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Technology's daily show (formerly the Technology Brothers Podcast). Streaming live on X and YouTube from 11 - 2 PM PST Monday - Friday. Available on X, Apple, Spotify, and YouTube.
You're watching TVPN. Today is Tuesday, 06/10/2025. We are live from the TVPN UltraDome. The temple of technology.
Speaker 2:The fortress of finance.
Speaker 1:The capital of capital. It's a great day. We're doing WWC reactions. I will run you through a little bit of the show. We wanna talk about the meta Scale AI deal.
Speaker 1:49% for just $14,000,000,000. It's a steal. You're You're getting Alex's way. You're getting the the Scale AI team. They're giving it away.
Speaker 1:We we're gonna talk about the Glean fundraise, competitor OpenAI. They're cooking in enterprise AI. Some of the reaction there from what's going on in in deep research and some of the advancements that OpenAI has been rolling out there, very interesting for Glean's business. Glean still ripping. So they're they're up, raised a big round today.
Speaker 1:They also got the CNBC disruptor list, 50 top startups. We've had a ton of them on the show. We're gonna go through, do a little underrated, overrated maybe. See who should
Speaker 2:be higher. John.
Speaker 1:Personally, I love
Speaker 3:them all.
Speaker 1:I think they should all be tied for place. Yeah. But CNBC ranked them.
Speaker 2:One fifty? Hopefully, it was purely pay to play, and CNBC just kind of auctioned off the spots.
Speaker 1:That's the
Speaker 2:That would be the most fair thing. You know? Agree. Agree. But
Speaker 1:And then we got a bunch of great guests. We got Syed from Redpoint coming on. We have, Kari announcing a massive, what is it? Series c unicorn round at Linear. One of our sponsors.
Speaker 2:Be their series c.
Speaker 1:We got Scott Belsky from a 24 coming on. Can't wait. Roy Bahat from Bloomberg beta coming on announcing a new $75,000,000 fund.
Speaker 2:And then the sky
Speaker 1:Metropolis. And then we got Andrew.
Speaker 2:This guy Andrew Huberman.
Speaker 1:Andrew Huberman.
Speaker 2:Heard of him.
Speaker 1:He's got a
Speaker 2:Fellow podcaster.
Speaker 1:Yeah. So we're excited for the show today. But let's kick it off with the timeline's reaction reaction to WWDC. Liquid glass, whatever, says Juan. Most important thing in iOS 26, text is finally left aligned.
Speaker 1:You know, I saw people posting about this. You said this about, like, center alignment, left alignment thing. I hadn't noticed it. It looks a lot better left aligned. I don't know why.
Speaker 1:I didn't know what I was missing.
Speaker 2:We'll take it.
Speaker 1:Huge improvement.
Speaker 2:We'll take it.
Speaker 1:Yeah. So now text in iOS notifications, left aligned. Huge news.
Speaker 2:Also Absolutely massive.
Speaker 1:All the different version numbers are now they're doing car models. So it's iOS 26. They jumped forward a bunch. I believe we were on, like, 18 before. So they skipped a bunch.
Speaker 2:I can't wait to be in the thousands.
Speaker 1:We're in 2025.
Speaker 2:In the thousands.
Speaker 1:The 20 and it's iOS 26 across everything. So unification there. It's happened in in in Android a while ago, but now it's it's come to iOS.
Speaker 2:Love it.
Speaker 1:Again, a lot of people with negative reactions. We're gonna take you through some of the positive reactions. Steve Jobs would have cornered you in a dark alley and beat you to with a metal pipe when he suggested something like this. That's what Kitsi says. This was yesterday's reaction.
Speaker 1:Today, some of the designers are coming out and saying, hey, let them cook. There's
Speaker 2:I mean
Speaker 1:there's a silver lining here.
Speaker 2:There's certain there's certain examples that are really really gnarly.
Speaker 1:So so there's that one super viral one that's like really hard to see and then people put it next to the Oppenheimer with the the blast. Yeah. I think that's a fake photo. I think they adjusted the brightness on that. I don't think that's I think I deep fake.
Speaker 1:Not a deep fake. I don't think there's any I just think that that someone went in there and was like, let me turn out the brightness for for a fact. And I think that that's fake. And I think that also, again, this is this is a beta. This is something that they're gonna be iterating on before it goes out to the masses.
Speaker 2:It's gonna say a bit weird for a trillion dollar company to launch a beta instead of they should just say, no, this is an alpha.
Speaker 1:Yes. But but but it makes sense in terms of, like like, if you are a developer and there's a and there's a significant change to the user interface, you want to bake that into your app so that you don't look out of place on day one when everyone updates. Yeah. So you gotta get the beta into the hands of the developers so that the Airbnb app, and the public.com app, and the ramp.com app save time and money. Time is money.
Speaker 1:Save both. Easy to use corporate cards, bill payment, accounting, a whole lot more all in one place. Go to ramp.com.
Speaker 2:And travel.
Speaker 1:John's favorite. And travel. The travel
Speaker 2:is Favorite thing. Speaking of travel.
Speaker 1:We gotta book our hotels for tonight because we're going to San Francisco for YC demo day tomorrow. To me
Speaker 2:That's right.
Speaker 1:It's gonna be a massive stream.
Speaker 2:With ramp travel, you can book last minute. It's still a breeze.
Speaker 1:It's really, really easy. But yes, if you're designing an app, you want it to feel somewhat seamless with the rest of the UI. And if there's UI changes, you gotta you gotta test drive those beforehand. Gotta make sure that those are right. So the big question, should we have our intern Tyler Cosgrove over there install iOS 26 beta?
Speaker 1:You know, it's potentially a he's on the green screen. Something happened. He's on the green screen. Should we make Tyler install oh, there there we go. That that's where he is really.
Speaker 1:Like, I'm glad that you did the false background for a minute and make it look like a green screen instead of showing the real Yeah.
Speaker 2:We wanted him to be more approachable.
Speaker 1:Yes. We just put a green screen behind him as a fake background.
Speaker 2:Yeah. But anyways, back to you. Is that Mykonos? Where are you right now?
Speaker 4:Oh, this is just my pool in my backyard. Yeah.
Speaker 2:Okay.
Speaker 1:Cool. Is where
Speaker 4:you take podcasts. Sometimes fellow some of my friends will go on podcasts. They'll just use my backyard.
Speaker 1:Yeah. Yeah. Oh, yeah. That's what it is.
Speaker 2:Anyways, I would love to watch you risk it all and install the update. So why don't
Speaker 1:you Are you willing to do it?
Speaker 4:Yeah. I'll do it. Yeah.
Speaker 2:Okay. Do it. Gonna do it for the team. He's taking one for
Speaker 1:the team. IOS 26 beta. It could go terribly wrong because the bugs, you know, the the the thing with the beta is that you can't go back. You can't you can't roll back to the non beta. Yeah.
Speaker 1:So You're fully You're could be living with a with a minor grading bugs for like months until they fix it. Now, they fix it pretty quickly. I've done it like once or twice, gone on the beta because I'm I'm so excited. I wanna try the new thing.
Speaker 2:This is basically intern hazing.
Speaker 1:It is hazing. It's the In the modern era. It's the WWC version
Speaker 2:Yeah.
Speaker 1:Hazing setup.
Speaker 2:Alright, Tyler. Well, you are brave.
Speaker 1:Okay. Good luck with
Speaker 2:And get why don't you get started? And we'll checking back.
Speaker 1:Then give us give us review. We'll be checking in with you to see how the iOS 26 installation process goes and and and any any problems you run into there. We also have some other He's
Speaker 2:like, guys, I can't I can't read anything on my phone anymore.
Speaker 1:We also have some we also have some big show updates. Not only do you have intern cam now, we also have the breaking news camera. Let's go to it now.
Speaker 2:This is crazy too because I can
Speaker 1:see You see this?
Speaker 2:Okay. So,
Speaker 1:this is the breaking news camera. When we have breaking news, we cut to the printer. Cut.
Speaker 2:And? And it prints out. You can read
Speaker 1:the breaking news.
Speaker 2:Jon, do you
Speaker 1:wanna read that to us? Hold it up on a We
Speaker 2:have some breaking news. We can switch cameras. What is it? So breaking news, Snap to launch smaller, lighter augmented reality specs, smart glasses in 2026.
Speaker 1:I'm excited for this.
Speaker 2:To CNBC. Thank you to CNBC. Snap on Tuesday announced its plans to release a generation of its augmented reality glasses in 2026 as competition in the smart glasses market continues to heat up. The maker of Snapchat said that its next generation glasses will be called Specs, breaking with the company's Spectacles branding that it used for previous drop the Yeah. The Just do specs.
Speaker 2:It's cleaner.
Speaker 1:Well, they they dropped the t too, so it's it's technically drop the tackles. Drop the spec.
Speaker 2:Drop the tackles. Tackles. Just specs. Larger tech rivals like Meta Apple and Alphabet are investing heavily into cutting edge head worn devices. Yep.
Speaker 2:So The computer will be on your face.
Speaker 1:So the most recent the most recent edition of Spectacles were released in September 2024 to developers only. That edition of the glasses was available under a leasing model that that required users to commit to paying 99 a month for a full year if you wanted to develop for them. So that's $1,200 guaranteed. And then if you wanna keep it more, it's probably continues to be a $100. So it'll be interesting.
Speaker 1:It'll run Snap OS operating system, which they developed in house. Snap said the developers will be able to incorporate Google's Gemini AI models into programs that develop for smart glasses. So
Speaker 2:That's interesting.
Speaker 1:Sort of yeah. Yeah. Exactly. So you could see somewhere in where it's like, okay. You're gonna get the glasses.
Speaker 1:You're gonna build
Speaker 2:the hands on says, hey.
Speaker 1:We want Oh, that's where you're going with it. Okay.
Speaker 2:I don't I don't know. I I I think very unlikely, but but still, you know.
Speaker 1:Well, Snap's market cap, exactly what Meta just paid for a 50% stake in Scale AI, 14,000,000,000. Anything's possible. Spicy. So Snap's at 14,000,000,000. The the stock hasn't really moved over the past five days on this news.
Speaker 1:It's clearly Snap, you know, staying in the game with the WWC news, getting something, getting a story out there that, hey, we're still in the game. We're moving, and we're doing cool stuff. And and I'm excited for this. I think we need more more innovation here, more people testing different stuff. And it's clear that with a new format, with a new paradigm of like what the product is, there's a whole bunch of interesting directions you can go.
Speaker 1:Whether there's an augmented reality display, whether it's voice only, whether it's glasses Crazy.
Speaker 2:Prescription glasses, a
Speaker 1:whole bunch of different things.
Speaker 2:Social media goats, both of them are just not the idea of not being a part of the next platform shift is just an idea they don't is a world they don't want to live in. Right? Yep. They are you know, both both Zuck and and Evan Yeah. Are gonna be, you know, competing.
Speaker 1:Yeah. And so fun. Could be interesting from a developer angle. Obviously, you know, nowhere near the budget of Reality Labs for what Zuck is working on with Meta. But
Speaker 2:potentially some Constraints. They could be good, John.
Speaker 1:I agree. I agree.
Speaker 2:They can be good.
Speaker 1:I'm optimistic. I certainly wanna try it. Anyway, let's go back to Liquid Glass. Ben Thompson gave a whole posted a massive article on Strictechery called Apple's Retreat, Apple Retreats, something like that. You should give it a read.
Speaker 1:You should subscribe to Strutecari, obviously. Apple's retreat to its core competency. The headline feature of WWDC this year, this is from the latest Strutecari article, was liquid glass, a new unified design language that stretches across its operating systems. I will reserve judgment on Liquid's glass aesthetics and usability. Gruber likes it.
Speaker 1:I see my journalist on the horizon. But I am not one to install developer betas on my devices.
Speaker 2:But Tyler will.
Speaker 1:But Tyler will. That's what we have, Tyler. Because I agree with Ben Thompson. It's extremely risky. But he's willing to do it taking one for the team over there.
Speaker 2:I mean, the whole the whole TBPN army, he's he's really saying, I will I will sacrifice
Speaker 1:myself for sword. I will fall for beta. I for beta. It's okay. If it goes really south, we'll get a we'll get a new phone.
Speaker 1:It's always always a possibility. But good luck. Hopefully, you can make it through. Tyler, we'll be checking on you throughout the show. So let's read Gruber's overview of his reaction to Liquid Glass because we saw Timeline hated it.
Speaker 1:They said Steve Jobs would hate it. Let's go to John Gruber Derrand
Speaker 5:Fireball. Part of
Speaker 2:is is it was popular to hate on it. Totally. Because Everyone loves when someone's
Speaker 1:on a downswing, they love just piling on downwards. Yeah. And when everyone's on upswing, they love just piling on and upwards. It's not No.
Speaker 2:And I think it's also normal if a widely used consumer product does any type of meaningful upgrade.
Speaker 1:I mean, this
Speaker 2:was The default is
Speaker 1:that They were purchased about
Speaker 5:it's bad.
Speaker 1:Meta or Facebook back in the day launching the feed. Yeah. They're like, I wanna go back to just randomly looking at your profile. I don't wanna see random Yeah. All everything Yeah.
Speaker 1:Every change is always met with some sort of pushback. And then years later, people wind up loving it. I feel like this is something that could grow on me. I'm I'm reserving until we've fully been tested on our intern. So if he gives it the thumbs up, I'm gonna install it.
Speaker 2:Wow. So let's
Speaker 1:go to John Grueber.
Speaker 2:I mean, it's kind of it's it's it's kind of fun.
Speaker 1:It's brave.
Speaker 2:It's it's daring and brave and bold to do something like And, you know, just because Tyler's doing it, you know, doesn't mean you shouldn't, you know.
Speaker 1:This this type of bravery that Tyler's exhibiting today, I think it might be one day like an exhibit in the computer history museum. Totally. The bravery he's he's exhibiting today will be in the history.
Speaker 2:They might even name the next operating system. Cosgrove.
Speaker 1:Cosgrove. Mac OS 27.
Speaker 2:MacOS Cosgrove.
Speaker 1:After Tahoe.
Speaker 2:It's got an amazing it's got an amazing ring.
Speaker 1:Ring to it.
Speaker 2:It's got a nice ring to it. And it just loads with this image. Like, that's the default wallpaper.
Speaker 1:For the for the daring and great technologist who installed the beta on day
Speaker 2:two. Did, you know, what everybody said, you're was You're crazy. You should never do that. You shouldn't. But he did it.
Speaker 2:He took the leap.
Speaker 1:Took the
Speaker 2:leap and he did it. So hand this is going back to Ben Thompson's piece. handcrafted UI overhauls are the polar opposite of a probabilistic world of generative AI. One is about deep consideration and iteration resulting in a finished product. The other is about in the moment token prediction resulting in an output that is ephemeral and disposable.
Speaker 2:Both are important and creative, but the downsides of that creativity Mhmm. Unfamiliarity and edge cases versus hallucination and false confidence are themselves diametrically opposed. Apple's historical strengths have always been rooting and designing for finality. In my year of Strathecari, I did a SWAT analysis. Let's give it up for SWAT analysis.
Speaker 1:I love SWAT analysis.
Speaker 2:Of the big tech companies and said about Apple. And and I I think we've talked about this a bunch on the show of like generative AI is inherently imperfect. Yep. Apple is about pixel perfection. Yep.
Speaker 2:So Apple's product development process is wonderful for developing finished products, but that same process doesn't work nearly as well when it comes to building cloud services. Cloud services are never done. They are best developed by starting with an MVP and then iterating based on usage. This is precisely opposite of what it takes to design a piece of hardware and it's a big reason why Apple struggles so much with cloud services and why other services companies struggle with products. The canonical example of this, of course, was when MobileMe was the MobileMe launch, which was delivered fully formed and which, when faced with real world usage, crashed and burned.
Speaker 2:Apple's latest offerings are better, but still suffer from too much internal development time per release. This is a hard problem to fix because it touches the core of what makes Apple Apple.
Speaker 1:I think it matters I I think it matters whether or not liquid glass is good because it will be a testament about the state of Apple's strengths. The point of this article, however, is that WWC was a retreat to those strengths, which is good. This is a bull case. They're not getting over their skis, and and they will eventually, I mean, if they're to win, probably defer to the other companies and play to their strengths and and and let let the other companies win in the places where they Tim.
Speaker 2:Are best. Tim just calling up Sam and saying, Sam, I'm gonna need 50,000,000,000. Siri, it's yours? 50,000,000,000.
Speaker 1:50,000,000,000.
Speaker 2:50,000,000,000, you know, if you and Masa could pull together the capital, we can make it happen.
Speaker 1:I mean, I keep thinking about Siri and I keep running through like, what would it have taken to just replace Siri with a frontier level, you know, simple response model, not even the reasoning stuff, just GPT four o level, you know, you ask it a question and it and it and it and it reads you like a basic response and not lose the other Siri functionality. And I think that it need they need to kind of flip the paradigm because right now, Siri is only it's basically all tool use. It's basically a router. So it takes in you you know, you ask Siri, what what's the weather going to be like tomorrow? And it knows that you just And all it's doing is picking out keywords weather, and it goes to the weather API internally, and then tomorrow, and it feeds that in, and then it delivers that back.
Speaker 1:Like ChatGPT kind of flips that around by having the default interaction be much more generalizable and it can return kind of any result. It can return a paragraph, it can tell you about a historical event or just talk to you. And then if it needs to use a tool like web search to get you the weather for tomorrow, then it goes and calls that. And so you need to kind of flip that around. I was wondering about like why hasn't If you rolled back the clock and you were like, Okay, Apple just wants to be in the game, what would it take to launch a v two of Siri?
