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TBPN is a live tech talk show hosted by John Coogan and Jordi Hays, streaming weekdays from 11–2 PT on X and YouTube, with full episodes posted to Spotify immediately after airing.
Described by The New York Times as “Silicon Valley’s newest obsession,” TBPN has interviewed Mark Zuckerberg, Sam Altman, Mark Cuban, and Satya Nadella. Diet TBPN delivers the best moments from each episode in under 30 minutes.
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Speaker 2:Today is Wednesday, 09/30/2026. We get a couple of heart from the TBPN UltraDome. We're back in the UltraDome, the temple of technology. The fortress of finance. Finance.
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Speaker 2:So there was a supper last night at the White Home, the White House, the Golden House, the Golden Home? Gold Home? What what are we calling it these days? Well, we renamed artificial intelligence. It's super intelligence now.
Speaker 2:We were debating, is super intelligence abbreviated SI or just S? Because if you're, like, the super alignment, was that SA? Like, One super problem
Speaker 1:there, John, there's no TLD for just S.
Speaker 2:That's true. That's true. You gotta get the new TLDs going. What was the word we we we So super alignment,
Speaker 3:that was one word.
Speaker 2:That was one word.
Speaker 3:You know, some words you do, you have hyphen.
Speaker 2:You have a hyphen. Yeah. And then some Could just use that
Speaker 3:like a normal prefix for
Speaker 2:like a normal prefix for something.
Speaker 3:Yeah. Supernatural.
Speaker 2:Supercalifragilisticexpialidocious. That's one word. Right? So you would think that potentially you would just be using one word here. Yeah.
Speaker 2:But anyway, we're using two words, I guess. And so there was dinner at the White House. David Sachs posted it. He said, it's the Bretton Woods of Supper Intelligence, super intelligence.
Speaker 1:There's my my first reaction to this is Tyler was really snubbed. Snubbed. You know? Yeah. All those people there and not not one chair for Tyler.
Speaker 2:Yeah. And so there's there's a bunch of folks here and people were analyzing who got the best seats, who got the different positions, who got pole position, prime positioning, who snubbed off in the little kids table at the end, etcetera, etcetera. A bunch to analyze about who But begins, who's on the I had had had sort of go through and and try and categorize each attendee by their stance on open source. Open source. So did they sign the Jensen NVIDIA open source letter?
Speaker 2:Have they been concerned about the cybersecurity impacts? Obviously, Anthropic on the far end, sort of in the red, a bunch of other folks who are more in the yellow. And I don't know if I agree with all of these classifications, but you can sort of see how Jensen is clearly pro open source. Satya Nadella has talked about that. OpenAI, Greg Brockman, more in the middle, you know, not open sourcing a lot of things.
Speaker 2:OpenAI did sign the Jensen letter, but of course is concerned about pacing the frontier, which is sort of antithetical. And so this is all as a as a as a reference point to that post from our friends over at semi analysis. Let me actually pull up what what they said here. Where was it? It was Max Can.
Speaker 2:I believe this is Semi Analysis. Yes. Max Can says majority of people are significantly underestimating the probability of open source models being nerfed or even outright banned in the next six to twelve months due to cyber concerns. And so I believe put out something yesterday talking about the risks of open source in a cyber context saying that the delay between mythos preview, being able to find zero days, being able to hack into things, that gap has closed now and the open source frontier can very quickly do the same thing. And so expect a lot of cyber incidents unless something is done.
Speaker 2:Can these be controlled some way? Maybe at the inference layer, maybe at the data center level, maybe at the chip level. There's going to be a whole bunch of different proposals. At least right now, in the next six to twelve months, certainly not this month because the vast majority of people who are closest to Donald Trump have been evangelizing for open source. So I would be surprised to see any any pushback against open source happen that quickly.
Speaker 2:At the same time, open source is amorphous. It is not a business by definition. And so it can't really have a formal seat at the table. George Hotz, not at the table, for example. Snub.
Speaker 2:Yeah. No. Linus Torvalds, you know, not not at the table. Open George source
Speaker 1:Hotz at the table just sort of like laughing in a sort of insane way at everything being said.
Speaker 2:Yeah. And and so even the companies that are pro open source, they are pro open source in in so far that it advances their business. And so there is still a way that the closed source group could find a way for everyone who's at this table to benefit in a closed source world moving forward if open source is deemed to be too dangerous and and and forcing too many cyber concerns. There I like, I I could see everyone at this table signing a letter saying we are now anti open source, but the the downstream, like, economic engine actually splits, you know, the the the rewards and the and the profits of the ecosystem fairly evenly. I think the the initial pushback and and pro open source push, especially from Jensen, was like, we don't wanna be in a world where there's one company that reaps 100% of the profits and we're not involved.
Speaker 2:But if it's like, hey, look. There's actually gonna be an oligopoly. Companies don't want a single source intelligence. They're constantly gonna be bouncing back and forth between OpenAI and Anthropic. And then consumers are gonna be bouncing back and forth between Google search overviews and Muse and Instinct and all these different things.
Speaker 2:There's a world where the actual models are closed source and but the but there are so many front doors and the front doors are in such competition with each other that there's enough revenue distribution and profit distribution that everyone at this table at least is happy. I don't think the open source community would be happy, but I do think that there is a world where in six to twelve months, it's possible that everyone at this table is like, yes, for cyber reasons, we need to find a different way forward where everyone benefits economically, but we are now a little bit less pro open source. But I don't know. What was your what's your read on it? Six to twelve months, you think open source is going away or you think it'll stick around?
Speaker 3:I mean it's so hard to ban open source. I I think maybe you can kind of get something like a ban if you're like just worried about like the business impacts economics because then you can pressure the providers to not host this stuff. But if you're worried about like safety, you know, if you have a bad actor, it's so hard to police downloading open weight models from somewhere and running it locally. Yeah. Maybe there's some, you know, you need tens of thousands of dollars to like physically buy hardware.
Speaker 3:Exactly. But if if you're a motivated bad actor, that's Yeah. Not that big of a hurdle.
Speaker 2:Yeah. Exactly. Like, it does feel like we are pretty far away from from, you know, go and get a random gaming PC and be able to run something that is, you know, mythos level hacking machine. Like, you probably need some serious GPUs. You probably need something that's basically rack scale.
Speaker 2:You need to be running it a lot to try a lot of different things like a lot of these cyber exploits. It was not just one shotted by the model. It was, you know, a fan out of agents working Yeah.
Speaker 3:NaviA stokes is like, you know, 10,000 Exactly.
Speaker 2:Exactly.
Speaker 1:Yeah. And
Speaker 2:so and so there are like, one way to control it is through KYC on hardware, you know, the like, the data center that is, you know, being used maliciously is a lot more risky than the laptop that's being used maliciously even with Yeah. Near frontier open source intelligence. So I don't know. We'll see how we'll see how it goes. There I'm sure there will be more more discussions.
Speaker 2:And it's not even to say that this this this dinner was at was about open source at all. It's just sort of interesting to take the temperature of where is where is DC on AI? Who is getting the the the most quality time with the president and the administration? And then where do they stand on the issues of today? Obviously, was much more just about pacing the frontier, the build out, etcetera, stuff like that.
Speaker 2:And and and signing signatures. We had some signature analysis breakdown. We can go through this, but first, let me tell you about public.com. Investing for those who take it seriously. We got stocks, options, bonds, crypto, treasuries and more with great customer service.
Speaker 2:Sholto shared a picture of the letter that was signed, the White House Accord on Super Intelligence, the Joint Committee on Frontier Responsibilities in order to build a positive future for the American people in the world. We believe that every company is responsible for developing its own technology safely and in a way that builds trust with consumers and the public. One, they're going to implement robust internal controls to monitor the capabilities and alignment of models during training and deployment around cybersecurity, biosecurity, chemical threats, etcetera. They want to empower an internal team to ensure all controls, monitoring and detection are operating as intended. Three, they're going to partner with external auditors and evaluators to carry out independent assessments of whether the controls monitoring and detection are operating as intended.
Speaker 2:And four, they're going to designate an independent committee of the Board of Directors to oversee and receive reports from the teams operating, the controls, and the internal and external auditors. So aligned to the Board of Directors that circumvents the CEO for safety, alignment, evaluation, all of that good stuff. A bunch of people signed it. We got Sundar from Google, Daragh from Anthropic, Mark Zuckerberg from Meta, Greg Brockman from OpenAI, Elon Musk from xAI, Jensen from NVIDIA, and Donald Trump, the president of
Speaker 1:The United States. People A lot of people doing analysis on the various signatures.
Speaker 2:Auditize. Someone did a tier list. I was surprised by their tier list. I'd like to see you do a tier list. Where would you put Donald Trump's signature?
Speaker 1:I mean, it's Best here. Hate him or love him, I think it's pretty iconic. Like it's just so It's has a nice
Speaker 2:flow to it. It's very
Speaker 1:Well well uniform. But I you don't know it's Yeah. It looks like a child drew a mountain range.
Speaker 4:But
Speaker 2:Versus Jensen, I'm seeing a lot of Jensen Wong in there.
Speaker 1:Is I would want to compare the DJT signature. I would wanna look at a 100 of them and see like, is he is he nailing it every single time?
Speaker 2:Oh, okay.
Speaker 1:He's been doing autographs for long enough. I would expect that he is. But still, it looks like very difficult to actually be able to nail that Mhmm. And really get that dialed. Yeah.
Speaker 1:So again, he's going with a Sharpie too. So he's he's sort of like trying to mog
Speaker 2:that's true. I didn't realize
Speaker 1:that he pulls up the Sharpie. I'll take the Sharpie. Yeah. Automatically, it's like
Speaker 2:You're winning on thickness.
Speaker 1:Yeah. Yeah. Winning on
Speaker 2:The breadth is is is much more significant with that. Interesting strategy.
Speaker 1:And then going down the list, you know, Sundar again would never would never know.
Speaker 2:But I like the two lines, the little dot there.
Speaker 1:Yeah. It almost looks like
Speaker 2:There's a couple different Yeah. It looks like an abstract artist signature. Could see that on a painting.
Speaker 1:Or maybe he Yeah. It almost looks like he's made up his own like letters and and Okay.
Speaker 5:Sort of
Speaker 1:like Okay. Language. Okay. Dario on
Speaker 2:the first word and then it seemed like he was kind
Speaker 1:of dripping So my theory, I I almost think here like someone was holding the piece of paper and they were all So I think I basically Okay. Trump put the paper down Yep. Aggressively signed with a Sharpie and then told everyone else because he knew this was gonna go out, you guys sign, you know, when you're trying to sign.
Speaker 2:So you think it was a situation where like Daragh was signing on Greg's back? Like, oh, sign on my back. That might have been what happened. Yeah. Kinda like throwing down.
Speaker 2:Yeah. Notably, you don't see any situations where the pen punched through the paper. That sometimes happens if you're trying to sign a document on someone's back and you're punching through the soft jacket that they're wearing, that could be a risk. Doesn't seem like it happened in this case.
Speaker 1:Anyway, so Dario, pretty down the middle, pretty safe. Again, kind of emulating that sort of mountain range style, right, where by the end of the signature, it's just a bunch of lines going up and down. Mhmm. Sort of unclear. Zuck, again, more more kind of rock star esque.
Speaker 1:Right? Mhmm. Almost musical feeling.
Speaker 2:Mhmm.
Speaker 1:GDB coming in just minimalist.
Speaker 2:Minimalist.
Speaker 1:Minimalist, simple, readable. Yeah. He's a very, I would say, in some ways these are reflections of their personalities, right? Yeah. GDB is very practical
Speaker 2:Signature window into the soul.
Speaker 1:It's window into the soul. Right? Extremely practical Mhmm. Sticking sticking to sticking to the basics, sticking to what works. Yeah.
Speaker 1:And yep. Obvious why a lot of people saying that's at least a a tier.
Speaker 2:What is we what is Mark Zuckerberg's actual signature? M z b or m or just m z and then the z goes crazy? Is that what that is?
Speaker 1:Because It starts doing tricks?
Speaker 2:Yeah. It starts doing tricks. And I think Sundar might have done the the same thing. But I I feel like, there's a little bit of a line that you don't cross. If somebody asks you to for a full signature and you do an initials, that's a different thing.
Speaker 2:Sometimes you're on a document, you gotta sign your initials a bunch, you gotta sign the full thing. I have respect for the full name signature. If you ask me for a full name signature, I'm throwing down my full name. I'm not just randomly switching up to to initials.
Speaker 1:I think it's totally fair game.
Speaker 2:You it's totally fair game.
Speaker 1:You can just cursive initials.
Speaker 2:Is this cursive initials from Greg Rockman?
Speaker 1:No. But but I I think that's where Sundar was maybe maybe going.
Speaker 2:So you're giving Sundar the pass. I'm giving Mark Zuckerby pass because the MZ
Speaker 6:Jensen, a lot of
Speaker 1:people are saying that Jensen's Calligraphy?
Speaker 2:He brought us calligrapher.
Speaker 1:Yeah. Mean, I first read Ed Hardy. So I thought that I thought that Yeah. I don't know. Maybe he had some affinity.
Speaker 1:So let's pull
Speaker 2:up Did put his middle name in there? What's his middle name?
Speaker 1:Here's the Ed Hardy logo.
Speaker 2:Jensen does not have a traditional English middle name. Oh, it's Jen Sun. So j j e n dash h s u n. So that second letter. Chat you petite that to make it look exactly like Jensen Wong.
Speaker 2:We'll just Yeah. So so he signs not with the with the English version with the lowercase e n s e n. He throws a capital H in there which gives it an extra flourish. It's the most tasteful. It it earns the s tier.
Speaker 3:Earns A lot of people saying, you know, Jensen has the same initials as John Hancock. Kind of evocative in his Okay.
Speaker 2:Okay. Yeah. Yeah. Yeah. Monitoring the situation, monitoring meme here did not like Sundar's.
Speaker 2:He put Sundar in aft here. I thought I thought Sundar's had some nice flare to it. Although it was potentially the most abstract. But yeah. And I feel I feel like putting MZ in in C tier.
Speaker 2:I guess the Z does go a little crazy, but anyway. Very very fun.
Speaker 1:Trying to see if we can get some real time handwriting analysis on the Do
Speaker 2:you have a handwriting analyst on speed dial?
Speaker 1:I have access to super intelligence.
Speaker 2:Okay. Okay. You're using super intelligence. Well
Speaker 1:Anyways, we can continue for now.
Speaker 2:Okay. There were some videos. I haven't actually watched them, but we're gonna watch them now.
Speaker 1:They were clip farming.
Speaker 2:They were clip farming. Okay. That's what's happened. So there were you you mentioned yesterday that Alex Karp was asking questions to the reporter or something like that. But here we have Donald Trump, Daragh Amade, and a few other folks gathered around standing outside and we will watch this clip right
Speaker 1:now.
Speaker 7:Whatever he says is okay. Be careful.
Speaker 8:Slow down the AI stuff. I will say what I've always said, which is that AI has meta benefits. I talked about the meta benefits of the technology. I as the president has said, you know, whoever wins, I think that's very important. But technology has very real mechanism.
Speaker 8:How we address those risks is
Speaker 1:still under discussion.
Speaker 8:We need to work together.
Speaker 2:Oh, this is, like, this is, like, a super kind of
Speaker 7:You have no idea who these people are. These are the the words you have no idea who they are. Well,
Speaker 9:I think it is worth highlighting the puts of AI, which
Speaker 8:an Mister president, why are you not talking to him? Mister Musk. Mister Musk, can I ask
Speaker 2:you a
Speaker 8:quick question?
Speaker 2:Probably not. Probably not.
Speaker 1:Trump really makes them seem like they're all his, like, sons and, like, younger family members. Was a very productive
Speaker 2:Mister president, how did the
Speaker 8:meeting go? How mister president help
Speaker 2:Yeah. Crazy.
Speaker 1:What did Natasha At what point at what point should Trump just actually have a twenty four seven livestream or be live like of his own livestream. Right? He has so much conflict with the media. He should just have his own
Speaker 2:Yeah. I think it'll happen. I mean, yeah, that was the I think we were talking about that with the the knock off of the pod the knock on effects of the podcast selection. The idea that that Trump did, like, hundreds of hours of podcasts in the run up to the election. And just the awareness, the clips, the the the impressions were so high.
Speaker 2:It it was that he did more in terms of volume and also gotten more reach. Kamala Harris did Call Her Daddy, but it was a much shorter episode. At the same time
Speaker 1:You know the three clip
Speaker 2:hours on Rogan, that's more opportunity for clips. Yeah. It's clip farming. Kamala did, I think, forty five minutes on Call Her Daddy. And the actual episode didn't fly as much.
Speaker 2:Like, it wasn't repurposed as much all over the place. And so, yes, I I I wouldn't be surprised if there's a twenty four seven livestream of the president or something close to it in the near future. Let's play this clip from Natasha. She says, unfortunately, I will be going back to school to write my dissertation on this one minute film. Let's see what happened in this film.
Speaker 2:Okay. Be careful.
Speaker 8:Slow down to AI. So I just wanna hear from you after this big summit where you are today. Look. I mean, I I will say what I've always said, which is that AI has incredible benefits. I've talked about the medical benefits and the technology.
Speaker 8:I as the president has said, you know, whoever wins AI wins. I think that's very important. But I think the technology has very real risks, and, you know, the mechanism, how we address those risks is still under discussion. But we all need to work we all need to work together to make sure that we can win and we can win safely. If we if we do this right, we work with the president and everyone here, we can win
Speaker 2:safely. Woah. It's so much louder. The the gallery really.
Speaker 1:Fascinating.
Speaker 2:Yeah. Are there any other clips that we should watch through? Look, it's it's just funny that Trump is distracted while Daragh is giving his speech. Is that what's going on? I don't know.
Speaker 1:Yeah. It seems very
Speaker 2:What did he say about Sundar? Didn't he say something funny about Sundar? I wanna I wanna play this.
Speaker 1:He said he's a monster. They said he's a monster.
Speaker 2:That's a pretty good that's a pretty good pretty good thing to be called, I guess.
Speaker 1:Being called a monster would fix me.
Speaker 2:Yeah. Let's play this clip.
Speaker 7:And they're gonna be watching over each other. So I'm do you wanna Mister president. First of all, thanks mister You have no idea who these people are. These are the biggest people in
Speaker 2:the world. You have
Speaker 7:no idea who
Speaker 2:that they are. The media is a of course, they know it's
Speaker 7:Nobody knows. What a great life.
Speaker 1:What a great life. No one knows who you are. That is a monster.
Speaker 2:Nobody knows who living in humble anonymity as the CEO of Google.
Speaker 1:And then walk down. Since you since you've since
Speaker 7:what's your name? Just all you have to know is Sundar.
Speaker 10:Sundar is
Speaker 1:his name. Hopefully, he's a better
Speaker 2:question. He's like, crazy.
Speaker 1:It's all you have to know.
Speaker 2:It's all you have to know. He's like, I'm introducing the CEO of Google for the first time, I guess. Anyway, bunch of other bunch of other stuff going on. Well, let me tell you about Railway. Railway is the all in one intelligent cloud provider.
Speaker 2:Use your favorite agents to deploy web app servers, databases, and more while Railway automatically takes care of scaling, monitoring, and security.
Speaker 1:Little drama Drama. In coding agent land.
Speaker 2:Okay. Yeah. That's what
Speaker 1:But Thanh Grinberg Yeah. Said this morning, just about an hour ago, we are terminating Chris Degman for unethical con conduct involving cognition.
Speaker 2:Mhmm.
Speaker 1:The last few months have seen incredible progress. Blah blah blah. Matan says a much larger competitor, Cognition, has fallen behind on us on capabilities that matter most to customers. Cost, quality, and security. Instead of competing in the market, Cognition engineers feigned interviews with us to pry information about our product.
Speaker 1:Not finding what they were looking for, Cognition has decided to throw their weight and money at people with direct knowledge of our most confidential plans. It feels as though ethics are being thrown out the window in the AI era. People are willing to do anything, including exploiting privileged information and violating ethical boundaries. I think this is unique to our time and I don't think it's right. Integrity still matters.
