Elad Gil, Jared Kushner & Eric Wu on AI in Business | Brain Co

Elad Gil joins Sourcery to unpack the story behind Brain Co, his new AI incubation venture with Jared Kushner (Affinity Partners) and Eric Wu (Opendoor). Brain Co was founded to solve a glaring problem: Fortune 100s and government institutions desperately want AI adoption but lack the engineering depth and infrastructure to make it real. Backed by a $30M Series A led by Gil Capital and Affinity Partners, Brain Co is already pulling in some of the sharpest AI minds and heavyweight backers across tech and finance. We dive deep into: The origins of Brain Co & why Jared Kushner approached EladEric Wu’s role after Opendoor and why he’s the right leaderWhy enterprise AI adoption is broken & how Brain Co fixes itThe $30M Series A and the powerhouse angels behind it (Databricks, Stripe, Coinbase, OpenAI leaders, Naval, Reid Hoffman, & more)How Elad thinks about incubation vs. investing Elad Gil: https://x.com/eladgil Molly O’Shea: ⁠https://x.com/MollySOShea⁠ Sourcery: ⁠https://x.com/sourceryvc⁠ Brought to you by: • Brex—The modern finance platform, combining the world’s smartest corporate card with integrated expense management, banking, bill pay, & travel. As a Sourcery Listener you get: 75,000 points after spending $3,000 on Brex card(s), white-glove onboarding, $5,000 in AWS credits, $2,500 in OpenAI credits, & access to $180k+ in SaaS discounts. On top of $500 toward Brex travel, $300 in cashback, plus exclusive perks (like billboards..) visit → https://brex.com/sourcery • Turing—Turing delivers top-tier talent, data, and tools to help AI labs improve model performance—and enables enterprises to turn those models into powerful, production-ready systems. Visit: https://turing.com/sourcery • Carta—Carta connects founders, investors, and limited partners through software purpose-built for private capital. Trusted by 65,000+ companies in 160+ countries, Carta’s platform of software & services lays the groundwork so you can build, invest, and scale with confidence. Visit: https://carta.com/sourcery • Kalshi—The largest prediction market and the only legal platform in the US where people can trade directly on the outcomes of future events: https://kalshi.com/sourcery Follow Sourcery for the latest updates! https://www.sourcery.vc/ Chapters: (00:00) Elad Gil (01:32) The “rule of 3” in markets: why industries collapse to 2–3 winners (04:56) From investor to incubator: why Elad started Brain Co (05:16) The “Brain” naming story & Braintrust origins (06:15) Meeting Jared Kushner & aligning on enterprise AI problems (06:54) Why Fortune 100s can’t adopt AI alone (07:13) Recruiting Eric Wu and assembling Brain Co’s founding team (08:29) Skipping SMB/mid-market → going straight to enterprise (08:51) Brain Co’s dual strategy: platform + bespoke apps (10:50) MIT study on AI pilots—why most fail & how Brain Co differs (12:26) Lessons from internet & mobile waves on long adoption cycles (15:30) Who are the real early adopters in enterprise AI? (16:38) The $30M Series A: Elad + Kushner co-lead, full angel investor list (18:47) Why Brain Co attracted top-tier operators & angels (19:23) Eric Wu post-Opendoor & Brain Co’s vision (20:47) Redemption stories & second acts in tech (22:54) Headlines vs. reality—what media gets wrong (27:18) Worst advice ever & “culture = winning” (29:04) Managing context switching & long-term planning (32:03) Lightning predictions: AGI, Mars robots, aliens (35:39) Outro & wrap-up

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

• 0:00Speaker 00

  Sometimes founders ask me, what's the biggest way to create a good culture?

• 0:04Speaker 00

  Welcome to Facebook. And the answer is winning. I remember when people said that SaaS was stupid and cloud was stupid, because why wouldn't an enterprise ever move their data to a third-party cloud that wasn't secure? I helped get this other company up and running called Brinko. We were just calling it Brinko. It was an internal placeholder, and then we were going to come up with something better. And like Apple and like Stripe and a few other companies, we just could never come up with anything better.

• 0:23Molly O'Shea?

  We should talk about the $30 million Series A. I'm really curious how you shift from investing directly into companies to incubating them. How did you recruit Ivanka's husband?

• 0:33Speaker 00

  Ivanka's husband?

• 0:36Speaker 00

  What's Ivanka?

• 0:38Speaker 00

  Jared came out to kind of talk to different people about AI and what was happening. We started just kind of comparing notes on what he'd been seeing from the corporate and government world in terms of people trying to adopt AI and not really knowing what to do. And I'd been talking to a lot of Fortune 100 CEOs and execs about sort of a similar thread. And so we kind of realized that the world's biggest institutions need to be able to have an easy way to adopt AI. When I met Jared Kushner, I think the media had portrayed him in a way that was very different from what they're like in person in terms of being very smart, driven, wanting to do the right thing for the world. One thing I've always wanted to do is like, imagine that I, well, I actually don't want to talk about this. I can tell you after. I still want to get on there.

• 1:12Molly O'Shea?

  Off the record, we have an exclusive.

• 1:14Speaker 00

  Yeah, exactly. Print it.