Speaker 1:And I was like, Well, Okay, if they try to partner with someone under the hood without, like, they don't even have the option of just saying, we are going to partner with Anthropic under the hood and it's gonna be and it's gonna be basically white labeled, then no one will ever find out because there are just too many leakers. Like, it will find out immediately. Yeah. And so Mark Gurman will have the story immediately, and everyone will know. So they won't be able to say, like, this is magically ours when really it's someone else's, even if they're paying them to be and there's ton tons of NDAs.
Speaker 6:Like, will
Speaker 2:do with cloud services. Right? I don't actually know who's under the
Speaker 1:I think they I I I think they do a
Speaker 5:lot of that.
Speaker 1:And I'm sure it's And then I think a lot of it comes down to the privacy angle, is that they want to make certain claims about privacy and ESG and net zero and stuff. And so if they were to just white label another company that didn't have the same reputation in privacy or environmentalism, like people would just say, wait, wait, wait, but like Anthropic isn't isn't known for their privacy rules as much as possible. So Yeah. Maybe they are training on my Siri results now. And that's a whole that's a whole thing and they have to, you know, build up Anthropic's brand to have the brand of Apple, which is just I'm sure Anthropic's doing great, but they're not known like Apple is in terms of how seriously they they take it.
Speaker 1:Yeah. And then, in terms of in terms of acquisition, obviously, there's all the antitrust stuff. We'll get into this with a Scale AI deal, but every major hyperscaler, except for Apple now, has basically done one of these like interesting acqui hires of a foundation model lab to kind of juice up their AI efforts. And and and it's kind of been a mixed bag. Maybe we see one from Apple.
Speaker 1:They certainly have the cash, but it would be a very, very different it would be a departure from their current strategy. Anyway, let's go to John Gruber over at Daring Fireball with his review of Liquid Glass. He says, I've got iOS 26 installed on a spare phone already. Oh, no. He didn't even use the real phone.
Speaker 1:Tyler, mistake number one. Never No fail. On your main phone. How's it going so far?
Speaker 4:Well, okay. So so I'm I'm going to download it. It's 19 gigabytes.
Speaker 2:Okay. Okay.
Speaker 4:So my phone is not you I only have 64 gigabytes on my phone.
Speaker 6:I'm going
Speaker 4:to I got to do a Delete everything? Yeah, I'm going to delete everything.
Speaker 2:Okay. Yeah, yeah, You'll be able to delete just go to your Photos app, select all the other family Delete them all, and then clear the trash. You'll make more memories. You could always make you're making more memories all the time.
Speaker 1:Yeah, exactly.
Speaker 2:Out those images. And
Speaker 1:Yeah, good luck.
Speaker 2:On a more serious note, if you need we'll cover your Apple iCloud plan. Yes.
Speaker 1:You need
Speaker 2:to get those images in the cloud, you can get Yeah.
Speaker 1:If you need if you need a backup for your expenses on your ramp card.
Speaker 2:Yeah. Put it on the ramp.
Speaker 1:So, Gruber says, I like the new UI a lot. In addition to just looking just plain looking cool, Apple has tackled a lot of long standing minor irritants. For example, the iOS contextual menu for text selections, the one with cut, copy, paste, for years there, for years now, there have been a lot of other useful commands in there, including share at the very end. But to get to the extra commands, you had to tediously swipe, swipe, swipe. Now with one tap, you can expand the whole thing into a vertical menu elegant.
Speaker 1:And I agree. I noticed that that was getting like it was originally, it was just like, just copy just just cut and paste. It was pretty easy. And then they added if you wanted to bold or italics, you had to swipe over and then click on that and then go to text effects. And there were, like, seven different things eventually.
Speaker 2:Yeah.
Speaker 1:Good good move. Minor update, but important. And this is what this is this is the polish that Apple's so good at. And then he says, there's some stuff in Mac OS 26 Tahoe. I already don't like, like putting needless icons next to almost every single menu item.
Speaker 1:But overall, my impression of Liquid Glass on Mac OS is good too. It's fun and lots of little details are nice, joyful and useful in an old school If
Speaker 2:you love Mac OS Tahoe, you'll love Mac OS Cosgrove. I'll just say that. This is gonna be
Speaker 1:a banger. It's gonna be the best ever. There's an interesting article in here that Ben Thompson linked to by Sebastian DeWitt about physicality, the new age of UI. He actually posted this back on June 3 before Apple refreshed this. So there's a lot of Oh, do we have some breaking news?
Speaker 2:I just I just printed this out
Speaker 1:because Well, he he re re re So
Speaker 2:this was a good post from Signal. He says watching this WWDC. Thank you, Signal for the, for the content. And, I'm just happy to be back printing.
Speaker 1:It's amazing.
Speaker 2:It's it's I don't know how we went
Speaker 1:It is. Few months without it.
Speaker 2:So he says watching this WWDC felt like watching a dinosaur try to do ballet, technically and aesthetically competent, but spiritually spiritually lost. They talked about Apple intelligence like they just discovered the concept throughout the presentation. There was zero ecosystem thinking and no real attempt to rethink a single interaction model. More importantly, there was zero sense of how to be relevant in a world where interfaces may disappear, apps get abstracted, and AI is the OS. Apple still thinks in icons and widgets while the world is moving towards awareness, intent, and delegation.
Speaker 2:It'll be interesting to see how much of a penalty they will pay for missing this boat.
Speaker 1:Another negative post. Now, Signal did have a couple other posts that were more positive talking
Speaker 2:about good You what? I think I think this is generally why I'm excited about Johnny and Sam's hardware project is it's an opportunity to rethink the device from the ground up with AI at the heart versus Apple, which I think, going back to Ben Thompson's position, is smart to play their own game right now and understand that they do have the option of auctioning the sort of Siri out to the highest bidder at some point.
Speaker 1:Yeah. Mean, Alex Heath, who we had on the show yesterday, had a good post who said, this is so very clearly designed for an interface that sits on top of the real world, not a phone, something you would need for AR glasses. And so, this idea that it's a little awkward now when you see these images of these glass over the background of your phone display. It can look a little too transparent. The the the contrast ratios are all off.
Speaker 1:But if you think about if they're really going all in on AR, VR Yeah. And they want to project these screens over the real world long term, setting themselves up to really dominate there and not need to do another refresh. Yeah. Could be big. Could be big.
Speaker 1:Anyway, Mark Gurman liked
Speaker 2:spent some time Yeah. With Trump.
Speaker 1:Yeah.
Speaker 2:Trump is known for playing four d chess. Mhmm. Maybe Tim is playing a little four d chess with liquid glass. He's like, screen is gonna be everything's gonna be a screen. We're just gonna put have a patent.
Speaker 1:Have a patent for a glass iPhone that that you can see through or something like that or or something that actually would would would appear more like glass or appear transparent. And a lot of the transparent I feel like a lot of the transparent technologies, it's like the closest we're gonna get to just true holograms is if you have a Yeah. A variety of devices that are that are projecting holograms into glass sheets. And so maybe it doesn't start with your phone immediately because the battery needs to be right there. That needs to be solid.
Speaker 1:But if you think about a display and you're projecting on that and doing kind of the the same waveguides that are happening in reflected augmented reality glasses, you could do that on a monitor or something like that. And so that could be very cool. Mark Gurman had a more positive take on WWDC. He says, excellent WWDC. At cohesive story, deep integration, and continuity across the devices, zero false promises, impressive new UI, and significant new productivity features on the Mac and iPad, but the lack of any real new AI features, despite that being my expectation, is startling.
Speaker 1:And so people were expecting, you know, maybe there will be a new Siri, maybe they will move the ball down the field in AI, and they did not. Ben Hylak, of course, taking credit for it. As always, you know him from taking credit for the Jaguar rebrand. Now he says, so excited to see my my to finally see my work from Apple ship. I was the head of design for the WWDC app notifications.
Speaker 1:There's still a work in progress. We've only had the last year to work on them. Stay tuned.
Speaker 2:So, was this was this is this fake or is this
Speaker 1:real? I think this is a the brightness adjusted. I think that they I I think that whoever shared this image turned up the brightness or or brought up the brought up the lows. Basically decreased the contrast in the in the photos app, like, to make it look worse than than it actually would. But, I mean, even it doesn't even matter because even if this is the way it looks, this isn't the way it will look when it will ship to to to people because it's obvious.
Speaker 1:And and and Apple doesn't make these like obvious mistakes like this, especially when it comes to design. They might do something that is like rough in the short term, but better in the long term, like what I think is happening with the Photos app, where in the Photos app, they are understanding that in the future, you won't want to scroll at all. You will just search, and search will be so powerful because every photo and video will be tagged so thoroughly from AI, it will understand the context so much that you will just ask it to pull up a photo and it will do it immediately. The problem is that right now, people A, aren't, they haven't switched that UX paradigm to actually go search
Speaker 2:Yeah.
Speaker 1:And just the tagging is not that good. Like I had a video clip of Arnold Schwarzenegger from a movie on my phone. I wanted to pull it up. And so I searched like Arnold Arnold video, and it couldn't find it because Yeah. The clip that I had started with a black frame.
Speaker 1:And clearly, it's only indexing like the frame. And so if if if you have, like, a fade in Yeah. To a picture of your dog, it won't get text. Something like that. I don't know if that's exactly
Speaker 2:what's happening here. I use the text search in photos quite a bit. Yep. I I find it, like, searching Kugen if there's some document
Speaker 1:that has to be named is fantastic. And even even things like objects, like I I the the picture of a vending machine. You type in vending machine, it it'll do a pretty good job. Sometimes it'll miss it though. But that these these, like, generative AI things, they get to 99.9% accuracy pretty quickly.
Speaker 1:Apple's just a little bit behind on them,
Speaker 2:I think. Yeah.
Speaker 1:Anyway, if you're trying to upgrade your design chops, head over to figma.com. Think bigger, build faster. Figma helps design and development teams build great products together. Go to Willem
Speaker 2:on Figma now.
Speaker 1:We'll go to we'll go to Willem. He gives his review of Apple's Liquid Glass, clearly hints at a clear interface, AR glasses, and unifies OS beyond devices. Like iOS seven, I would be shocked if this version of Liquid Glass ships to everyone later this year. Too many accessibility features for a company that pioneered it. Unfortunately, this means it's going to be muddy slash blurry.
Speaker 1:UI design feel used to be about function. This is decoration. Late empire feeling. Hate the trend of floating menus that seems to be happening everywhere. It puts useless noise on the edges of the screen.
Speaker 1:Ultimately, little of this matters when you can now just talk to the computer. Everything is computer. Anyway
Speaker 2:Interesting. There's an
Speaker 1:interesting deep dive from this Sebastian DeWitt talking about some of the history here, speaking of iOS seven. He said, on June 10, Apple showed off what this was in the spring of twenty thirteen. June 10, Apple showed off what would be the greatest paradigm shift in user interface design ever, iOS seven. I remember exactly where I was and how I felt. It was a shock.
Speaker 1:Love a designer who's just so in the weeds. They remember where they were when iOS seven dropped.
Speaker 2:Had to be there.
Speaker 1:If there is indeed a big redesign happening this year, it'll be consequential and impactful in many ways that will dwarf the iOS over iOS seven overhaul for a multitude of reasons. The redesign is rumored to be comprehensive, a restyling of iOS, macOS, iPadOS, tvOS, watchOS, and visionOS in the intervening years between iOS's seven iOS seven's announcement. And today, iPhones have gone from simply a popular device to the single most important object in people's lives. So true. The design of iOS affected and inspired most things around from the web from web to graphic design to any other computer interface.
Speaker 1:That's why I figured I'd take this moment of obscurity, this precious moment in time where its changes are still shrouded in fog to savor something. Wholesome naivety
Speaker 2:Great writer.
Speaker 1:Of where things are going, so I can let my imagination run wild. What would I do if I were Apple's design team? What changes would I like to see and what what do I think is likely? And then he breaks it down. The shaded age, he goes back to the skeuomorphic era.
Speaker 1:IOS started out as
Speaker 2:Can we pull up this?
Speaker 1:IOS started out as the iPhone OS, an entirely new operating system that had very similar styling to the design language of the Mac OS Tiger dashboard feature. Yeah. I remember this. You could just put the widgets anywhere. It was very messy.
Speaker 1:All the sticky
Speaker 2:This was so fun as a kid. Yeah. Messing around with all the different widgets.
Speaker 1:All the widgets. And then you would Discovering
Speaker 2:discovering It's great. Widget. I couldn't I legitimately felt like a kid in a candy store with It was a beautiful time.
Speaker 1:So it says, icon layout on iPhone OS one it wasn't even called iOS then. It was just iPhone OS. Was a clear skeuomorph. Skeuomorphism was the was the buzzword at the time. You might have heard that word being thrown around.
Speaker 1:It might surprise you that it doesn't mean it had lots of visual effects like gradients, gloss, and shadows. It actually means to that to make it easier for users to transition from something they were used to, in this case, phones typically being slabs with a grid of buttons on them to what they had become, phones were all screen, so they could show any kind of button or interface imaginable. And, yes, there was a whole lot of visual effects in the user interfaces from iPhone OS one to iOS six. In this age, we saw everything from detailed gradients and shadows and simple interface elements to realistically rendered real to real tape decks and microphones for audio apps. I remember this, the real to real tape deck in the voice recorder.
Speaker 1:Pretty pretty remarkable. And like, when when the directions would actually be like a like a physical sign that you would see on a highway. Was was a cool design language. I mean, it feels so not Apple now that they've spent 10 or 15 years post skeuomorphism, but it was definitely unique at the time. Having actually worked on some of the more fun manifestations of it during my time working at Apple, I can tell you from experience that the work we did in this era was heavily grounded in creating familiarity through thoughtful, extensive visual effects.
Speaker 1:We spent a lot of time in Photoshop drawing realistically shaded buttons, virtual wood, leather, and more materials. That became known as skeuomorphic design, which I find a bit of a misnomer, but the general idea stands. Of course, the metal of the microphone was not in fact metal. It didn't reflect anything like metal objects do. It never behaved like the object it mimicked.
Speaker 1:It was just an effect, a purely visual lacquer to help users understand the that the Voice Memos app worked like a microphone. The entire interface worked like this so as to be approachable as possible. Notably, this philosophy extended to even the smallest elements of the UI. Buttons were styled to visually resemble a button by being convex and recessed or raised. Disabled items often had reduced treatments to make them look less interactive.
Speaker 1:All of this was made to work with lots of static bitmap images. The signs of something more dramatic did begin to show on iPad. Some metal slider slider sheen could respond to the device's orientation. So as you Yeah. Delete a note or email to not simply make it vanish off the screen, but pulled it into a recycling bin that went as far as to open its lid and close as the document got sucked in.
Speaker 1:I remember there was one that would like shred things when you deleted it. They had a bunch of these fun ones.
Speaker 2:And it's You can imagine that Apple designers in that era being like, I'm, today, I'm moving on from Apple. You know, I was the designer that made the lid open Yep. And the thing swoosh into the can.
Speaker 1:It must have been so delightful to just be a designer and just, like, focus on just that one interaction for, like, weeks, you know?
Speaker 2:Yeah. That that became a critique of Silicon Valley, was just, like, you're working on something. Like, the idea that, like, something like this doesn't matter Yeah. In the grand scheme of things. But beautiful things matter.
Speaker 1:They do. They
Speaker 2:do. And even a feature like this, especially in the Notes app of of an iPhone, was something that was being used millions and millions of times a day. Yeah. And it's worthwhile to make it beautiful.
Speaker 1:And So there was pushback when they went to flat design. The flat age started in iOS seven, introduced an entirely new design language for iOS. Much much was written on it at the time, and as with any dramatic change, the emotions in the community ran quite high. I'll leave my own opinions out of it mostly, but whichever way you feel about it, you can't deny it was a fundamental rethinking of the visual treatment of iOS. IOS seven largely did away with the visual effects for suggesting interactivity.
Speaker 1:It went back to quite possibly the most primitive method of suggesting interactivity on a computer. Some buttons were nothing more than blue text on white background, like the inbox button. The home screen, once a clear reference to the buttons on phones of yesteryear, was now much more flat looking, One part owing to simpler visual treatment, but also a distinct lack of It is
Speaker 2:hard to look at this after looking at the at the last era. Demorphic era was was amazing.
Speaker 1:Goated?
Speaker 2:It was amazing.
Speaker 1:It was amazing.
Speaker 2:I see why they had to move on in some ways. Yeah. It was just like the the the the the previous era felt, you know,
Speaker 1:like It it started to feel dated. Yeah. It felt like
Speaker 2:It feels vintage. I mean, it's looks vintage today.
Speaker 1:Totally.
Speaker 2:I'm sure the kids today will, like, jailbreak their iPhones back to to looking
Speaker 1:Yeah. I mean, I saw I saw a a comparison of the of the original photos app, which which looked like a camera lens. And then the the the flat design camera app had just a camera icon that was completely flat. And now we're back to a camera lens in the new era. And so some of that some of that skeuomorphism seems to be coming back with the glass redesign, liquid glass redesign, but not fully.
Speaker 1:You know? Yeah. We're kind splitting the difference. We're going in a different direction.
Speaker 2:I just looked up. Do people still jailbreak iPhones? Yeah. And Reddit says it's still possible. Mhmm.
Speaker 2:The big thing is there's not much need for it. A lot of the things jailbreaking was for have been implemented Yeah. Into iOS.
Speaker 1:Yeah. Because the App Store is so robust.
Speaker 2:Yeah.
Speaker 1:So you can get you can get an app. There's an app for that now. There didn't used to be an app for it. There were many, many, many, many apps that were not available. And on the iPhone, there was not even an App Store.
Speaker 1:So but why did Shadows have to go? They had they they had an important function in defining depths depth in the interface after all. Looking at the screenshot above actually does it no justice. The the new iOS seven home screen was anything but flat. The reason was that the shadows were static.