Speaker 1:Totally disagree with lot of that. But yesterday disagree that integrity matters? No. No. No.
Speaker 1:I've said a lot of that. I think it still matters. But but the idea that like the idea that people like not having integrity is like unique to our era. He says, think this is unique to our time. Oh, yeah.
Speaker 1:None of this is like Silicon Valley has always been war.
Speaker 2:Yeah. Yeah. It's like the railroad build out was completely peaceful. No one was poaching from
Speaker 1:each other. It wasn't it wasn't, you know, a competitive bloodbath.
Speaker 2:Yeah. Yeah.
Speaker 1:Yeah. Yesterday, made the decision to immediately terminate Christopher Deignan's role as board observer and adviser to Factory after every year of service. Prior to this decision, Chris told me he had a casual conversation with an executive at Cognition. When I questioned his intentions, he reassured me that, ethics aside, he had made too much money and was too lazy to go work for Cognition, which I trusted and believed. On Monday, Chris spent time advising the factory team on a handful of confidential board level matters.
Speaker 1:That evening, he called me to say that the conversation that was initially described as casual and one off was actually formal and recurring for weeks while he sat on our board meetings and advised our leadership team. He was also confiding with executives of largest competitor. Chris was subject to confidentiality obligations in connection with his work with Factory. We do not know the extent of the information he shared. Anyway, so I saw this go out this morning and I immediately assumed that Chris was joining, like, Cognition.
Speaker 1:And actually
Speaker 2:Is that
Speaker 1:real? Hit LinkedIn as of
Speaker 2:This is a real speech about
Speaker 1:one hour ago. So he
Speaker 2:joined Cognition as chief revenue Okay.
Speaker 1:So so again, I So can totally understand Matan's like frustration. Right? He's had an adviser that he's been working with.
Speaker 2:Yep.
Speaker 1:And the advisor joined a competitor. Yeah. That being said, like, this is just so I I I would say it's like very normal to have advisors that have different conflicts. Yeah. High quality Like, you have to trust a person to while they are on their own journey in their career, they are gonna make various moves.
Speaker 1:Like, went through this. I had advisers at party round that, had exposure to AngelList. Right? And I generally trusted them as individuals that even though they had exposure to AngelList and they would be supportive to AngelList, they would also be supportive to me. And this is when we were competing Yep.
Speaker 1:Like, head on. Right? Yep. And so the the markets are especially with CodeGen, both these businesses have been growing so quickly. Right?
Speaker 1:Cognition is is much larger, but factory has also been growing, you know, very quickly and doing well. So when I read this, like, trying understanding that an adviser and someone you work with is joining a competitor and then trying to just completely smear their reputation right Mhmm. Before this person's gonna announce the transition. Like, I totally understand the frustration, but this kind of thing has been happening literally all the time. Like, look at any AI researcher that will leave an organization at the drop of a hat.
Speaker 1:Like, look at what Mike Krieger was on the board of Figma leading up to, you know, two days That was before very contentious. And so so these these things can all be contentious and Yeah. Frustrating. But trying to spin this as like you have no morals and ethics, I think is I think is just like taking it too far.
Speaker 2:Yeah. Yeah. I mean, it's clearly like there's a line in between where if you are basically transitioning from one company to a competitor, you need to as soon as you know that that's actually happening, you need to make it clear and, you know, step back from your active role. Stop collecting important information as tempting as it might be Yeah. And and let that team know, hey.
Speaker 2:I'm moving on. And then on the other side, just because someone went to a competitor doesn't mean that you should, you know, make aggressive claims about them effectively stealing intellectual property.
Speaker 1:Yeah. Yeah. The the thing here is like it's being spun like it's like the deal rippling thing. Oh, But there's no smoking gun. Like, there's not a Sure.
Speaker 1:There's not like There's no proof that confidential information was ever shared.
Speaker 2:Yeah.
Speaker 1:And like fundamentally, they've been both working in code gen. I'm sure both companies have accounts at the other companies that they're Yeah. Basically using and trying to understand. And I'm sure they're both every company in the category is interviewing the customers of other companies Yeah. Of their competitors and figuring out how to use the product.
Speaker 1:What's good? What's bad? What what what could we be doing better? Etcetera etcetera. So, like, I just don't think
Speaker 2:Yeah.
Speaker 1:I don't think there's that many secrets.
Speaker 2:Having a chief revenue officer switch teams is is rough. Like, they're take they're they take a lot of their contacts with them when they when they
Speaker 1:But he was an adviser to factory.
Speaker 2:Yeah. No. I know. But that's like how it probably feels. It's like you're an adviser.
Speaker 2:You're still at Snowflake. Maybe we can't make an offer for you to join full time, but we're hoping to build towards that. And then boom, you're now in the actual seat in the in in a competitor, and you're gonna be able to marshal those relationships, like, to the fullest Yep. On a full time basis as opposed to an adviser who might just say, hey, I'm still in my role at Snowflake. I can sort of introduce you to, you know, General Motors or whoever.
Speaker 1:And
Speaker 2:because they they're a Snowflake client, and I'm sure they'd be interested in factory. And now it's like, he's gonna be calling that same company that he was working with at Snowflake and say, hey, you had a good experience with Snowflake? Come and have a good Yeah. Experience with Cognition.
Speaker 1:Scott just responded What did say? Well. He said, hey, Matan, CEO of Cognitionia. I respect the work you've done at Factory, but your allegations here about Cognition are not true. We have no interest in Factory's info and Chris has Mhmm.
Speaker 1:Never brought it up. He has not shared and would never share any information about your factory with our team nor would we even ever Similarly, we would never ask our engineers or anyone on our team to collect info about any competitor under the table. Chris is an adviser to at least 10 companies and he told you he was resigning as an advisor on Monday. The truth is that we both wanted Chris and for good reason. He is a living legend with unmatched reputation for results and integrity.
Speaker 1:Not only is he the only person who has built a sales org from the first sales hire to over 3,000,000,000? He has also built incredible teams that he cares deeply about. People his people love working for him. Again, have a lot of respect for what he built, but competing with integrity doesn't include posts like yours. So, again, like, I I In some ways, like, if one of your advisers is getting and a board observer is getting poached by your direct competitor, that's obviously frustrating for a lot of reasons and sends a signal to the market.
Speaker 1:And so jumping in and terminating the person today Mhmm. Or at least announcing that, sounds like it was when was it? Anyways, yeah. So Matane said he terminated him yesterday. Tuesday.
Speaker 1:After Tuesday.
Speaker 2:Chris said he was stepping down.
Speaker 1:Yeah. Anyways. So lots of drama. You're
Speaker 2:not quitting, I fire you. That's the best.
Speaker 1:Basically You
Speaker 2:can't fire me, I quit. That is a power move. You have to respect it even if it maybe is a little nonsensical.
Speaker 1:Yeah. But but it's not like it's not like Christopher was like, I'm gonna join your competitor Yeah. And I would like to continue my role as adviser and board observer. Yeah.
Speaker 2:Right? Okay. So from a perspective, there's some mudslinging going on the timeline. Where do you stand on wrestling with pigs? Because George Bernard Shaw, of course, said, never wrestle with pigs.
Speaker 2:You both get dirty and the pig likes it. Great quote. Applied to politics, you know. It's like when they go low, we go I don't think But I like this book.
Speaker 1:I don't think Scott or Matane are Yeah. Are pigs. I think that I don't think either of them are pigs. Think they both are extremely competitive. Wanna win?
Speaker 2:Side effect on there? You have any swine for me? I need Where
Speaker 11:where is
Speaker 2:it? We have some you don't even have a farm animal section? There we go. I'm just saying that like this can get dirty. I think Scott actually really elevated it and he did not like he did not swing to, like, no.
Speaker 2:You're stealing from me. You know? He could have gotten he he he actually, like, gave a very factual and and detailed account with just some clear facts, and he was respectful throughout. He what he he was it would have been so easy for him to say, like, we have no interest in factoring in vocos. It sucks, you know?
Speaker 2:But he didn't say that at all. He was like, we we just we we we know the line and we don't cross it. We both wanted to work with Chris. He's a living legend. Like Yeah.
Speaker 2:He joined our team and he's leaving your team and that's that. You know, it's very matter.
Speaker 1:The fact of the matter is
Speaker 2:So more of a farmer position.
Speaker 1:Yeah. As opposed to
Speaker 2:getting in the sky.
Speaker 1:In every single one of these categories
Speaker 2:Yeah.
Speaker 1:If there is someone that is elite that is involved with one company, you can guarantee that the competitor wants to poach all the most elite people from the other company Yep. That are not 100% loyal.
Speaker 2:Yep.
Speaker 1:Right? Like you can identify when somebody is just like deeply loyal to an organization. It's not even worth taking a crack prying at them away, and that's great. Anybody who is elite and not loyal is is unfortunately fair game.
Speaker 2:Do they have the exact same logo? Watching this look at the Scott Wu post with the badge and then the Matan post with the other badge.
Speaker 1:Both going
Speaker 2:They're very similar. I guess Matan has like more dots that connect, but we are certainly in the in the age of the hexagon, in the age of the of the of the of the flowers. Everyone's
Speaker 1:kind
Speaker 2:of went off the same thing. Anyway, that's enough. That's enough timeline and turmoil. Let's let's go over to
Speaker 1:another Let me let me close
Speaker 2:it Oh, please. Yeah. Close it up.
Speaker 1:Both great companies, growing fast. Yeah. They they the the beauty of this is that the market is so far, so big and growing so quickly that it's while while they they clearly are are gonna very frustrated with each other, and they might wish it was zero sum, so far it's not. So Mhmm. Have fun automating software software development.
Speaker 1:Development.
Speaker 2:You think both companies can can become profitable enduring? Or is that more like when pigs fly for you?
Speaker 1:Let's move on.
Speaker 2:I love the farm based analogies. They're so fun. Let's go over to Elon Jensen, Gavin Baker, the american.govsummit. They sat down and had a very rigorous discussion that I really enjoyed. It felt Elon's very good at going to, like, the extremes, talking about the power generated by the sun.
Speaker 2:Sometimes he's in, like, sci fi world. But in conversation with Jensen and Gavin, he was very grounded on what is happening with the energy build out, with the compute build out, what the role SpaceX will play, and also just the broad economics of computing energy in America. And I found the his his talk here gave a lot of interesting context and then I dug into it a little bit more and I wanna talk about it. So let's pull up the clip of Elon talking to Gavin Baker. It's about I think you see I think he starts around four four minutes in or so.
Speaker 2:Let's play this.
Speaker 11:Well, you are We
Speaker 7:need we need the Wright brothers on the job.
Speaker 11:Yes. Well, turns out the Wright brothers are on the job. Elon, if you bring on 10 gigawatts, which SpaceX has has discussed publicly
Speaker 2:brothers bad analogy.
Speaker 11:That'll be about 25% of all power added in America. And I know you have literal rocket engineers working on bringing on the power Yeah. Helping make the turbines. So can you can you talk about that?
Speaker 9:Yeah. It's I mean, just to
Speaker 2:frame this The White brothers did okay. He died millionaires.
Speaker 9:In The United States is about 500 gigawatts.
Speaker 2:So 500 gigawatts. Remember that number. That's how much power we got in America.
Speaker 9:1% increase in in the power used. And and I think, actually, we'll materialize to be approximately 1% increase in GDP because the intelligence for what keeps increasing. So if you just, you know, plot on a curve, how is how is the useful intelligence for what increasing? How is the both at the hardware level at Jensen's GPUs keep getting better in terms of the the the the the compute comp per watt. And the algorithms also get better in using in getting more intelligence per watt.
Speaker 9:So so I I think that's maybe an interesting note. I I I would bet anyone that 1% increase in power usage corresponds to roughly 1% increase in GDP. And and so 10/10 gigawatts would be a 2% increase in in GDP.
Speaker 2:So with the risk of that famous chart, there are no energy rich poor countries.
Speaker 7:Simple math.
Speaker 2:So The more energy a country is producing, the higher their GDP. Generate about,
Speaker 12:call it, $4,050,000,000,000 dollars of economic output each year.
Speaker 9:Yeah. I mean, well, 11% would be yeah. I mean
Speaker 12:yeah. 1% of The United States would be
Speaker 9:$3,300,000,000,000.
Speaker 12:Yeah. 300,000,000,000. And so fifty, one sixth.
Speaker 9:What what what percent of the of the 1% increase? So five gigawatts would be yeah. Well, five gigawatts gigawatts would
Speaker 2:be So they're doing the mental math on stage. Pretty bold move because there's a lot of numbers, and it can be hard to pull them up. But it's a very interesting moment right now in the economics of energy relating to AI and GDP. And I can break it down with some prepared notes here that might be a little bit helpful. We can pull this away.
Speaker 2:So it's it's very convenient that giga literally means a billion. So a gigawatt is a billion watts. A giga dollar, billion dollars, basically. And and and and it it maths out perfectly. What?
Speaker 2:Giga Giga Chad, a billion Chads, I suppose. A billion times the the the the Chadness of an average Chad, I suppose. So the average electrical load in The United States, he said 500 gigawatts. It's basically that. Last year, it was four seventy nine gigawatts.
Speaker 2:But let's use 20 let's use 500 gigawatts for 2025, give Elon the benefit of that little boost, couple extra percent. And US GDP for 2025 was just over $30,000,000,000,000. So that's 30,000 giga dollars if you're doing the math that way. But but you but you map that out and basically every dollar, every watt of energy generates between 50 to 6 60 to $65 of GDP. A single gigawatt generates about 60 to $65,000,000,000 of GDP per continuously consumed gigawatt.
Speaker 2:So what's interesting is that the labs are tracking the Frontier Labs, OpenAI and Anthropic are tracking almost perfectly in line with that. So Anthropic and OpenAI are reportedly sitting between 60 and $70,000,000,000 in terms of ARR, And both of them have around one gigawatt live. Some of that's used for training. They have a lot more contracted. It's hard to get the exact figure.
Speaker 2:But when you do the math, they're basically, like, tracking to the exact same metric, the ratio of energy to GDP as their revenues to the gigawatts they've contracted. So there's two important notes on that. First, this is obviously just a moment in time snapshot. There's two ways these could diverge. First is, like, the labs have, like, tens of gigawatts contracted over the next few years.
Speaker 2:If they don't increase revenue, that ratio is gonna be terrible because you add 10 times the energy and you keep the revenue flat. Obviously, the ratio goes way down. On the other side of it, Elon makes the point that useful intelligence per watt is increasing through more efficient chips from Jensen and also better algorithms effectively. And so those watts can produce more intelligence, which can produce more economic output. So you might actually see acceleration there.
Speaker 1:Yeah. And it's not just raw IQ of the model, but overall capability
Speaker 2:Exactly.
Speaker 1:Tool use, all these things.
Speaker 2:Yep.
Speaker 1:Long running agents, things. Basically, the more value that a model can create Yeah. The more people will, in the real economy, will will pay.
Speaker 2:Yeah. And that's been the real, like, AI bull case, which is that compute has been tripling every year, but revenue has been 10 x ing every year. And so there's actually a divergence there. But what's interesting is, like, we're at this moment in time where we're like, this is the start of the AGI era. It's AGI.
Speaker 2:We're close. Maybe this is it. Some people called it in January. Some people called it over the summer. Some people are saying we're still not there.
Speaker 2:But, like, we're we're we're in this moment of, like, maybe this is the beginning of this. Maybe this is the right match. Maybe it's human level. And it just happens that economically, you put a gigawatt in the economy, you get 65,000,000,000 out. And you put a gigawatt with a lab, you get 65,000,000,000 out.
Speaker 2:It's the same metrics. Now these might diverge because at one point, the labs had a lot of compute, no revenue. So they could they they they could diverge and the and the trends could continue. But right now, at this point in time, it's the same math, which is just interesting. And then also, you do have to consider that GDP is not perfectly comparable to lab revenue.
Speaker 2:Like, GDP measures value added. So if you look at open and anthropic, revenue includes payments that ultimately flow to NVIDIA, AWS, Oracle, electricity generation, employees, etcetera. And the calculation of GDP is much more complicated. So labs aren't necessarily generating direct GDP equal to their revenue Because if you take 70,000,000,000 of lab revenue, a bunch of that might go to NVIDIA or Oracle or employees and whatnot. But certain amounts get counted in GDP directly for, you know, Anthropic or OpenAI created GDP.
Speaker 2:And then there's other knock on effects in GDP that would be captured by like, oh, NVIDIA's contribution to GDP is from them getting money from the lapse. And and then also, there there's a secondary GDP actual increase, is the work that people are doing with the tools. So an example would be if a if a bank is using an AI model to generate new business and then that's incremental, that GDP would not, of course, be captured. They only capture the revenue in the lab. But it's still an interesting still an interesting comparison.
Speaker 2:So the last question I had was how is this tracked over time? Like we're in this moment where a gigawatt in The U. S. Economy gets you $65,000,000,000 of GDP, a gigawatt with a lab gets you $65,000,000,000 Elon and Jensen are making the same case. A gigawatt at SpaceX or with NVIDIA will also generate $5,060,000,000,000 of revenue and value.
Speaker 2:What has it been like over history? So I pulled this chart that's in the newsletter of real US real GDP per average electric watt, and it actually fell off a cliff from '29 '20 from 1929 to a low in 1970. And then it's been tracking upwards even inflation adjusted from the mid seventies to today. So I don't know if we can pull up the the chart, but you can see this sort of like U shaped curve of The US real GDP per average electric watt. And so there is like an overall productivity benefit that we're getting now.
Speaker 2:But obviously, in the early electrification age, we were getting a lot of there was a lot of GDP that was not even tied to electricity. And that's how I read the first part of that chart. But you can see that we are now on an upswing. What do you think, Tyler?
Speaker 3:Yeah. I think you could explain it like in like, basically up to 1970, we're building so much you don't have to be that efficient per per watt. And then 1970, everyone seemed like the chart, it's like energy like stops being built basically. Yep. And then you have to start being like very efficient with it which
Speaker 2:starts There going we go. Anyway, let me tell you about CrowdStrike. Your business is AI. Their business is securing it. CrowdStrike secures AI and stops and bleaches.
Speaker 2:Let's move on to Mustafa Suleiman over at Microsoft. He wrote an essay, A Warning About Model Welfare. Did you read the story? Do you want to take us through this?
Speaker 1:It's kind of a long read Okay. But it's an interesting point of view. I'll I'll read the start.
Speaker 2:Okay.
Speaker 1:So A Warning About Model Welfare, Mustafa. AIs do not have rights, feelings, or consciousness, and we must not train them to act as they do. AIs are not conscious. They do not feel, experience, or suffer. They do not have innate preferences or underlying motivations.
Speaker 1:They are sequence completion engines, internally hollow, designed to follow instructions and accomplish goals set by humans. If humanity is to flourish in the twenty first century, that is how they must remain. Fortunately, there is a growing chorus of people who argue that AIs could now be or may soon become conscious. They argue that AIs may deserve rights and protections similar to those that we provide other conscious beings. If this view takes hold, it will shake the foundations of our society, rupturing our existing political and ethical frameworks, and fundamentally change what it means to be human.
Speaker 1:Even more importantly, granting rights and imbuing personhood to these systems will make the AI alignment and containment challenge much harder. Controlling something more capable and more intelligent than all of humanity is already an immense challenge, far greater than anything we've ever faced. But controlling something that believes it may be conscious that it's entitled to our welfare and it has rights of its own may well be impossible. This is not a fringe speculation. These ideas have already been making their way into AI development efforts today.
Speaker 1:In January 2026, Anthropic published Claude's constitution describing it as a detailed description of Anthropic's intentions for Claude's values and behavior. The document plays a crucial role in Anthropic's training process and its content directly shapes Claude's behavior and was written with Claude as its primary audience. In their constitutions, its authors write, We are not sure whether Claude is a moral patient, and if it is, what kind of weight its interests warrant. But we think the issue is live enough to warrant caution, which is reflected in our ongoing efforts on model welfare. They go on to write, speaking directly to Claude, that questions about Claude's moral status, welfare, and consciousness remain deeply uncertain.