• 1:16Molly O'Shea?

  With Eric Wu, are you guys going to do anything with Open Door?

• 1:20Speaker 00

  You mean like a take-private or something?

• 1:21Molly O'Shea?

  No, but that would be interesting.

• 1:32Molly O'Shea?

  One of the things that, when I was doing research, I was listening to a previous podcast you were on, and there was a really good one with Patrick O'Shaughnessy. And you were talking about markets and how they collapse usually to two to three winners. So can you explain how that works and like what the framework is around that?

• 1:49Speaker 00

  Oh, I think there's, there's lots of different market structures. So there's some things that form natural monopolies, right? And so that for a long period of time was like the Microsoft OS or other things like that. And then the internet displaced that and allowed new entrants, and then mobile created another entry point. So some things actually naturally are just one player really dominates. It's kind of like Uber in the US or whatever now. There's many markets, and this was something I had to learn because I didn't invest in things. Some like it's not a monopoly, but it turned out multiple players could win. That are actually oligopoly market structures where you have a handful of very large players. Now, sometimes you have these large players and then you have a lot of fragmentation. You know, the three big players on 50% of the market and everything's fragmented. And that traditionally has been payroll, ADP, paychecks, and then a bunch of stuff.

• 2:34Speaker 00

  And then hopefully now Rippling and other sort of gusto and related companies. And then I guess deal is another one. And then there's and then there's markets where things are just default fragmented. It's like the restaurant business, right? There's thousands of restaurants in San Francisco. And so depending on different aspects of the market structure, what sort of customers you have, how dependent are they on your good product? Are there network effects or there are scale effects, et cetera? That drives which market structure you end up with. So I think there's lots of different ones in tech and consumer tech. The monopoly markets were more common. That was Google to some extent in search.

• 3:17Speaker 00

  That was Microsoft with the OS, et cetera. And then in many, many other markets, it's more an oligopoly structure. Payments is a good example where there's AdGen and there's Stripe and there's PayPal. And you know, there's a variety of players.

• 3:29Molly O'Shea?

  Do you think moats change over time?

• 3:31Speaker 00

  I think that for some companies, they build new moats over time for sure. I think there's a handful of ways to have a moat. And I think there are things, things just tend to collapse into these sets of things. Usually I find it's kind of the opposite of there's no good generic startup advice, you know, kind of thing. But the reality is there are patterns too. And so, you know, one mode is a scale effect. So for example, if you're a payments company, the more scale you have, the cheaper your interchange fee is on the backend, which means you can charge less, which means you can get more scale. And so you have the cycle, right? That'd be one example of a scale effect. There is ecosystem effects. Salesforce is a good example. Everybody's built an app on top of Salesforce. Everybody's selling those apps are integrated in a deep way.

• 4:14Speaker 00

  That helps create defensibility because if you're trying to build a Salesforce competitor, you may also have to build all these apps at once. Right? So you have more to build against and it's tougher. So there's these ecosystem or platform effects. Some businesses have long-term contracts. So for example, in the medical distribution world, McKesson and that sort of world, all the pharma distribution, people end up in these like three to seven year contracts. So the entire industry is effectively locked up between a handful of players because they each own a chunk of it. So there's a lot of different types of, I mean, I'm not going to keep going because it's like listing all my companies alphabetically, right? But fundamentally, there's only a handful of ways to do this and they tend to be very consistent, but they tend to be very strong. Network effects is another one, you know?

• 4:56Molly O'Shea?

  Shifting into one of your other strategies. We covered investing macro and everything like that. But I'm really curious how you shift from investing directly into companies to incubating them. There's a couple of companies that you started that start with brain. So what's the deal with these brain companies?

• 5:16Speaker 00

  I mean, so Anker came up, Anker Goyle, who's the CEO and founder of Brain Trust, came up with Brain Trust, which I thought was a great name. And I helped him really early get that up and running and did a lot of early customer calls. And initially, we talked about just doing that as like an open source project and all this stuff. And then it kind of converted into a company. So we were just doing it for fun. It's like a kind of a side project. And then when I helped get this other company up and running called Brinko, we were just calling it Brinko as a placeholder.

• 5:46Molly O'Shea?

  Really?

• 5:47Speaker 00

  Yeah, it wasn't meant to be the long-term name and hopefully Anker isn't upset, you know, that we have another brain thing in the family, but it was meant to be like kind of funny and quirky and it was an internal placeholder and then we're going to come up with something better. And like Apple and like Stripe and a few other companies, we just could never come up with anything better and the people who are working on it liked it. So it kind of stuck. So it was inadvertent.

• 6:06Molly O'Shea?

  How did you recruit Ivanka's husband?

• 6:09Speaker 00

  Ivanka's husband? What's Ivanka?

• 6:14Molly O'Shea?

  Ivanka Trump?

• 6:15Speaker 00

  Oh, yeah. So I met Jared when he was, so Jared came out to kind of talk to different people about AI and what was happening. And we started just kind of comparing notes on what he'd been seeing from the sort of corporate and government world in terms of people trying to adopt AI and not really knowing what to do. And I'd been talking to a lot of Fortune 100 CEOs and execs about.