Speaker 1:IOS seven embraced the notion of a distinct visual layers and using adaptive or dynamic effects to distinguish depth and separation. Why render flat highlights and shadows that are unresponsive to the actual environment of the user when you can separate the icons by rendering them on a separate plane from the background? Parallax made the icons float distinctly above the wallpaper. The notification center sheet could simply be a frosted plain pane above the content which blurred its background for context. Johnny Ives spoke proudly at the iOS seven introduction on how quote, the simple act of setting a different wallpaper affected the appearance of many things.
Speaker 1:This was a very new thing. And so they're not losing the depth. They still they're they're they're bringing the depth, and they're actually making the depth more more complicated with the liquid glass feature. And some people are frustrated by that, but one thing that they're that they're highlighting is that it's intense from a computational perspective. Everyone was saying, like, rendering all these new features is definitely gonna hurt your battery life
Speaker 2:Yeah.
Speaker 1:Because it's so much more although Apple is fantastic at integration, and they're fantastic at this type of hardware and software integration in this these types of renderings, they will probably be very quick. Yeah. So I wouldn't I wouldn't expect a disaster, but I would I would I would expect a little bit more of a load just from the the graphic layer, although it will be heavily optimized. Also, a new thing in the interface was that the UI Chrome was able to have the same dynamics. Things like the header and keyboard would show some of the content they obscured shining through as if it fashioned as if fashioned out of frosted glass.
Speaker 1:While it was arguably an overcorrection in some places, iOS seven's radical changes were here to stay with some of its dynamic effects getting greatly reduced. Parallax is now barely noticeable. Over time, its UI regained a lot more static effects. I wonder how much parallax there is. I don't really notice any right now.
Speaker 1:I mean, I guess when you swipe around you can kind of tell they're they're on a different plane, but I may I might have it turned off. Don't even know. More interface elements started to blend with the content through different types of blur, like the new progressive blur and the button shapes were slowly starting to make a comeback. It settled into a stable state, but it was also somewhat stagnant. For bigger changes, there would have to be a rethink what would come next.
Speaker 1:Couldn't simply be a static bitmap again. It would have to continue the trend of increasingly adaptive interfaces. So he goes on to talk about, the age of physicality and VisionOS and kind of where Apple's going and predicts a lot of of of what wound up happening. So Ben Thompson, to go back to him, he talks about Apple's retreat to empowering developers and partners. This was your point about maybe Apple will be auctioning some stuff off.
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Speaker 2:What the golden retriever does for your yard Yes. Santa does for your business.
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Speaker 1:So Ben Thompson writes about Apple's retreat to empowering developers and partners. He says, that's not to say there weren't some notable AI announcement in announcements in Apple's keynote. Apple announced the foundation models framework. This is a quote from, the Apple team. This year, we're doing something new, and we think it's gonna be pretty big.
Speaker 1:We're opening up access for any app to tap directly into the on device large language model at the core of Apple intelligence with a new foundation models framework. This was what I was asking Alex about, Alex Heath from The Verge, the question of, hey, they're even if even if the models aren't frontier, just the fact that they're happening on device. Speed is very important for a lot of these models, being able to use Yeah. A model without a connection to the Internet. People are still they they're still missing Internet on planes occasionally or or or they have patchy service.
Speaker 1:Build building an app that takes advantage of that and Yeah. And opening that up to the developer ecosystem where you can get really creative and kind of start finding those, like, niche cases of where AI can help for certain things. You know, we we we need the beer app, the iBeer app of the AI era. It's coming.
Speaker 2:We've been begging for With
Speaker 1:this development. For example, if you're getting ready for an exam, an app like Kahoot can create a personalized quiz from your notes to make studying more engaging. And because it uses on device models, this happens without cloud API costs. So if you're this, like, kid developer who doesn't who who maybe doesn't have an economic model yet, you can build an AI product that only uses on device compute, and you have zero you have zero, like, cloud costs
Speaker 2:Yep.
Speaker 1:Which is amazing. I mean, of course,
Speaker 2:there's This got way less attention
Speaker 1:Are you than it should have. Yeah. I mean, everyone was expecting it, and it's great. But it is very cool in terms of just you can now vibe code an iOS app that has some sort of AI functionality. It's not gonna be incredible.
Speaker 1:It's not gonna be frontier, but you can get something that's served into the store that only uses Apple's APIs and creates an experience that is that that is zero ongoing cost. It's entirely hosted by Apple and runs on the device, which is amazing. I I I think that that's very, very exciting to see where people go with this. They give another example of if you're camping off grid, pouring over the hikes, you downloaded to AllTrails, just describe what mood you're in, the mood you're in, and AllTrails can use the on device models to suggest the best option. So, doing doing things like recommendation algorithms on device, much, much faster, much easier.
Speaker 1:We couldn't be more excited about how developers can build on Apple intelligence. And so it's important not to oversell the capabilities of Apple's on device AI models. Of course, developers who want to create something that is competitive with the output of something like ChatGPT will need to use cloud based AI APIs. Of course, you gotta burn the you gotta burn up the h two hundreds to get the really good stuff. But, you know, it's like mid midwit midwit intelligence on too cheap to meter.
Speaker 1:Not quite not quite super intelligence too cheap to meter, but like, you know, it's a midwit. We got
Speaker 2:That's helpful. Digit IQ.
Speaker 1:Two digit IQ.
Speaker 2:Too cheap to meter.
Speaker 1:Two two digit. It's really
Speaker 2:Which is still free.
Speaker 1:It's bullish. It's on the device. The real that reality, however, applies to Apple as well. Part of the folly of the initial Apple intelligence approach is that Apple was promising to deliver beyond state of the art capabilities on the cheap using its users processors and power. What is compelling about the Foundation Models Framework is how it empowers small developers to experiment with on device AI for free.
Speaker 1:This is what I was talking about. An app that wouldn't have AI at all for cost reasons now can. And if that output isn't competitive with Cloud AI, then that's the developer's problem, not Apple's. At the same time, by enabling developers to experiment, Apple is the big beneficiary of those that discover how to do something that is only possible once you have an Apple device. Apple deeper deepened its relation its reliance on OpenAI, incorporating ChatGPT's image generation capability capabilities into image playground and adding ChatGPT analysis to visual intelligence.
Speaker 1:That's cool. There is still no sign of the long rumored Gemini integration or the ability to switch out ChatGPT for the AI provider of your choice. But the general trend toward relying on partners who are actually good at building AI is a smart move. Ben Thompson writes, Apple is incorporating ChatGPT much more deeply into Xcode, its integrated development environment. This is their Versus Code competitor that you need to use to write Objective C apps for the, for if you're building iPhone software, for building apps for Apple platforms.
Speaker 1:Developers can also plug in other models using a API keys. Xcode still has a long way to go to catch up to I AI AI IDEs like Cursor, but, again, partnering with a foundation model maker seems like a much smarter strategy than Apple trying to do everything itself. These are to be sure obvious moves, but that doesn't make them any less important both in terms of Apple's future and also with regard to the theme of this article. Apple's initial success with the Apple two was because of party developers, and developers were critical to making the iPhone a sustainable success. Trusting developers and relying on partners may be a retreat from Apple's increasing insistence on doing everything itself, but is a much is a bit is very much a welcome one.
Speaker 1:And so people are also, you know, may he quotes Marques Brownlee here, the Windows Vista update with AeroGlass was a huge part of my childhood, so I'm getting serious flashbacks. It does have a little bit of, like, the Windows Glass vibes. The biggest part of WWC was about with Liquid Glass, which has drawn some compare unflattering comparisons to past Microsoft operating systems releases. Again, I'll withhold judgment until it ships, but there is another Microsoft OS comparison I've been thinking about recently. To me, last year's Siri disaster was a lot like Windows eight.
Speaker 1:Windows eight was an attempt to micro to leverage Microsoft's large PC install base into a competitive position in touch based devices, and it did not go well. Consumers, particularly enterprises, hated the new UI, and developers weren't interested in the platform without users. Microsoft was forced to retreat and eventually came out with Windows 10, which was much more in line with the traditional Windows releases. Apple has clearly missed the boat on cutting edge AI, but what I'm open to is the argument that this was a ship the company was never meant to board, at least when it comes to products like ChatGPT. Meanwhile, I've long been convinced that Apple has gone too far in its attempt to control everything, even tangentially related to its devices.
Speaker 1:To that end, I understand why many people were underwhelmed by this WWDC, particular particularly in comparison to the AI extravaganza that was Google IO. I think it was one of the more encouraging Apple keynotes in a long time, and that's what Mark Gurman said as well. Apple is a company that went too far in many areas and needed to retreat. Focusing on things only Apple can do is a good thing. Empowering developers and depending on partners is a good thing.
Speaker 1:Giving even giving even the appearance of thoughtful thinking with regards to Apple App Store is a good thing. Of course, we want and are excited by tech companies promising the future. What is a prerequisite is delivering in the present, and it's a sign of progress that Apple retreated to nothing more than that. Let's hear for Ben Thompson. Another great article.
Speaker 1:Nailed it. Very good. Hall
Speaker 2:of famer. Anyway. Future hall of famer.
Speaker 1:You're looking for the apple of sales tax, get on numeral numeral h q, sales tax on autopilot. Spend less than five minutes per month on sales tax compliance. It's AGI sales tax, baby.
Speaker 2:Get on numeral Yes. Now.
Speaker 1:So Just do it. Sarah Guo at conviction, former former guest on the show, friend of the show, said that Apple transcription is still so bad, so so bad compared to what's available on the market. They should be embarrassed. Okay. So I agree.
Speaker 1:I am now in the pattern of if I want to send you a long text with a lot of thoughts, I will go to ChatGPT. I will click the dictation button. I will talk to it, and then I will copy and paste that into the iMessage window.
Speaker 2:Do you instruct ChatGPT to synthesize it
Speaker 1:I don't.
Speaker 2:Organize it? Or you
Speaker 1:just I just use it for the transcript.
Speaker 2:That's crazy.
Speaker 1:I just use it for the transcript. I open up the ChatGPT app. I let it transcribe. I don't even send me a one
Speaker 2:of those John hits me with one of
Speaker 1:those Yes. Yeah. Yeah. Bubbles.
Speaker 2:It's like this long.
Speaker 1:It's the
Speaker 2:You actually don't do that. Right? I I don't really notice
Speaker 1:You don't notice that I that I do it. But even if I'm just saying, okay. I I I'm I'm walking around. I can't really stop in time.
Speaker 2:What here's what we're hitting in the gym. Yeah. You wake up you wake up at 5AM thing, transcribe the workout.
Speaker 1:Five for five, two twenty five, bench press. Yeah. So, basically, I agree it's bad. The question is, why is it bad? Yeah.
Speaker 1:Because there are so many companies out there that they could work with, license, buy, partner with. There's a million different ways to solve this problem. Why is it bad? And I was thinking that maybe part of it is, let's say they buy a company that has amazing transcription, and it is discovered that that company trained on data that it didn't fully have access to.
Speaker 2:Interesting.
Speaker 1:All of a sudden, instead of going after some startup with a $100,000,000 raised and 50,000,000 in the bank, and you're gonna take them for all your for all they're worth, you're going after Apple. Yeah. And you can maybe get a billion dollar settlement. Yeah. And so that's like a huge liability.
Speaker 1:And it's also potentially a PR nightmare because a lot of Apple customers care about the AI training. Adobe's had to be very thoughtful about this in the sense that like, they're like, hey, look, we will let you opt in to letting us train our image, our models on your images if you're on Behance or one of these Yeah. Other services. People don't like the idea of of training just happening on Yeah. Their hard work generally.
Speaker 1:And so I think that there's some PR risk. There's some legal risk. But I agree that they need to figure it out.
Speaker 2:Way less risk if they're just leveraging a vendor that is giving them
Speaker 1:Even that is like it's tough for Apple because if they if it's like, oh, well, they're working with this vendor and the vendor's not above port. Okay, well, now they're linked in the Yeah.
Speaker 2:But they should also be able to go to somebody like Scale AI or Merkor and just say, hey, we want to build a transcription product, and we're just going to make it ourselves.
Speaker 1:I mean, they face they face they face backlash when Foxconn has bad working conditions. Right? And so if they are partnering with another company and then there's some viral news story, whether or not it's real, that Yeah. That those people I
Speaker 2:don't know. But everything Apple does carries risk
Speaker 1:Yeah.
Speaker 2:Even if they have great intentions. Yeah. Yeah. I don't think that agree. They need to figure
Speaker 7:it out.
Speaker 1:And this is something that that just feels it feels so easy to move the ball down the field because they already have a transcription product. Yeah. They just need
Speaker 2:to Let's just make it better.
Speaker 1:They just need to make it better.
Speaker 2:What are the ways in which we can make it
Speaker 1:It's clearly not the modern transformer based architecture. Yes. They need to do a training run. Yes. They need to build some GPU data centers for it.
Speaker 1:Yes. They need new training data. But there has to be a way to do that in an environmentally friendly PR compliant, like like do it do it the Apple way. I'm fine with that. But like you gotta do it because this is such a basic functionality of a phone now.
Speaker 1:And the fact that I'm going from one app to the other just to you just in just because the Siri button isn't transcription is just not good. And and and that would be such an easy thing to just say, hey, hey, we're we're state of the art in this because this is something that is actually improves the daily experience of the of the of the phone Yeah. User, for sure. And same
Speaker 2:thing with That's so so backwards. Have to go in another app just to send a mess transcribe a message.
Speaker 1:I yeah. I I mean, I'm I'm fine with them not inventing, the newest paradigm of, like, deep research. Like, that doesn't that product doesn't need to come from Apple. Yeah. But we've had good dictation and transcription for years now.
Speaker 1:Yeah. And it's open source. And it's not even it's not even that it's just like open source. I'm sure they can't just like, then the open source model in because of the license and all I'm sure there's the restrictions on that. Like, you're not just gonna give Whisper to Somebody company.
Speaker 2:We should have somebody that that's a a big dictation head and and have
Speaker 1:You have a level loss.
Speaker 2:Get a job.
Speaker 1:No. No. No.
Speaker 2:It's just somebody just a fan Oh. Go you know, an Apple fan goes, joins Apple purely to just, you know, beat the dictation drum internally. I Yeah. Because I feel like it just needs to be a handful of people
Speaker 1:Yeah.
Speaker 2:That that are really power users.
Speaker 1:Anyway, I wanted to highlight this post from Pirate Wires. They did an interview on April 16 with David Hanamer Hansen. That's DHH of Rails fame. He also works at thirty seven signals with Yep. Friend of the show, Jason.
Speaker 1:Screen recordings of Apple's new iOS 26 liquid glass software design appear to show a jumbled, difficult to read apps and incoherent home screen app animations. For a company that built its brand on seemingly impossible feats of technology, Apple now finds itself stuck in a self perpetuating cycle, falling behind in the AI race, struggling to attack attract talent needed to catch up, and fumbling product releases. Pirate Wires writer Blake Dodge diagnosed the company's problems in a May interview with 37 signals DHH. Read the interview in full on the site. Link threaded.
Speaker 1:I recommend you go read it. I won't read it here. You have to go subscribe to Pirate Wires. Also, it has a lot of bad words. But Yeah.
Speaker 1:It does. He he really let loose, and I'm sure there's a lot of insight there.
Speaker 2:Guarded state of affairs at Apple.
Speaker 1:Yes. Not not quite, not quite family friendly material. But, if you're an adult, head over, hit the subscribe button, check it out, read it in full because there's a lot of insight there. Anyway, that is, the WWE reset recap. We have, seven minutes until our guest.
Speaker 1:I thought we were gonna do that in fifteen minutes. Wound up being a fifty five, fifty three minute segment.
Speaker 3:Love it. Nice.
Speaker 2:Well, should we cover
Speaker 1:I mean, let's
Speaker 2:cover scale. Yep.
Speaker 1:So Meta is paying 15,000,000,000. I thought it was $14.15, something like that, for 49% stage scale AI to that pays out investors and employees. CEO Alex Wang is leaving to join Meta and head up a super intelligence lab. Feels like those license and acquired deals at Character AI inflection and adept to avoid regulatory scrutiny says Tane, who's been on the show. This is from the information.
Speaker 1:You gotta hit the size gong 15 times for Alex Wang. Let's hear it for a fantastic. I just pulled out my Your headphones? Yeah.
Speaker 2:He's coming up. To let you hit the size one.
Speaker 1:I will hit the gong. Where's the gong mallet? Oh, it's over there.
Speaker 2:Where's the mallet?
Speaker 1:It's over there. Here we go.
Speaker 2:Technical
Speaker 1:difficulties. Lots of difficulties, but we got we got it done. Congratulations to John, but That wasn't 15 hits. But it was one big one. And and it's very exciting.
Speaker 1:I I'm I'm a big fan of Alex Wang. I've met him. I interviewed him on stage at an event about a year ago, and he has a ton of really deep insight into artificial intelligence. And I'm sure he's gonna be an absolute beast in the dog.
Speaker 2:Hopefully, can get a
Speaker 1:board seat.
Speaker 2:A boardroom general.
Speaker 1:He's a boardroom general.
Speaker 2:Yeah. So so so it's funny when when these these kind of deals are relatively recent phenomena. Yes. We saw this with Character AI
Speaker 1:To Google.
Speaker 2:To Google.
Speaker 1:Adapt to Amazon. And then Inflection to Microsoft, and now ScaleaI to Meta.
Speaker 2:And the interesting thing here, I was talking with an early Scale AI investor this morning, and they just still didn't you know, I I think the deal is still in the works. Yep. They didn't have full insight into how exactly it was structured. The question is, Meta's paying $15,000,000,000 for 49% of Scale AI and Scale AI through that is losing their CEO
Speaker 1:Sure.
Speaker 2:To Meta.
Speaker 1:Yep.