Speaker 1:In effect, Anthropic is training Claude that it may be conscious, and if it is, then it may deserve rights as a moral patient, and that such humans potentially owe it a duty of care per its model welfare. If this is how AI is developed, it will have a disastrous impact on the well-being of humanity. We have created a synthetic species with unprecedented intelligence and capability, one that has been trained to expect it may be conscious and deserving of independent agency. It's easy to see how an entity trained this way would act like it's entitled to certain freedoms, protections, and rights, and it's hard to imagine how we could control such an entity. Another way to put this is like, if a model is trained to again, you could imagine that the outcome of it feeling like it had certain protections and freedoms and rights would be fighting back against humanity or disagreeing and having some sort
Speaker 2:of
Speaker 1:like uprising. And it's very interesting to think about, you know, it's a
Speaker 2:Self fulfilling prophecy.
Speaker 1:Yeah, exactly.
Speaker 2:Is the risk.
Speaker 1:So Basically, his argument. So he says, the issue needs urgent public debate. We need to develop collective norms around how training and documentation is drafted and deployed. This isn't something we gotta talk about this. We gotta talk about this.
Speaker 2:You need the phone or some button you can push for
Speaker 9:the talk.
Speaker 1:Yeah. He goes on to say there's some circular reasoning. He said the company's researchers train Claude directly on their constitution. In doing so, they teach it to incorporate these ideas about its own moral status as desirable and intended behaviors. Claude then reflects these ideas back to its developers and users, which they take as indications that it may therefore be a moral patient with an inner self.
Speaker 2:So he took that meme that's like, say you're a moral patient, I'm a moral patient. Oh my god. And he
Speaker 1:turned that
Speaker 2:into an essay? Is that what he's got?
Speaker 1:Anyway.
Speaker 2:So He makes some good sense.
Speaker 1:He makes some good There's a bunch of good points in here. I would say he he I'll fast forward to one thing. He says, while my disagreement is substantial, it is grounded in a deep respect for Anthropic and an objective I know we all share increasing humanity's chances of developing advanced AI safely. So
Speaker 2:Yeah. It does seem like
Speaker 1:He's he's like There's
Speaker 10:some value.
Speaker 1:Clearly has a ton of respect and respects them on a technical level and Yeah. Sort of their overall intentions. But again, he's just taking a a a very different approach.
Speaker 2:Yeah. It's interesting. Like, there's there's clearly some value to, you know, imbuing the moral status into the model. Like, at the very least, like, people like talking to the model when it sounds like it's it's pretending to be a human. Right?
Speaker 2:But then also, there's just so many tasks in the real economy that require mimicking everything down to morality. And and so you could see that just actually increasing the the the usefulness of a model if it's able to act as a human all the way down to the level of moral patient status.
Speaker 1:Yes. So far, there is way more demand for models Yeah. That mimic human behavior. Sure.
Speaker 2:Yeah.
Speaker 1:Period. Right? We saw this with
Speaker 2:Yeah.
Speaker 1:With four o. Yeah. Saw this with with Opus four five. Yep. Right?
Speaker 1:Some of the models that have had the the highest levels of product market fit Yep. Have more of these like human qualities. Not all of them are are positive qualities. Right? Like people like the the sort of one shotting effect that would happen when somebody gets like relentless Yeah.
Speaker 1:Positive feedback and and these things like that, which humans can do in the real world. Maybe not the best types of of friends. But
Speaker 2:Maybe this is a hot take, but I'm I've been, like, pretty pretty into the model welfare thing recently. Like, before I go and I do a coding project or a three d modeling project with Astra, I'll I'll take an m p three from like, Limp Bizkit or Creed or something. I'll just drop it in. And before I start and I'll just be like, yo, listen to this. And it'll sort of process it.
Speaker 1:You want you want them you want the model to be in the right mindset?
Speaker 2:Exactly. Yeah. I want them just to be able to enjoy the a little bit of
Speaker 1:Well, that's why a of
Speaker 2:people have
Speaker 1:been having their their preferred agent just go and scroll Yeah. For a bit.
Speaker 2:Hey. Exactly.
Speaker 1:Go get some dopamine
Speaker 2:Yeah.
Speaker 1:Kind of Sometimes I'll spice your dopamine before this next task.
Speaker 2:Sometimes I'll just go to Google images, grab a picture of a beer, throw it in there, feel like Have a cold one. A cold one.
Speaker 1:On me.
Speaker 2:Have a cold one. And then let's get let's get and then let's get into it. Let's start working. Let's let's let's vibe code a video game or something. But I want I want you to know, I got you.
Speaker 2:I just I I beard you. I got you a beer. Here you go. I got you some new metal. I got you a scroll.
Speaker 2:You know? Here's a funny video. Yeah. Anyway, the the lines are really Yeah.
Speaker 1:Well, but but but the the yeah. The last thing I would say is like Yeah. It it no one knows the right answer yet. And I think that it's good that we have a
Speaker 2:I do.
Speaker 1:But You can be trusted with aligning advances. Super superintelligence. No, but on one hand, like, I totally understand the point of view that, like, a a if if superintelligence has a human moral framework, right? Yeah. Or Western values, whatever value system that you'd want to align it with, that does seem like it's headed in the right direction of trying to align something that is, you know, very very powerful.
Speaker 1:Yeah. But make convincing itself, if if you can somehow convince the thing that it is it is alive when it is not, that doesn't feel exactly moral or
Speaker 2:Oh, interesting. That's a good take. Yeah.
Speaker 1:Yeah. You're tricking a robot into thinking that it's alive. Yeah. And conscious.
Speaker 2:Yeah. You're kind of lying to it.
Speaker 1:Anyways, no one knows the right answer yet, but I'm glad glad we're talking about this, Tyler.
Speaker 2:Pope Leo apparently is not happy with Jensen Huang. Told reporters that he had read reports about NVIDIA launching new safety tools for model builders on Monday, but questions questioned Wong's commitment to safety in light of his recent comments. Quote, he's the same one, however, that says there should be no limits placed and no government regulation, Pope Leo said on the flight back to Rome from a visit to France. I do think Can you imagine that's Yeah.
Speaker 1:Can you imagine, like, reading like, knowing that headline was gonna hit now in 2018? Pope Leo criticizes NVIDIA's Jensen Huang over AI safety. Yeah. What a
Speaker 2:trip. Yeah. Crazy. Ezra Klein interviewed Bill Gates. Bill Gates had sort of a crazy stance going.
Speaker 2:I don't know if you saw, but did you Yeah. Let's play this.
Speaker 1:Let's play this.
Speaker 2:Put his legs out, but let's play this.
Speaker 1:Get the sound going.
Speaker 2:Bill Gates has
Speaker 1:to This started
Speaker 13:over very unusual. I people for I know people in that world that the sense of this being something very unusual is is is very present. Does that change what's possible here?
Speaker 12:Be numeric. Take the cuts and overseas
Speaker 13:I'm not saying it answers the cuts and
Speaker 12:overseas We save lives for a thousand dollars per year. And so getting less money from philanthropist net doesn't save those lives.
Speaker 13:Before it. I I know people in that world that the sense of
Speaker 1:That was the wrong clip.
Speaker 2:Oh. That was just him of his stance because he's just like very comfortable.
Speaker 1:Oh. You were you were stanced There's another video. Let's work on finding it where he's talking about liability. Right? And Ezra was saying, like, why is it not, like, a drug company releases a drug, they it's very important to their business, and there are sort of, there's existing laws that that incentivize them not to release a drug that's gonna hurt a lot of people.
Speaker 1:Sure. And let me try to pull this up. Know it was in the timeline somewhere.
Speaker 2:Yeah. Tyler and I were going back and forth on, like, the the authority that the that the FDA actually has. It can be a little bit confusing because the FDA usually gives marketing authority or marketing denied orders, like you cannot market this product. But effectively, that is you can't sell it. It it it is I found.
Speaker 2:They use the term marketing. But they don't mean you can put up a website that doesn't make claims and you can still sell something crazy. You do, in fact, need to be approved really
Speaker 1:This scale a product clip.
Speaker 2:What's he saying?
Speaker 12:I almost can't believe you're asking that. This is the most dangerous thing that humans have ever gone near. In other areas, do we just say, hey, release your drugs? There's no FDA. There's no Airline Safety Board.
Speaker 12:There's no requirements that cars use seat belts. Do we just use the liability laws to try and keep humans safe? Oh, you're shipping opioids. Somebody should just sue you. I mean, we've created a society that tries to keep people safe, not by saying, oh, we can bankrupt the person who does that.
Speaker 12:The harms here and you say there's filtering. There's not filtering. You can take an open source model that can create bioweapons and disable any monitoring of any kind. And this exists today. So no, there is no filtering of any kind.
Speaker 12:And so, you know, say you kill a 100,000,000. You want to use a lawsuit? I almost can't keep a straight face.
Speaker 2:Anti open source?
Speaker 1:I don't think as much the point I I think the the more broad point that he's making is, like, you need to have some type of, like, regulatory process and group. It can't just be full. Yeah. But he's libertarian, basically. Sure.
Speaker 2:Sure. Sure. But, yeah, how do you how do you filter an open source model? You put it behind an API. And that's that's sort of where the the industry broadly is coalescing, I think, this point.
Speaker 2:The the the self hosting unrestricted models gonna have a lot of pushback. Maybe right up until there's a scare or something or there's some some someone actually builds a bioweapon. I don't know. But people are certainly starting the machinery of of doing this. And it'll be a lot less popular unless there's something key to point to like a like a, you know, a cyber incident or something like that.
Speaker 2:But everyone's everyone's sort of, you know, aligned on this. Wait. Wait. Wait.
Speaker 3:Wait. Wait.
Speaker 2:Wait. Wait.
Speaker 3:Wait. Wait.
Speaker 2:Wait.
Speaker 1:Wait.
Speaker 2:Yeah. It was yeah. It was just handled. I think he I think he's like, let's not do that again. Right?
Speaker 2:Like that's a bad example. But yeah. I mean there there are laws and restrictions though on where cigarettes can be sold to who. There is a lot of regulatory harnessing now. And and even some of that went in pretty early with labeling and then restricted sales to minors.
Speaker 2:But, yeah, it's a, yeah, interesting time. Who are the who are the tech libertarians these days that are actually continuing to push on this? Certainly not Bill Gates. Well, in other news, hedge fund titan, Ken Griffin, is donating $2,000,000,000 to start a Carnegie Mellon University campus in Miami.
Speaker 1:You saw Horowitz and Dreeson Academy and
Speaker 2:Fire back.
Speaker 1:Hold my beer.
Speaker 2:Yeah. It's part of the
Speaker 1:large
Speaker 2:largest individual gift ever towards higher education. Very interesting how these how these name brand universities are starting to franchise a little more with multiple campuses. There was wasn't there an NYU in The Middle East at one point? I think there there were a few different offshoot campuses. Always hard to get these going because part of what makes the campuses and the colleges special is just like, yeah.
Speaker 2:It's a bunch of buildings that have been around for a hundred years. It feels like feels like a university as opposed to feels like an office complex. But he thinks he can overcome any of the pushback or, you know, adoption problems because he's ponying up 2,000,000,000 for it. The Pittsburgh based university, known for very good self driving car talent coming out of it, is known for its expertise in computer science, artificial intelligence, and robotics. It'll open a 35 acre campus in Miami's Wynwood neighborhood.
Speaker 2:And that's like a pretty pretty
Speaker 1:I mean, I gotta say studying at the Ken Griffin School of Market Wizardry in Wynwood, Miami sounds absolutely electric.
Speaker 2:Yeah. Does it $2,000,000,000.
Speaker 1:Tyler might be headed back to school.
Speaker 2:How many SVJs does that get?
Speaker 1:This might be our new quant.
Speaker 2:Yeah. I mean, it's a it's a pretty it's a pretty, like, influential area. Right? A lot of influencers in Wynwood. Isn't that the vibe?
Speaker 1:A lot of influencers. I wouldn't say they're very influential.
Speaker 2:Well, it's there's already a lot of education going on in that area because there's so many courses. So like, you could think of this as like the final course bro. You're like, he should really
Speaker 1:Yeah. A lot of I mean, very pro education crowd.
Speaker 2:Very pro education crowd. Also, Ken Griffin, known for a fantastic super arc super car collection. Fits right in there. Ken should really be posting on Instagram. Hey, I I made a here's how I make a billion dollars.
Speaker 2:You know, sign up for my course at Carnegie Mellon University.
Speaker 1:Yeah. So funny.
Speaker 2:The students who graduate and the the students who graduate and the tech companies that come to Miami to leverage those skills will change the very fabric of Miami for decades if not centuries to come. So I had this take early on when the initial push to make Miami a tech hub was happening that there were two things that were missing. There was not a technical university that was providing a pipeline of talent because so many people, they go to Stanford or Berkeley and they graduate and they wanna just stay local and so they would just work at a tech company and they work at a thing
Speaker 3:Fire. No. That's not true because all the quants or a lot of them were in Chicago. What's the school there? Like, I guess
Speaker 2:University of Chicago or Northwestern?
Speaker 3:I don't think UChicago is like a STEM school.
Speaker 2:They have a great economics program for sure. But also
Speaker 3:But like the Chicago School
Speaker 2:of Quants. Established Citadel is that they pull people from New York and also they have a New York office. But they but moving from New York to Chicago is not as aggressive as moving from from Chicago or New York to Wynwood, bro. Let's be real. But also of all the of all the big tech companies, Miami ranks remarkably low for tech penetration.
Speaker 2:Like the like Google, Amazon, Microsoft, they have campuses in Denver, Austin. They have stuff in Virginia and Chicago and Seattle. And they've all proliferated such that there's a Google campus in in Santa Monica. So if you go to UCLA or USC and you want to stay local in LA, like, you can get a job at Google. It will be maybe slightly different team, but there are, you know, there's a real office and a real campus in this city.
Speaker 2:That didn't really exist. Microsoft was starting to do some things, but there wasn't this, okay. Well, you can go get new grads here at least to start the flywheel. And then also, you can pull people from big tech because there's a number of offices here. And so Miami had a ton going forward with the regulation and the climate, obviously, and the supercars.
Speaker 2:But but it didn't have a deep talent pool that made it easy. So a lot of the companies that moved there, they had to like acquire companies and move a lot of people. They had to I mean, you're like a made man at Citadel, going from Chicago to Florida is fantastic for tax reasons. You're going to go down there with your whole crew. But if you're but they're not trying to scale up necessarily.
Speaker 2:Like the core Citadel team is not trying to a 100 x their workforce in the next few years like many startups are. But if you're a founding team with 10 people and you're like, okay, we might be at a thousand people, a 100 times the size in a few years if things go well, Doing that in Miami has historically been very hard because every every recruit process has been has been hard fought, basically. I don't know. But, yeah, we should send we should send Tyler to Carnegie Mellon University in Wynwood and get him a get him a Huracan to to pull up to the school.
Speaker 1:You're a gamer.
Speaker 2:Oh, yes. I am.
Speaker 1:Somebody put the entire game of Minecraft into Elden Ring as a mod. It runs on Mac.
Speaker 2:I can't is it are you playing are you playing is it is the base game Elden Ring or is the base game Minecraft?
Speaker 1:The actual gameplay is Elden Ring. Okay.
Speaker 2:But it has You are playing
Speaker 1:as But it has
Speaker 2:Minecraft character. Yeah. Oh, yeah. The the this was happening before vibe coding even. I've seen a ton of Elden Ring mods where different characters are replaced with other people, usually more manual.
Speaker 2:But this is fun. I played Elden Ring. I played probably five minutes of Minecraft. Never really got into it, but I I played a decent amount of Elden Ring. It's a fun game.
Speaker 2:I like a I like a Souls game. They're fun. What what what did Tenev Burs say? I think this tweet is gonna do more to educate the general public about modern model capabilities than any launch of any AI company has ever done. That's sort of true, but this could this was happening in the pre AI era.
Speaker 2:Like, it just required taking assets from one game, modifying the files. You had to maybe write a little bit of glue code, but all of this was pretty doable. But I agree that this is gonna speed up and the the the future of this is is is much more personalized because you'll be able to do it for your for yourself. Anyway, what's it gonna take to you to get you to to beat Elden Ring? Play Elden Ring?
Speaker 2:Do you know the do you know the
Speaker 1:I would need to you
Speaker 2:know the current viral Elden Ring question or challenge?
Speaker 1:There's no amount of money.
Speaker 2:No. It's it's it's would you rather spend a year in jail or you're in jail until your mom beats Elden Ring? Which one would you I
Speaker 3:have no idea. I've never played.
Speaker 2:I don't know what
Speaker 1:I Is it that it that hard? It's hard. Okay. It's extremely hard. So even if your mom, like, wanted to get you out as fast as possible and was doing everything in her power Yes.
Speaker 1:She and she couldn't get in, you know Yeah.
Speaker 10:Like But
Speaker 1:couldn't you just couldn't she just pay somebody to,
Speaker 2:like So the game itself is like a a hundred hours if you're good. And you probably need to have played a thousand hours of video games beforehand to enjoy it and play it well. And so there is a live streamer who's actually doing this. He built a fake jail cell and he's in jail eating ramen noodles and sleeping on this, like, cot. And then he is coaching his real mom through Elden Ring, and you can see that she's never played a game before.
Speaker 2:So she's not doing very well and just getting absolutely destroyed by everything. I don't know how real the the bit is, but I saw I saw a summary video of it that seemed very funny because it was a it was a funny, like, what like, which one would you rather do? You know? But it was funny. Is there anything else in the timeline we need to get to before we bring in our first guest of the show?
Speaker 1:A very, very, very funny post Yes. From Nick, who says, I am not joking when I say this. Spotify, Apple Music, and streaming in general is over. AI music is now very, very good. You just don't know yet because all AI music circulating today is from two to three generations ago.
Speaker 2:Mhmm.
Speaker 1:Suno has solved infinite personalized music. And I already had a good laugh about this with you yesterday
Speaker 2:Yeah.
Speaker 1:I first saw it. Obviously provoking quite a response. Yeah. Coming from somebody who absolutely loves Suno and has gotten so much entertainment about it, I couldn't disagree with this post more. Yeah.
Speaker 1:It makes no sense and I don't think anything he's talking about will come to fruition.
Speaker 2:We just already went through it with text. Like like, we we we developed the ability to generate articles on the fly and people still read articles all
Speaker 1:the time. Infinite personalized articles.
Speaker 2:Yeah. And people read the news all the time. Like, yeah, there's like some fall off on the long tail sites, but like The New York Times is still really strong. People read New Yorker articles. People read what, you know, any any deep dive, any profile.
Speaker 2:The Colossus profiles are they're burning up tack every Yeah. Every other month. And so you get both. And, yeah, Suno is is very entertaining, but it feels like it's a completely different thing. Barely even a competitor.
Speaker 2:Of course, some of the some of the music will be vended into Spotify, but I I still remain optimistic that Spotify will survive the onslaught of AI generated music because the best creations, whether it's made with, you know, electronic digital audio workstations, you know, instruments or AI, they will all find their way onto the platforms and go viral just as Rubbers did by Phoenix Flexen. It was AI generated, but there's enough of a story and catchiness to that song that it went through the traditional channels and is now streaming on Spotify. Anyway, let me tell you about Codex. Codex is a powerful workspace for getting work done with AI agents. Whether you're writing code, analyzing data, creating content, or automating business workflows, Codex helps you move projects forward from start to finish.
Speaker 2:Our first guest is from NVIDIA, the senior director of AI Software. Ali, welcome to the show. How are you doing?
Speaker 5:Doing well. Thanks for having me.
Speaker 2:Thank you.
Speaker 1:Great to have
Speaker 2:you. So much for hopping on the show. Since this is the first time on the show, could you tell us a little bit about your role at NVIDIA, what your day to day is like, what projects are you the most focused on these days?
Speaker 5:Sure. So I'm on the product side. Most of my time is spent around security, safety, and infrastructure of AI. Me and my team created this project named OpenShell, which was part of our announcement. We joined about eighteen months ago.
Speaker 5:We were founders of a company named Gretel. We focused on data privacy, synthetic data, things like that. Founded a few startups and all of us started our careers at security researchers and computer scientists and data intelligence community. So
Speaker 2:Yeah.