• 6:43Speaker 00

  About sort of a similar thread and there was Luis who works with Jared, who similarly was having these sorts of conversations. And so we kind of realized that there was a very clear need and pain point around very large scale enterprise, government, like the world's biggest institutions need to be able to have an easy way to adopt AI for various workflows and purposes. And so we thought it would make a lot of sense to kind of build out a company that could have a core platform that you could then build different applications on top of that would serve those needs. And so Eric Wu came in as sort of a founder and chairman. And then Dan Ashton, who you know, and Mersha and others came on as sort of the initial founding team. And we kind of just were off into the races from then. And Clemens recently joined as CEO of the company. So.

• 7:28Molly O'Shea?

  How do you think about, and I think this company is really interesting because you're going after one end of the AI market that has been underserved so far. Like, we're seeing a lot of value accretion in the hardware layer and then now in the LLMs, but like the services really has not been tapped into yet because it's just a downstream effect, I think, if downstream is the right word. But I'm curious from your standpoint, like, how large is this opportunity? You talked about TAMs before, but like, how large is this and who are they going to be?

• 7:57Speaker 00

  Yeah, I mean, I think this is a truly massive, massive TAM. And so, you know, it really is, if you look at a startup's lifecycle normally that's doing B to B, you tend to start off with smaller businesses you're selling to, and then you realize that's a tough market and you go mid-market and you spend a couple of years in mid-market and then eventually you do big enterprise and you land your first multimillion dollar deal and you're ecstatic or you have a $10 million deal. It takes you like three to seven years to get there. It's sort of a thing, let's just jump straight to those customers. We have access to them. We know their needs. We can build really aggressively against it, but we can also attract a caliber of engineer to work with them that they just won't necessarily have access to in any other way.

• 8:40Speaker 00

  And that's because we have created a team or brought on a team or hired a team that are the types of people that normally be working at the foundation labs, right? They'd be working at OpenAI or they'd be working at Google or they'd be working at some of these great companies. And we've really taken the approach of saying we're both going to build out this platform. So it's a common piece of infrastructure that everybody can use. But then on top of that, we can build bespoke apps and then resell those apps to other people in the same vertical. And so if you're dealing with one of the world's biggest healthcare chains, you can repeatedly provide that to the world's biggest healthcare organizations because they all have similar needs. And so we think that strategy has actually worked really well. And there's enormous pent up demand because every CEO is asking, what is my AI approach? What's my AI strategy? I know it can impact my margin or my productivity

• 9:24Speaker 00

  or my, my sales output. You know, maybe I can double sales through it. But they may not necessarily have the resources to, to go right at it immediately, or they'll have a research team internally that's working on it, but that team can use extra resources. Or they can use some of the product work that we provide.

• 9:40Molly O'Shea?

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• 10:22Molly O'Shea?

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• 10:42Molly O'Shea?

  Do you think that the MIT study was correct?

• 10:48Speaker 00

  I think it had aspects that were correct. So basically, the study you're referring to is the one that says that AI doesn't really help anything or whatever.

• 10:57Molly O'Shea?

  Yeah, it said 95% of AI pilots are garbage. But if you read it, it says 63% of ones that were internally created were actually successful.

• 11:09Speaker 00

  Yeah, I don't know how much I believe that kind of data. I think it depends on what they mean by pilots and garbage and what does it mean? And a lot of people mess around with things and try it, right? The first time. And so often, the AI adoption cycle at a big enterprise is you have a small team that's doing almost like skunkworks or research, or they're suddenly become the AI team. And they go and they try some stuff and they prototype it and they mess around with it. And they're just learning how to use it, right? It's a new technology and it takes time to learn how to use it. And then usually there's three places you can implement it as an enterprise. You can buy something from a vendor. So you're like, I'm going to buy Decagon for customer support, or I'm going to buy a bridge for medical scrubbing or whatever it may be. And so then there's your vendor selection process, who do you work with and all this stuff?

• 11:53Speaker 00

  Harvey for legal would be an example of that. There's a second set of things that you do, which is internal tooling. How do I make my internal teams dramatically more effective? How do I build apps for them internally to do things? My ops team is doing this repetitive work and use AI for that workflow. And then there's stuff that gets into your own product that you're offering externally to your customers, right? Those are sort of the three levels of AI for an enterprise. And so when I see a study like that, I'm like, okay, which of these things are they doing and what did they try and who was actually working on it? And is it the right talent and all this stuff? And the reality is, if you look at mobile as an example, when mobile first came out, everybody said the exact same thing, or the internet, right? The internet was this giant transformative wave.

• 12:36Speaker 00

  People forget that some companies literally spun out their internet division as a tracking stock because it would trade so highly, they could pull in a billion dollars through an IPO of some random piece of whatever business they had. And then when those stocks collapsed a few years later, as a dot com bubble collapsed, they rolled them back in super cheap. And so it's just a way to are getting some money by branding something as an internet company.

