things that no one wanted to work on were space and AI. OK, so so so so Palantir I grabbed to get together actually with 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, there were bake offs with banks to help them with financings. 57:59 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, $17 billion company. And now, of course, 10 years later, they do the IPO. 58:15 And like, you know, I see, I see them post like our long standing relationship with, with SpaceX. And like when I'm thinking to myself, my just 10 years ago, I, I couldn't even get anyone over the age of like 35 to come with me to this meeting. But yeah, you know, but but, but back then we, we kind of rolled out for, for a debt financing actually 120 page memo of SpaceX and the SpaceX plan. 58:45 And, and this was a time where rockets were basically exploding half of the time and, and, and returning maybe 30% of the time. And, you know, there was no satellite constellation, there was no Starling. There was an idea of Starship, which 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 constellation to become the world's largest telco provider. 59:18 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, and to help fund the real thing, which is, and I remember this distinctly is putting people on Mars. And Elon corrected me and said, no, no, yes, on Mars. 59:36 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, but just like on Earth, like solar flares or things that affect the solar system. 59:56 So ultimately you'll also have to to leave the solar system. So he went out of his way to like the language was a multi planetary species or something like that. And I read that as 110 years later, it rhymes a lot, right? It's become a lot more sober now. 1:00:11 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 this is the kind of stuff where you just knock it out of the park. 1:00:33 And that's what venture capital is all about. I, I don't really care about like, no, the, the certainty of not losing my money like that's, that's trivial. I I I want enough reasonable probability shots on target to to to get an audaciously large outcome. 1:00:51 Speaker 2 Our last question we ask all of our guests, what's conventional wisdom or advice do you think is generally bad advice? 1:00:57 Speaker 1 This is the part where where I enter the podcast unprepared. Well, I, you know, a lot of people that that are listening maybe are also founders and 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 beeves on on on my end. 1:01:18 I would not underestimate how much even among the top firms, 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. 1:01:42 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, and like diligence. And I, I know some founders who are like very diligent and very nice and answer all the questions. 1:01:59 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, or this and that. 1:02:20 And that can that can sometimes be a turn off, honestly, 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. 1:02:31 Speaker 2 That's true for almost everything, for so many things, Yeah. It's true for, you know what, It's true for trends. It's true for, you know, hiring. It's true for dating. In some ways, it's true for. 1:02:43 Speaker 1 But then I guess so much advice is, is 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 there's this like famous sequire pitch deck at the order of like what you what should your pitch deck have? And like, hey, ask your ask your advisors for like warm interest. 1:03:03 By the way, I read all my emails and I think most, most good investors 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. So, so I see everything. 1:03:18 I just respond to very few things. Yeah, exactly. And, and so, you know, warm info are not slightly less interesting, but how to manufacture social proof? Are there specific angels that can support you and your, your, your journey? What can you say and how do you want to say it to someone? 1:03:36 And what can you point to credibly that that evokes the sensation of proof from people that the people you're trying to raise money from what care about what doesn't necessarily have to be other investors. You know, it can be professors, this can be interesting angels, it can be, you know, interesting things you've done. 1:03:57 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. Whether you have a pitch deck or not, you know, sometimes doesn't even matter that much. 1:04:12 Speaker 2 All right, this has been amazing. I knew it'd be great. This has been incredible. Thank you, Morts for joining us on summation. I hope everyone like comes away from as like excited from this as I did, but I really appreciate you being on on the show. 1:04:26 Speaker 1 Thank you so much. 1:04:27 Speaker 2 One more thing before we go. I've 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. 1:04:45 It's free. New content comes out twice a month. You could subscribe at oren.substack.com. That's oren.substack.com.