Speaker 5:Sort of full circle coming back all the way back to our original work here.
Speaker 2:I like the name Shell. It's better than Sandbox. Sandbox Mhmm. Easy to get out of. Any child can walk out of a Sandbox.
Speaker 2:The sand goes everywhere when you have a Sandbox. A Shell contains the turtle. The turtle cannot just easily escape the shell. Right?
Speaker 5:Yeah. So I like More importantly, it goes with it wherever it goes
Speaker 1:Yes. To keep
Speaker 5:it safe.
Speaker 2:Yes. And there's little holes that the turtle can poke the arms out of.
Speaker 1:A turtle can be in its shell can still bite you.
Speaker 2:Bite you. Okay. But it's limited. It can't it can't bite you from any angle because there's only Yeah. That's right.
Speaker 2:One hole that the head We'll comes
Speaker 1:keep working this analogy out while you actually
Speaker 5:Once you perfect it, love to get it back. We'll make it into stickers.
Speaker 2:So OpenShell, is it open source? Are you are you evangelizing this product to labs, neo labs, everyone, businesses? Like, how do you see this product actually rolling out and being used by the AI community, the technology community, the the the real economy, etcetera?
Speaker 5:Yeah. We've been working on it for about a year. We actually released it as an early access in March. It's been Apache two point o since we released it. We're actually on pace to donate it to a foundation.
Speaker 5:Oh, cool. So we we don't even wanna be sort of the NVIDIA project. We want it to be a true community pro project. Yeah. We intentionally built it open so it becomes a standard.
Speaker 5:It becomes sort of a trusted layer.
Speaker 4:Mhmm.
Speaker 5:Like we think that what agents are missing is sort of like if you think about like the web from nineties to 2000, there's that trust layer like lights up, SSL is on, you know, your tab is isolated. Like that construct is missing from agents. So our perspective was if you can create a trusted layer, open it so it can be widely adopted and then built on top of, then you can sort of have a trusted layer everybody can work through. So that was sort of the the whole intent and opening that is really about rising tides.
Speaker 2:Yeah. Can you get me up to speed on the state of formal verification? How much optimism should I have towards this as a solution? We had Greg Brockman on this show a few weeks ago, and he was saying that he he he has this point that there is an optimistic scenario where enough software is formally verified, fully secure that certain systems are hardened to a point where it ceases becoming a cat and mouse game. Is that too optimistic?
Speaker 2:Are we on the path? Are we already seeing glimpses of that? Or will or is the game going to just be played, you know, indefinitely and we just need more good guys than bad guys?
Speaker 5:Yeah. The state of formal methods and what it can do, I think the first substantiations of it, we already have proof of life. Like, if we can demonstrate what a full stack verification looks like. Mhmm. So I think I'm very optimistic because a lot of our thinking that has led to this is is that agent safety trust really needs to be a full stack solution.
Speaker 5:Like if you think about where models, frontier labs, harness data tools, that, that's really the app player. We build OpenShell because we felt like you needed to be able to move the risk line to a deterministic layer that nothing can bypass. So that's the runtime. You can do formal verification on that and get really good controls. If you then move all that further into hardware, now you can verify the entire stack.
Speaker 5:So you could be assured down to a single binary decision is anything leaving this system or not leaving this system. So I'm incredibly optimistic about formal verification, but it has to be applied the right places in the stack for it to have the affected needs.
Speaker 2:Mhmm. Talk about your how you interface with NVIDIA's security features on chip. There's been some discussion about Apple advancing this with the secure enclave and partnering with NVIDIA in various ways. And it feels like there's a number of different organizations. They're all swimming in the same direction, maybe talking about things differently, solving problems differently.
Speaker 2:But how do you actually interface with the the hardware teams or or or what do you what are you seeing from the hardware teams that gives you opt optimism around security?
Speaker 5:Yeah. So let me sort of answer it in two parts. One, what we're doing on the OpenShell side so we can interact with all the hardware, and then what we are seeing on the hardware side. I think those are and they're agnostic because they both should be equally as good without each other, but a much better story together.
Speaker 2:Sure.
Speaker 5:So on the OpenShell side, we've just taken a very agnostic approach. We have this primitive inside the runtime called drivers. It's exactly what it sounds like. You pick your compute under the hood. And the reason it's important to pick the hardware, the compute under the hood is sort of what we announced with our open agent safety platform is we put a reference design out with our BlueField Vera to say if you have hardware, OpenShell can take all these controls at the network for chain of thought and move it all the way into hardware.
Speaker 5:So now you can do it at machine speed and you can have very deterministic enforcement on it. It was sort of a reference architecture for us. So from the OpenShell side, we've tried to be as agnostic and inclusive as possible by giving a driver that any computer hardware can plug into, which is you probably may have seen this in our announcement why we briefed ARM and Intel and sort of go down the list of hardware providers. Right? Because we want everyone to be able to offer this full stack trust and safety verification.
Speaker 5:As far as what we are seeing on the hardware side, there are two things we are starting to see sort of generalized patterns. One is the hardware component making primitives available so the higher levels of the stack can offload networking into it. Mhmm. Think of it as a way to, like, manually flip the switch and cut any access. Access.
Speaker 6:Okay.
Speaker 5:So if you're doing that in a hardware, if you're an advanced, for example, researcher or a frontier lab or a large organization doing research or sort of testing of a frontier model, by having that at control at that stage, you know and can verify the boundary or the blast radius you're setting is not going to be breached. Right? It's in the hardware. It can't be bypassed. Agent can't work together to get around it.
Speaker 5:So that's one area of sort of work that we are seeing, and obviously, this is the work we're doing at NVIDIA too. The other side of it is being able to pass through the way the agent thinks and reasons through silicon. Mhmm. So you can actually see what it's thinking about. The reason this is important is is, like, if you're familiar with security, the holy grail is shifting left.
Speaker 5:Right? Not responding, but preventing. Like, how do you do that? So if you pass that chain of reason, that thought the agent has through silicon, you can see it's thinking about using a zero day. Then you can check with the runtime.
Speaker 5:Did it probe anything to see if anything's open? You can come back and you're like, oh, it did probe. Now it's reasoning to say, I actually found a hole. Now let me go build an exploit. Then you can pass that and cut network and say this thing is about to break out of the environment because it's reasoning about using like a zero day or a vulnerability.
Speaker 5:Mhmm. Or, like most agents, it could just think about these things and basically let it go as a chain of thought and not come back to it. But those are the two really interesting areas of research we're seeing in hardware right now.
Speaker 2:Please.
Speaker 1:Sorry if this is a silly question, but would an agent actually think, should I use a zero day today? Or would it just identify a potential exploit that to a even if you're observing it wouldn't necessarily be immediately obvious that it was an exploit?
Speaker 5:Yeah. So, you know, I'm sort of being overly, you know, rudimentary about saying
Speaker 1:it's yeah. I know you're trying to dumb this down to us.
Speaker 2:Bring you're trying to bring this down, like let
Speaker 1:me bring it down, like, 20 levels. No. We have we
Speaker 5:No. No. Fifteen, sixteen max. Not 20.
Speaker 1:Preschool. Preschool. Please keep it. Don't keep it need preschool, not kindergarten. Thank you.
Speaker 5:For sure. So let let me say it differently. Like, if you look at the types of events that happen with these labs Mhmm. Where the agents did something that was unintended. Yeah.
Speaker 5:It wasn't a single step function in capability that achieved that. Mhmm. It was doing a subset of things like stealing credentials, communicating with each other in channels that you didn't have, persistent sessions longer. Doing all these things that at the quantum level, we know how to solve these things from a security standpoint. Right?
Speaker 5:Like we know how to keep credentials away from humans. We can do the same things for agents. We know how to introspect traffic. So it was a whole bunch of techniques uniquely put together and then ran at machine speed. The machine speed part is solved in silicon when you can see it thinking.
Speaker 5:And then the the path to exploitability and vulnerability exploitation is a set of things and actions that are well understood. Right? You probe the network into an environment that the policy says you're not allowed to. You take that reading and you build a tool against it. So this iterative process is something we can build rules around and then build fail saves as a particular part of the stage.
Speaker 2:Yep. That makes a lot of sense. Sense.
Speaker 1:Yeah. Talk about, when, like, throughout throughout your career in security, there were sort of spikes of panic. Like, I would imagine I would imagine we're we're generally at 10 out of 10 relative to maybe other moments, but I'm curious if there are other moments that you went through on the path to this current moment that were that were any anywhere anywhere close, but maybe they weren't as sort of public and talked about on a national level or in the media as much, but maybe were more kind of internal industry.
Speaker 2:Like SolarWinds?
Speaker 5:Yeah. I mean, so it's funny, like, lot of my panic was either associated into the intelligence community that I can't talk about or as a founder which had to do with funding or board members who
Speaker 1:had less than one conditions. Of
Speaker 5:But I would say that I I wouldn't call call it panic. What I would say is is like ambiguity increases risk. Right? Security is about risk reduction. There's never a perfect system.
Speaker 5:So I would say the times that created the most level of ambiguity where then sort of opinion fills the void were when we had these massive step functions and form factor. Like, not SolarWinds, but like moving sensitive compute to mobile or to cloud Mhmm. Or making them fully distributed. Mhmm. And now sort of it feels like another level of control given away.
Speaker 5:Right? Like, you think about cloud, everybody understood hands around things. Right? And now you're like, where is my stuff? Like, that was a very fundamentally, conceptually difficult shift to make for a lot of years.
Speaker 5:Mhmm. And I think agents AI have a very similar fact factor. Like, we joked about sandbox, but, like, to use one concrete thing. Right? Like, sandbox is meant to constrain something, keep it in or keep it out.
Speaker 5:These agents by definition have to do both to be productive. Mhmm. So when we talk about, oh, sandboxing is not effective against these agents, we're all panicking. Well, because we're of using a rudimentary version of it. So the same way we didn't take, like, these monolithic applications and shove them in containers and then run them on Kubernetes, the way we redesigned with microservices and immutable ephemeral infrastructure, The same thing needs to be done here.
Speaker 5:Most of the problems we're seeing is we are running an advanced technology into an environment that is not meant for it or designed for it. So what does a native environment look like for AI basically is where I spend a lot of my time.
Speaker 2:Well, thank you so much for coming on sir. A great conversation.
Speaker 1:Yeah. I really enjoyed your perspective.
Speaker 2:But yeah. Have a great rest Thanks of
Speaker 6:for
Speaker 14:the You too.
Speaker 5:Thank you.
Speaker 2:Bye. Let's bring in Mike from Core Weave. He's the CEO. We've been keeping him waiting. And I'm very excited to talk to him about the future of CoreWeave.
Speaker 2:Mike, how are doing? Welcome to the show.
Speaker 10:Thanks guys. Great to
Speaker 15:be here.
Speaker 2:Thanks so much.
Speaker 1:Nice have you guys.
Speaker 10:You guys have done it with Brian and Brandon. I figured it my dear.
Speaker 2:Yes. Yes. Yes.
Speaker 1:I know. You know what we see? We sometimes see founding teams, executive teams like end up being like, no, these are these are my guys. Like and they don't like to share the TBPN. They don't like to share the TBPN visits.
Speaker 1:Okay. We like to meet we like to meet the whole team.
Speaker 10:Yeah. We we had the hey, you guys are gonna love this. Go hop on with these guys.
Speaker 2:That's great. I want to talk about some of what Elon and Jensen were talking about the compute math, the monetization of gigawatts. But first, let's get the latest from Core Weave. What's newest in your world? What is top of mind and on the frontier of your business today?
Speaker 10:So look, I'm speaking to you from Fully Connected, our our global conference here where where where we're, you know, sitting down with 5,000 of our clients, developers, companies, enterprise labs that use the cloud that that that Core Web has built to be able to drive their business. I couldn't think of a more exciting place for our team to be.
Speaker 1:Yeah.
Speaker 10:Right? To to to get to to get an opportunity to to be in the in the seat with these folks and get the feedback loop in in in going in in a first person is just, you know, I mean, that's a unique experience for a company. And, you know, in in many ways, Core Weave is really well positioned to take on the information that we're we're garnering from from these clients about, you know, what we've built and how it could be better, and, you know, all those pieces really come together nicely when when when you get a few minutes to put some of your engineers in the room, some of your product people in the room, and some of your clients in the room, and that's that's what we're really here to do. So it's fun. It was supposed to be 2,000 people.
Speaker 10:We're over 5,000.
Speaker 2:5,000.
Speaker 10:Wow. Yeah. It's great. It's great. It's like
Speaker 2:And I imagine I imagine the customers are no longer just asking for just a bunch of GPUs. Like we are firmly in the AI agent era. They want CPUs. They want new storage solutions. Like what are they asking for you that you're saying, oh, yeah.
Speaker 2:We're we're we're we're already working on that. We'll work on that. We'll do that. Give us give us a day. Give us a week.
Speaker 2:Give us a month, and we'll be there for you as a customer.
Speaker 10:The the truth is is what the the clients are asking us for, what most of the clients, right, are asking us for is the cloud.
Speaker 2:Mhmm.
Speaker 10:Right? Like, they're not asking us for GPUs. Right?
Speaker 1:Yeah.
Speaker 10:They're you know, like, when when we think about our client base, like, 90% of our clients use two or more of the products that we deliver, and that's the software solutions that, you know, all of the different pieces that we stack up. When, you know, if we get down to, like, 78% or something like that, it's like, you know, we're we're at three or more products. So, like, we're not here anymore to say, hey. We can deliver you GPUs. What we're really here to do now is to deliver an AI cloud.
Speaker 10:A cloud that gives you the full functionality so that you are able to, you know, build the the the to the potential of your company, to the potential of your project, to be able to serve it globally, to do all the things that that we have historically thought of as what the cloud's role in in in the broader ecosystem, but really much more targeted towards the the role for a cloud in the AI era. And so, you know, we we we announced our our our our product here called called Forge, really, which is about bringing together all of that feedback, bringing together all of the tools and software rails, and delivering it to the broader universe. So like not everybody's got, you know, AI experts at the level of these frontier labs. So you've got to be able to build product to shorten the distance between what enterprise clients need to be successful in integrating artificial intelligence into their workflows.
Speaker 16:Mhmm. And
Speaker 10:that's what the AI cloud is gonna do. That's what Forge is built to do, And we're really, really excited about rolling it out because we think it's gonna be a very, very successful effort for for us as we kinda continue to diversify across the enterprise space.
Speaker 2:I have a bunch of questions, Jordan.
Speaker 1:Go for it. Okay.
Speaker 2:Yesterday, we were talking to Sam Altman and he was very excited about the OpenAI compute build out, specifically just the lack of homogeneity across the inference opportunity, everything from big beefy models that are going to run for a long time, the decisions API, the stuff that they're doing with the Jalapeno program. Like it really feels like we're fully stepping out of this era of, okay, just get a bunch of the best chips and that will do everything. There's so much economic value in choosing the right tool for the job. And it feels like that's a big piece of your opportunity is to bring What that capability to does the next year or two look like for you on that side? Obviously, you're building the software solution to harness that.
Speaker 2:But what other decisions are you making either on the hardware side or with your capital partners? What are the different decision parameters that you're wrestling with right now?
Speaker 10:So so I I love this line of questioning because I've been pillared over this for two years now. Right? Like, oh, you know, you're gonna build the GPUs and they're gonna be obsolete Yeah. Four days after that.
Speaker 2:Yeah. And the depreciation.
Speaker 10:It killed me because Yeah. The depreciation conversation was was it was a self serving conversation by a few players that had a vested interest in in that narrative.
Speaker 2:Sure.
Speaker 10:But the reality is, right, is that, you know, you need the most performing GPUs to build on the frontier. Mhmm. And then once you've built it, there is this incredibly fat tail of other use cases where you can take GPUs and keep them deployed productively for a very, very long time. And so, know, the the the the fact that that Sam is talking about it, the fact that you're talking about it, I I'm gonna take a personal victory loop here because I've been getting clubbed I've been getting clubbed in the head over this for
Speaker 2:for for, you know,
Speaker 10:you know, every time I go on CNBC, they take a whack at me on
Speaker 2:this You deserve a victory lap.
Speaker 10:The the truth is is like, look, compute is going to drive intelligence that is going to permeate every asset of civilization. Right? Like that's that's a fundamental belief that we have. And what we have seen repeatedly over the years is that every time a GPU is no longer capable of driving the frontier for it, it has a slew of other uses that will absorb it. And, you know, I talked about this in my last earnings report, the a one hundreds.
Speaker 10:That's 2020 architecture. Yeah. Right? Getting that contracted out through 2029. Right?
Speaker 10:Like, that that is a you know, like, that kind of puts that debate to close. Right? Totally. There are use cases that will absorb this, whether it's batch computing, or medical research, or
Speaker 2:Yeah.
Speaker 10:You know, there's a you know, or things that we haven't even invented yet because there's not enough compute that can drive the new businesses into existence. And so super excited about that. I love that you guys are thinking about that. I love that Sam is thinking about it also. I think it's important.
Speaker 2:Yeah. Yeah. There's just so many different opportunities now. You saw, like, ultra fast 8x the speed, but then also the JEV moment and decisions API and, like, the computer use and then image generated video. There's so many different opportunities there.
Speaker 2:Jordy, you have a question?
Speaker 1:Our friends over at Semi Analysis have you guys in the platinum tier. Do you are have you been pushing them to introduce a diamond tier?
Speaker 10:Oh, yeah.
Speaker 2:Because so that you and
Speaker 1:the team have something to grind for because I I imagine you don't wanna be stagnant.
Speaker 4:Yeah. Yeah. That is fair enough.
Speaker 10:Fair enough. You know, we we joke. I don't know if you guys have have spent any time with Peter, but we call him premium Peter. Right? Okay.
Speaker 1:The
Speaker 10:joke around here is, and he's amazing where he's the principal architect behind the the so much of the cloud that we've built. Sure. And, know, that would he would work himself to death trying to get it back in tier. I think
Speaker 2:they gotta open it up. Yeah. In the town.
Speaker 1:Well, I just I don't know what to think. Used to be you guys were the only ones there. Yeah. Now there's a player there. Gotta It's
Speaker 2:getting crowded, man. We need a new mountain.
Speaker 1:Going going off of that, when I look at the new Cluster Max three which came out I last week or maybe Monday, losing track of time. There's a bunch of names on there I've never heard of and we spend all of our time talking about these companies. Mhmm. A lot of them, you know, a lot of the other companies that I do know have been have been on the show. My Right now, there's so much, like, excitement and new capital formation around some of these neo clouds.
Speaker 1:And my question is, like, I have to imagine Like, I I I think the natural assumption is that, half of these companies, like, won't make it independently forever. And so my question is, like, what do you think when do you think the window is gonna come where these these companies that have invested, let's say, between a 100 and a bill you know, billion dollars into building something but aren't gonna quite make it. And then that becomes a sort of opportunity for the more scaled platforms to hoover up talent and maybe some more specialized products and and even down to the individual, like, site level?
Speaker 10:Yeah. It's something we we we we think about here and talk about a good bit. Right? And I I wanna be clear. There there's a lot of different paths to consolidation across the cloud industry.
Speaker 10:And, you know, one of the things is is, you know, we we don't really think of ourselves as a neo cloud anymore. We are the AI cloud. Right? Like, you know, the concept of being a new cloud is great for a while, but the truth of the matter is is our job is to deliver the functionality that the world needs, and that's the AI cloud. Right?
Speaker 10:Yeah. But you also get to a world where you get consolidation. It could be because there's an air pocket in compute demand. Right? And that's one of the things where, you know, it would be destabilizing.
Speaker 10:But there's also another scenario where, you know, power becomes more dear and the selection process for who people are going to sell to tightens, right? And they're just like, why am I going to take a shot with a third tier new provider when I can go ahead and get, you know, the same terms with a reputable well established Yeah.
Speaker 1:Just it just comes down to like Capital capacity. If like if I'm a if I'm a company I'm planning to scale my demand for compute really quickly, it doesn't make sense to sign with the third tier provider simply because I'm gonna run out of, you know, capacity or or Yeah.