• 13:00Speaker 00

  Again, I think the 90s is a very interesting lesson for today in terms of when we'll be coming. So if you look at the early mobile wave as an example, the first B of A like mobile website was really bad, right? You go to this janky kind of HTML site that was on your phone, on your browser, and you couldn't really do anything and it would crash half the time. And then 10 years later, you can do these amazing things in the app, right? You can scan checks and OCR them. You can take out money by tapping it against the ATM in case anybody ever uses cash for whatever nefarious things people do. Or if, I'm just kidding about that.

• 13:35Speaker 00

  You know, you can send money really easily with Zelle or Venmo or other things. And so something that be of a mobile app is really useful, right? But it took a decade and it just takes time to adopt these things, to learn new patterns of usage, to understand how to use it properly, for users to adapt themselves to it. So I just think it's going to be one of these long arcs. And to say that things should immediately be working is not reflective of any technology wave that's ever happened. And in the internet, people said the internet doesn't matter. And in the early crypto days, people said crypto doesn't matter. And people always say these things don't matter. Oh, I remember when people said that SaaS was stupid and cloud was stupid because why would an enterprise ever move their data to a third-party cloud that wasn't secure and etc. You know, it's always the same thing. So I just view it as like, there's that old saying of old wine and new bottles.

• 14:20Speaker 00

  And I think that's what this is.

• 14:21Molly O'Shea?

  Old wine and new bottles. How do you think about, and I'm sure you've talked to like many Fortune 500 CEOs, teams about this. How do you think about how different companies are approaching AI? And which ones are doing it right? Like, what are they looking to do? What are the key components of that? And then how do you decipher? How do you know like which teams are just not going to make it? Because they're just not thinking about it correctly.

• 14:47Speaker 00

  Yeah, I mean, I think these things are 10-year journeys, right? So the migration of the cloud has taken 15 years for many companies. Some companies are still using COBOL and very old programming languages for the services they run, right? You'll literally find a COBOL installation running some core server for a company doing payment processing or whatever, and it hasn't been touched in 40 years, right? So I think people misunderstand the state of software and sophistication. And they may be very sophisticated. They miss out these old legacy things. And so it's kind of hard to say, hey, we're just going to grade somebody on something, right? There's all these other things, moving pieces, how did they deal with data? You know, the whole migration to a Databricks would be an example of something that some companies are still doing, right? To get to data lakes and modern data infrastructure.

• 15:32Speaker 00

  So it's a very uneven world around these things. And so often what you need to look for is early adopters. And then you can work with them to really help implement something that's very useful for them or to build on top of this platform that is an example Brinko has. The thing I found striking, having worked in different businesses for a long time, is in every industry, there's a set of early adopters and they're trying to be the key influencers or decision leaders or opinion leaders in that area. So for example, if you're selling HR software, I think it's Costco and Home Depot and a few others are great at adopting new benefits, new HR software, et cetera, which you wouldn't expect, right? These are big, you know, impressive enterprises, but they often adopt things before younger companies will or smaller companies will.

• 16:17Speaker 00

  And so often what you ask yourself for any new product is who are the tastemakers? Or who are the people who in general tend to adopt things more? And can I work with them first? Because they'll be fastest, they'll be easiest, they'll be the most thoughtful, they'll give good feedback. But they'll also spread it to other people because other HR departments call them for advice and view them as sort of a leader.

• 16:36Molly O'Shea?

  We should talk about the $30 million Series A. How did that come together?

• 16:40Speaker 00

  Yeah, I think what we decided to do was, there's almost two ways you see people incubate things. One is they take a lot of common stock and they try to control the company and they try to, and we did the opposite where we said, we'll just put money in to buy our ownership stakes. And, you know, the equity should really go to the employees and the founders and the people running it day to day. So we kind of approached it as a more traditional financing structure.

• 17:04Molly O'Shea?

  And who was involved?

• 17:06Speaker 00

  Yeah, I mean, we had a great group. So I, my fund and Jared's, which is Affinity, co-led it. So we each put in half and then we had a great sort of bevy of angels across AI.

• 17:23Molly O'Shea?

  Can I read them off? I have them.

• 17:25Speaker 00

  Yeah, that'd be amazing. It's a better clip from you.

• 17:27Molly O'Shea?

  I was trying to tee you up for this.

• 17:28Speaker 00

  Yeah, please.

• 17:30Molly O'Shea?

  Where, oh, here it is.

• 17:31Speaker 00

  Yeah, please, I memorize in alphabetical order. You should do it.

• 17:34Molly O'Shea?

  This is gonna take a while.

• 17:35Speaker 00

  Yeah.

• 17:36Molly O'Shea?

  It's gonna be hard for me to pronounce all their names. We have the CEO of Databricks. We have Andre Karpathy. We have former chairman and CEO of Dow Chemical. We have the CEO of Perplexity, CEO of Coinbase, CEO of Applications at OpenAI, Chief Product Officer at OpenAI, former chairman and CEO of EY, Global Co-Head of Blackstone Real Estate, founder of Angel List. That's Naval.

• 17:59Speaker 00

  Yeah, Naval's great.

• 18:00Molly O'Shea?

  If you didn't know.

• 18:01Speaker 00

  Yeah, love Naval. He's so good.

• 18:03Molly O'Shea?