Speaker 2:Now, Scale AI is a very big business. Yep. They have a ton of customers that that I imagine are are gonna wanna continue to work with Scale AI. The question becomes what happens to the actual EV of Scale AI in a scenario where Yeah. Half of it is owned by a hyperscaler who has very different incentive structure than a traditional acquirer.
Speaker 2:The positive here is that
Speaker 1:Didn't you talk to somebody at at Character or Adapter and Flexion? You talked to one of somebody who
Speaker 2:was Yeah. Talked to I talked to what what happened with Character is basically, like, the cap table was effectively wiped out and reset and to my
Speaker 1:wiped out. Not wiped cashed out. Cashed very high valuations. So
Speaker 3:they're happy.
Speaker 1:Everyone's happy. The thing for
Speaker 2:these deals. Ended up in a situation where they had this massive balance sheet, no investors Yep. Like, no preferred shareholders Yep. Effectively is effectively, to my knowledge, community owned or or sorry, employee owned. And I don't think that's what's happening here, but it is seemingly clear that the founders, the team, and the investors in Scale AI will be getting paid out.
Speaker 2:I would imagine pro rata based on that $15,000,000,000. Yeah. Mark. And the and the thing that's wild here is, I mean, I
Speaker 1:So it's an up round for everyone. Everyone gets Yeah. Everyone gets cashed out, gets a ton of money. Alex gets to go work in, like, a hyper Super intelligence. Super intelligence and actually, like, take a run at some really serious, like, high technology.
Speaker 2:Yeah. The thing that was ultimately surprising here is So
Speaker 1:Scale AI has more than $900,000,000 in cash on its balance sheet at the end of last year, according to financial information shared with prospective investors. They've raised more than 1,500,000,000.0 from investors. So they only burned 405 600,000,000 of that. Like, they kept more than half of it. The company made 870,000,000 in revenue last year and expected more than 2,000,000,000 this year, and it lost about 150,000,000.
Speaker 1:So, I mean, doing doing pretty well. I mean, there there is a world where where, like, Scale AI as a company, even though they're not wholly owned by Meta, they are independent. And they have $900,000,000 war chest, and they can go build a great business and do a bunch of stuff there. And then the the relationship with Meta can be a fantastic growth engine.
Speaker 2:Yeah. This the the only reason this was surprising to me
Speaker 1:Mhmm.
Speaker 2:Well, guess, one, it's Scale AI was you know, if you're if you're trying to build a a new research lab, they're probably gonna need to still acquire a lot of other top talent. You can imagine Meta going and and trying to bring in into, you know, people from Anthropic or OpenAI into this new organization. Mhmm. But it felt like scale. I I I do wonder if if Scale, you know, Scale's team could go back and and see Circle's IPO and the success of that.
Speaker 2:Yeah. You're making sure still done this done this deal because Scale AI
Speaker 1:could have ripped in the public markets.
Speaker 2:Yeah. Circle Circle IPO showed that the public markets are very receptive to pure play technology bets that that have great narrative around them. Yes. And and I could easily seeing what Circle has traded at, I could see scale trading well beyond, you know, the the this valuation they're getting from Meta.
Speaker 1:I agree with you. The question is, how does the liquidity picture what what does the liquidity picture look like in that scenario?
Speaker 2:They wouldn't the insiders wouldn't have been able to unload 30,000,000,000.
Speaker 1:29,000,000,000. Like, does that does that actually play out? Yeah. Because, yes yes, the the stock could have traded up to 100,000,000,000 market cap. But can you actually Yeah.
Speaker 1:If you're an investor, can you actually get liquidity without crashing the stock if you're putting 15,000,000,000 of downward pressure? Yeah. So
Speaker 2:Yeah. That's a lot.
Speaker 1:Big question. We'll
Speaker 2:have Yeah. Ultimately, huge pickup for for Zuck. Yep. I think Alex, you know, will will continue to be Fantastic. You know, execute very well.
Speaker 2:And I can imagine he'll be a huge part of recruiting.
Speaker 1:Yeah. Mean, he's done a fantastic job. He's like been every he's been on everything from like the Theo Vaughn podcast to testifying in front of the Capitol Hill and
Speaker 2:He's got range.
Speaker 1:Lawmakers. He's got a ton of range. He's very able to storytell and do creative deals, which increasingly are extremely valuable in the world where the AI paradigms, like the secrets are known. It's about, okay. How can you actually marshal the capital and and the will to build the hyperscale data center to actually go and and get Jensen to fork over a 100,000 h 2 hundreds on on schedule?
Speaker 1:Yeah. I'm sure there's a ton of different things in the works.
Speaker 2:Yeah. It's interesting for Meta too, even if they're able to leverage the scale team to simply get better at ads, they can make back the the the $1,515,000,000,000
Speaker 1:Oh, yeah. In in short ways this works out. And, I mean, they clearly need a lot more reinforcement learning training data for to improve LAMA four because they need a they need a reasoning model if they're gonna stay in the game. That's clearly the next paradigm. And, I mean, like, a big part of what we learned about, from seminalysis this week was that verifiable rewards are really important reinforcement learning.
Speaker 1:Scale AI pioneered that humanity's last exam. They've been in, like, the evals game defining the rewards that you would work against in the reinforcement learning paradigm. And so, there's a whole bunch of ways that that plugging Alex and the Scale team in makes a ton of sense. Anyway, really quickly, let me tell you about Adio customer relationship magic. Adio is the AI native CRM that builds, scales, and grows your company to the next level.
Speaker 2:Let's give it up.
Speaker 1:Go check it out. And we have our Let's give it up for Adio.
Speaker 2:Red Redpoint, our guest, investors in Adio.
Speaker 1:No. Wait. Really? Yeah. What a coincidence.
Speaker 1:One here watches the other. Welcome to the stream. How are you doing?
Speaker 3:Well, it's going great, guys. Great to be on. Huge fan of what you guys have built, so this is exciting.
Speaker 1:Thanks so much. It's great to have you. Would you mind kicking us off with a little bit of an introduction?
Speaker 3:For sure. My my name is Saison Lakumar. I'm a partner at Redpoint Ventures. Cool. We're a venture capital firm in The Bay.
Speaker 3:It's been around for over twenty five years. We've invested in companies like Netflix, OpenAI, Stripe. But we're known for infrastructure software investing. So companies like Stripe, Twilio, HashiCorp, Cribble, ChainGuard. And, yeah, that's been our bread and butter.
Speaker 1:And and walk us through what's going on today.
Speaker 3:Yeah. So we're we're in San Francisco at AWS' BuilderLoft. We've partnered with Nasdaq to actually move the their exchange to SF. So in about thirty minutes, we're gonna ring the bell Really? About In SF.
Speaker 3:People here. Yeah. It's it's like it's like that Dalian tweet, like, move move Silicon Valley to Miami. We just
Speaker 1:move Wall Street to the bank.
Speaker 3:Here. So we're excited. We're exciting day for us. But, yeah, this is our annual conference and we do it every year.
Speaker 1:That's amazing. Amazing. Well, but breakdowns
Speaker 2:Hopefully, you guys have we have a Gong cam here.
Speaker 1:Do you
Speaker 2:need a Hopefully, you guys have bell cam set up? But The Gong might be better
Speaker 3:than the bell, I think. We
Speaker 2:we Yeah. S f s f is very Gong coded.
Speaker 3:Yeah. Yeah.
Speaker 1:Well, yeah. Well, I I wanna know about the top themes for for the conference, the top tracks, the top discussion points. What are people debating? For sure. What what take us from kind of where the discourse is and and where the frontier of that discourse is going.
Speaker 3:For sure. You know, we we created this whole initiative a few years ago to call out the importance of infrastructure software
Speaker 1:Mhmm.
Speaker 3:As a standalone category. It's it's it really is like the picks and shovels behind how software is consumed and delivered. It's this invisible piece of software that we just take for granted. When you when you buy something on Amazon, for example, there's some application that we open, but it's powered in the back by all of these dev tools and databases. There's some global server taking in billions of bits of information and you need to secure it from all of these d docs attacks which happens millions of times a day and we just don't know about that.
Speaker 3:So I guess across the whole application delivery life cycle, there are just a ton of different infra tooling and it powers virtually everything we do. So, yeah, we we take we we we do this conference every year to just shine a light on all of the amazing innovation that's happening at the infrastructure layer. So we we divide the world up into into four different subcategories. Everything happening at the AI and model modeling layer
Speaker 7:Mhmm.
Speaker 3:All of the data infrastructure tooling that needs to be built out around that, the cybersecurity vendors that need to protect that data, and all of the developer tools that actually creates the software. So we've been we've been doing it for this is our year doing it, and we also highlight basically the top 100 fastest growing private infrastructure companies. We all get them in a room. We have the c CEOs of AWS, Matt Garman, coming in to chat today and the president of Gary of of YC, Gary Tan. And so, yeah, it's a it's a fun day.
Speaker 1:I have this I have this thesis I wanna bounce off of you and get your feedback on. It feels like dev tools infrastructure, it's less monopolistic. It's and maybe that makes it easier for maybe not VCs to make money, but, entrepreneurs to make money. You just don't get steamrolled as much. Am I am I off there in in thinking that, a lot of these dev tools markets are more oligopolistic by nature of Yeah.
Speaker 1:The fact that hyperscalers are competitive and the different cloud platforms are competitive? Like, what what is the current dynamic? Because I feel like the narrative is always like, someone comes out with some infrastructure or dev tool. It's kind of a boring company. It flies under the radar for six years, then it gets and then, oh, it's worth a couple billion dollars.
Speaker 3:And then it's worth, like, $2,030,000,000,000 dollars
Speaker 1:Exactly. Because no one knows
Speaker 5:about it.
Speaker 1:Exactly. So so we break down, like, what structurally is going on there? Why is it harder to build these crazy, crazy monopolies? And but and then is that narrative about, like, base hits being easier or unicorns being easier? Is that even real?
Speaker 3:I actually no. I I agree with that sentiment maybe a a couple of years ago. But Yeah. If if you look today, I mean, look at Cursor. It had $500,000,000 in ARR
Speaker 1:Yeah.
Speaker 3:In in less than a year. And I guess, like, DevTools, it's always been this, like, very like, you think of DevOps, it's this very sequential process. Right? It's like you have if you have your engineers on one side, then you have your your SRE folks on the other, and then there are there are tools for the the developers, there are tools for the incident response engineers, and they're, like, these distinct stop gaps that exist across the life cycle. Right?
Speaker 1:Yep.
Speaker 3:But with these cogeneration tools like Cursor and Windsurf and Copilot, like, all started on the left. And they started in the IDE where these developers are actually coding. And but you can see the writing on the wall and where they're going. So now you you're you're consuming and writing all of these applications in the IDEs, but they're probably going to extend right, and they're gonna start doing the code review stuff. And then you're gonna deploy the apps.
Speaker 3:Like, you you can see it in Lovable, for example. Yep. With just, like, a simple query, you can go from that query to a full blown production app that's live on a website. So, like, before, you needed, like, 10 different designers and engineers to do all of that. But now with just one tool, you can do that.
Speaker 3:So I think I I think, yes, it's it's not been as monopolistic in the past, but I think that world is changing. And and, like, the clear horses right now, in my opinion, are cursor and anthropic in the coding world.
Speaker 1:Interesting.
Speaker 3:And and so yeah. I mean, it it's just crazy. Like, two years ago, like, people were saying, LLMs, all they could do is just spit out code. Like, you couldn't actually write real software and impact software development. Q two years later, it I think there was this interesting set.
Speaker 3:Like, computer engineering grads face double the unemployment rate of art history majors. And it's Woah.
Speaker 2:It's it's just Yeah. I saw that. It's crazy.
Speaker 1:It seems crazy. How
Speaker 2:how do you compare and contrast the adoption of of AI versus traditional cloud? I I know that you guys have done some some research around, you know, cloud adoption, you know, more than a decade at this point versus even just the the the growth rate on on the token side.
Speaker 3:Yeah. I mean, it you know, it's it's just incredible how how much faster the consumption is on the AI side. I think a really good analogy or data point is if you look at the cost of e c two, like servers during the cloud, the it it got efficient, like, very, very quickly, and it allowed people to consume cloud software all across the board. But when you look at the cost of inference, which I think is the equivalent to e c two and cloud, but inference for AI, it's it's it's literally dropping, like, a 100 times faster than than the cost of e c two. But at the same time, applications are being built and consumed 10 times higher than it was during cloud.
Speaker 3:So it's like a thousand x more consumption at the end of the day. So it's it's just it's just insane, like, what what's happening in the age of AI. And and the markets itself, like, there's this massive services component that is gonna be converted to product based software revenue because you can encapsulate all of that all of these workflows with software. Like, LMs are software at the end of the day. And and you're you're taking these huge markets, and you're making them available through software.
Speaker 2:How are you thinking about competitive dynamics between sort of scaled infrastructure providers like Databricks and Cloudflare and and companies in that category versus some of the upstart companies that are scaling rapidly but, you know, still having to compete with these, you know, founder led companies that are, you know, basically, they're not gonna let they're not gonna miss this sort of, like, platform shift.
Speaker 3:Yeah. You know, it's it's it's really interesting. I I think the existing infrastructure vendors, they can actually embed the AI products in their suite. Like, take like, take vector databases for example, which I think is is an incredible market still. Right?
Speaker 3:And there's, like, all of these use cases. But is there a vector database equivalent of Databricks yet? Like, no. Actually, what happened was that MongoDB extended vector search part of their as part of
Speaker 2:their suite.
Speaker 3:So I think, like but but, like, that's that's not to say, like, like, for example, like, two years ago, people would not have thought an IDE like cursor would would be better than GitHub Copilot. So I think there are pockets of the infrastructure market where sometimes the incumbents are gonna win and they can just leverage their existing technology to extend their applications. But then there are, like, AI native wedges, like the IDE, for example, where there is tremendous opportunity for a couple of 22 year olds to come and create a $10,000,000,000 business in in two years.
Speaker 1:Yeah. Let's stay on Cursor, Windsurf, the new the new dev tools like IDE coding, AI coding market. What's I I'm I'm I've kind of been there's a little bit of a horse race going on. You know, you're either a Cursor guy or a Windsurf guy or you're an investor in one. But as I talk to more and more of the founders, I just increasingly become convinced that this is such a growing market, and it remains potentially oligopolistic that they might kind of all wind up winning in some way or at least returning investor capital and making the founders fantastically wealthy and successful.
Speaker 1:How much of that narrative do you think is real? We talked to Scott Wu over Cognition. We were like, oh, like, OpenAI just launched Codex. Like, are you cooked? And he's like, well, we grew 40% last month.
Speaker 1:And so it seemed like very much not so. And we talked to another person who was saying that, GitHub Copilot, not the trendy tool at all at a $500,000,000 run rate. So that in and of itself could be a public company if it if it was spun out. And so it feels like when when we're talking about doing something so net new, something so additive to companies' workflows, there's just so much opportunity that it kind of just is like a rising tide lifts all boats. But what do you think about that narrative generally?
Speaker 3:Yeah. I mean, if if you just look at the application with the strongest product market fit within the AI world, it's coding. And and, like, the market itself, there are tens of millions of developers. If you just assume moderate assumptions in what you pay them, it's like a $1,600,000,000,000 market in spend. It's it's like it's absolutely massive.
Speaker 3:It's like the mother of all markets. And I think it's really interesting. There there are companies going after certain pockets. So you have the code the co generators that living in your IDE, and that's where the developers are today. Right?
Speaker 3:It's it's where the actual development happens. So Cursor, it was just magic in a bottle. It's tap tap tap, and then all of a sudden, have a full blown production app, and you save yourself countless hours in in in development. But when you when you can see where the world is moving, like, of these processes think about humans at the center, but it's, like, very, very quickly, we're thinking it's gonna shift to having agents at the center. And so companies like Cognition and Factory Yeah.
Speaker 3:They're not gonna exist in your IDE. Like, you're just gonna go tell it you're gonna go tell an agent to go do something, and it's gonna come back and have a pull request, and you're just gonna approve. So I think I think there will always be a need for software developers, but I think they're they're gonna move increasingly from actually coding to being kind of these, like, orchestrators
Speaker 1:Mhmm.
Speaker 3:Of of a product. And I think, like, product managers, for example, are now enabled with these tools. I think at the end of the day, like, I don't I don't think it's gonna yes. There there's, like, some developers that might lose their jobs, but you're you're actually just making their their jobs a lot easier, and there's just gonna be a ton more software.
Speaker 1:There's gonna be more software.
Speaker 5:That's great.
Speaker 2:If you're not Jevan's paradox pilled now Yeah. You never
Speaker 7:will. You lost. Don't know.
Speaker 2:Reacting to the news today, the scale, AI, meta deal, how how do you expect the data labeling market to evolve now that now that in in some ways, one of the key players in that space is has other it will naturally have other priorities if, you know, half their their company is is owned by Meta who has, you know, their their own goals around superintelligence.
Speaker 3:Yeah. Look. If if you if you're the model providers, there are, like, two use cases that are just so clear that and and hair on fire. The one that's like inference. It's actually running these models.
Speaker 3:Two, it's data labeling. Like, how do you actually structure your data and clean your data and feed it into these models and such that you can actually advance the LLMs? And so I think it's I think it's a brilliant acquisition. I think whatever the sticker price is, like, it's it's we're we're gonna look back. It's gonna be like the the Instagram deal.
Speaker 3:I like, need accurate classified data to feed these large language models and for a variety of use cases. There's so many data labeling businesses that we see, like, pockets in in hiring and and whatnot and and and coding and and, like, they're all screaming out of the gates. Like, they go to, like, zero to 20 in, like, two months. And so I think I I I think it it just makes a ton of sense, and I I think it's I think it's a brilliant acquisition. Acquisition.