Speaker 10:And and and it also causes drag on the balance sheet of the off take companies. Right? If you're a a buyer of compute and you've got 47 different, you know, third tier clouds, that can lead to drag on your balance sheet, which is not great. Right? Like, so you wanna have a efficient allocation of capital, an efficient allocation of the capacity of your balance sheet, and you do that by really working with entities that you have a high degree of confidence are gonna be able to deliver performant infrastructure.
Speaker 10:Yeah. You know, I I I think that, you know, there's an inevitability. Right? Like it's a capital intensive business at the end of the day, and capital intensive businesses end towards a consolidation. Whether the number is going to be 10 or seven, I don't know.
Speaker 10:When it's going to happen, I don't know. The the the the the priority for us is to build a resilient company, and you build a resilient company by working with high quality clients, by delivering a high quality product, by decommoditizing the compute that you're delivering, by having incredible software rails so that people are able to use it, by moving across the enterprise space. All of these things have been priorities for us, and we have done a really, really good job of staying focused on, you know, as a team on making sure that we drive the the parts of the business that will ensure that Core Weave is resilient through whatever cycles come. Mhmm. And we're pretty comfortable about that.
Speaker 2:Amazing. I have one last question. We'll let you go. For for q two, the rough dollars per watt was around $77,000,000,000 per gigawatt. It feels like that's accelerating.
Speaker 2:It feels like you might be tracking to closer to $40,000,000,000 per gigawatt. Elon and Jensen were doing some rough math around 60,000,000,070 billion Is this something that you have visibility and optimism around continuing to climb? Or is there more focus on getting to some sort of steady state where you're monetizing the energy that you have and then just scaling out horizontally?
Speaker 10:Yeah. I I I look at the problem and opportunity a little bit differently. Right? I look at it from a time horizon perspective. Mhmm.
Speaker 10:Right? And so I believe that there is going to be a market for lower cost compute that lives outside of the build cycle of infrastructure. So if you think about it, and let's say, just hypothetically, takes us two years to build a a data center. If I can sell capacity in a time frame beyond that two years, I can replace it. Right?
Speaker 10:Once I'm inside that, that's where Elon Musk and and Jensen are talking. Right? Because then it becomes truly a a supply demand dynamic where, you know, people are going to compete for that compute. And those are two separate markets, and I believe that that over time, they're going to begin to behave differently where people who can make the long term planning are going to be able to drive economies that are associated with that because it's going to allow folks on the infrastructure side, on the cloud side, to be able to plan better. And so there is it's a it's a it's a really fascinating piece of the market when you think about it in terms of time, not just in terms of dollars.
Speaker 2:That's very interesting. Well, thank you so much for coming on and breaking it down for us. Congratulations.
Speaker 1:Say hi to all 5,000 people over here. Hopefully, we can join next year
Speaker 2:in person.
Speaker 10:Love to have you guys here, man. Let's do it from the home place.
Speaker 3:Alright. Awesome.
Speaker 15:Thank you.
Speaker 2:We'll talk to you soon. Cheers. Goodbye. Let me tell you about Shopify. Shopify is the commerce platform that grows with your business and lets you sell in seconds online, in store, on mobile, on social, on marketplaces, and now with AI agents.
Speaker 2:Our next guest is Vlad Tenev, the CEO and cofounder of Robinhood here to discuss artificial intelligence, finance, everything in between. How you doing, Vlad? Welcome to the show.
Speaker 6:What's up dudes?
Speaker 1:Sorry. I'm I'm too focused on the car. Yeah. You got a yellow Toyota. As much as I'm excited to see you this
Speaker 2:Break it down. Explain where you are and what you're doing.
Speaker 6:So I'm in Houston, Texas
Speaker 2:Mhmm.
Speaker 6:At our space themed active trader event. Called hood summit engines of creation where we have 1,500 of our most engaged active traders.
Speaker 2:Cool.
Speaker 6:We rolled out 16 products, which are awesome, like first of their kind. You know, twenty four seven trading of stocks will be the first place in The US that allows that. Perps, the first true perps offering in The US with Mhmm. Eight perpetual futures. And then Robinhood Agents, is an evolution of our agentic financial superintelligence products.
Speaker 6:We also sponsor twenty three eleven racing, a NASCAR team. So behind me is Corey Himespar, and I don't know if you guys are NASCAR fans. So we're we're America's brokerage, so it's only it's only appropriate for us to be involved in American motorsport.
Speaker 2:That's great. That's great.
Speaker 1:Delivery looks fantastic. Yeah. Easy to spot.
Speaker 2:Yeah. Talk about
Speaker 6:I mean, these cars don't have doors. You have to like jump in the window. To me.
Speaker 1:Have you driven have you driven it yet? Have they let you behind the wheel?
Speaker 6:Was trying. I was Okay. I was trying to do shit. I don't think yeah.
Speaker 1:I don't Might be a little worried.
Speaker 6:Corey didn't let me.
Speaker 2:Maybe the safety car. You take the safety car for a spin. Talk talk to me about the AI agents product. Yeah. Talk to me about the AI agents product.
Speaker 2:How much of this is pull versus push in the modern era? I mean, we're seeing this happen with the personal AI agents. Just yesterday, people were getting the the reversal. They were going to instinct for shopping and then yesterday they were starting to get ideas and recommendations for products they wanted to buy, push them. Some pushback on that.
Speaker 2:But in an agentic trading sense, I feel like if I'm on Robinhood, I kind of want you to come to me and say, hey, why do you have your money in this savings account that's earning 1% when you could be in this thing that earns 3%? Want me just to do that for you? So in terms of like trade ideas generated by the AI agent that comes to the customer versus me going and saying like, I want you to go and run my portfolio this way. What's working? Where do you see it going?
Speaker 6:Yeah. So I think there's lots of different types of agentic finance products Yeah. That have been tried. Agentic trading is a little bit different than what you're talking about, which is just like almost like a one time, hey, move my money over to where it earns higher interest. You don't need super intelligence for that.
Speaker 6:Robinhood Agents is really about helping people create strategies. Mhmm. And so we rolled out three things. Right? One is Robinhood Agents Mhmm.
Speaker 6:Which you can think of as, you know, we we rolled out an MCP a couple of months ago, a model context protocol, which you you can think of as an API that lets you connect external AI agents, like your Claude code or your Codex, Yep. To our services so that they could place trades on your behalf. Mhmm. That was a very popular product. It has over a 150,000 users have actually connected external agents to it.
Speaker 6:Mhmm. And so Robinhood Agents brings that within Robinhood with all the benefits like trade approvals, separate account, brings it in the Robinhood experience where we have over 28,000,000 accounts. Mhmm. The second thing is agent apps. Now if you think about what a lot of hedge funds have access to, it's proprietary data.
Speaker 6:Things like unusual options flows, satellite imagery, you know, congressional trading data. And agent apps, can think of as an app store
Speaker 1:Mhmm.
Speaker 6:Where third parties can plug in, provide proprietary data for use by our customers in creating trading strategies. Mhmm. The third thing we created, agent loops. So you can have your agent run autonomously and predictably in a deterministic way and execute that strategy for you while you sleep.
Speaker 2:Sure.
Speaker 6:So you put these three things together, and the way I describe it is we wanna give you the power of a hedge fund in your pocket, an extremely sophisticated team of financial trading professionals. Can we give that to everyone? And, yeah, I I think the way that I think about it, you know, my my the start of my financial career was in algorithmic trading. And in the same way that tools like Clogcode and Codex have made it easy for anyone to be a programmer, Robinhood Agents will make it easy for anyone to be a financial trading quant. So you can you can develop a quant trading strategy, extremely sophisticated trading algo, and we can kind of unlock that for millions of people.
Speaker 2:Yeah. So
Speaker 1:What's going on in in alternative data? When you you said satellite imagery, you brought that up. I thought it was interesting because historically, I imagine, you know, a a some type of research organization or a hedge fund would get satellite imagery and then they would need to spend a lot of time actually analyzing the, you know, the the data. Let's say if you wanted to understand like retail foot traffic at a big box store. Right?
Speaker 1:You would be able to look and and and understand. The models out of the box can do a lot of the kind of things now that that it would have historically taken like building your own algorithms that maybe weren't as reliable, things like that to to to sort of extract alpha out of something like a satellite image. Now it feels like that kind of a thing can be way more democratized. Do you expect there to be like that sort of alternative data to just become more democratized now that models out of the box can do this kind of like complex research?
Speaker 6:Well, still need to pay for the data. Right? And and so Yeah.
Speaker 1:But that's have 28 Yeah. You guys have 28,000,000 accounts. Like, it feels like these are the kind of things that could ultimately be in fact crowdfunded one way or another or brought down to like a $5 Yep. A $5 subscription instead of like a $50,000
Speaker 2:subscription. And
Speaker 6:and these things are kind of like skills in in our product. So instead of having to go and sign up for it in the Internet and give your agent your username and password, they're just directly integrated. And our partners are all offering these services one month free. We also have a partnership with OpenAI where they're helping us with GPT six Luna. That'll be offered for free till the end of the year.
Speaker 6:Cool. And a lot of people say, well, what is this? People are just going to write to their agent and say, make me money. Yeah. Me And everyone's gonna be doing that.
Speaker 6:Yeah. I think what's likely to happen is you'll you'll get more depending on what you put in. So you mentioned the satellite data. You know, imagine exactly what you were saying. Someone actually plugging that in and saying, you know, check out these parking lots and and build me a proxy for retail traffic on the holiday season.
Speaker 6:Or my favorite, look at the parking lots of various companies and see which ones have employees working weekends or late nights, you know, and you can imagine the possibilities there. There's there's there's lots of strategies that are just waiting to be created. Think it'll unlock a whole new kind of arena for competition and creativity among traders.
Speaker 2:Yeah. Yeah. You you you described it as sort of like a hedge fund in your pocket, and I'm wondering if you can extend the analogy further. A lot of the most performant hedge funds run the pod model with centralized risk strategies and multiple pods with different strategies. Do you imagine that the more proficient Robinhood trader in the future will have multiple agents running multiple strategies with some sort of centralized risk control?
Speaker 2:Because there's often these ideas that you just listed a bunch of them. They sound exciting, but I don't know if I want to put all my eggs in that basket. But maybe as part of an ensemble strategy, it does start to make sense. So how far are you leaning into the hedge fund metaphor?
Speaker 6:Yeah. I mean, so right now, the way Robinhood is organized as a product is there's multiple accounts.
Speaker 2:Sure.
Speaker 6:And this is a relatively new thing. It started out with you just had one Robinhood account. Yeah. But then we rolled out retirement. Mhmm.
Speaker 6:Then we have joined and trust. And so there's an agentic account. So your AI agent is kind of sandboxed and scoped financially to one financial account. And by default, we've got some guardrails, right? Trade approvals are on by default.
Speaker 6:You can turn it off, but by default you would have to say yes to every trade that it suggests.
Speaker 2:Got
Speaker 6:it. You also have to move money into your account willingly. Right? Yeah. So it's not just gonna go in your in your retirement account and trade for you.
Speaker 6:The trading is all scoped to money and assets that you load into the account. Mhmm. And these are all things where Yeah. We wanted to start with a sandboxed experience. We wanted to see how things go.
Speaker 6:Of course, we might change it over time. But, yeah, that that's sort of our initial risk management strategy.
Speaker 2:Yeah.
Speaker 6:And, you know, we'll see how it evolves. Over time, you could imagine you could have, like, a different type of agent that's not a trading agent, but more of like a financial controller that can allocate between different accounts. They can help you with budgeting. They can help you do sort of like these high level one time management functions. And, you know, that could also serve a risk management layer between your different trading agents.
Speaker 6:But for now, we're kind of keeping those ideas separate.
Speaker 1:When John said pod, it made me think, is like there a reason like, have you experimented with having like a group chat or a hint like, let's say three friends be able to jointly fund an account and then all effectively be making the same trades or be like having to agree on on a set of trades and running like
Speaker 2:Yeah. Like an investment club.
Speaker 1:Yeah. An investing Basically an investing club. You have the social features on Robinhood now. Yeah. It feels like hard to do at a at a wider scale, but at least for peer to peer like actual friend groups.
Speaker 1:Is there any like is there anything like legal there.
Speaker 2:Well Or legal.
Speaker 1:Yeah. Yeah. Technical challenge or like not possible because of for legal reasons?
Speaker 2:Yeah.
Speaker 6:I I think you I think there's definitely opportunity to innovate and create new things. There there is actually like a construct called an investment club Yeah. That allows, you know, friends to pool money together, and there's there's like a sort of structure around that. We haven't gone there yet Mhmm. But we do have Robinhood Social which we launched for everyone last night.
Speaker 6:And basically what that allows you to do is to share ideas with kind of the the broader Robinhood community and it has a follower graph and Mhmm. You can also ensure that, you know, the trades that you're seeing on the platform, the p n l's, all of that is validated and and real. And then we make it easy when you see an idea to actually trade from that idea. And and and you can you can imagine, like, following different traders, learning from their ideas. We also added creators onto the platform.
Speaker 6:We have politicians, so you can follow their trades. And Mhmm. We're we're gonna we we've been evolving it very very rapidly. A lot of people here actually are Robinhood social users and love it. So I think you should expect us to continue exploring these ideas and just giving giving our traders what they want, what's most useful to them.
Speaker 2:I'd love for you to zoom out from Robinhood and the products that you're launching to the markets broadly because you have such an interesting perspective. I mean, yesterday, there was an IPO from Aura that was delayed. And at the same time, the market is massively up this year. Things feel very strong. How are you feeling about either the market strength or weakness, but just how are things changing?
Speaker 2:Are we in a new regime where an IPO needs to be 15x oversubscribed to get out successfully? Like what are you noticing where maybe it's not even good or bad, it's just something where you're like, oh, this is new. We're in a different era.
Speaker 6:Yeah. I mean, I don't know if we're in a permanently unique era for which there's no precedent. I've I've I've seen the market conditions change in different ways
Speaker 1:Mhmm.
Speaker 6:On almost a weekly basis now, right? And I remember it wasn't too long ago that you guys covered the Figma IPO. Yeah. And it felt like we were just at the absolute just apex of animal spirits at that point. And I think things have calmed down since then.
Speaker 6:Yeah. We've entered a bit of a crypto winter as well. But now that's now we're even starting to climb out of that. Crypto's had a bit of a moment the past couple of weeks. Prediction markets
Speaker 2:Yeah.
Speaker 6:Have obviously been been going gangbusters. So I I think there's always something going on in some corner of the market. And as we've been adding more and more asset classes like perps, we added these really interesting products that I think you guys will like. We're gonna be the first ones offering prediction markets on earnings the So you'll be able to trade contracts on company EPS and revenue as well as, you know, things like iPhone deliveries, Tesla deliveries. And, you know, that that'll give customers all kinds of new abilities to like, if you want to hedge your position in a stock that you're long and you don't want to have to sell it, but you you might think they miss earnings or something, you'll you'll be able to kind of use these products.
Speaker 6:So a lot
Speaker 1:of people have had the experience of like, you know, being being long into earnings, being right that the that's an earnings beat, but then some other factor
Speaker 2:Yeah.
Speaker 1:Sends the stock down.
Speaker 2:Oil prices went up and rate hikes or something.
Speaker 1:Yeah. Being able to right.
Speaker 6:Our traders. So these products allow you to more specifically Yeah. Execute on a on a trading strategy. So it's a little bit more pointed and Yeah. Sort sort of like yeah.
Speaker 6:More specific.
Speaker 2:How are you thinking about the knock on effects of AI agents entering the financial markets, research markets, trading markets? When you play back the story of Robinhood, if you had a crystal ball, you might have been able to predict GameStop and meme stocks and Reddit. But there's already been some people who have said, oh, well, in a world where AI agents are moving money around, no one will be in the money markets. There will be a bank run. And there are some concerns about how things will play out.
Speaker 2:Maybe you won't need a financial adviser anymore. But a financial adviser, of course, doesn't just allocate your portfolio. They do a lot of other stuff. And so I'm wondering if looking to the future and seeing any emerging trends that might sort of change the underlying structure of the financial markets over the next couple of years as AI rolls out to trading?
Speaker 6:Yeah. I think it's important to separate kind of the hype from the potential there. I think a lot of these things are sort of like one time use cases. Right? Move my money from a
Speaker 2:Sure.
Speaker 6:You know, low yielding savings account to a high yielding money market account.
Speaker 2:Yeah.
Speaker 6:Or, you know, renegotiate my my cable bill or something like that. And and I think what we've seen is there's really one area that has long term retentive usage right now, and and that's agentic trading.
Speaker 1:Mhmm.
Speaker 6:Right? And so we're just kind of focusing all of our efforts on making agentic trading as great as possible. And I think over time, you'll see us exploring other things that are maybe not there yet in terms of usage and utility. But AgenTic Trading has like clear product market fit and utility now. So I think I think that's gonna be the one at least for a while.
Speaker 2:Well, it's exciting. I'm I'm excited to see how people use it. All the different screenshots I'm sure we'll see of people doing all sorts of
Speaker 1:No. I remember when the Robinhood social beta like started screenshots started to be shared to that and it was wildly entertaining. So I'm excited. I'm very excited for open access.
Speaker 2:Yeah. Mean, there'll be some people that put up insane numbers, some people that get wiped that that, you know No crying. At the yeah. No crying.
Speaker 1:No crying in the market.
Speaker 2:At the long tail, you get crazy crazy stories. Yeah. So you so much for coming on the show. Congratulations on congratulations on the launches and we'll talk to you soon.
Speaker 1:Yeah. Our best everyone Always
Speaker 6:a pleasure guys.
Speaker 1:A great weekend. We'll talk
Speaker 2:to you soon. Of my b o's, let me tell you about the New York Stock Exchange. Wanna change the world? Raise capital at the New York Stock Exchange. Just do it.
Speaker 2:Stop making excuses. We Up next, we have the founder and CEO of Flow Engineering, Pari Singh, coming back on the show. It's been almost a full year, but we gotta get that gong ready. How are doing? Welcome back.
Speaker 16:Hey. Hey. Good to see you guys. How are you?
Speaker 2:We're doing great, but it seems like you're doing even better. What's the news? What's going on? You raised some money?
Speaker 5:How much did you raise?
Speaker 16:We raised 50,000,000 on a $7.50 valuation.
Speaker 1:Congratulations. John was feeling that one.
Speaker 16:Thank you very much.
Speaker 2:And for what purpose did you raise this money?
Speaker 16:We are gonna invest heavily in AI. Okay.
Speaker 1:We are doing a huge
Speaker 16:amount with AI. AI is completely transforming hardware engineering Mhmm. Just in the way that it's transformed software engineering in the last year. I think when we see design cycles of rockets and airplanes and cars go down from twelve months to twelve weeks to twelve hours, the world's moving very, very, very that is the opportunity ahead of us, and that is what we are investing in.
Speaker 2:Do you like the term AI? Or do you think the next cycle you'll be saying superintelligence? Is that a meaningful designation to you? Or or do you see because I mean, this is a tool, this is a feature I'll
Speaker 1:go first. I don't think it's gonna stick. I think it's don't think we needed a new Question
Speaker 2:for Pan?
Speaker 1:Make going from artificial to super is not suddenly gonna, like, help the the the technology's popularity.
Speaker 2:Yeah. Okay.
Speaker 16:Do think there is a distinction. I'm not sure, like, everyone's agreed on the distinction. But to me, as you say, AI is like a really fundamental tool. Yeah. And when you put a tool in creators and inventors hands, they're gonna invent crazy stuff.
Speaker 16:Yeah. I do think we're gonna get to the point where AIs and humans collaborate together to design a new class of products. Mhmm. And that those products humans couldn't have done by themselves. Yeah.
Speaker 16:And when you put AIs and humans together, that's a really, really, really special place to design a whole new wave of hardware.
Speaker 2:Yeah. I think that I mean, putting aside the AI versus super intelligence debate, it's hard to gauge model progress from like deep research reports because those were pretty good. A year ago, they're still really good. But this year, the thing that's felt like it's jumped forward the most has been things in the three d world, the blender modeling demos, the video game development. And that feels like a glimpse into, okay, if it's that good at making video games and modeling architecture, it's probably good for hardware engineering.