  Noam Brown, AI researcher at OpenAI. We have Patrick Collison, CEO of Stripe. Reid Hoffman. We have Sarah Guo. Is that how you pronounce it?

• 18:13Speaker 00

  I think so. I think it's Guo.

• 18:15Molly O'Shea?

  Well, I've been listening to like a lot of different things and pronunciation. Pronunciations.

• 18:19Speaker 00

  We should ask her. We should call her.

• 18:22Molly O'Shea?

  Sarah Guo.

• 18:23Speaker 00

  Yeah.

• 18:24Molly O'Shea?

  And then we also have the CEO of Together AI. How do you get all of these people on one cap table?

• 18:30Speaker 00

  Well, I mean, I think a number of people helped really pull this around together. Eric was very involved. Jared was involved. Dan, the president of the company, you know, really drove the fundraiser day to day. So I think it's one of those things where people were just very excited about what we were doing. It was one of those moments where everybody you talked to was like, of course, this is needed. Of course, I've seen use cases. Of course, I've seen people ask me about this. So I just think it's one of those things where we thought it was a clear indicator of just like how interesting and exciting what we're doing is. And then as people met, Dan and Clemens and the team, I would get texts where they're like, oh, my God, these are really impressive people. Right? Like, I wanna, I wanna back whatever these people do. So I think it's also the caliber of the people involved operating the company really matters.

• 19:14Molly O'Shea?

  And with Eric Wu, are you guys going to do anything with Open Door?

• 19:20Speaker 00

  Oh, you mean like a take private or something?

• 19:23Molly O'Shea?

  I mean, no, but that would be interesting.

• 19:26Speaker 00

  I know where that question was leading.

• 19:27Molly O'Shea?

  Partner with them. Maybe they'll be a customer. Maybe they'll transform Open Door and help them, you know, fill in that market cap that they just got up to.

• 19:35Speaker 00

  Eric is awesome. He's so good. It's one of those things where he's so impressive in terms of how good he is at operating things and getting things done and thinking about things strategically. Like, you know, I backed his very first company, Movie, like years ago. And then I backed Open Door and I've worked with them over the years. And then I started working with them on BrainCo and I was just so impressed. I already knew him and I already knew he was very good, but he's really taken things to the next level.

• 20:02Molly O'Shea?

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• 20:39Molly O'Shea?

  Between all of your investments and the companies that you've funded, what is the best redemption story that you've seen?

• 20:45Speaker 00

  A redemption story? How do you define redemption?

• 20:47Molly O'Shea?

  Coming back from the ashes.

• 20:49Speaker 00

  Oh, I mean, I think there's a couple of examples of that and it depends on what's meant by the ashes, right? There's a few founders that I've backed where there were some, you know, bumps along the way with their first company in one form or another, even if the company was successful. So an example would be Parker Conrad from Rippling. I backed him at Zenefits. I was an angel in that company and then I invested in the first round of Rippling. And that was a good example where there was obviously controversy around the company. I always thought he was amazing. I always thought he would have some amazing redemption arc. And so I got involved with Rippling in the very first round as sort of a vote of confidence behind him and what he was doing. Palmer Lucky is another one where I backed Andrew in the very first round and he was controversial,

• 21:34Speaker 00

  given what had happened at Meta early on with him. I think in both cases, they basically got thrown under the bus in one form or another. So I think they deserve that that arc. So I think they've done amazing things. I mean, when I met Jared Kushner, I think similarly, the media had portrayed him in a way that was him and Ivanka both, actually, in a way that was very different from what they're like in person in terms of being very smart, driven, wanting to do the right thing for the world.

• 22:01Speaker 00

  So at this point, I think I've worked with lots of people who in one form or another, at one time or another, had gone a little bit through some firestorm and came out the other side, you know, stronger and more motivated and crisp on what they care about and what's important in life. And, you know, because I think experiences like that for many people, and I'm not saying anything specific to any of these individuals, I've just observed in general that sometimes a controversy also just makes you crisper about what's important to you, like as a person.

• 22:32Molly O'Shea?

  Most of those do run through the media cycles and the harsh reality of what can happen to you in the news. I'm curious, from your standpoint, you have podcasts, you put out a book, you're like close to all these worlds, these personal stories. What do you think people most get wrong about headlines versus reality?

• 22:52Speaker 00

  Oh, I mean, for certain media, the headline is literally the opposite of reality. And we've seen that a lot throughout COVID and some of the claims that were made and then reversed a year or two later. I mean, literally reversed. It wasn't like, oh, we were slightly wrong. It was we were completely wrong, right, on so many topics. And so I think it's very hard to trust reasonably large swaths of the media. And you've probably heard or talked about like the Marie-Gal Men effect, Gelman, I never know how to say his name. Do you know this whole story? Okay, so Michael Crichton, the author who wrote Jurassic Park and all these things, was trying to coin a phrase that would reflect a situation where, say, you're reading the New York Times and you read an article about something that you're an expert in.