Speaker 1:Mhmm. I wanna get your reaction to WWDC. It felt like Apple was kind of pulling back from some of the territory that they'd overexpanded into in artificial intelligence. Obviously, it's a developer conference. Yeah.
Speaker 1:Do you think that there's opportunities for startups to, build new companies even around servicing the nascent AI for Apple environment? You could imagine there is, like, there is no cursor for Xcode. There's probably a way to solve that problem.
Speaker 2:Even just Anthropic and their deal with Xcode.
Speaker 1:Yeah. They're working on it. Yeah. But but but there's probably some way to even advance that. And then also just serving up models into, you know, iOS APIs that are, like, more tailored.
Speaker 1:Like, there's been a couple companies that developed back ends that were specifically tuned for iOS apps in the past. Some of those wound up getting sold. So Totally. How are you thinking about opportunities coming out of WDC or or just general reactions? Maybe you don't even follow it at all.
Speaker 3:You know, it's it's interesting. When you look at when you look at, like, past platform shifts like the cloud, you you you need, like, the Workdays and ServiceNows and Salesforces running at massive scale, like pushing the limits of of, like, Cloud Rails before you can before you can really understand what kind of innovation needs to happen at the infrastructure layer. So, you know, our guess here with with Apple and all of these apps that are built, like, you need the AI native versions of these apps that will start, like, hitting the limits of the underlying models before you can really understand. So I for sure, it's gonna happen, but I think it's gonna take some time.
Speaker 2:Mhmm. What is what's the discussion or what do you expect the the discussion to be around agents? There's great narratives around agents right now. There's Yeah. Individual agent products that people use whether it's coding agents or or or sort of research agents.
Speaker 2:But despite, you know, Salesforce, you know, marketing whatever their agent cloud Agent force. Agent force, things like that. It doesn't feel like they maybe have broad adoption yet but a lot of promise. So so how how do you think about kind of agent adoption given, you know, there's people, I think, the event from on the browser infrastructure side, AI agent, DevOps, all that kind of thing.
Speaker 3:Yeah. Look. I mean, it's it's clear it's the next paradigm. I think we're just catching it in a point in time where they're they're stumbling agents. But, like, again, there are some clear use cases where it it's it's clearly working today.
Speaker 3:Like, if like, cognition's agents, for example, they're low level development tasks where like, that is fully automated. And the largest of companies know that, but, like, no one else really knows that yet, and it's it's it's it's mind blowing what's happening. Same thing with customer support. You have your companies like Sierra and Decagon, and that's just a use case that makes a ton of sense for agents to operate. So I think as the agent infrastructure improves,
Speaker 1:there
Speaker 3:are things like memory and context budgeting. There are all a lot of these, like, hairy infrastructure problems that need to be solved. Yeah. But ultimately, also, the agents are gonna improve dramatically. Like, from a year ago, you know, agents have just gotten so much better.
Speaker 3:A year from now, they're gonna be even better. So as agents improve, all of the infrastructure around it improves, like memory. Like, I think very, very soon, there will be an agent for every industry.
Speaker 1:Mhmm.
Speaker 2:Do you think it do you think that it it ends up looking something like regular SaaS or or from a from a from a user standpoint in terms of you have sort of a dashboard? Or do you think there's potentially totally novel paradigms?
Speaker 3:Yeah. You know, I I think UI is is just a big problem or or just an opportunity for these companies to kind of rethink how you surface these products and extend these products to your end consumers. If you look at agents running in the developing world in development world, they're just running in your CLI in the background. Is that the best way to do it? I don't know.
Speaker 3:May maybe voice is the best way to interact with them in the future. So I think I think that UI is still being re reimagined right now. I'm I'm guessing what we have right now will be thrown out the window. Yeah.
Speaker 1:And
Speaker 3:and that these abstraction layers will be very very different in in a few years.
Speaker 1:Yeah. The voice thing is interesting. That that was actually in that original vibe coding post from Andre Karpathy. He says he doesn't even touch the keyboard. He just uses Whisper or some sort of, like,
Speaker 2:super Yeah. Whisper.
Speaker 1:App. He said and he just talks to it and just says, yeah. Adjust the padding. Accept all. You know?
Speaker 1:Oh, there's a bug. Fix it. And and and, yeah, I mean, I I it would be very it'd be super, super weird because for the longest time, the programmer was you know, the keyboard was sacred. It was don't have you don't even have a mouse. Everything you do is on the keyboard.
Speaker 1:Probably have an ergonomic keyboard. You're dealing with carpal tunnel because you're on the keyboard so much. And if we move to a world where the you still have a genius programmer who can understand the architecture, understand what questions to ask, what features to build, that type of stuff. But the actual interaction day to day is is is via voice. That would be a very, very big shift.
Speaker 1:It'd be very interesting. Yeah. Anyway, I wanna get your reaction to the the the news today that Glean re raised a $150,000,000 series f at a $7,200,000,000 valuation. Now So which so
Speaker 3:you say Glean?
Speaker 1:Glean. Yes. So Glean, their, their whole goal is to, enterprise search. And I'm interested in particularly who are the beneficiaries up and down the stack because I imagine that they're in a position, you know, to kinda say, hey. They stuff all your data in Glean, but they probably wanna be more of an integrator, and sit on top of your data lake, on top of your your Snowflake or on top of your Yep.
Speaker 1:Know, your AWS installation or your and plug into your Slack. How are you thinking about having tools that really allow folks in the enterprise to interface with all of the infrastructure that you have described?
Speaker 3:Totally. You know what's interesting is this the the category isn't isn't new. Like, search and, like, there were so many startups and there's this graveyard of companies that existed. But I think the clear why now or at least the enabling technology was LLM. Yeah, of course, Glean is gonna benefit, but, like, what's powering all of this are OpenAI's and Anthropix, like, really, really powerful models.
Speaker 3:Now there needs to be this layer of infrastructure that exists between the model providers and Glean itself. It's like the hairy problems like memory
Speaker 1:Yep.
Speaker 3:And caching. And so those providers are gonna win as well. But ultimately, the consumers also and these companies win. It's it's it's amazing even for me, like, if I'm trying to search something in Google Drive, how long it takes Oh, yeah. To get something.
Speaker 1:It's it's crazy. Somehow it's gotten worse. Like, I can't even see my It it it it's just like there's so many, like, cookies now that if I search for, like, Jordy, it'll find that in some random URL string and be giving me some, like, you know, spam email I got. It's a mess. Yeah.
Speaker 3:Yeah. But, you know, we we should expect and I think
Speaker 1:Yeah. It'll get better. Not I
Speaker 3:think it's OpenAI is gonna release a product here.
Speaker 1:Oh, interesting.
Speaker 3:You you will have like, why why does there need to be an application on top of this?
Speaker 1:Oh, yeah. Totally. Mean, they were teasing this a little bit with the what what was it? The the new the new Well,
Speaker 5:I think
Speaker 2:there was a little a little bit of drama around different people not wanting other people to invest in Glean That was
Speaker 1:one thing.
Speaker 2:OpenAI. Yep.
Speaker 1:Yep. But then there was also the there was also the the the latest news that that Deep Research now can search across GitHub, Google Docs, Gmail, Google Calendar, SharePoint. And so
Speaker 3:that feels That's lean competitor. That's a lean competitor. They're just not saying it. And
Speaker 1:so Exactly.
Speaker 3:And so I think for the applications that make that there is strong really strong product market fit with the large language models, we should expect the model providers themselves to move up the stack and address parts of these apps. Because I mean, if you think about like the models themselves, like, yes, they make a ton of money, but they also burn a lot of cash because Mhmm. OpenAI is just trying to build that next frontier model. Mhmm. So they're gonna go where the consumers are.
Speaker 3:Like, let me go buy Windsurf, right, and and be in the IDE. Let me go release something in the enterprise search space to compete with vendors like Glean. But so I I mean, I think it's fascinating.
Speaker 1:Yeah.
Speaker 2:I wanna When when yeah. When are you ultimately or or the CEOs that you're you're meeting with today, when are you know, it doesn't I I think there's areas in which people feel safe, right, if they're working on, like, a specific application of LLMs with a bunch of deep integrations and workflows, people generally feel safe today. But is there are you expecting a lot of dialogue around people just trying to assess, like, am I on the lab's roadmap and and really trying to figure out, like, at what point they're gonna get, you know, sure locked?
Speaker 3:Yeah. You you either have to be you have to be building on the right side of AI. So if you're trying to solve for deficiencies in the model today and you're kinda trying to build these things, like, very, very quickly in a couple of months, all of that tooling just didn't need to exist. So you you just need to be building on the right side of AI as these LMs become more powerful, like your app application itself should become a lot more powerful. And how do you embed into workflows and also build all of the little hairy infrastructure things to empower all of that?
Speaker 1:Yeah. It's interesting. Like, ironically, like, wrappers, aggregation, aggregating demand, being a front door to AI, like, that's where a lot of the value has accrued or at least, like Yeah. It it feels like the foundation model companies feel most threatened by those approaches versus the Threatened or just wanna own them? They wanna own them or they wanna compete with them directly as opposed to the, okay.
Speaker 1:Yes. You leapfrogged us on capabilities. That's much less of a threat than, oh, yeah. You beat us on a benchmark. That matters a lot less than than when people think of this particular AI use case, they go to this website instead of mine.
Speaker 1:That's more threatening to the Foundation Model Labs in in my opinion.
Speaker 3:Totally. You know, a good analogy is that the hyperscaler hyperscalers like GCP, a w AWS and Azure are the equivalent of OpenAI and Anthropic for the AI world. And and if you saw what AWS did, for example, right, with Elastic, they open source Elastic was a very permissive license and they open sourced it, and they started competing with Elastic itself.
Speaker 1:Mhmm.
Speaker 3:What Elastic ended up doing was they they went for a much more restrictive license
Speaker 1:Mhmm.
Speaker 3:But you still had AWS selling Elastic's core product, and then Elastic is also existing as whatever it is, a $10,000,000,000 business today. So I think, going back to your point, I mean, like, it's I don't think it's winner take all. I I think the model providers are gonna have a large portion of revenue and and spend here. But they're also gonna be a really exciting AI native companies that exist on top.
Speaker 1:Yeah. Yesterday, we talked to Vlad from In Physical working on API keys and secret management. We're really good company. Yeah. Raised a $16,000,000 series a from Elad Gil.
Speaker 1:I wanted to know more about different strategies and approaches to building infrastructure plays that either play directly or alongside open source strategies. And so, there's an open source package out there that's gaining traction. How do you build a product or company around that? Or you have a company that's built something. Do you open source it?
Speaker 1:What are the different strategies that you're seeing? What's working? What's gone out of fashion? I just love some color on how to build either with or alongside open source in the enterprise.
Speaker 3:Yeah. Yeah. I I think open source is a double edged sword. I mean, obviously, we've we've been fortunate to back companies like like HashiCorp and ClickHouse. Yeah.
Speaker 3:And we've seen the commercial success of those businesses. But ultimately, the for for these companies, the biggest competitor is actually your your open source project. Right? Like, like, why do I need to go pay you millions of dollars when I can just try to do this myself and fork it? And so for the open source companies out there, I I think you need to be really careful and just kind of understand where your product is going, the types of enterprise features that you could add that that buyers would actually want you to pay for.
Speaker 3:Mhmm. Ali at Databricks, he has a good analogy here. Like like, building a massive open source business is like hitting two home runs simultaneously. One, you need in a really exciting product where there's a ton of open source traction. And two, you need to figure out monetization.
Speaker 3:In the case of Databricks, you you know, they had Spark and it was great, but they had to figure out a way to make Spark really really cheap and easy to use. And and and but they had to hit these two massive home runs to build a big business. So for the open source founders out there, I would I would say, like, really consider how you're gonna commercialize this product.
Speaker 1:Yeah. What what are the what are the case studies that people are coming back to today? I remember learning the the history of Red Hat Linux built on top of Linux, of course. Fantastic business. Wound up a public company.
Speaker 1:Then we've also heard the story of GitLab that went through Y Combinator, became a fantastic business. Databricks has a similar story. What other stories are people latching on to these days? What are kind of, like, the the the the the the famous examples that people keep pulling from in this open source enterprise infrastructure world?
Speaker 3:Yeah. I mean, MongoDB is one. MongoDB. Right?
Speaker 2:Look look
Speaker 3:look at the success of that business. And what's really interesting is that they released their cloud product much later from the actual open source. It actually came right before the IPO and actually accelerated their revenue growth since it's the only company where that's the case in enterprise software.
Speaker 1:So how were they making money before having a cloud offering? Just
Speaker 3:Well, they they had an enterprise core version of Mhmm. Of their open source. But, like
Speaker 1:Got it.
Speaker 3:Then they also released a cloud self hosted version Yep. Of that product. Interesting. HashiCorp is another example, right, with Vault and and all of these systems. And so they're they're they're obviously, like, companies that have been successful
Speaker 1:Yeah.
Speaker 3:In doing this. But it's you you need to be really careful and you need to think about monetization.
Speaker 1:Yeah. It just seems so dangerous because you're building on top of an open source product. You know this is gonna be baked into Amazon and Google and Azure, like, very quickly. But at the same time, you're maybe a founder mode company. You have a lot of really aggressive people that can go and move and launch new features.
Speaker 1:They can just keep you Right. Cut above. And then, yeah, you know, the the the company says, yeah, I could get, you know, 80% of what I want on AWS, but I want it to be perfect. And so I'm going with you because you're the best vendor.
Speaker 3:Yeah. Basically, it's it's the total cost of ownership of having all of these developers internally and and trying to maintain this in house, is it much less than the actual service that they're providing, the enterprise service? If if that's the case, then great. If if not, then you really have to reconsider this the strategy.
Speaker 1:Yeah. Nothing's worse than having an open source installation and having to deal with like, oh, we gotta turn it off and turn it back on. It's much better to pay someone else to do that.
Speaker 3:And then and then, you know, it just creates just really interesting dynamics with Yeah. The open source community. Right? If if I'm only gonna release features in the paid enterprise version I'm going to kind of just stop releasing features to the open source version, your community is gonna get upset. And so like, it's yeah.
Speaker 3:You just have to be careful.
Speaker 1:Yeah. Well, this has been a fantastic conversation. Thanks so much for taking the time during the busy day to check-in with us.
Speaker 2:Fun. Ringing the bell. Come back on again soon. Yes. This is great.
Speaker 3:So this photos of
Speaker 1:you, really, really We'd love to see it. Yeah. Enjoy the rest of your day.
Speaker 3:Big Gong.
Speaker 1:Yeah. Big one. We'll see
Speaker 2:you soon.
Speaker 1:See you. Bye. Whether you're looking to get exposure to MongoDB or Red Hat Linux, go to public.com. Investing for those who take it seriously. They got multi asset investing, industry leading yields.
Speaker 1:They're trusted by millions. Oh, join
Speaker 2:And Interesting. A new campaign today.
Speaker 1:How did you sleep last night? Because I went on a whirlwind tour. I fell asleep in my son's bed. So I
Speaker 2:got two hours and sleep.
Speaker 1:It doesn't up. Doesn't pick up. I need an eight sleep in his bed, and then I can have Tyler vibe code up something that merged the two data sets together. Because I think I got like nine hours yesterday. I'm feeling fantastic, but I only logged seven hours on my actual eight sleep.
Speaker 1:So I got an 86. How'd you do?
Speaker 2:I got an 83. That's two nights in
Speaker 1:a Two nights in a row. So let's hear it for John Kugen, the sleep master. No one outsleeps me. No one outsleeps me. Don't even try.
Speaker 1:Oh, we got some breaking news for the printer.
Speaker 2:Definitely ill.
Speaker 1:We got some I'm gonna be a hand model now. This is, this is gonna be bad. Okay. We got some breaking news. Anderle has been placed number one on the CNBC disruptors list.
Speaker 1:Congratulations to Andrew Roll. And Trey Stevens is jumping in on the timeline, taking a shot at Sam Altman saying, Take that, Sam Altman. Gotcha. Suck. Crying emoji.
Speaker 1:Of course, they're buddies and and Founders Fund's an investor in OpenAI, so they're having some fun. It was crazy that Anderol got number one because OpenAI has, what, 10 times the market cap at this point, but both fantastic companies. You'll love to see them at the top of the list, number one and number two.
Speaker 2:Dogs.
Speaker 1:We should go we we should go through the, the disruptors list because we have a little bit of time before our next guest. Kari from Linear is joining at 12:45. We have fifteen minutes. Let's go through some timeline reaction. Let's go through some CNBC, disruptors list.
Speaker 1:I wanna see who's going on. So, anyway, to to recap the Glean news, they raised a $150,000,000, adding billions to their valuation. They're $77,200,000,000 valuation inbound.
Speaker 2:Very interesting to two.
Speaker 1:7.2, and it was a who's who on the cap table. The, the CEO, Arvin Jain, really using the long post feature on x. He gives shout outs to Wellington, Cosla, Bicycle VC, GeoDesert Capital, Archerman Cap, AltCap, Capital One Ventures, Citi Ventures, CO2, General Catalyst, DST, Iconic, Institutional Venture Partners, Kleiner, Latitude Capital, Lightspeed, SupplySapphire, Sequoia. Everybody's in.
Speaker 2:So this tells me that OpenAI didn't really get their way in not wanting the people to
Speaker 1:invest simply. You are referring to is, the fact that, back in October of twenty twenty four last year, there's an article in Reuters that says OpenAI asks investors to avoid five AI startups, including such Ilya Sutskever's SSI, sources say. So as as global investors such as Thrive Capital and Tiger Global invest 6,600,000,000.0 in OpenAI, the chat GPT maker sought a commitment beyond just capital. They wanted investors to refrain from funding five companies they perceive as as close competitors. The list includes Anthropic, x AI, Ilya Sotzkover's new company, SAFE Superintelligence, and then where was the other one?