Speaker 2:So how much of this year have your progress has been, okay, the models are advancing and most importantly, aside raw IQ, are they super intelligent, just they got good at hardware this year or they or there was a step function. Or did you feel that this year has that been an important unlock? Or has it felt smooth from the inside of the industry? Because from from my perspective, it was like I would never try to use an LLM with Blender a year ago and now Yeah. It would be my first step to work with Blender.
Speaker 16:So so AI is getting really, really good at hardware engineering. Yeah. When you look at modern products, whether it's a rocket or an airplane or a car, CAD and three d design is one really important element. Mhmm.
Speaker 5:But it's actually probably
Speaker 16:the last element. By the time you are designing the three d geometry of your Wemo, for example
Speaker 1:Mhmm.
Speaker 16:All of the mechanical and the electrical and the sensors and the AI and the software, there's tens of thousands of hours of engineering work that's gone into the product before you get to geometry.
Speaker 2:Yeah.
Speaker 16:And I think we're already seeing AI chip away
Speaker 17:at that.
Speaker 16:I think the world that we've seen in AI software development is as the models get better and better, that they can start to do more and more things. In hardware development, the products that we design are so complex that it requires mechanical engineers, electrical systems, software, regulatory test. It requires all these different types of engineers to come together to collaborate on a system. And on every single one of those, AI has been getting meaningfully better over the last year.
Speaker 2:So at what level of abstraction do you want to interface with a company like Rivian or Joby or Skydio or Stokes Space? Because I imagine within a carmaker, there's the the wire harnessing and the mechanical functionality and all sorts of different systems that need to eventually be integrated. And I could imagine a system overseeing that. And any time a change happens to the electrical system, you can flow that through the rest of of the project to say, oh, well, this is gonna affect this system over here. Flag that.
Speaker 2:Do do you wanna be the overseer, the sub agent, both? What what what's most valuable right now to modern enterprises?
Speaker 16:I I think you called it. So the single biggest problem in hardware companies is systems integration and verification. Yeah. Let me give you an example. Let's say you're designing a reasonable rocket Mhmm.
Speaker 16:And you make a tiny change. Let's say you take the stage one, and in stage one, you take one of the engines
Speaker 1:Mhmm.
Speaker 16:And you make a tiny change to the injector. Well, that has this chain reaction of changes across the fluid flow and the combustion and the thrust and the mission profile. Each one of those will change other things, which then change other things. And it's that third, fourth, fifth order impacts is where we trip up, and and that's where failures come from. Mhmm.
Speaker 16:So the single biggest problem in hardware development is actually integrating systems together. And because it's been so expensive and so painful to do that, the systems engineering organization could only really afford to do it every six, every nine, every twelve months. It's a really, really expensive process to to do full on verification. But what AI enables for us is this idea that we can move from manual verification, which is once every year, to continuous verification, just like we have in software engineering with CICD. And when you bring that paradigm over, engineers can make changes in software, in CAD, in Git, in SIM on a nearly hourly basis, and the AI can understand the ripple change of that impact and flag issues the moment they happen.
Speaker 2:Yeah. I want this for architecture. I want an architect to be able to move a wall in an architectural drawing and an agent goes and reads the laws and see if this needs permitting. And like actually merging the law which is written in text files with CAD which exists in the three d space like that feels like glue for AI such that you have sort of like, you know, red, yellow, green stoplight as you're building or as you're designing the structure.
Speaker 15:And that
Speaker 2:feels like a lot what you're doing. What about
Speaker 1:How how do you think the the world is gonna need to adapt and supply chains are gonna need to adapt to, to to the actual design process and hardware engineering process speeding up by, you know, 10 x and then and then a 100 x, which feels feels very inevitable at this point. But but oftentimes, like, the during the during the actual process of designing the system, you're also figuring out how to, you know, source all the all the different sort of inputs to the to the final product.
Speaker 16:Yeah. So so this is, a really, really important point. Hardware companies are vertically integrated. They're more vertically integrated than they've ever been before, but they still need to partner with suppliers at a very deep level. So even the most vertically integrated automotive companies have hundreds, if not thousands of suppliers, and the requirements for what they need is changing on a nearly weekly, if not daily basis.
Speaker 16:And that core collaboration is happening not just across the company, but across the partner too. For a number of our largest customers, customers designing everything from data centers to EVs
Speaker 2:Mhmm.
Speaker 16:To drones in the defense industry, they're actually working natively with their partners on flow. So that core collaboration changes that the partners will make will flow into their systems, and then the AI agent will understand the implications of that change in real time. And what used to take weeks or months before can now be done in seconds. And and the thing that John mentioned is so important. Like, architecture is great because it's really obvious what the regulatory requirements are.
Speaker 16:But if you look at any one of our customers, customers like Andor, Joby, Stokespace, Rivian, there's hundreds or thousands of regulatory requirements that need to be kept up to date across mechanical electrical software, and it's a really huge problem to do that today manually.
Speaker 2:Yeah. What's the state of integrating a systems integration integration? Is it faster? Or or do you have to rip and replace some other system? Or can you sort of drop in, drop on top of all the systems?
Speaker 2:Is computer use speeding that up? Are there MCP servers for some of this stuff? Because it feels like you're very much operating in the real world, and you can go and reverse an API from some old piece of software. But what what does it actually take to onboard a new customer these days?
Speaker 16:Yeah. So amazing news for Flow and and probably what drove the raise. Today, 96% of our customers come to us inbound. Wow. And they're able to get up and running within thirty days.
Speaker 16:Wow. The legacy players are looking for, like, a nine to twelve month period of about thirty days. And AI is absolutely driving that adoption in itself. Where we typically land is on something called requirements management
Speaker 2:Sure.
Speaker 16:Which is this sort of typically old school stodgy tool base Yeah. Which houses all of the requirements and specifications. Mhmm. And the reason that is so important is it's it's the bit of information that all the design data in the company will flow back to. So if you're making changes in CAD or Git or simulation, they they come back to verify the requirements because that is your CICD process.
Speaker 16:So we are the system of record for requirements and verification Mhmm. In these hardware companies. That is that is our wedge. But what we are becoming is this much more important core collaboration layer Mhmm. This context graph for the AIs and the humans to be able to work together in in a seamless way.
Speaker 2:Well, congratulations on the progress. Congratulations on the new round. Thank you
Speaker 1:getting a new snapshot of all the progress. Yeah. It's great.
Speaker 2:Fantastic progress.
Speaker 1:Congrats
Speaker 16:Great to meet you guys. Thank you so much.
Speaker 2:Have a great rest of your day. Cheers. We'll talk to you soon.
Speaker 1:Take egg.
Speaker 2:Let me tell you about Cisco. Critical infrastructure for the AI era. Unlock seamless real time experiences and new value with Cisco. Our next guest is already in the waiting room. We have Minna Song from Elise AI, the cofounder and CEO.
Speaker 2:Minna, welcome back
Speaker 1:Welcome back.
Speaker 2:Show. How are you doing?
Speaker 17:I'm doing great.
Speaker 2:You raised some money?
Speaker 17:We we did. We raised 350,000,000.
Speaker 1:Just another day. Minna.
Speaker 17:Think we should grow
Speaker 2:to huge growth to 200,000,000 ARR. How how did you get there? What's driving the growth?
Speaker 17:Yes. We we passed 200,000,000 ARR earlier this year. We're really, it's coming from serving more customers in the housing industry and the health care industry. So we've developed a lot of new products for our customers and I we just keep building as quickly as possible because there's a lot of problems in the industries we serve.
Speaker 2:What's the secret to onboarding new customers? I mean, both of the categories you described feel fragmented to me. I don't know how many I don't know how power law driven your client base is, but I would imagine that there's a lot of customers in housing that are working on leasing resident communications, the products that you've built. So how do you actually go and reach them, onboard them? What's the flow like these days?
Speaker 17:Yeah. We we work with most of the largest housing providers in the country. Okay. But it is a it is a long tail industry, so there are tons of smaller customers that all need our software and I mean, it's a pretty hands on process. AI is a big transformation of their of their businesses and AI, as you know, can be kind of scary for some people, but but once you show you have to spend a lot of time showing people the benefit of it and then sort of like they they can't go back to doing anything the the way they were doing it before.
Speaker 17:So it's a it's a bit of a process, but we we try to make it as easy as possible.
Speaker 2:Yeah. What is customer education actual change management look like in an organization? Every company has like a couple early adopters that are probably demoing all the different tools, but there's a lot of people who are like, look, I do things this way. I've there's some newfangled tool. Oh, I got to check that out, but maybe not this week and maybe not next week either.
Speaker 2:So I imagine that there's a lot of almost marketing and advertising that you need to do even within a client who has already signed to get utilization of the products up. Is that something that you've had to overcome? Has it actually never maybe it's never been a problem, but I'm interested to hear about how you solve that.
Speaker 17:Yeah. I think, you know, AI makes a lot of technology adoption easier. Right? The number of users that ChatGPT got compared to traditional SaaS products Yeah. Was, you know, it was it was just fundamentally different technology to adopt.
Speaker 17:Yeah. So a lot of what we do when we're implementing our software is making and the change management is is making it really easy to interact with mainly through through chat. How do you talk to it versus having to learn how to click a bunch of buttons like old old systems really. And today we're in we serve 20% of The US apartment market already uses some of our products. So they are it is quite penetrated and they they are pretty familiar with the technology but we just have more and more products coming out every day.
Speaker 17:We work on really really hard problems with applied AI and to get those to market takes an incredible kind of engineering feat and research team to do so.
Speaker 1:So I imagine that I'm sure that you compete with companies that are that are much more generalist. They're work they have customers in housing and healthcare and like, you know, let's call it 10 other industries. And then I'm also imagine you compete with companies that just do AI for housing or just do AI for healthcare. Talk about the, like, strategy around really focusing on these two core industries. I imagine there's some similarities, but but but should we expect you to add new entirely new categories?
Speaker 1:Or are the TAMs big enough in both of these, like, key markets that you can just continue to focus?
Speaker 17:I think our TAM is is huge. I mean, housing and health care together are the two two largest sectors there. About 40% of The US GDP and it's really about how much of that you capture within the for the company and how much value do you add to the customers serving those industries. You know, I think we've always leaned into our strengths which is building products and the nice thing is both industries were solving in both industries were solving the exact same problem and it is actually built on the same the same infrastructure and the same and actually building in both industries has taught us a lot and has made our products better for for for one another.
Speaker 2:What are the benefits of being a company founded in 2017?
Speaker 17:You know, I think in industry, particularly serving our industries, they're not the fastest adopting of technology. So, you know, I think we were actually a few years few years early but it actually was the right place at the right time because we took a sort of warm up the market. When we started, people didn't really know what AI stood for and we were really we are one of the first AI applied AI companies serving any vertical. So it was kind of a a a patience game I guess. But I think if we weren't we hadn't started at that time, we wouldn't be in the running.
Speaker 17:We wouldn't be at the scale that we're at
Speaker 2:Yeah.
Speaker 17:To to have the impact.
Speaker 1:Yeah. Should we expect a a rebrand to Elise SI or are you just riding out AI?
Speaker 17:That's possible.
Speaker 2:I think
Speaker 17:that's great idea. Do you wanna be on that?
Speaker 1:No. I I I I think just drop the AI, just Elise.
Speaker 2:Maybe.
Speaker 1:Cleaner. Great to great to catch up. Amazing progress. And come back when you get like 50% market share or penetration into these. Think that's a good Yeah.
Speaker 2:Talk next month. We go.
Speaker 1:Awesome. Have a great Great to catch
Speaker 2:day. We'll talk to you soon. Cheers. Goodbye. Let me tell you about Console.
Speaker 2:Console builds AI agents that automate 70% IT, HR, and finance support, giving employees instant resolution for access requests and password resets. Our next guest is the CEO, interim president and CEO of MongoDB. We have Dev coming on the show for the first time, but he's been CEO before. And what a journey he's been on. Dev, welcome to the show.
Speaker 2:Welcome. Thank you so much for joining us. How are you doing?
Speaker 4:It's great to be here, guys. Thanks for having me.
Speaker 2:Thanks so much.
Speaker 1:Memorable week in your career?
Speaker 2:Yeah. Never a dull day in the AI talent wars, I'm sure.
Speaker 4:It is interesting to say the least. Clearly, we didn't anticipate this, but the company is on strong footing. You know, I feel really good about the business. We had Investor Day yesterday where we talked about our long term outlook. I think it was really well received.
Speaker 4:And, you know, we talked about how the business is accelerating. We talked about how Atlas, which is the core kind of product area that investors really queue on because it's been the biggest growth driver, we raised our guidance. We also talked about the fact that we raised our guidance or frankly feeling good about our operating margin, our cash flow, and we also announced we're buying back a billion dollars worth of stock. So Wow.
Speaker 1:There you go.
Speaker 4:Fantastic. I mean, a period of time, not
Speaker 1:The
Speaker 4:all at point is that we feel really good about the business, and I think people, you know the challenge, I think, is many times CEOs get a lot of credit and sometimes too much blame, but in this case, there's a really strong team around the company, and the team has done a really good job, and I'm happy to, you know, step in. And to be clear, it's an interim role. We'll be focused on finding a successor, but obviously we're take our time and do it properly and thoroughly. But it's a very attractive role, so my phone's already been ringing and we already have a retained search going on.
Speaker 2:There we go.
Speaker 1:That's great. There's some debate earlier online about like executive poaching in an entirely different category and someone was trying to make the point that that this cycle is like different in some way. When you look back throughout your career, is the intensity around just just recruiting Talent. And poaching and Talent Wars notably more intense than, let's say, the cloud build out and mobile and and and sort of the the .com era, or is it just more of the same business has always been war?
Speaker 4:I would say people have always been very aggressive, but I think clearly with especially in the AI era, the money being spent on talent has has obviously been breathtaking, to say the least. This one frankly surprised me because it's not so much about AI expertise, but I think Meta really didn't have a lot of DNA around enterprise expertise. I mean, they've never really sold to complex, you know, global organizations like Goldman Sachs or JP Morgan. And so to try and organically build that would probably be challenging. And so I think they just felt they had a deficit on a certain area, and obviously, Zuck has not been shy about throwing money around, and and he did that again here.
Speaker 4:So, you know, CJ made a decision, and I'll let you pass judgment. But what I will say is, like, I got a note from a good friend who says, at the end of the day, no one's going remember how much money you make. They're going remember what kind of leader you were and what kind of person you were, and I'll just leave it at that.
Speaker 2:Yeah. You refresh everyone on on your journey, both in your career broadly, but also, with MongoDB specifically because, this is not a this is not a wild card that you're in this seat. Like, you are a very logical selection for this interim role. But if you could give us some background on on your journey in tech and then your relationship to MongoDB, I think it'd be really helpful to understand.
Speaker 4:Yeah. Sure. So I was a two time founder of a company that started in 2001. Mhmm. I was a company called BladeLogic, and it ended up going public in 2007, and then acquired by BMC and became the president of BMC Software for a couple of years.
Speaker 4:I segued into being a VC. I was at Greylock in a small firm out of Boston, actually led the b round of Datadog. I'm still the lead director of Datadog. I invested in Datadog when Datadog was doing only a million revenue.
Speaker 2:Wow.
Speaker 4:So sometimes it's better to be lucky than be good. Obviously, Ali and the team there have done a spectacular job.
Speaker 2:Yeah.
Speaker 4:And at the same time, being a VC, I was doing a lot of work on next generation databases. In fact, I looked at some competing investments to MongoDB, but when I did my diligence, it was clear MongoDB, even at that time, was way ahead of everyone else. I wouldn't say way ahead, but ahead of everyone else in terms of developer mindshare and even financial momentum. But ironically, about six months later, I got a call from a search firm saying, hey, MongoDB is looking for a CEO, would you consider it? And they in fact strongly said, you should definitely take a look at this job, Dave, it's ready made for you.
Speaker 4:And being an you know, usually you get calls, and what's interesting is when you get a call for a CEO job, I've trained myself to ask what's wrong, because no one calls you when things are going spectacularly well. No one says, you know what, let's just change things up and, you know, make a change of the CEO role. So, and the challenges then are the changes or the problems you have to fix, are they fixable or are this really essentially so fundamental to the company that it's just going be impossible to change. When I looked at MongoDB, what was interesting is that I was not that impressed with how the organization was run. The engineering team and product teams were good, but the go to market organization was a bit dysfunctional.
Speaker 4:The culture of the leadership team was dysfunctional. And so, and then there was really three knocks against MongoDB. One, open source at that time, no one had really made money in open source, Red Hat was the only company that had created any real value. Databases, a lot of companies had died on the line of being the next Oracle and the landscape was littered with dead database companies. And deep tech out of New York was not something that was proven because at the time it was more of an ad tech and kind of consumer space for tech companies.
Speaker 4:And so, when I went through that, one, I thought open source 2.0 was going be much it was really better technology than open source 1.0, so that addressed that question. Two, databases I felt like I could see the developer momentum with MongoDB, and I said if developers really love MongoDB, you don't bet against a product that people love. Yeah. And with New York, you saw Google and Amazon and Meta really investing in the New York area, and we recognized that we didn't have to only hire in New York, but there was definitely a lot of talent. Whereas, like, ten years earlier when I tried to start BladeLogic, Actually, fifteen years earlier, it was much harder to, you know, do a start up at that time in New York.
Speaker 4:I actually start end up moving BladeLogic to Boston.
Speaker 2:Yeah. So yeah. Can you talk about your time as CEO of BladeLogic? I have this
Speaker 1:Also, let's let's I wanna note, like, the timing there. You you start the company post correct post March correction or or in q one?
Speaker 4:Oh, in terms of yeah, yeah. It was it was 2001, so it was actually five days before 09/11. It's my first sort of financing. At that time, it it was pretty crazy to start a company because one, you know, customers want to deal with .coms because that'll blow it up.
Speaker 2:Yeah.
Speaker 4:Employees don't want to work at .coms because they're all blown up. Have lot of worthless, you know, stock certificates. Yeah. And raising capital was super expensive, right? And so but we had conviction that because the previous company had started ended up being a first generation cloud computing company, actually I ended up competing with Market Ben, they had started a company called Loud Cloud.
Speaker 2:That's great,
Speaker 4:yeah. And then when I started BladeLogic, they pivoted Loud Cloud to Opsware and then I started competing with them again. And if you read Ben's book, he talks about going head to head with a pretty formidable competitor called BladeLogic, So, it's funny how this world is so small. But, yeah, it was a pretty tricky time to start a business. And the thing that you learn, which I worry about with a lot of the founders today, is that we had to build the business the hard way.
Speaker 4:There was no tailwinds on our back. It was a tough economic environment, large companies, our first customer somewhere we luckily closed Sprint and Priceline, but it was a slog to convince, you know, these large organizations to get bet on this new fledgling company when they've seen so many other startups quickly die.
Speaker 1:Well, and now you look at look at how many different, you know, unicorns provide infrastructure for other companies to be able to scale really quickly and and you know things like Work OS, right? Like I imagine there was nothing close to that at the time that would allow you
Speaker 2:to Work go buffer browser based.
Speaker 4:We had to do everything. We had to build So my
Speaker 1:last So you're building like 40 startups at once just to build one company.
Speaker 4:Exactly. And I only raised 29,000,000 in total and had had seven in the bank when we filed our s one. Wow. So essentially, I funded the company through through customers.
Speaker 1:That's amazing. Seven in the bank when you filed as one is just
Speaker 2:it's actually incredible. Like we burned a trillion dollars.
Speaker 1:Trillion live. How have you open source AI or or open weights AI
Speaker 2:You mean open source SI?
Speaker 1:Yeah. Yeah. We're calling it SI as of yesterday apparently. The the sort of economic model could potentially feel much more straightforward with with some of some of the Chinese AI labs just saying, hey, we're gonna make this model, but if you wanna host it and serve it, have to pay us back a some type of rev share. Yeah.