• 23:36Speaker 00

  You're like, oh, my God, they got all this wrong. It's complete bullshit. And then you flip the page and you read an article about something that you don't know anything about and you believe it. Right, but you just read something that they wrote that was completely false. So he called this the Murray Gell-Mann effect because Murray Gell-Mann was a two-time Nobel physicist. And so he's trying to choose the name of somebody really smart and attribute it to them to make the effect seem more weighty or important. So it's kind of like a branding exercise to name it after this physicist. But I think everybody has that, right? You'll read something and be like, oh, I know this and this is obviously false. And then there'll be the next story and they'll be like, oh, of course this must be true. And I think one of the big lessons for me was a, a lot of this stuff is just false and a lot of it is manufactured and there's agendas behind these things. I don't think it's an accident over and over and over again.

• 24:21Speaker 00

  I think it's purposeful. I think it's really bad for society that people act this way. But also I think it just reinforces, and it's interesting, a lot of the outcry in either traditional media or online is, oh, well, don't trust that person. They're not an expert. They haven't, you know, they're looking at the data directly, but what do they know? And you're like, well, actually that's the best way to actually understand things. And so I remember early on in COVID, in late January, early February of 2020, I actually sent out an email to founders saying, hey, I think this COVID thing is real and it's going to be really bad and they may shut down cities and all this stuff, right? Because you saw them weld people into their apartments in Wuhan, right? Yeah. Which usually doesn't happen. It's kind of an odd of thing. Not every day.

• 25:05Speaker 00

  Yeah, you kind of notice it if you're paying attention. And then a few months later, my chief of staff pulled all the data off of the government websites and it was very clear the demographics that were actually impacted by COVID. And that had very deep policy implications in terms of what you should be doing societally. Should you be shutting down schools or not? Probably not, actually. And so we wrote this up and it got circulated to a bunch of governments and we got calls from the White House, we got calls from the UK government. We actually got a number of phone calls on what we wrote up because it's very data-driven. It was just like, here's the data and here's some basic implications. And then, of course, policy went in the opposite direction, right? But I think it was clear, like, what was real, what wasn't real, quite early. So I think you kind of run into that over and over again.

• 25:48Speaker 00

  And to some extent, if to tie that back to startup investing, I think people tend to project a lot of things onto the world. And there's lots of forms of that. As a founder, for example, you project the way that you act onto employees if you haven't managed before. And founders are perfectly fine with chaos and uncertainty and risk. But most people aren't. Most of your employees want a stable direction. They want to feel like the thing is working and they want to know where to go. But as a founder, often early on in your career, you don't provide that because you don't realize you're projecting onto people your own viewpoint. That happens societally. Or how do you interpret certain information? Or how do you really see the world in a clear and crisp way? And so one of the things I try to do as an investor is ask, what is the reality of this thing? Not what is the thing I hope it is, the thing the founder is telling me that, you know,

• 26:33Speaker 00

  what do I, what is really going to happen here? What is the physics of the situation? A friend of mine used to work with Steve Jobs. And he said that the thing that he felt that Steve Jobs had wasn't a reality distortion field. You don't change reality. Reality is what it is. He just was able to see things more crisply and articulate them with the fewest number of words in a way that would motivate the person to act against that reality. So it wasn't reality distortion. It was clarity of seeing and clarity of communication. And one of the things I found that tends to correlate with very good founders is that clarity of thought. And it's often reflected in crisp communication.

• 27:15Molly O'Shea?

  What's the worst advice you've ever received?

• 27:18Speaker 00

  The worst advice I've ever received? I mean, I think there's a lot of advice out there that I just don't agree with, like, follow what you're passionate about, or, you know?

• 27:26Molly O'Shea?

  Really?

• 27:27Speaker 00

  Yeah.

• 27:28Molly O'Shea?

  Why?

• 27:29Speaker 00

  Because most people's passions are really bad, dead-end things to follow. Like, realistically, right? Do you want to have a good job or not? Do you want to have a family? Do you want to, you know, et cetera? I think societally, we've been giving really bad advice around very basic aspects like that.

• 27:45Speaker 00

  So, you know, one thing I've always wanted to do is like, imagine that I, well, I actually don't want to talk about this. I can tell you after. I still want to get on there.

• 27:57Molly O'Shea?

  Off the record, we have an exclusive.

• 28:00Speaker 00

  Yeah, exactly. Print it. Yeah, I think, I think that's one piece of advice that usually isn't good. Every once in a while, your passion lines up with something really important for the world or really important for a field or discipline or industry or society. And great, follow your passion. But most of the time, it's really bad advice and it actually leads people to a suboptimal state in life. I've also find that people, you know, sometimes founders ask me, what's the biggest way to create a good culture? And the answer is winning. That's the best way to create a good culture. It's not the motivational speeches and the kombucha. It's like, when you're winning, everybody's excited and they want to show up and they want to do good work. And that's true in many aspects of life.

• 28:39Molly O'Shea?

  Okay, so Sorcery is sponsored by Brex, one of your early investments. Love Brex. And they're all about spending smarter, moving faster. They are a performance, modern, intelligence, finance platform. And I'm really curious, from your standpoint, on how you manage performance between all of your projects. You are constantly context switching. How do you manage that?