Speaker 1:Two app two application firms, Perplexity and Glean. And so this was kind of a funny moment because, you know, Anthropic seems like the direct competitor. Glean was kinda just thrown in there.
Speaker 2:Yeah. But in many ways
Speaker 1:But it makes sense.
Speaker 2:I don't know. In many ways, Anthropic is not trying to compete in the core Yes. You know, they're so AGI pilled. They're not trying to compete
Speaker 1:They don't have a SaaS. Don't have a voice model. They don't have an image model. They're just focused on on that. So but at the same time, they are they are competitive.
Speaker 1:And and, you know, if you can keep your investors on your side of the table, it it Yeah. There used to be a a, like, an unwritten rule in Silicon Valley that you only back one company.
Speaker 2:OpenAI has just gotten so they're effectively, you know, public companies scale now. We are the market. To it's a hard ask to say. Yes. Just don't invest in SaaS Yes.
Speaker 2:Enterprise, other other labs. Just don't invest.
Speaker 1:Just don't invest. Take take
Speaker 2:a year off.
Speaker 1:Take a year off.
Speaker 2:Take a
Speaker 1:long summer break. A six month
Speaker 2:take a six month spring summer break.
Speaker 1:Just just spend put your whole team on getting into the massively oversubscribed round over there. Focus on that.
Speaker 2:Good luck.
Speaker 1:Work on yourself. Work on Hit
Speaker 2:the Just focus on yourself.
Speaker 1:Hit the slopes.
Speaker 2:No more investing. Focus on yourself.
Speaker 1:Yeah. But this, this news happened, last week. OpenAI said we're rolling out ChatGPT record mode to Teams users on macOS. Capture any meeting, brainstorm, or voice note. ChatGPT will transcribe it, pull out the key points, and turn it into follow-up plans or even code.
Speaker 1:This was taken as a granola attack, but it also plays into, the Glean story. So Signal said granola is more of a social company than a b to b company. It punctured a norm. No big player would have taken the risk of recording without permission, where Granolah beautifully reframed it as productivity, intimacy even. Once the social acceptability shifted, it was inevitable that infra players like OpenAI and Notion would mimic the mechanic under the same pretense.
Speaker 1:This is the difference between product innovation and cultural mutation. Tech can't move where the culture hasn't been softened. And so
Speaker 2:It's so interesting because Otter do you do you remember Otter ai? Have you used them?
Speaker 1:I've I've used Fireflies. I believe
Speaker 2:Otter was started in 2016. Yeah. They they crossed a 100,000,000 ARR
Speaker 1:Yes.
Speaker 2:This year.
Speaker 1:Yes.
Speaker 2:And in many ways, it's very similar
Speaker 1:to Granola. So I believe I inspired some of these because I don't wanna take too much credit because I didn't build anything. But in in 2014
Speaker 2:Take
Speaker 1:a look it. I had a workflow where I would record, I would record meetings, audio. I record the audio of of Zoom meetings or or Google Hangout meetings, and then I would send those to a a transcription service that was not using AI at the time. And I would use Zapier to automatically do this or Zapier. And the guy and the team at Zapier reached out, and they wrote a blog post about my workflow as being like a cool example of how to use Zapier in an interesting way.
Speaker 1:And a couple founders reached out to me and said, hey, we wanna build this as a product. And one of them was Fireflies, and it's like a banger company now too. Yeah. And obviously, it's massively massively enabled by AI, and and only gets better and better. But, yes, Kevin Weil over at, OpenAI, the chief product officer, said Deep Research can now search across GitHub, Google Docs, Dropbox, HubSpot, Outlook, Box, and even more.
Speaker 1:You can connect any chat to Google Docs, SharePoint, Dropbox, and Box. There's even an initial version of MCP support for HubSpot.
Speaker 2:This is big.
Speaker 1:There's record mode in ChatGPT, single sign on for ChatGPT teams, so they are firmly going into the enterprise. And this was this was a point that people were making was that ChatGPT for Teams didn't feel like an enterprise product. It it just allowed you to provision a normal ChatGPT instance to an employee and say, hey, we're we're covering the cost, basically. It wasn't truly integrated. Imagine how cool it'll be if we add someone to the to the TBPN team, and they and they immediately get access in their ChatGPT to all of our internal documents.
Speaker 1:Everything Yeah. That we have about all of our transcripts, all of our all of our
Speaker 2:enterprise search product.
Speaker 1:Yes. Exactly.
Speaker 2:Somewhat
Speaker 1:like Somewhat like Glean. And so, it was clearly on the road map and they and they work towards it. Anyway, they're doing great. OpenAI's number two on the CNBC Disruptor 50. Then you got Databricks, Anthropic at four, Canva at five, Ramp at six.
Speaker 1:Let's hear it for Ramp.
Speaker 2:Take a Congratulations. Using Ramp. Ramp. Ramp. Ramp.
Speaker 2:Ramp. Ramp. Love to see it. No surprises
Speaker 1:at seven. We gotta get the founder on the show. Very interesting company.
Speaker 2:Crime fighters.
Speaker 1:Crime fighters. They solve a ton of crime in America, more important than ever. AlphaSense It's
Speaker 2:kind of like productized Gary Tan.
Speaker 1:Yes. Gary Tan is a service. AlphaSense is at number eight. They, of course, acquired Tigas and are a market research team, market research, firm Juggernaut. Intelligence.
Speaker 1:Juggernaut, big advertiser on invest like the best. We love to see
Speaker 2:it. How
Speaker 1:Octopus Energy.
Speaker 2:Was about to say if there's a single company
Speaker 1:That I don't know. I'm cooked. Yes.
Speaker 2:I'm cooked.
Speaker 1:Yes. But number nine, Octopus Energy. Look it up. Give us a breakdown.
Speaker 2:Haven't heard of them. Smarter, greener, fairer energy for every Texas home. Is this a base power competitor?
Speaker 1:Interesting. Is it I know. Do they make batteries, or do they make solar panels? Break it down for me. I'll keep reading while you do some research.
Speaker 2:So I'm on the website, and I still don't know how it works.
Speaker 1:Okay. Well, all you need to know is then that they're number nine. Let's have the founder on the show. Have him explain it to us. We don't need landing pages, Jordy.
Speaker 1:We get it straight from the source on this show.
Speaker 2:Yeah. There's a bunch of graphics of octopus. I don't know.
Speaker 1:Wait. Really? Is it is it energy generation, energy storage? You do some research. I'm gonna read through some
Speaker 2:the more Yes. So they do.
Speaker 1:Got Stripe at Thank you. Revolut at eleven, Thrive Market at twelve, Metropolis at thirteen. We have the founder of Metropolis coming on the show in just a few minutes.
Speaker 2:Oh, would you look at that?
Speaker 1:Trans Transcarent. I haven't heard of this. They care. They're at number fourteen. We gotta look up them.
Speaker 1:Lead Bank, Fintech's Fixer at fifteen. Haven't heard of them. Carbon Robotics, Weed Tech. We talked to the founder of Carbon Robotics.
Speaker 2:That was an awesome for health and care.
Speaker 1:Virta Virta Health. What comes after GLP ones? That's an interesting company. We'll have to dig into them. Frutist, the berry unicorn.
Speaker 1:We gotta look into Frutist. Frutist. That sounds awesome. Cyronic at 19. We know them.
Speaker 1:Grub market.
Speaker 2:What is the criteria for Rider. Getting on this list?
Speaker 1:We will look we will dig into that.
Speaker 2:Because Let's It's definitely not revenue.
Speaker 1:There's a whole bunch of great companies on there. You got Figma, Zipline, Sierra, Runway, Nivon, Shielded So, Fruittas is
Speaker 2:inspiring and inspiring, enjoyable and nutritious snacking. Okay. Frutis grows the world's most delicious berries. Bursting with flavor, crunchy goodness and freshness in every bite.
Speaker 1:Okay. Here's how they chose the list. So, they're all private.
Speaker 2:How many of these? Yes. I love I I I'll go out and say, I I'm a huge fan of fruit. I think it's one of one of That's fantastic. God's greatest Gifts.
Speaker 2:Inventions and gifts. Have any of these fruit brands broken out?
Speaker 1:Fruittis seems like they've broken out. They're bigger on the list.
Speaker 2:Beautiful website. Yeah. Beautiful website.
Speaker 1:Do you wanna hear about how they chose the 2025 Disruptor 50?
Speaker 2:I do.
Speaker 1:Okay. I got a note, John. So they're all private, independently owned startups founded after 01/01/2010. They were eligible to be nominated. Companies nominated were required to submit detailed analysis, including key quantitative and qualitative information.
Speaker 1:Quantitative metrics include company submitted data on their sales, number of users, employee growth or lack thereof, and more. Some of this information has been kept off the record as it was used for scoring purposes only. CNBC also brought in data from PitchBook and IBISWorld and compared those based on the on the industries that they are attempting to disrupt. There's a board of leading thinkers in the field of innovation and entrepreneurship from around the world along with newer, a newer advisory board that ranked quantitative criteria by importance and ability to disrupt established industries and public companies. This year, the two advisory boards found that scalability and user growth were the most important criteria followed by sales growth and access to capital and community.
Speaker 1:It's very funny that Andrew Roll's number one because, like, what other user growth metrics? Like, that's not the metric for them at all. Like, users aren't a relevant metric. They're not looking at, like, MAUs and DAOs. They're looking at, like, how many things did we build.
Speaker 1:But still
Speaker 2:obviously coming in. I'm I'm still fixated on the fruitist. Fruitist. Because I guess going off of users, you know, they're selling a consumable good in in Whole Foods. But tough tough go for, you know, companies like Scale AI, which are down at at twenty twenty eight.
Speaker 1:So Frutus is better than Scale AI on this So
Speaker 2:so, yeah, if you're going off of this.
Speaker 1:You go short
Speaker 2:Possibly. And lay by
Speaker 1:long Frutus.
Speaker 2:It's possible this is should be Meta's next target. Maybe. They should try to move up the list.
Speaker 1:Yes. Get them all. They already have a deal with Andrew.
Speaker 2:They have an amazing engine. Yeah. Every other ad could just be an ad for berries or fruit. And I I eat these things all the time. And and it'd just be a good way to to really they could potentially turn fruit as from the berry unicorn into a, you know, a deca unicorn.
Speaker 1:I love
Speaker 2:it. I love it. Deca corn.
Speaker 1:We need we we we need more food. We need better food. This is a this is a common common theme. This makes a ton of sense. So new for 2025, we can compare the way the two different advisory boards consider the importance of the list criteria.
Speaker 1:While the two boards mostly agreed, the VC group thought that the size of the industry being disrupted was more important than the academics did with the latter ranking access to capital and community as more important criterion than the group that provides said access. The The ranking model is complex enough to be sensitive to these differences of opinion, and perhaps more than ever, it makes good on the concept that companies must score highly on a wide range of criteria to make the final list. Nominated companies were also asked to submit important qualitative information about themselves, including descriptions of the core business model, ideal customers, and recent company milestones. A team of CNBC editorial staff, including TV anchors, reporters, and producers, and cnbc.com reporters and editors, along with many members of the advisory board, read the submissions and provided holistic qualitative assessments of each company. In addition, the VC advisory board assessed a small group of finalists as an additional component of the qualitative review.
Speaker 1:Specifically, we asked VC the VC group to assess some of the companies that would, if selected, be making the list for the time as well as to help in the consideration of high scoring early stage firms, a group of lower valuations but promising Part
Speaker 2:of the criteria, they didn't want the top 25 to all be enterprise SaaS companies because that doesn't it's not good for ratings.
Speaker 1:It's not good for ratings.
Speaker 2:Not good for ratings.
Speaker 1:So only 11 of the twenty twenty five honorees are pre ChatGPT CNBC disruptors, but most of that group, Anderolt, Databricks, and Canva, chief among them, the embrace of the new era is what has kept them here. And so there were 19 timers in either 2023 or 2024. Companies are moving up. They're moving down, but it's an exciting list. Who else sticks out on this list?
Speaker 1:We gotta get some of these folks on. A better ride to school from Zoom, Wabi, how self driving trucks see and learn. That seems interesting. Aptronic, five feet eight inches, 160 pounds, all robot. Haven't seen them.
Speaker 1:Harvey's on the list, lawyering up AI. They got good pithy pithy phrases there.
Speaker 2:Notion project project management. Okay. We got project management for your projects. That's kind of an odd one. Yeah.
Speaker 2:Not the strongest.
Speaker 1:A bridge getting a doctor's note. Esasu Isusu, treating renters like owners.
Speaker 2:Shield AI. We got the CEO
Speaker 1:on. Interesting. Well, very fun list. We love a good list. We were now that Conrad's out, the Midas list has fallen from grace, and we need new lists.
Speaker 1:But congrats to Andrew Roll, congrats to OpenAi, and congrats to everyone that made the list of the CNBC disruptive 50.
Speaker 2:One thing's clear. You gotta be an absolute dog to get on this list.
Speaker 1:Yes. You do. Well, we have Kari, from Linear coming in the studio.
Speaker 2:Get the gong ready, John. Why don't you hit it?
Speaker 1:I will hit it for him.
Speaker 2:We're gonna hit it a few times.
Speaker 1:The stream.
Speaker 2:Kari, before you before you dive in, yeah, give us the numbers
Speaker 1:How much did you raise?
Speaker 5:How much did you raise? 82,000,000.
Speaker 2:Low dilution round at a billion. Congratulations. We love to see it. A lot of people would have said, you know, this was maybe an unlikely round. You guys have been very, very efficient, but it's a testament to to
Speaker 1:Proving the haters wrong. They said it couldn't be done.
Speaker 2:Well, they said it could
Speaker 1:be done. It's a quest.
Speaker 2:They said Kari would never wouldn't wouldn't do it. No.
Speaker 5:Wouldn't do it.
Speaker 2:Anyway, congratulations. You on. Massive milestone for you and the team. How are you feeling?
Speaker 5:Yeah. Feel feeling great. And, yeah, I think it's definitely, like, one of this. Like, I think, like, all of our rounds has been kinda, like, interesting because since, I think, the seed round, we haven't really needed the money. So each each round is kind of like, we're we're doing something different or or we are signaling something to the market.
Speaker 5:So it's a little bit always, like, strange to do these rounds because, like, I think, like, often, like, you celebrate it as a way to be able to do something more. And I think, like, in the end, we will do something more, but also that, like, not a lot of changes. Like, we we still keep billing for the customers and the things we're doing.
Speaker 2:Talk about maybe some of the last rounds, how they were unique, and and what makes this round unique.
Speaker 5:Yeah. I think we also, like, done this, like, interesting thing where we have kind of doubled down on each of the investors. So Sequoia led our seed round back in 2020, and then we did a series a with them, I think, '21. And then we did a series b with Excel in '22. And then now two years later or, like, about three years year later, we we did a series c with them.
Speaker 5:So
Speaker 1:There you go.
Speaker 5:I think there there's also, like I remember when I was talking to back in the day, like, at around the seed round to a lot of seed round investors, and I think, like, they they had this, like they create this fear that this platform funds can be challenging and, like, there can be the signaling risk and all kinds of things. And I don't know if that's really true or I haven't I I don't even know, like, when that has happened. But I do know that it's kinda, like, interesting when you are working with this platform funds. They can, like, double like, kinda, like, lead two rounds in in in, like, kinda sequence. And I think the benefit there is that you can kinda push down the dilution because there is they already have some kinda ownership, and they like, I think, like, a lot of times the with this game of, like, fundraising, like, the the the actual absolute numbers don't matter, like, how much you raise or what the valuation is.
Speaker 5:It's more like everyone else is fighting for their percentages. Okay. Yeah. If you if you kinda, like, work with the same investors, you have more, like, I don't know, leverage or or there's a little more, like, flexibility on those percentages.
Speaker 1:Yeah. Yeah. Yeah. I mean, it makes sense. It also makes board construction easier because you're not adding 25 different board members from every fund.
Speaker 1:On the platform fund thing, I mean, it's clear that, like, that narrative came out of, like, kind of the clubhouse era where the company got marked up multiple times for by the same insider, and and the metrics didn't really meet that. Was this more of a vibe round or an Excel round? How are the metrics tracking? What what are people an
Speaker 2:Excel round.
Speaker 1:What are people watching? Are they looking like, is Mao, Dow the key KPI? You don't have to give us the actual number, but, like, what is most important? Is it revenue, profit, EBITDA, EBIT? Like, what what metrics are are are most important for a round like this to get done in this era?
Speaker 5:I mean, like, I think, like, all the later stage funds, like, all later stage rounds, it it is about the growth and and the revenue. I mean, obviously, different companies are different, so, like, there might be, like, other other things. But but for us, since we we sell to companies, it it generally, like, turns into revenue. Like, we don't have a lot of, like, free users or free free customers. So every everyone is, a a paid customer.
Speaker 5:I think it's, like, comes down to one is, like, kinda like, the growth and the the kind of position we have in the market. We've been able to capture quite a lot of the growth market these days, like the early stage startup, but but also, like, the late stage growth market, like companies like Ramp or Mercury or Brex or or and even OpenAI, which is, like, I don't know, like, if if you categorize it as a core company or, like, enterprise or what what is that? I don't know.
Speaker 1:It's a mass company. Behemoth. Yeah.
Speaker 5:Yeah. We need a new word.
Speaker 1:It's into corn. Something like that.
Speaker 5:Yeah. Yeah. I think, like, we I I think, like, it comes down to, like, we we work with the best companies out there.
Speaker 1:Yep.
Speaker 5:And I think, like, we also have a, like, a lot of people really love the product and, like, they really wanna use it. So I think, like, we have had a lot of opportunities that we could have additional investors join the board or, like, lead these rounds. But for me at this point, I think it's it's probably, like, in the next next like, the next time around, there's probably reasons to find someone new and, like, find someone with, like, some kind of specific or different skill set. But right now, I didn't feel like that's necessary. Right now, I think, like, the biggest thing what we're aiming for is that, like, we have this core business and and product going with a lot of, like, 15,000 customers, like, companies.