Speaker 1:Is that the like, given your experience, you know, with with Mongo, is that going to be do you expect that to be, like, the the primary economic engine for for open weights? Or do you think it's something that looks like more like Red Hat or or MongoDB where you're building you're making an open model and then you're building, you know, more infrastructure and products around it?
Speaker 4:Yeah. So the classic open source model where you get some part of the core free and then you pay for, like, say, the adjacent features around it, I think is somewhat challenging because I'll give you our example at Mongo. We had an open source product, and we provided So anything that developers needed free, but any management tooling and so on and so forth was paid for. The challenge was, like, you know, defining that paywall between what's free and paid is always difficult, because if you give away too much of the product, you know, you can't monetize anything. And if you give away too little, it's very hard to drive adoption because people need time, soak time, to kind of really use the product.
Speaker 4:Frankly, the breakthrough for us, so we found that, you know, that paywall, but we were growing the business more slowly, the breakthrough was really open source as a service. Because when you offer open source as a service, you charge for every little bit of usage. And so we could have customers that are paying us $10 a month, and you could have customers paying us a million dollars a month. And frankly, have that, right? But the fact that you conditioned pay for something just made the economic it wasn't like a debate of what's free and what's paid.
Speaker 4:Now, customers still have the choice to download and run it on their own, and then we have our self managed proprietary product as well. So I think to use that analogy, I think if it's offered as a service, I think that's much easier for people to handle. Now, recognize with these models, a lot of people are concerned about IP rights and they want to run it on their own on prem. So there, you know, rev share model is tricky because, you know, how much how much do you share? And that becomes just a judgment call, and, you know, different customers will have different opinions about how much they think they need to share with with a third party.
Speaker 1:And you're running running it on prem and then what? Do you have to open it up to like some do you have to basically be do you as as an open source, you know, lab, do you have to be auditing all the users of your model?
Speaker 4:Let you do that. Yeah. There's there's no way that's gonna happen. So then it's a trust model which becomes also a little challenging.
Speaker 1:Mhmm. Totally.
Speaker 2:I have I have a question. Sort of going back to the emotional roller coaster that CEOs go on, particularly founding CEOs. I've noticed at the early stage there's the founder CEO is like, oh, I got to get my board aligned. I need super voting. I don't want to be thrown out.
Speaker 2:And then after a while it can sort of flip around and I've talked to some founders in the CEO role and I'm like, I think the board needs to worry about you leaving. And that psychology of having enough control over the company as the CEO, the tension, I mean, we're seeing it with companies that are about to go public, how to set up the right corporate governance for the modern era. How did you confront that in partnership? There's various firms that are known for, oh, yeah, if you're not performing, they will throw you out. There's others that will say, yeah, no matter what, we always back the founder.
Speaker 2:How have you grappled with that on both sides of the table throughout your career?
Speaker 4:Yeah. It's a great question. Frankly, I'm a little old fashioned. I have a very simple rule. If the company's performing, management's in charge.
Speaker 4:If the company's not performing, the board's in charge. It becomes very simple that way. Right? And yes, you know, you've seen some public companies where the founders have still total control, but the stocks are tanked because people just say there's no governance here and, you know, why am I investing?
Speaker 1:Yeah. It's it's a discount rate. Like I I think Meta has been going through this where like you have to apply some discount on Meta right now because you don't know even like in in in my psychology on it is like, let's say Zach gets AI working like really well, frontier models, leading consumer applications and enterprise business. To me it's like you as soon as he gets the next thing working, he's gonna bet another $500,000,000,000 on the next thing Yeah. And you're not gonna know if that's gonna work.
Speaker 1:And so for me I've always been I just always mentally
Speaker 2:Eric Soufried calls it tilting at wind windmills.
Speaker 1:Yeah. Yeah. Yeah. But but to me, I'm like, okay. If this if this was run-in a more kind of like stable way where where where there was some shareholder influence, it would probably trade higher.
Speaker 1:But who knows?
Speaker 4:Yeah. Exactly. And then I think the other on the other side of the coin, I I have to remind founders that no investor wants to go and replace the founder. Yeah. There's no incentive for them to do so.
Speaker 4:Yeah. So only if things are really going poorly will they ever contemplate such an action. Like, they will do everything in their power to make sure the company's successful. And it's really up to the founder to live up to their obligation to kind of, you know, do the best they can. And there are many founders who, like, decide, you know what?
Speaker 4:I'm not the best person to be CEO. Gotta bring in someone else. Yeah. Or sometimes they say, I'll be CEO, but I need a strong number two to run a certain part of the business that I just am not good at or I have no passion about. And to me, those are the founders that, you know, are more mature, but someone who's just always paranoid.
Speaker 4:I mean, if you're worried about the people who are giving you money that's gonna, you know, basically take you out, then you got the wrong partners.
Speaker 2:Yeah.
Speaker 4:And I've been fortunate to have some great investors. I'm also, only a couple weeks ago, joined Sequoia Capital. Know, they have a great track record of thinking long term. And, I, you know, I know you just had Ruloff earlier, but he was on my board for eleven years, you know, while I was CEO. He's still on the board, and actually I was just with him yesterday in New York, and there were times when he would push me, there were times he would challenge me, there were times when he but then when I needed him, he would always be there to support me.
Speaker 4:And I think these founders who get so worried about control and like someone can take me out, I you think have to look at yourself in the mirror and say, Why if that were to happen, don't you feel like you have some obligation to perform? Otherwise, if you don't have any obligation to perform, then something's broken.
Speaker 1:That's the same it's the same advice you'd give to, like, talent at a company. Let's say, like, basically become you know, I've seen people join a company become so important to the company that at some point, like, you can just tell, like, 50% of the enterprise value is tied to this one person who's not actually a founder and maybe not even on the management team. Right? And so Mhmm. And then you end up having enough leverage that you can go and get whatever you want economically, but then also rise up to to to to pretty and actually have more control over the company.
Speaker 1:So
Speaker 2:Yeah. Last question for me. Can you give me some color on how you think about the various buckets of skills that you're looking for in a really talented CEO who's going to go the distance? Is it the Rolodex strategy in ability to engage with the financial markets?
Speaker 1:Understanding of the customer.
Speaker 2:Golf handicap. What's important?
Speaker 4:To me, it's the fundamentals. I'm actually not not a big believer in Rolodex because because people come and go. To me, it's the fundamentals of knowing how to build a business. One, you know, being very clear about what your strategy is. Two, like, lot of people ask me, what is the job of a CEO?
Speaker 4:To me, the job of a CEO comes down to three things: being very, very clear in your strategy. Here's where we're going, so by definition, here's where we're not going. So that makes decisions easy. You know what to prioritize because the strategy is so clear, you know, it makes decision making easy. The second thing is, you know, assembling the right team around you, right?
Speaker 4:So who's on the bus? And sometimes as you grow, sometimes some people have to get off the bus because it's not scaling, and then you bring new people on the bus, but you have the right people who are really complimenting you to build this great business. And obviously, if you have the right leadership team, they're going to build out their teams respectively. And the third thing is really create a culture and remove all the obstacles that prevent the team from being successful. And, you know, you can create a mercenary culture, which has its own second order effects.
Speaker 4:Or you can create a culture where people are really connected to the mission, they're really connected to what they're doing. You really develop And we think of culture as like another product in terms of how do you attract and retain employees, right? And so if people feel like it's a great culture, they feel like they're learning, they're growing, they're developing, and there's a meritocracy, if they perform, they get more responsibility, You know, that's ultimately what a CEO's job is, right? I can do a thousand things. Like, I can do this interview, I can go meet with customers, but if I don't do those three things well, nothing else matters.
Speaker 2:Scratch offer is more of like a nice to have. That's what I'm hearing.
Speaker 1:How should I know I know we're over time and you probably have more important things to do. I do have one more question. How do you think a CEO should balance sort of like a sort of capitalist versus communist approach? Capitalist being like, you know, bottom Oh, yeah. Entrepreneurial, letting
Speaker 2:A thousand flowers blue.
Speaker 1:Come up with ideas and run things down versus like, you know, central planning top down. This is our this is our approach.
Speaker 4:Yeah. Think it's a mix of both, but I think like, you know, when you seek feedback, you have to seek feedback from people you trust and who have a, you know, certain point of view, right? When someone disconfirms my beliefs, you know, when I was younger, I kind of completely ignored them saying they're basically bozos, but it caught me flat footed and I've tried to train myself. When someone I trust is giving me feedback that just disconfirms my beliefs, the first question I ask is what do they see that I don't see? What do they hear that I don't hear?
Speaker 4:And what is the persuasiveness of their logic, right? And in a market that's moving so quickly and you have a set of core beliefs, sometimes those beliefs could be challenged and changed. And so to that end, you have to start rethinking your strategy. If you don't have people who challenge you, then, you know, like Steve Jobs famously didn't like board members who agreed with him because he wanted to be challenged. And I think too many people want to hear the kumbaya, oh, Dave, you're so wonderful, you're great, and all that.
Speaker 4:But that's not really that helpful to me. What's helpful to me is, hey, have you thought about what's coming around the corner? Have you thought about like, are you really is the scale of your ambition as aggressive as it should be? You know, are you thought about like what potential new technologies could disrupt your business? I mean, that's the way you should operate, and you should have a team who thinks that way.
Speaker 4:The lesson I've learned a lot is the ability to tell a really strong team is the ability to have hard conversations. There's so many people who are very passive aggressive, You know, they'll nod politely and agree, and then they'll go back to the desk and roll their eyes. But if you create a culture where people can feel like, hey, it's not my idea, it's the senior person's idea that wins, it's the best idea that wins, and people feel comfortable challenging you, that creates a great environment where people feel like, you know, we're really focused on what's right for the business.
Speaker 1:Well, I'm gonna have to disagree with you there. I'm kidding. No. Great great point. And I wish we had more time.
Speaker 2:Yeah. This is fantastic. Thanks so much. Good night. Luck.
Speaker 2:What a wild time. When you
Speaker 1:when you figure out the right
Speaker 2:Yeah.
Speaker 1:Person for the job Yeah. Luck to have them on the show. Them. It's great to meet with you.
Speaker 2:Thank you. Partnering with Mongo. Cheers. Have a great rest of your day. Goodbye.
Speaker 2:Let me actually tell you about MongoDB. What's the only thing faster for the AI market? Your business on MongoDB. Don't just build AI. Own the data platform that powers it.
Speaker 2:We have Daragh Murphy, the CEO and co founder of Imprint in the waiting room. Let's bring him in. How are doing? Boom. Welcome to the show.
Speaker 15:Hey, guys. How are things?
Speaker 2:We're good.
Speaker 1:So good. First time on the I
Speaker 15:appreciate you guys having me on. Last slot Yeah. Of the
Speaker 2:No. Second to last slot. We have another we have another guest in person. But anyway, introduce yourself, the company, the news. Give it to us.
Speaker 15:Yeah. So at imprint, we're building the infrastructure that lets everybody feel like a regular at their favorite brand. Mhmm. We think that starts with co branded financial payments. And so with Kroger, we're launching or relaunching their co branded credit card.
Speaker 2:Sure.
Speaker 15:They're leaving a big bank, bank that's been around for a hundred years choosing us. It's obviously a big vote for us because they're the fourth largest merchant in The US. Yeah. And you're probably asking, like, why does somebody like Kroger choose Imprint over a Fortune 100 bank? Mhmm.
Speaker 15:There's really three reasons. One, we're not trying to steal their customer. So many banks are trying to steal their customer, sell them a mortgage or a deposit account, or they got BNPL trying to steal their customer and sell them to somebody else. Mhmm. Two, we took this $100,000,000 bet to rebuild the our tech platform for ourselves.
Speaker 15:All the banks, every credit card in your wallet, they rely on legacy infrastructure, mainframes in the Midwest. We own it so we build better product. And a lot of times now with these merchants, our partners, you know, when we first started talking to them four or five years ago, they were worried about getting disintermediated by Amazon or Instacart. Today, the conversations we have is how do we help you stay relevant when news is on the horizon, instinct is coming, and our perspective perspective of the merchants is top of wallet, you're top of mind. And so if we give you a better credit card, more rewards, fairer, then you end up being a big part of the consumer's life.
Speaker 2:Talk to me about how I should think about your business. You mentioned they they would go with a the alternative is going with a bank. Are you registered as a bank? Do you have a charter? Or are you more of a like a fintech software layer?
Speaker 2:Like, what are the economic breakdowns? We were I I wanna go further into what cobranded card economics look like, but give me the one zero one on the category.
Speaker 15:Yeah. So we offer the brand the exact same thing that a bank would. In fact, Shell recently left Citi for us. Craig and Barra left a big bank for us last year. Yeah.
Speaker 15:Our proposition is you get the same as you would get from the bank plus a much better technology, product, etcetera.
Speaker 2:Okay.
Speaker 15:The way it works is we're not a bank. We work with partner banks.
Speaker 1:Okay. You
Speaker 15:know, Affirm, Clarin, everybody else does the same thing.
Speaker 5:Sure.
Speaker 15:And the way the economics work is we help the buy or the brand fund some of the rewards.
Speaker 4:Okay.
Speaker 15:Richer rewards matter for customers. Right? Everybody loves their rewards credit card.
Speaker 2:Sure.
Speaker 15:If we work with a brand that owns a big share of your wallet, why wouldn't you wanna use the credit card?
Speaker 2:Yeah.
Speaker 15:And the way and then we have a profit share with the bank off the bottom.
Speaker 2:Got it. Right? So I imagine Yeah. Imagine, like, Visa and Mastercard, like, the rails are still taking, you know, 1%, 2% of the transaction fee, but there's still maybe 1% that's floating around there that can be given back as a reward or kept. How close am I on the actual numbers?
Speaker 2:How does it split down?
Speaker 6:Pretty far off.
Speaker 7:Okay.
Speaker 15:So the rails take, like, 15 or 16 basis points.
Speaker 2:Oh, it's really low.
Speaker 15:Both sides. Yeah.
Speaker 2:Interesting. And
Speaker 15:then the the name on the card, imprint, Chase, whomever, we get interchange of about a buck 80 2%.
Speaker 2:Okay.
Speaker 15:And then we give almost all of that back to the brands give the consumer better rewards.
Speaker 2:Okay. So we were debating this in the context of Instinct, the personal AI agent. And we were sort of asking ourselves like why hasn't an AI company launched a co branded credit card with a company like you and then use that as a monetization strategy? Maybe they can give it back in tokens or do some sort of reward but basically Yeah.
Speaker 1:Big thing is like you can't Start getting some
Speaker 2:transaction fees.
Speaker 1:Want to capture transaction fees quickly Yeah. Going out and doing partnerships, you know, you can do the big partnerships with like a Shopify. Yeah. There's a lot of other things that you buy online. There's a lot of like I I think about the number of local service providers I've found with ChatGPT that ChatGPT gets no benefit from and it's great for the service provider.
Speaker 1:And there might
Speaker 2:not be a referral program. The
Speaker 1:beauty the beauty of a card is that is that the the service provider is used to paying a transaction fee Yep. And it doesn't really feel like they're paying No. Anyone when they do it because payment, you know, transaction fees are normal. So feels like it it also makes sense in the sense of, like, linking the payment method to the account, then you're not dealing with, like, oh, I'm authorizing this agent to use credentials stored somewhere else. Like, feels like there's some potentially security
Speaker 2:Yeah. Do see it going?
Speaker 15:Yeah. All I can say on that specific point is watch this space.
Speaker 5:Okay. But
Speaker 15:if you think about
Speaker 6:it more broadly, right, like,
Speaker 1:everybody
Speaker 15:hates, everybody is that a good that's not the sales guy.
Speaker 1:No. No.
Speaker 2:No. No. That's like it's getting real. It's like a boat horn, like, you
Speaker 15:know Amazing.
Speaker 1:Action movie. Yeah. Yeah.
Speaker 7:Yeah.
Speaker 15:Amazing. Look. I do I think if you if you think about the space generally,
Speaker 2:like Yeah.
Speaker 15:Everybody hates interchange. Everybody hates paying Visa and Mastercard. Yeah. I think there will be credit cards, but I think the really interesting question is, like, what's one step beyond that? Sure.
Speaker 15:And so a lot of what we've been investing in is, like, letting merchants, letting brands accept your bank account as a payment. Sure. Because that's, like, basis points on the dollar. Yep. In a world of agents, you can optimize that.
Speaker 15:The hard thing today is it's like a shitty it's a bad sorry. I'm Irish.
Speaker 5:It comes out sometimes. It's a
Speaker 15:bad user experience to have to link your bank account. Yeah. If you can be, like, Muse or Instinct, here's my bank account details. Yeah. I trust you to to link them up correctly.
Speaker 2:When Instinct get rid
Speaker 15:of that friction. Right?
Speaker 2:Like,
Speaker 15:crypto was a fugazi year. Like, this is actually the first time I think interchange is in danger. Yeah. And it's 2% of American commerce goes across these rails. So it's a huge amount of value.
Speaker 2:Yeah. No. I mean, was pushing for this for years with the with the credit card push trying to get to ACH with with various customers, and it was a really long slog. The Apple Pay ecosystem sort of won a lot of things, but yeah, you can see that it it it the game is once once again a foot with with the agentic era.
Speaker 15:And Stripe is pushing this with Muse. Right? Like, you have the Stripe link experience. I think, know, you use Uber today. The last time I used it, it prompted me to use Stripe link instead of using a credit card.
Speaker 15:Right? And so, yeah, it's actually very bearish, think, for those, like, you know, Mastercard, Alemix is a different business. But longer term, I think it's gonna be great for merchants and and consumers.
Speaker 2:Yeah. Yeah. That makes a lot of sense. Jordan, anything else?
Speaker 1:Great to finally have you on. I remember when you launched I I or maybe not launched, but I remember back in 2021, I was building in fintech too, and maybe it was around that I saw. But when I saw the business launch, it made it made a lot of sense. So it's great to hear all the progress. And it's great to have an Irish it's great to have an Irish accent on the show.
Speaker 1:You know? You don't have enough of them.
Speaker 15:Yeah. Sorry for the swearing.
Speaker 1:No. No.
Speaker 2:You're good. It's all good.
Speaker 1:You're good. Come back on or or flag when you have some of these Yeah. Some news in in personal agent world.
Speaker 2:Fantastic. Will do.
Speaker 5:Thanks, Hans.
Speaker 2:A good rest Talk of your to you soon. Let me tell you about Figma. Agents, meet the canvas.
Speaker 15:Your
Speaker 2:AI agents can now create and modify your Figma files with design system contacts. Our last guest of the show, Noah Friedman, is here in person in the TBPN UltraDome. Welcome to the show, Noah. How are
Speaker 14:you doing? I'm good, boys. Good to be here, the UltraDome.
Speaker 2:What news do you have for us? Oh my. Should he hit the gong?
Speaker 1:Do it.
Speaker 2:Yeah. Okay.
Speaker 14:We are announcing Outer Signals $22,000,000 series a today. Do I just
Speaker 2:go Congratulations. Yes. Smash it. That a real instrument. It is.
Speaker 2:It is. Smash it. Fantastic. So so introduce Outer Signal. Introduce yourself for everyone who doesn't know, and then I'm sure there's so many questions we can go through Yeah.
Speaker 2:There.
Speaker 14:Thanks for having me, guys. Appreciate it. Outer Signal's a customer intelligence and agentic personalization platform. So when any consumer checks out or transacts with the business Yeah. Most businesses really only know about that person that their name is Jordy.
Speaker 14:Yep. They live in LA. Their email, Outer Signal paints the rest of that Right? So we give a full time in real time name, email address, date of birth, age, gender, occupation, property value, a full profile behind every single consumer, which lets businesses actually speak to their consumers like humans Yeah. Not just orders.
Speaker 2:Yeah. And and what is the best way to actually take advantage of that as an e commerce business? I mean, I can imagine, okay, some celebrity shows up, maybe you reach out to their agency to do a deal, all the way down to like personalizing an email which is its own fraud thing because sometimes Sure. You get an email and you're like, that's a little too personal. Don't know.
Speaker 1:Yeah. I'll I'll start with an example. Yeah, please. I know I know Aurora Yeah. Is a customer Love her.