• 29:02Speaker 00

  You know, I'd like to get to, well, I think there's lots of different approaches that people take to sort of manage context switching. Sometimes people block out hours of the day to do certain things. You know, Jack Dorsey, when he was running Twitter and Square famously would have chunks of the day for Square and chunks of the day for Twitter. So he could just show up and be focused. So some people take that approach. Obviously, if you have a team, there's things you can delegate specifically that allow you to sort of multitask things or create a distributed environment to getting things done. So I think there's lots of things like that.

• 29:32Molly O'Shea?

  What do you use?

• 29:33Speaker 00

  It's a mixture of some team leverage and then

• 29:38Speaker 00

  You know, I think it's just trying to emphasize what are the most important things to get done in a given day or week. And so sometimes I'll sit down in the morning, I'll say, what do I actually have to do today? There's all these things I could do today, or I'll get sucked in today. But what are the two or three things that if I get them done are actually important? And then what's that for the week? And I think that's really useful. One exercise that I'm about to go through is I'm going to try and think 10 years ahead, which is of course silly and stupid and it never actually works. But I basically want to think in terms of one, three, and 10 years, and think across four spheres, and kind of plan against that. And so I don't want to wake up 10 years from now and say, where did the 10 years go? You know, John Lennon has this quote that life

• 30:22Speaker 00

  is what's happening when you're making other plans. Right? And so the spheres I want to start thinking about are, obviously, there's personal life and kids and family. And how do you want to think about that? There's society and societal impact. That's things like the monuments projects or other things like that. Like, how do you want to actually make the world or your neighborhood or your society better? There's the work side of it, you know, like, what do you want to impact? What do you want to build? What sort of institution do you want to leave behind? Or what do you want to accomplish? And that could be impact goals, it could be financial goals, it could be a variety of different goals. And then the last piece is more like, how do you think about relevance in the world and society over a longer arc? And so I'm kind of thinking across those, those four things.

• 31:04Molly O'Shea?

  That's a perfect answer. Thank you, Brex.

• 31:06Molly O'Shea?

  Sorcery is proudly sponsored by Carta. Carta is transforming the private marketplace, connecting founders, investors, and limited partners through software purpose-built for private capital. Trusted by more than 65,000 companies in over 160 countries, Carta's platform of software and services lays the groundwork so you can build, invest, and scale with confidence. Carta's fund administration platform supports over 9,000 funds and SPVs, representing nearly $185 billion in assets under management, with tools designed to enhance the strategic impact of fund CFOs. For more information, visit carta.com/sorcery. That's C-A-R-T-A dot com slash S-O-U-R-C-E-R-Y.

• 31:53Speaker 00

  Enrique actually called me and was feeding me that information.

• 31:56Molly O'Shea?

  Really?

• 31:56Speaker 00

  Yeah, it was great.

• 31:57Molly O'Shea?

  Is he in the room with us right now?

• 31:58Speaker 00

  Yeah, Pedro is in spirit. He's with us today.

• 32:01Molly O'Shea?

  Okay, so as we close out, I want to go through some quick future predictions.

• 32:05Speaker 00

  Okay.

• 32:06Molly O'Shea?

  Okay, first, we're gonna do some from CalShe. Are you ready for this?

• 32:09Speaker 00

  Yeah.

• 32:09Molly O'Shea?

  It'll be, it'll be fast.

• 32:11Speaker 00

  Okay.

• 32:11Molly O'Shea?

  When will OpenAI achieve AGI?

• 32:14Speaker 00

  I have no idea. Because people always say, what's the definition of AGI? And what is it? You know, people always dodge the question that way. So I was gonna dodge the question.

• 32:20Molly O'Shea?

  Pick a year.

• 32:20Speaker 00

  I don't know what it means.

• 32:21Molly O'Shea?

  Before 2030? Before 2020?

• 32:24Speaker 00

  I don't wanna, I don't wanna bias CalShe. I don't wanna destroy their whole marketplace.

• 32:29Molly O'Shea?

  Look, the markets, it's up to the markets, free markets.

• 32:33Speaker 00

  Yeah.

• 32:34Molly O'Shea?

  Free markets.

• 32:34Speaker 00

  Yeah.

• 32:35Molly O'Shea?

  Okay. This one's a little bit more fun. Will a humanoid robot walk on Mars before a human does? What do you think the odds are?

• 32:43Speaker 00

  Probably quite high, like 80%.

• 32:45Molly O'Shea?

  Really?

• 32:45Speaker 00

  Mm-hmm.

• 32:45Molly O'Shea?

  Why?

• 32:46Speaker 00

  You can send them any time of year. The length of the journey doesn't matter. You don't need to worry about life support and other systems being built in that are self-sustainable. You don't have to worry about food. There's a lot of things you don't have to worry about.

• 32:59Speaker 00

  I mean, we already sent a robot to Mars, right? We have Mars rovers. So we've already accomplished that part. So a humanoid version of that seems fine. I don't know why we care if it's humanoid. But let's do it. I'm in.

• 33:11Molly O'Shea?

  I think they're thinking of Optimus in particular.

• 33:13Speaker 00

  Yeah, that probably makes the most sense.

• 33:15Molly O'Shea?

  Yeah. Yeah. Right now, the odds-

• 33:16Speaker 00

  With somebody's brain uploaded into it. I wonder whose brain it's gonna be.