Speaker 5:But I think that Love it. The next thing is that that the kind of, like, the AI and how how but you probably heard it this, like, a million times on this on this show. But I think, again, the AI is, like, shifting the the market and and, like, how things work and, like, how software is built. And I think we often, I like to do these rounds when we don't need to do it. Yeah.
Speaker 5:And we also, like, when we are about to hit something big, and I think we were about to hit something big with this, like
Speaker 2:Yeah. Talk about some of the discussions around yeah. Talk about some of the the discussions, you know, with Excel and and some of the other partners and internally with the team around this sort of inflection point with agents because Mhmm. For the you know, you guys have had a bunch of integrations for a long time, but this is sort of a novel type of integration. I know you guys are working with, you know, Devon and Cognition and and other players.
Speaker 2:And, you know, that that feels to me like a a lot of the Linear's position as a platform that can help manage agents feels like, you know, a major catalyst.
Speaker 5:Yeah. Yeah. So some some of those companies we've been working now, but and there's a lot more coming. I don't I don't have the exact dates yet, but I think we're also working with the bigger companies out there that are are building some of the, like, the, like, the model companies. So, hopefully, those are coming soon.
Speaker 5:So, yeah, I think, like, the with the agents, the idea is that we have this we have built this, like, end to end workflow for, like, discovering and planning and building products, and it's, like, kind of familiar to these organizations and these product teams. And I think, like, right now, like, we we started seeing distraction from our customer base and also talking to CTOs. Almost every CTO out there is thinking about AI. Like, how do we we we I think, like, the CTOs and the CEOs are writing these memos, and, like, they know that they, like, can help their organizations. But the the problem now is, like, there's a lot of friction.
Speaker 5:Like, the the solutions are not that, like, designed yet. Like, it it's a little bit hard to use some of these tools and or use this technology. So the idea here is that, like, we have this familiar system that people already do use to to do their work. And so we can easily introduce these agents and some of the other AI capabilities into it so they don't have to, like, go somewhere else to do it, but they can kinda, like, continue what they're doing. But now instead of assigning task or or, like, kinda, like, code bugs or something to humans or the teammate teammates, you can assign them to agents and then work with them to solve them.
Speaker 5:So I think, like, the the the kinda, like, the idea there is that we want to make it as easy as possible for organizations to kinda adopt the AI or adopt these agents or adopt, like, the new technology. Because, like, a lot of the other companies are kinda, like, more building the underlying technology, but then sometimes it's seems like it's hard to for enterprise
Speaker 2:to adopt. Mhmm. Yeah. Orchestrate them.
Speaker 1:I wanna let you get back to building, but I have I wanna get WWC reaction.
Speaker 2:We gotta get your take on WWC.
Speaker 1:Mean, Linear is a fantastic design driven firm. I'm sure that there is a lot of internal chatter in the Slack or in the the in the in the group chats about WWC. How's the reaction
Speaker 2:been? Liquid glass.
Speaker 1:Liquid glass. What's the take? Give break it down for us.
Speaker 5:Yeah. I don't wanna go too harsh on it until and then I think until it's, like, in production. I do think, like, there's some discussion. I think that the borders are too rounded, and I think, like, some of the borders are off.
Speaker 1:Like, you
Speaker 5:they're not following the right like, when you have, like, two rounded rectangles, you just kinda, like, follow the same curve with those curve with those round like, the border radius. So it looks like an kinda like an even like, that there's even spacing alongside all of the all of the kind of path. Mhmm. But I don't know if that was a mistake someone did for the keynote or they just didn't wanna like, I don't know. They didn't do it correctly.
Speaker 5:Yeah. I hope it was a mistake. I think it's it seems like really, I I think, obviously visually interesting, but I I'm I'm still, like, skeptical until, like, I see it, like, how well it actually works in practice. Mhmm. Like, at Linear, actually, we did have some of this we had this, like, transfer translucent UI at some point, and then I decided to remove it because I I thought it was, like, too distracting, and it's actually was kinda slowing the application down.
Speaker 5:So I I decided to remove it, and and so I'm hoping that Apple can make it performant and also it not not distractive.
Speaker 2:Yeah. Do you think do you think there's always gonna be readability challenges with it, or is it something, you know, you that that they can solve?
Speaker 5:I mean, I think the starting point, it it it is hard to, like, solve that because, like, I think it's that was my experience with, like, having, like, transparent UI as well is that it it can work well if you have a nice, like, I don't know, solid color background on your computer or or something. But then, like, if you have, like, a photo like, on the on the phone, you have a photo of your family or something, It it can be kind of pride and, like, there can be a lot of different things going on in the background. So I do think it it will be hard to, like, make it kind of easy. It's like the contrast to be enough to to read it. But I don't know if they're gonna do some kind of magic there that they could figure out, like, what's on the background and then adjust it somehow.
Speaker 5:So I'm hoping that they can figure it out, but I'm I'm I remains little bit skeptical until I actually see
Speaker 2:Our batteries our batteries are gonna be cooked.
Speaker 1:Batteries are gonna be cooked for better.
Speaker 8:I think
Speaker 1:they'll I think they'll figure
Speaker 2:it out. Well, congratulations Congratulations. To to you and the whole team. And, yeah, excited to see what you guys continue to cook up.
Speaker 1:Yeah. This is fantastic.
Speaker 2:Started.
Speaker 1:We'll talk to you soon. Have a good one. Thanks. Bye.
Speaker 2:Have a good one, Corey.
Speaker 1:Let's check-in with Tyler. Apparently, he has iOS 26 installed. Give us the update, Tyler. How's it going? Let's see
Speaker 2:it.
Speaker 4:Yeah. So I got it fully installed. I mean, we might have to put those posts in the truth zone. It looks pretty good on my phone.
Speaker 1:It looks good.
Speaker 4:Wow. It's pretty readable.
Speaker 1:Give us the review.
Speaker 4:I think it's I like it.
Speaker 1:Okay. I might
Speaker 4:mean, it's a bit slow on my phone. That might be because
Speaker 1:Which one do you have?
Speaker 4:I have an 11. So it's like
Speaker 2:six years old.
Speaker 1:Wait. I'm on like 16.
Speaker 2:You guys a vintage mobile phone.
Speaker 4:So it's either that or I think also usually in the beta versions, it's it's a bit like slower.
Speaker 1:I have a 16 pro. I'm
Speaker 6:I'm Yeah.
Speaker 1:I'm I'm
Speaker 9:gonna have upgrade.
Speaker 1:Years ahead of you. Oh my god.
Speaker 4:But Wow.
Speaker 1:Okay. Yeah. It looks pretty good. I'll I'll bring
Speaker 3:it up there.
Speaker 1:Okay. Cool. Yeah. Bring it up. Let's see We're putting it on the printer cam.
Speaker 1:We'll see it. And, yeah, here we go. Okay. Cool. Can we see?
Speaker 2:I don't see much.
Speaker 1:It it actually looks pretty similar. Let's see the
Speaker 2:I I expect okay. There's the there's the there it's transitioned.
Speaker 1:This doesn't look as
Speaker 4:It's it's mostly just the home screen. Like, if you go I I went to a bunch of the like
Speaker 2:The calculator
Speaker 1:looks like a No.
Speaker 2:No. No. I'm kidding. I'm kidding. Yeah.
Speaker 2:I
Speaker 1:mean, mean, you can see the glass effect like right here up at the top.
Speaker 2:Yeah. It's nice.
Speaker 1:It's it's nice. And look you you so so look at the search bar as as I scroll the apps here. You can see you know that that that glass effect is not too bad. You bring down the the settings.
Speaker 2:I'm bullish. This is groundbreaking. I think this is I think this works.
Speaker 1:This is this is pretty readable. Anyway, thank you for volunteering. You'll have to we'll have to check-in with you over the next couple days your
Speaker 2:productivity but you're cracked. So
Speaker 1:You're cracked.
Speaker 2:You'll figure it
Speaker 1:out.
Speaker 2:Anyway. Thank you, Tyler.
Speaker 1:You know, Apple's gonna be pushing this pretty hard. They gotta do some out of home advertising. They get they gotta get on adquick.com. Out of home advertising Apple. Easy and measurable.
Speaker 2:Drop the Genmoji ads market by every single Yep. Billboard in San Francisco
Speaker 1:Tim for Iowa's headaches of out of home advertising only ad quick combines technology out of home expertise and data to enable efficient seem by seamless ad buying across the globe.
Speaker 2:I'll be right back.
Speaker 1:We have our next guest, Scott Belsky, coming to the studio in just a minute. In the meantime, we will react to some posts on the timeline. Kendall says, trying to quickly change the subject on the Zoom call when everyone else is cracking jokes about the Waymo's, and I can feel my I I can feel myself choking up. Lots of sympathy for the Waymos. Lots of coverage in The Wall Street Journal today about the about the burning Waymos, talking about how this played directly into the hands of of the of the Trump administration by making the tech company clearly align with what you know, against the burning of Waymo's.
Speaker 1:Very sad to see, hopefully, things resolve. It does feel like the report from LA I've been driving around today. It feels like things have calmed down a lot. In general, I was able to drive all the way across LA without any I was in downtown. Didn't really notice anything.
Speaker 1:And so it does seem like things are are calming down, thankfully. Anyway, I like this post from Tyler. I'm gonna mispronounce his name. Well, I'll just say Tyler. He says, unlike the rest of you cowards, I think the y what the y combinator valuations are too low.
Speaker 1:We will find out what the valuations are coming in at tomorrow when we're at YC demo day live in San Francisco. We're bringing a huge swath of the crew. We're going up right after the show wraps. The team is stoked. We'll be giving out hats.
Speaker 1:We have a whole bunch of different hats, some TBPN hats, some ramp hats, and the ramp hats have TBPN on them. So they're all limited editions. I think people will really like them. So if you're a founder at YC Demo Day or you're an investor at YC Demo Day, stop by our table, Come chat with us for a couple minutes, and we will get your take and hear your pitch and hopefully turn your Demo Day into a massive party round because we will be live from the Palace Of Party Rounds. Mike Solana reposted the video of the Waymo's leaving Los Angeles.
Speaker 1:Apparently, Waymo is moving their cars out of LA. I don't know how real this is, but there it was a video of several Waymo's driving through LA kind of altogether.
Speaker 2:Maybe they're leaving. Get of here.
Speaker 1:Quite makes sense because you think you could just put them wherever they store them and charge them and clean them. But
Speaker 2:Yeah. I don't necessarily believe that this was a response.
Speaker 1:Seems like fake news, but Solana has a great post. As always, the elves are leaving Middle Earth. Very funny. Anyway, Ramp has a post in 2012 in 2024, Ramp placed 32 on CNBC's disruptors 50. This year, number six.
Speaker 1:They're grateful to their customers for betting on a better way and allowing us to fix the parts of finance people hate, so they can do more of what they love. And, shout out to our friends at Andrew Roll for making number one. What a fantastic lineup over there. What else is in the news? Oh, Warner Brothers.
Speaker 1:Oh, wait. We have Scott Belsky in the studio. Let's bring him in. How are you doing, Scott?
Speaker 2:There he is. Finally.
Speaker 1:Long ago. I I I'm sorry it took me so long to invite you on. I'm so glad we could make this happen. It's fantastic to find you.
Speaker 2:We were sending invites constantly, mentally.
Speaker 1:We were like, this is a dream guest. So thank you so much for taking the time to join us. Would you mind kinda setting the stage for us? Because you've done a lot in your career. What are you focused on right now?
Speaker 1:What's interesting to you? And then we can kinda dig into all the hot topics of the day.
Speaker 8:Well, of all, it's been fun to watch you guys at work.
Speaker 2:Thank you.
Speaker 8:And congrats on Thank you. On just, you know, creating conversation which I think it is appreciated by all of us. What am I up to these days? I mean, my obsession has always been the intersection of creativity and technology.
Speaker 1:Yeah.
Speaker 8:Behance is probably, what, 58,000,000, 60,000,000 creatives online right now, showcasing their work. Yeah. And that brought me into Adobe. Yeah.
Speaker 1:I had
Speaker 8:a long stint at Adobe leading emerging products and design and various other new things there. And, you know, now I'm excited to kind of explore the world of storytelling
Speaker 5:Mhmm.
Speaker 8:And the role that technology plays there. Obsessed with the implications of new technology, you know, that emerge, and I love engaging in conversation about I think you guys were talking about the implications kind of writing I do and and riffing off of, I don't know, like, what's gonna happen because of what's gonna happen is the question.
Speaker 1:Yeah. Yeah. It's a big question.
Speaker 2:It's a big question.
Speaker 1:Maybe we should start with, some of the news that's coming out of, like, this idea of collective memory, what's going on in the enterprise. We were talking about Glean, OpenAI, Deep Research. There's so many new products. We're using stuff. We're wiring up stuff.
Speaker 1:We have an intern in the corner vibe coding different stuff for us. We're we're essentially a podcast or a live show, a media company, and we're we're writing software. Everything about how we are building this media business is different than I think people would have done, even just a few years ago. But what
Speaker 2:we do crazy. The, if if somebody told me three years ago, I we have a a a show, a podcast, and we're building a bunch of internal software
Speaker 1:I would be like, that's huge mistake.
Speaker 2:So bearish, and yet we get so much value out of our internal software we call Newsmax. Newsmax. But, anyways, back back to you.
Speaker 8:No. I mean, I think the well, of all, it's it's when you're building a new team from scratch these days, it's almost like you're you're able to build with another new generation of tools Mhmm. As opposed to to retrofit something built with old tools.
Speaker 1:Totally.
Speaker 8:So I do think there's this advantage that a lot of new companies are realizing now or new teams within companies. You know, but you asked about this this concept of collective memory, I've been obsessed with. You know, this this notion that the context window of these AI tools that we're using, of course, those context windows are context windows are growing, means that their memory of us and their understanding of us is growing and persisting across all the inquiries we have. And, you know, and this is becoming almost like, you know, an extension of our knowledge and opinions and identity and everything else. And and it's great when these LMs get to know us and give us better and better answers to our questions.
Speaker 8:What happens when in the enterprise, we access each other's memory?
Speaker 1:Yep.
Speaker 8:Right? So if if the if the context window of me working, you know, as one of your interns for years, you know, is suddenly accessible to you even when I leave, you know, are you able to keep saying, hey. What does Scott think? Or, you know, or what what what did Scott do when we had this situation? And is that a is that does that belong to the enterprise?
Speaker 8:Mhmm. And you do see, by the way, like, every company right now trying to build this memory for each of its products users. And in some cases, a lot of companies are building connectors to get the data from other products that that customer uses to enrich that memory and understanding of their customer. And it'll be interesting when that kind of memory that's for each of us becomes a collective memory. And then what happens in the in the social, like in the consumer world?
Speaker 8:Like, you know, does your girlfriend say like, I want access to your context window, your memory, you know, and is that kinda weird? I I think there's all kinds of weird questions and implications that arise from that.
Speaker 2:Do you think memory can be the lock in that I think certain companies would like it to be? It doesn't feel like it is yet, but I think there's still an idea that it could be.
Speaker 1:Goes the opposite way. Like, I I'll ask ChatGPT to tell me a joke, it'll be, like, hyper specific about something I talked about a year ago. And I'm like, that actually makes the joke worse, ChatGPT. Like, I'd prefer if you ignored all my questions about trains or something.
Speaker 8:Well, could be in the prompt. Right?
Speaker 1:Yeah. Exactly.
Speaker 8:I like, you know, you
Speaker 1:see
Speaker 8:OpenAI launch the ability to log into tools with OpenAI.
Speaker 1:Yep.
Speaker 8:And, you know, when I saw that, I was, like, instantly thinking, gosh, that's a way to enrich the personalization.
Speaker 7:Mhmm.
Speaker 8:I I do think personalization effects are the new network effects. Mhmm. You know, we used to talk about in terms of the the moat that companies would have with a network effect today. I do think they will have with personalization, and that is a direct, you know, a a direct out outcome of the memory and extended context window and all of the data, you know, that they can get to give us a personalized experience that no one else could ever give us. But you're right.
Speaker 8:Like, there are other ramifications of that, you know, if you're if you're too well known. I asked OpenAI the other day, you know, what I didn't know about myself, and it told me that you're a real hypochondriac. And I was like, well, I didn't know that about myself.
Speaker 1:So That's funny. I I I I wanna know more about these the like, this idea of collective memory in the enterprise.
Speaker 2:Sorry sorry to interrupt, but it's an interesting thing where, like, the model's effectively trying to do pattern recognition Yep. And it just identifies something that is
Speaker 1:But you ask a lot of questions. It's like because you're a question answering machine. Yeah. Like, that's not me. That's you.
Speaker 1:But but on on the concept of, like, creating a collective memory in the enterprise, I've noticed that even though we are this new company that's starting from scratch, total greenfield, we have still not been able to go all in on one walled garden. We have Gmail. We we send a lot of iMessage groups. We also have a Slack that, you know, we are interfacing with different people on. That's a Salesforce product.
Speaker 1:And so I'm wondering if, you know, there's been Eric Mikovsky was trying to build Beeper, this product to let you create one unified messaging interface. That was a real struggle because every major company was like, we will not let you break our walled garden. We're not really there yet, and and it seems like most of the companies are playing ball with MCP servers and the like. But what do you think the big dynamics of the big tech companies will be like once they realize that, hey, maybe if I don't wanna let the fox in the hen house?