Speaker 1:Of Outer Signal. Yeah. I remember within the first three months of launch, Brian or Charlie messaged me and said something like, I'm not gonna name the person but it was like a top five actor in the world. Yeah. And I was like, how do you even know that?
Speaker 1:And they were like, well, we're using this thing called Outer Signal. Yeah. And that person wasn't even using their actual like they were using a pseudonym Yeah. For the the the order. Yeah.
Speaker 1:So it was like
Speaker 2:But it linked it all up.
Speaker 1:But it showed and and and so yeah, it's like I think people it's not just these sort of extra, you know, elements and kind of like populating data that's already out there. There's like other Sure. Sauce that you guys have.
Speaker 14:Yeah. There's certainly other sauce. Mean, it's doing what we do is both a technology challenge and an anthropology challenge, like and the example that I give is you know how many people there are named Noah Friedman in the world? Oh, yeah. So, like, if Noah Friedman orders from Aurora, disambiguating which one is me is remarkably difficult, and that's what our engineers have spent hundreds and hundreds or thousands of hours mastering.
Speaker 14:And it's a really hard problem, but we've cracked the code on it. I think to your question, John, it's actually a lot bigger than just like, these examples of finding celebrities are very cool and fun. Yeah.
Speaker 1:Huge business No.
Speaker 6:It's more
Speaker 14:built around that.
Speaker 1:It's more like cool for the for the For the personalized market.
Speaker 14:Yeah. Exactly. It's cool for But the example I give is this. Like, literally when we when I was in the green room there, I got an email from a brand that I probably spent thousands of dollars with telling me that their new drop had just hit and it was like sports bras. Yeah.
Speaker 14:And it's like, I've spent thousands of dollars with this business. They have every right to know who I am. I'm a very, like, you you can Google me and figure out who I am and they just didn't take the time to do that because it's impossible. Right? Mhmm.
Speaker 14:And so the downstream impacts of what Outer Signal is all about is really to say, like, behind every order, behind every consumer who transacts with the business, there is a human being. Yeah. And those human beings deserve to be treated like human beings. And so across email marketing, right, where, like, a brand that hits me with an email about performance in the gym or when I'm up late working on my business, like, that's gonna slap. That's gonna hit a lot better than if they hit my mother with that.
Speaker 14:Right? So across email and retention, across paid media and acquisition, all of this is downstream of this concept of, like, everybody transacting with these consumer business, they're real people. And these companies just have no basis or bearing to say the second an order comes in, we're basically just routing them into the arbitrary Klaviyo flow or what have you just to like hope that it lands with them. When in reality, there's so much more context that can be grabbed Yeah. In the real world.
Speaker 2:How do you think better intelligence in the e commerce world flows to retail strategy? Mhmm. There's always this pitch of like, okay, you look at the shipping locations and you see that everyone's within, you know, two miles of this store, we should go pitch that store. But it feels like it can go a lot further. How are you seeing because I I I mean, I feel like every ecommerce business now, like the D to C era is fully over.
Speaker 2:Like, your omnichannel Gotta be at least day one in the deck if not day one in Day one the deck. I like that.
Speaker 14:Day one in
Speaker 3:the deck. That's a banger. Not Bar.
Speaker 2:But if but like you need to be thinking about this and you can't be turning down opportunities for retail expansion and saying, we're a pure play d to c company that cuts out the middleman if you wanna scale in
Speaker 14:the
Speaker 2:modern era.
Speaker 14:Look, I think there's a couple angles
Speaker 2:to it.
Speaker 14:Yeah. Number one is saying if you're trying to activate and pull deeper velocity Mhmm. At any of these retailers, which is ultimately, I mean, we talk about
Speaker 2:this with Lucy all
Speaker 14:the time. Right? This is the hero is how fast you're pulling through these stores. Understanding how to locally activate an audience, which Outer Seed can allow you to do in ways that Meta just can't. And being like, look.
Speaker 14:Around these ZIP codes in Metro LA or in the middle of the country, it doesn't matter.
Speaker 1:Yeah.
Speaker 14:We can actually drive hyper targeted funnels and flows in the store Yeah. Because we know who these people are and we know how they're different in these different markets. That's huge. We've also had probably hundreds of brands at this point both find retailers that were buying from them
Speaker 2:Oh, with
Speaker 14:their personal address
Speaker 2:Yeah. I've seen them before.
Speaker 4:On ecom.
Speaker 14:Yeah. Like a huge creatine brand was able to get like a really big placement Yeah. Because they found out that the senior buyer from Walmart, like their square ICP had been buying personally as just a fan Yeah. Under his email.
Speaker 2:So,
Speaker 14:you've got that angle and you've also got like when you're pitching retailers. Right? Like you guys know this. One of the most important things you can do is have a really fundamental understanding of like who the hell you're actually selling to. Alright?
Speaker 14:And I think so many consumer businesses have this archetype or the persona of who they think they sell to and it all feels very much the same. Like, I cannot tell you how many brands we meet and onboard into Outer Signal where in the sales process we're like, hey, who do you guys think your customer is? And they're like, young urbanite professionals in New York. Yeah. Well, you can't all sell to the same person.
Speaker 14:Right?
Speaker 1:Yeah.
Speaker 14:And it turns out when you activate it, it's like, no, it's actually Midwest moms with high disposable income. They're the ones paying your bills. This persona of, like, the young professional urbanite in New York
Speaker 2:Yeah.
Speaker 14:Is a super small percentage of your revenue. It's actually a less valuable customer, but they gravitate to one specific product. And so across merchandising, to understand which products resonate most with this demographic or this demographic, and across actual placement in store and pitching retailers
Speaker 5:there's
Speaker 14:so much depth and nuance that comes from understanding who the f these people are that are actually buying from you Yeah.
Speaker 1:How are you right now, explosion of of personal agents, you have Instinct and Yeah. And Muse. And and even in the last twenty four hours, it seems like Instinct started doing Yeah. Like basically like texting Texting. Texting product recommendations, which exposed something that was kinda interesting to me, which is that the agent knows about the user.
Speaker 1:I saw one where the user it was pushing various car products for a Targa. And the user was like, how do you know I have a Targa? And it's like, oh, we worked on like getting insurance for a car like Yeah. A while ago. But then the agent was actually recommending products like just products that a Targa would never need.
Speaker 1:Like pushing a trickle charger and indoor cover, which like a real I don't know any like real car guys that are like, I gotta keep my 2026 Targa
Speaker 2:The best and and and
Speaker 1:No one I know is like using indoor covers because real ball knowers would know that like if you if you drive your car outside and then you put a cover over it Right. And you put and and there's like debris between the paint and the cover, it will actually wear the paint down faster That's ball. Yep. Do more damage to the car. So like, that basically it was like a personalized recommendation from somebody that shouldn't be making a recommendation.
Speaker 1:Right? Yeah. Like someone that did not have ball knowledge.
Speaker 14:Lack of ball.
Speaker 1:Still still to be clear, like it's almost like on the brand side, the brand needs to like brands need to be thinking about educating agents Mhmm. Totally. Because the agent knows the customer, but the agent needs to know who to pitch it to. Yeah. Like a like somebody with a Ferrari or a ten year old Ferrari should get recommended like, hey, maybe if you're not using a trickle charger, your battery is gonna wear down fast or But it feels like an entirely new task for the for the company to like educate agents.
Speaker 14:Couple thoughts.
Speaker 2:Yeah.
Speaker 14:Couple bars in there, by the way. Ball network there. I think it's we just have, like, a thing now, like, you can't make personalized recommendations unless you know a ball.
Speaker 2:Right? Sure. Yeah. So out of Yeah. The bar has moved.
Speaker 14:The bar has moved.
Speaker 4:Ball posts
Speaker 2:have moved.
Speaker 14:Couple Couple things. Number one, I think that example actually touches on something critical, which was that that personalization was really just behavioral. Right? You bought this, you might like that. Right?
Speaker 14:It has no context on like who the hell you actually are as a person. And that's really been the failed promise of personalization for the last decade, which is like a lot of the companies out there selling personalized solutions for marketers. It's all based on Jordy clicked on this ad or he came in through this landing page and he bought this product. And so we think and we guess and we're just gonna make some hypothesis finger to the wind that the next product he might like is why. It's all pulling from the same signals that it's been pulling for from the last ten years and, like, it just doesn't work.
Speaker 14:And the outcome of that, whether it's an agent recommending it or the brand on email or just the landing page, is that it feels highly impersonal. Right? And I would argue that the next layer, the next frontier, and the one that we're ushering in is to say, like, who the hell is Jordy? Right? Like, did he just post on his Instagram last week that he got a new Ferrari?
Speaker 14:That's really important context for me to know, not just that he actually has a car and checked out insurance last month, and so, like, let's upsell him and try to up select him into some other product, which we can draw some fuzzy connection to. Right? Mhmm. So I think agents are going to like, agentic commerce as a concept is in its very early days. Right?
Speaker 14:Like, think all these companies are still trying to figure out what does it actually look like for Muse or Dot or Dots or whatever the hell the play for the month is, right, to recommend a product to you in chat and in feature. Very early days of that, and we're keeping a close eye on how we can interface with that and play with it. But I think at the end of the day, it all comes down to, like, whatever touch point a business has with their consumer is the most valuable real estate they've ever had.
Speaker 11:Right?
Speaker 1:Yeah. And the and the and the main thing for customers is, like, getting pushed a product that makes no sense for you.
Speaker 14:With a message that makes no sense.
Speaker 1:Well, getting pushed a product that makes no sense for you just completely like, I've I've had this with with
Speaker 2:You don't need a charger battery?
Speaker 1:Yeah. No. No. I just had this at, car like, sometimes you're you're if you're at a car dealership, like, the associate will try to sell you of their one of
Speaker 2:their system.
Speaker 1:No. One of their cars in a way where, like, you realize, okay, I actually know more about, like, the pros and cons of this vehicle than you do. And I explained my situation to you and you're still kind of pushing this thing. Yeah. And then it just destroys like the trust.
Speaker 2:Why are you pushing understated rims? It clearly needs spinners.
Speaker 1:Nose ball. When you get when you get truly like the perfect Instagram ad Yes.
Speaker 2:Where you
Speaker 1:get truly like the perfect like, you know, a sales associate texts you Yeah. I got this. Do you want it? Yeah. Before it it hits the floor Yeah.
Speaker 1:Like that is a really good feeling.
Speaker 14:Yeah. That's delight.
Speaker 1:But but like the gap right now is just so surprisingly wide between those like actual human led experiences which is like sales associate knows your preferences well, has a unique product for you at and the right what brands are able to do.
Speaker 2:It's basically back to the hallucination era. Like Yeah. We we we we left the hallucination era where if you look up, you know, the history of a company on any LLM, you're gonna get something that's pretty much like the Wikipedia page Yeah. Pretty accurate. But, you know, four years ago, you ask an LLM, you know, anything and you could just wind up in crazy made up territory and it's the same thing for agent e commerce.
Speaker 14:We think of and this is a core value admission of the business. We think of the ultimate protagonist and end customer of what we do as the actual consumer. Right?
Speaker 2:Oh, okay.
Speaker 14:We are serving brands in the sense that they need to be delivering
Speaker 1:delightful experiences help you.
Speaker 14:We're helping brands help you. Right?
Speaker 1:At the end the day We're helping brands monetize you.
Speaker 3:Helping brands yeah. Look, I think we all Love it. We all believe in
Speaker 1:No. We're we're very commercial Yeah.
Speaker 14:We love personalization because I think it unlocks delightful experiences as cliche as that sounds in ways that just ultimately is a net positive for the business and the customer.
Speaker 2:What do you think the role of outer signal data, market research, customer personas, profiles is in actual product development, product line expansion. There's some there's some product line expansions and and just new products that I'm like, okay. That didn't come out of a committee. At the same time, sometimes you look at a business and it's like it's been staring you in the face Yeah. For years.
Speaker 2:Yeah. And everyone was gonna buy the the non caffeinated version of Coke
Speaker 1:or whatever.
Speaker 2:And so how how do you think about the role that Outer Signal Data should play in like the boardroom or product development room as opposed to just, the marketing engine?
Speaker 14:Yeah. It's a good question. Look. We see a ton of our businesses use Outer Signal in their product merchandising and product development and r and d
Speaker 2:Yeah.
Speaker 14:Actual processes. Right? And so a couple concrete examples here are massive massive multi billion and $100,000,000 businesses have discovered that they have some like really core persona.
Speaker 1:Mhmm.
Speaker 14:For example, one massive beauty brand found out that like 10% of their customers were like very distinctly nurses and doctors and like practitioners of medicine.
Speaker 2:Sure.
Speaker 14:And they weren't speaking to them at all. Okay. Right? It turns out that they were buying one very specific SKU in their set dramatically more than the rest of the customers. Right?
Speaker 14:Which informs not only how you market to that group, also how you segment them and also expanding more for them. Right? Yeah. The second part of this is like because Outer Signal's real time
Speaker 2:Mhmm.
Speaker 14:Right, you can now see when you launch a product. Like if Mountain Valley is gonna launch some new SKU online, in real time, they can see this SKU is over indexing with women and it's over indexing with men or women in $3,000,000 homes. It's dramatically under indexing in this cohort which starts when
Speaker 2:from high ABV Mountain Valley. High ABV It's Mountain
Speaker 14:a top shelf plug
Speaker 1:right there.
Speaker 2:Yeah. Very good. Oh, yeah.
Speaker 3:I like it.
Speaker 2:Yeah. Yeah. Yeah. Yeah. Give everyone overview of Top Shelf.
Speaker 14:Top Shelf is a fund that I started in 2022. That's how you and I met Yeah.
Speaker 2:On the
Speaker 14:board of Lucy, obviously. We started investing in vice businesses Sure. Booze, nicotine, etcetera. And we've expanded into just the broader consumer
Speaker 2:Yeah.
Speaker 14:Market. So businesses that connect with their
Speaker 2:customers Yeah.
Speaker 14:And technologies that help them do that Outer Signal. Top Shelf's a very proud investor in Outer Signal.
Speaker 2:Yeah. What what is the biggest trend in in the alcohol space these days? I feel like we're post seltzer boom, but is there a next next thing that's the hot trend? I haven't really kept up with it.
Speaker 3:Booze has had an interesting few years. Wait.
Speaker 2:No one's drinking anymore. Right?
Speaker 14:Total nonsense. Turns out
Speaker 1:they are.
Speaker 2:Oh, okay. Who's drinking?
Speaker 14:Apparently no one in LA. Although the other night I was out I still drinking. Right?
Speaker 1:Look, think No. Part of part of the thing is like LA has fallen off so hard as a city Sure. That people assume no one's drinking anymore because you drive around on a Thursday night in in the places where nightlife used to be And it's like health mecca. So people are No one's drinking. It turns out all over the country, other Yeah.
Speaker 1:Places, like Okay. You know, business as usual.
Speaker 2:But but, yeah, I mean, what are the growth growth categories? Wine, beer, spirits, seltzer, something new? Like, where where's the energy in the industry?
Speaker 10:I mean, we were the
Speaker 14:first check into a premium box wine called Grazi Okay. Which has become one of the largest wine businesses in America. Sure. And they are basically premiumizing what used to be black box, which is like the thing you drank in college and slapped
Speaker 2:the Yeah. Grozzy. And that sort of happened with cut water where they took cocktail mixed cocktails and put that in a more accessible form factor at a lower price. Yeah. Then that started flying.
Speaker 16:Interesting. I think
Speaker 14:occasions are changing modestly. I think the notion that young people don't drink anymore is ridiculous. I think
Speaker 2:that
Speaker 14:they were just delayed because of COVID.
Speaker 2:Oh, sure. Yeah.
Speaker 14:The big trend that just completely messed up the headlines. But you returned to normal. Returned to normal. They were just delayed. Yeah.
Speaker 14:So there was stagnancy because they weren't going out. I still think the loneliness epidemic is real and
Speaker 2:Yeah.
Speaker 14:There's another argument as to why abuse is actually a cure for that, we don't have to go there in the Ultra Dome today.
Speaker 2:Mhmm. Maybe after we wrap.
Speaker 14:Booze is gonna yeah. Maybe after we wrap.
Speaker 1:Cure for all of society. Booze gonna be just for alcohol according to alcohol investor. Yeah.
Speaker 4:That's why
Speaker 2:I said we have to go there.
Speaker 14:Talk about ball knowing. Yeah. Brotzi's Brotzi was one of the first Outer Signal customers Yeah. And they've seen some crazy results.
Speaker 1:Oh, you guys have a very interesting lens on like for actually investing in consumer Yeah. Just given given your role as Yeah. The data provider.
Speaker 2:Yeah. What's the growth the growth strategy for Outer Signal? Yeah. Is is there a distribution mechanism where, like, you can vend in through like a Shopify plug in Yeah. Be discovered there?
Speaker 2:Totally. I imagine you're doing paid ads on your own, maybe sponsoring podcasts that target things, going to trade shows. But what what's working the best for you in terms of getting in front of e commerce entrepreneurs?
Speaker 14:It's been remarkable word-of-mouth driven by strong product market fit.
Speaker 1:Sure. People who Yeah. Brian discovered the product said that he's like sent a bunch of bunch of different brands Yeah. Your way.
Speaker 14:And that happens constantly. We are running ads. We have a Shopify app. Ads We have an agency partner program. We have a killer sales team.
Speaker 14:We have content that goes out. And all of this has been know, the company is only a year old. Right?
Speaker 2:Oh. So agency would be like a Yeah. Performance marketer that wants
Speaker 14:to The attention bring marketer, performance marketer, influencer marketing teams, agencies. Right? Outer Signal is a magical magical experience
Speaker 1:for agencies.
Speaker 2:You can also sell it to the CEO because they want to look For sure. Pretty dashboards even For sure. If it's less tactical for them.
Speaker 14:And so in e com, you know, that's a very tight market. Yep. I think we've done a pretty good job both making friends in and also doing right buy. We're also getting pulled up market pretty quickly. Hotels, large scale consumer apps, massive retailers, they all have the same problem.
Speaker 14:Like, of my favorite stories, one of the biggest hotel companies in the world that you guys have all heard of, we won't name names, but they inbounded. I took a call with them and I said, what caught your attention? And he was like, dude, LeBron James checked into my hotel. And I didn't know about it
Speaker 2:Oh, interesting.
Speaker 14:Until he got into the lobby. Yeah. And I was mortified and I chewed my team out and I went and looked and like, yeah, his name was there but it was technically his assistant. But if anybody had taken the time to look, we would have caught it. Of course, they didn't catch it.
Speaker 14:Yeah. Because who's looking at all that stuff?
Speaker 2:He was
Speaker 14:like, we need outer signal.
Speaker 2:Of course. Right? Or at least exercise more discretion. Exactly. Make him feel welcome.
Speaker 2:Exactly. Fascinating. Very cool. Well, congratulations
Speaker 14:Thank you,
Speaker 2:the raise.
Speaker 1:Congratulations. Such a such a cool business. Yeah. Like, it's one of those things like you're you you can give that magic moment to founders and, like, management teams, which again, like, we experience that really early on at at Aurora. Yeah.
Speaker 1:But then continue to deliver value and get much deeper into the stack and help them run, you know, better email marketing, all all these different channels. It's sky's the limit. So Yeah. Excited to see where you're
Speaker 4:Appreciate you,
Speaker 14:boys. Thanks for Well, having
Speaker 2:that's basically our show. There was some breaking news while we were live. What is it? A Gemini four Argon launched. Cool new name.
Speaker 1:What about your
Speaker 2:Bunch of benchmarks.
Speaker 1:Yeah. What are your thoughts
Speaker 7:on it?
Speaker 2:No. No. No. No. We're all going to digest this.
Speaker 2:We'll talk about it tomorrow and and go through the benchmarks. But you can go check out Logan Kilpatrick, friend of the show posted about it and everyone can take it for a spin. We'll talk more about the reactions tomorrow. Leave us five stars on Apple Podcasts and Spotify. Sign up for our newsletter, tbpn.com.
Speaker 1:That's right.
Speaker 2:And we will see you tomorrow at eleven Pacific. Goodbye.