• 33:19Molly O'Shea?

  Oh, my gosh.

• 33:20Speaker 00

  Yeah, it's gonna be very exciting.

• 33:21Molly O'Shea?

  That's really interesting.

• 33:22Speaker 00

  That's probably that AGI question.

• 33:22Molly O'Shea?

  Well, it's probably-

• 33:24Speaker 00

  Who do you send?

• 33:25Molly O'Shea?

  X, XAI's brain.

• 33:27Speaker 00

  You probably send XAI, yeah. So it'll just be-

• 33:29Molly O'Shea?

  Everyone's-

• 33:30Speaker 00

  Yeah, it'll just be making memes from Mars. That'll be amazing. I would be down for that. I would love memes from Mars. I would follow that.

• 33:36Molly O'Shea?

  Really?

• 33:36Speaker 00

  On the X, yeah.

• 33:37Molly O'Shea?

  How, how will they make memes from Mars?

• 33:40Speaker 00

  They would just tweet them or post them. I'm sorry.

• 33:42Molly O'Shea?

  Post them.

• 33:42Speaker 00

  I don't say tweets anymore. I used to work at Twitter, so like, I think I'm allowed to still use OG terms, but most people can't.

• 33:48Molly O'Shea?

  I don't know. I'm not the-

• 33:49Speaker 00

  You get banned.

• 33:49Molly O'Shea?

  I'm not the police there.

• 33:50Speaker 00

  You get thrown off.

• 33:51Molly O'Shea?

  Really?

• 33:51Speaker 00

  Yeah.

• 33:52Molly O'Shea?

  Oh.

• 33:52Speaker 00

  Yeah.

• 33:53Molly O'Shea?

  Well, right now, the odds for this are at 32%.

• 33:55Speaker 00

  Oh, really?

• 33:56Molly O'Shea?

  I think there's tremendous upside in this one.

• 33:58Speaker 00

  Yeah, I should actually invest in that one. That's good.

• 34:02Molly O'Shea?

  On the theme of outer space, I really want to get your opinion on this.

• 34:07Molly O'Shea?

  First, on what the odds are for this, and then also your opinion on the topic in general. Are you ready?

• 34:12Speaker 00

  Yeah.

• 34:13Molly O'Shea?

  Will the US say that aliens exist this year?

• 34:16Speaker 00

  Oh, I think the odds of that are low, just given historical precedent.

• 34:20Molly O'Shea?

  Why?

• 34:21Speaker 00

  Well, just given historical precedent. So there's three scenarios, right? Scenario one is aliens exist and the US government knows about it and they won't tell us. Why would they tell us specifically this year if they'd known for a while? Right?

• 34:34Speaker 00

  There's they don't exist, in which case they could tell us, but then they're lying. But maybe there's a reason to do that, right? So that's unlikely, or they don't exist and they don't tell us. And the last one is that they exist and they don't know. And so if they don't know, why would they suddenly discover it this year?

• 34:48Molly O'Shea?

  Do you think they exist?

• 34:49Speaker 00

  I'm sure there's alien intelligence somewhere in the universe. It's a big universe. I don't know. What do you think?

• 34:53Molly O'Shea?

  Definitely.

• 34:54Speaker 00

  Yeah.

• 34:55Molly O'Shea?

  Definitely.

• 34:55Speaker 00

  Yeah. Do you think you've met alien life?

• 34:58Molly O'Shea?

  Probably.

• 34:58Speaker 00

  Yeah. Yeah, some of this goes kind of weird sometimes.

• 35:01Molly O'Shea?

  Yeah, I think I like definitely walked across the street with a few this morning.

• 35:06Speaker 00

  Yeah.

• 35:07Molly O'Shea?

  Gets a little sketchy. You never know.

• 35:09Speaker 00

  Yeah, it's kind of rough. Yeah.

• 35:12Speaker 00

  That's why I don't walk around a stuff anymore, that alien life.

• 35:14Molly O'Shea?

  You don't? How do you get around? Waymo?

• 35:16Speaker 00

  I just use bikes.

• 35:17Molly O'Shea?

  Bikes?

• 35:18Speaker 00

  I don't really.

• 35:19Molly O'Shea?

  Okay. I'm not going to do that, but thank you.

• 35:22Speaker 00

  The biking or the Waymo?

• 35:23Molly O'Shea?

  I'm not going to.

• 35:23Speaker 00

  Okay. Yeah, smart.

• 35:25Molly O'Shea?

  It affects my podcast outfits.

• 35:29Speaker 00

  It's a good optimization function.

• 35:30Molly O'Shea?

  Okay, well, Elad, Elad, it's a pleasure to have you on.

• 35:34Speaker 00

  Molly, Malaya, thank you. I appreciate it.

• 35:37Molly O'Shea?

  Hey, it's Molly. If you enjoy our interviews, check out our newsletter, sorcery.vc, where we deliver a once a week top deals and tech headlines email, and also go deeper on our podcast interviews. Subscribe to Sorcery today. And don't forget to subscribe to the podcast on YouTube, Spotify, Apple, or wherever you listen. Link in description to sign up.