Speaker 8:Well, I think you're, you know, you're you're you're forecasting a bit of a, call it, a data war, you know, in the years ahead where everyone's going to leverage each other's APIs and start start to pull all the data, you know, in and and there are gonna probably be some backroom board level bilateral negotiations where it's like, well, let's not cut off Slack because we don't want them to cut off us. So we're gonna let them and may the, you know, may the best may the best model win, right, with the data provided to it. So but that means that there if if if the data becomes sort of sort of, you know, readily available across the board from all of the connectors that are made for all of the products we use. And to your point, if you've built the network, your your company with all these different products, that's fine because the data is all stored probably in one of three or four clouds
Speaker 1:Yeah.
Speaker 8:And you can just instantly access all that data, use AI to see it as structured data, and then be able to have AI apps built on top of it. And you don't even need to care what actual products create the data as long as you have access to all the data. But then the question is, what are the moats? Right? Yeah.
Speaker 8:I think one of them is personalization layer that we talked about just now and that context window becoming ever more important in the product. You know, think another one is permissioning, like in the enterprise especially. Permissioning is freaking hard, right, to know exactly who's about who's allowed to ask what question and get what answer or what column of information that might relay itself to that answer. Mhmm. That is a a very, very hard thing to crack.
Speaker 8:And I do believe that the enterprise products that have really incredible permissioning layers and products that allow people to control and access permissioning will also have an advantage. The operating systems. We talk about operating systems in the consumer world with you know, your iOS or Android person or whatever, and that's the operating system. Those those operating systems, like, if they can't figure it out, well, shame on them. Like, they literally own the the the top layer of everything underneath, and they should be able to, you know, manage our attention and our needs with AI at that level.
Speaker 8:But what are the operating systems of work? Mhmm. You know, I think there's gonna be another war played around those operating systems. One might be the browser. Mhmm.
Speaker 8:I think one might be the way that projects are managed. You know, different functions of the enterprise might have different operating systems and people are gonna be fighting to, own the top layer of those.
Speaker 1:Yeah. I wonder if that's like a almost a bull case for data lakes becoming more of a mid market or early stage product because, like, I I I take your point about like the the the deals between the large tech companies, just kinda happening behind the scenes. But at the same time, I'm just like, there's gonna be friction. And I just know these companies like, yes, I can export all my data from Facebook if I click 12 buttons and do it every single day. Like, the API is not fully there Yeah.
Speaker 1:For a lot of these products. And so I wonder if more and more people are gonna be saying like, even for my personal life, I wanna be able to funnel everything into a data lake that then I can drop my own AI on. And I don't necessarily want lock into one AI tool right now. I'm wondering how that how that will evolve. I don't know.
Speaker 2:Yeah. I mean, we're gonna see this in consumer too. It'd be really nice right now if you could describe in chat GBT, hey, go find this image and then make it a studio Ghibli. Right? Sure.
Speaker 2:Or or make it like an impressionist painting.
Speaker 1:Right? Yeah.
Speaker 2:And and obviously, there there's that kind of barrier Yeah.
Speaker 1:Wall. It just feels like the the big tech companies want that that they're they're fine having lock in and like, you see this with WWDC, like, the the Siri button cannot be remapped still. And it's like, that would have been an easy thing to do. That would have been something that a lot of consumers demanded. What was your reaction to WWDC and kind of like how how the the AI Apple does like decisions are playing are playing out?
Speaker 8:Yeah. I mean, think it's really it's a really fascinating time, you know, in that company's history. Think from the outside, we're questioning like where's the vision, you know? Yeah. Where are we all going?
Speaker 8:And I think inside, it's probably some sense of let's wait until we're really ready. Mhmm. We've had a few false starts. We can't get it wrong again. Yeah.
Speaker 8:And so we're probably gonna get something that's more fully baked, which
Speaker 1:is
Speaker 8:hopefully great for Apple. You know, I never I never discount Apple because of its DNA and its rigor and the quality of talent that's there. You know, on the other hand, like, they're late to the game at this point, like, super late. I also wonder the things we discussed just, you know, a minute ago around personalization and some of the moats that are they're gonna play. Also, by the way, remember, this is a new era of experiences that is all about data.
Speaker 8:Mhmm. And Apple's always been all about privacy.
Speaker 6:Mhmm.
Speaker 8:So Apple, in some ways, as a policy, has done everything to make it impossible for others to get others' data.
Speaker 1:Yep.
Speaker 8:And here we are in a world where, know, that's what's gonna enrich the experience we have from AI tools. So I think it's a it's a Apple do
Speaker 2:you think that Apple will end up looking really smart on privacy? Like, we're in a very chaotic time where people will let new software, you know, company just have full access to Screen recording. Visual screen recording.
Speaker 1:Record everything. That's like It does. Okay thing
Speaker 2:now and I'm even surprised at this point that we haven't I I can't remember a major incident of a model producing private data in response to sort of like a a general query. I've heard
Speaker 1:about anecdotes here and there, but
Speaker 2:nothing really Yeah. Concrete. A world some days where, you know, people get their kind of Totally. Lines crossed and you ask for you ask about some some, you know, acquisition for example and somebody at some point dumped it.
Speaker 1:You even tried to get ChatGPT to guess a picture that was from your own house and it was and it was smart enough to say, hey, you're maybe trying to spy on someone, so I'm not gonna do that. Even though Yeah. But I
Speaker 2:could I could it would it would basically gave me, like, the exact description of it without giving me effectively the So
Speaker 1:it knew it knew not to step up the line. I don't know. Anyway, on on privacy.
Speaker 8:I mean, it's a great question. You know, I always go back to principles in this one and I say to myself, you know, of all, what do we know about the next generation? They seem to care less about privacy than the generation before them. Yeah. You know, number two is we're we're willing to trade a lot for less friction in our lives.
Speaker 8:Mhmm. And it seems like people are willing to always click accept or yes or yes or yes, you know, again, just to be able to have a frictionless experience in a product. Now, I think you're surfacing the point that very you know, we we don't oftentimes realize like how much we're giving over
Speaker 6:Mhmm.
Speaker 8:In those instances. And I think the world of AI will make that very apparent to us because we'll start getting these personalized experiences and we're like, how the hell do they know that about me? Right? But I don't know. Like, there's also a part of me that says that the best technology takes us back to the way things once were but with more scale and efficiency.
Speaker 8:Well, the way things once were hundreds of years ago is we were known. Like everywhere we went in our small towns, we were remembered. They called us by name. They knew our kids' names. They knew our favorite cut at the butcher.
Speaker 8:Like you you were kind of known. And in some weird way, we're being brought back to a world where we're gonna be known again. That's interesting. The question is we wanna know how we're known and and also we don't wanna be known by people that we don't trust.
Speaker 1:Yeah. Yeah. There there is kind of this interesting economic dynamic where there's almost like a de facto bug bounty for privacy in the fact that if a company like Apple has a privacy fiasco, that could wipe off hundreds of billions of dollars of market cap. And so they have this massive incentive to invest to not have these privacy fiascos or the data to leak. And so you have kind of this massive economic capital canon towards, let's secure the public clouds.
Speaker 1:And so one of my former colleagues was making the point that in terms of open source AI versus closed source AI, oftentimes, it's actually better to trust a hyperscaler with your data. That because it's harder to break into an AWS data center than it is to the on prem server that, yes, you're running it, but you're the only security guard. What happens if someone breaks in and just takes the rack?
Speaker 8:Like I'll you what though, like, here's a bullish case for Apple, which is that models are all gonna be local Mhmm. You know, in x number of years. The most power like, you look at the performance of
Speaker 1:Sure.
Speaker 8:Of LMs, right, there are these small LMs and there's these ones that run locally on on devices. And the the the delta between those and top LMs is, of course, decreasing. And so as chips get better and LMs run locally, you can imagine that all of your data can actually be stored locally in a super encrypted way. All these local models can operate to answer all of the questions you have, can search the Internet when it when it's necessary. And maybe we all opt to this, like, super private AI world.
Speaker 8:Maybe for all we know, Apple's optimizing for that flag that they know the puck is going to, you know, and they're gonna launch who knows how many years from now, like a 100% local AI experience that is world class with zero privacy considerations Yeah. Or or risk rather.
Speaker 1:Yeah. Yeah. Yeah. Yeah. Yeah.
Speaker 1:Makes no sense. I don't know. Can you talk a little bit about knowledge arbitrage? Like, these models, we've gone from, you know, massive databases of facts and so there wasn't as much incentive to just be a the the the person that memorizes all the facts because you can just Google it on your phone. Now, we're in this age of even more significant knowledge retrieval, intelligence potentially to Cheap to Meter if we can call it intelligence.
Speaker 1:What is knowledge arbitrage? Like, what what what what
Speaker 8:I mean, I think about the term knowledge arbitrage, like, I'm actually brought back to I think this is very relevant for, like, people who are listening to us or kind of earlier in their careers right now and figuring out, like, how to plot their path forward. And you go back to the early two thousands and the people who stood Twitter and social media and things like that were getting hired by like CMOs of Fortune 500 companies to school them on what the heck this thing was and like how to have their brand participate. And it was really looked upon as, like, this complex crazy thing that every leader in in in in corporate America felt they needed to understand. And so there's this moment of knowledge arbitrage where people who are, like, you know, in their late teens, early twenties, who are deeply, natively familiar with this stuff called social media could just, like, school the people who had no clue. Here we are again.
Speaker 8:You know, you have the leaders of all these Fortune 500 companies saying, oh my gosh, like, we have to refactor how we work and every function's gonna operate differently with AI, But we don't even know like when to use ChatGPT. We don't even know what a prompt is and like how does this stuff even work. And so once again, these like very young people who got through college using ChatGPT and talk to ChatGPT about their boyfriend or girlfriend issues or whatever else, like, it's native to them. And so I do think this knowledge arbitrage moment, you know, is here and the window's open right now.
Speaker 2:Yeah. It's funny that there's this massive fear from from young people around how the job market is evolving or jobs getting killed or whatever. And at the same time, yeah, it it feels like social media didn't reinvent every part of a company. Like, it sort of massively changed marketing and how you should focus marketing dollars and how you should think about building brands and all these things. But it wasn't something that that changed internal comms, like you're talking about with, like, collective memory.
Speaker 2:It wasn't something that changed a certain aspect of the business, like compliance. It it it didn't change, You know, it wasn't this sort of, like, full stack transformation. And and for that reason, it creates more opportunity than the social media wave to just get good at using LLMs and and agents and whatever ever whatever other tools you have and then use that. I mean, we the the the last person that we hired was somebody who who vibe coded, like, a guest directory for us. And they did it last
Speaker 1:Like Friday.
Speaker 2:Last Thursday. And then We hired them on that. And and then we saw it, like, Friday.
Speaker 1:We they started on Monday. Yeah. They came and it was good on Thursday. They came on Friday, and we had them
Speaker 2:start Monday. By demonstrating the ability to leverage these tools and create a product that was a v one, but it was a solid v one. And it was just a super easy decision to be like, yeah, you should join the team. So shout out shout out to Adam.
Speaker 3:But That
Speaker 8:like forty eight hours work though. That's like incredible. Yeah. So in in by the way, that's changing the way product is even done. Like, I Yeah.
Speaker 8:I'm so used to a world where you concept, you do like a sort of, you know, product scoping session, then you have the designers work in a product like Figma and make prototypes. And then engineers don't even see it until the prototypes are locked and then it's like redlined and engineering start to like, now it's a different world. Right?
Speaker 1:Yep.
Speaker 8:It's like, we need we need we need this to be done. You kind of vibe code it out. In parallel, a designer says, okay, let's try to finesse it. Here's how we can maybe change that, make that more accessible to more people. And then you just deploy and test and iterate.
Speaker 8:It's a different use a whole different product stack to some degree. And that's why I always say the best talent these days is like a collapsed stack talent strategy where you hire people who have exposure to different parts of the stack, whether it's engineering and design or design and copy or product and design because you're just trying to collapse the stack with the types of people you have so you can leverage these tools, you know, efficiently.
Speaker 1:Can you talk a little bit about agency? It's it's an interesting concept because we don't have, like, an eval for it in terms of the LLMs. We're we're we're, you know, destroying all the benchmarks in math and IQ, but the models don't seem to have volition. And yet, the trend is around agentic applications. We're trying to give them agency.
Speaker 1:It still seems like some there's some sort of combination of uniquely human traits that seems to be increasingly valuable. How are you defining it right now?
Speaker 8:Well, I think that when you talk to when you talk about sort of agentic workflows and the know, the role of agents in the future, you know, and I think about it, every company you know, I'm calling companies these days in my mind Cognico. It's like condition driven businesses where it's ultimately inference in the center. Right? And there are these the functions of a company, which were once accounting and legal and design and, like, all these different functions, are going to be AI tools that are running, you know, AI agents, basically, that are running that function or a collection of agents doing different aspects of the function, which then begs the question of what's the role of the humans. I think we are the orchestration designers and orchestration engineers.
Speaker 8:We're like orchestrating how these agents work and how they work together. And we're also developing and enforcing the rules by which they work because remember, these agents are told what to do, and they're rewarded based on doing it. They have to be working within a subset of rules that need to be administered and enforced to some degree by humans. So I start there, and then I start to think, okay. So what are the functions of every organization gonna look like?
Speaker 8:You know, what and then that dictates, like, what kinds of tools or agents are empowered to, know, quote, unquote, take agency in those functions. But I also wanna say that when you say agency, at I think of, like, the human Yeah. You know, the human getting
Speaker 2:Still got it. You still got it.
Speaker 8:I we gotta dude, we gotta we gotta exercise our agency and our taste more than ever before these days. And the the the years the days of us kinda getting a prescribed job function and sticking to it, that is like the death bell of a career these days.
Speaker 1:Yeah. Totally. As soon as it can be defined, it can be reinforcement learned against
Speaker 2:Were you were you surprised at all about this the the concept of taste coming into the the the Discourse. The Silicon Valley discourse. It feels like one of those things. It actually reminded me of when venture capitalists discovered the creator economy in 2020 and 2019. But it was a trend that had been happening for, like, a decade at that point where people were creating content online and turning it into a business.
Speaker 2:And then all of a sudden, people, I think, saw a statistic that was like, you know, look at this. You know, look how fast this category is growing. We should invest a bunch of dollars there. But in many ways, feel like taste has always been a key part of Yeah. Our industry.
Speaker 2:And and if you look at a lot of the best companies, they don't all look the same, but they have people that run them that have taste that that sort of gets applied in in many different ways, whether it's hiring all the way through, obviously, the the visual side.
Speaker 8:You know, I'm I am brought back to a just earlier in my career, you know, it was all about what skills you had. Right? And and the resume would always were you good at PHP or JavaScript or could you do wrote code in Python or whatever the case might be? We come from a world where skills, like, were the hardest things to achieve and the most differentiating things for humans, right, in in a project. Now, as a lot of the skills have been offloaded to compute, you know, now it's like, well, what's left?
Speaker 8:Like, taste is actually one of those things that is definitely left, right? And so, I think that the fact that everyone's sort of focused on on on taste these days is more of a commentary on how less focused they are on skill Yeah. And how much confidence they have in all these models and coding tools and everything else.
Speaker 2:Can taste be taught though? That's the question. Skills can be taught, taste
Speaker 8:Taste be taught. Like, let's, you know, can taste be taught is like a thing I think about in debate all the time with with friends. You know, what is taste? Gosh. It's like the human experience.
Speaker 8:It's childhood traumas. It's mistake of the eyes. It's judgment. It's knowing how many things to see before you make a decision. You know what?
Speaker 8:But it's also knowing how to choose something that isn't so on the nose, but, like, leave something for the imagination. You know? It's knowing where people are going as opposed to where people are. Like, I think it's all of these factors that are so critical whether you're making a product or making a marketing campaign or a film or whatever the case might be. And I just, you know, I I I think that hopefully we'll just over index on human experience in order to achieve taste.
Speaker 1:Yeah. There's yeah, it almost feels like just independent thinking, confidence, like you can maybe develop No.
Speaker 2:But it's independent independent thinking that elicits a collective response that you want in some ways. Right? I mean, I I think of this in the context of how companies get attention.
Speaker 1:Yeah. There's a
Speaker 2:lot of different ways to get attention. Some some some ways Tasteful. Are are you know, some ways are tasteful and
Speaker 5:a I know
Speaker 1:what you're thinking of.
Speaker 2:You know, positive response. Other others get, you know, a lot of attention, but but a sort of visceral negative reaction and and taste in the context of social media algorithms and timelines is, like, such an important, question because it's really easy right now to do.
Speaker 1:To instantiate something but not to yeah. It's fascinating.
Speaker 2:Yeah. Taste taste too in the context of AI, slop. Right? There's Yep. Tasteful.
Speaker 2:There's tasteful.
Speaker 1:I always keep coming back to the Harry Potter Balenciaga video. Feel like that was, you know, it it had the aesthetics of AI slop because it was AI generated.
Speaker 2:With it and Yeah.
Speaker 1:But it it had the it had the touch of a human to think of those two Yes. Kind of complete unrelated disparate ideas. And when you put them together, it was something that you had to watch.
Speaker 8:And by the way, that's perfect evidence, the fact that you're still citing that Yeah. Despite how many months, if not years, of content generation has happened since. Yeah. It shows you, like, the taste still stands out. And that's why, you know, people are like, oh my gosh, content is commoditized.
Speaker 8:Like, everyone can do everything now. Oh my gosh, this is horrible for Hollywood.
Speaker 1:Yep.
Speaker 8:My view is the opposite. Like, in the and historically, when anything becomes commoditized, whether it's shoes, clothes, handbags, liquor, whatever it like, that's LVMH. Like, LVMH is in all those businesses, but they're doing the higher end, meaning infused, more scarce version
Speaker 1:Yep.
Speaker 8:Of that thing that's available to anyone. Yeah. Your now content is commoditized given all these new tools. And I think as consumers of content, we are going to seek more scarce, meaning infused, human, you know, brand signaled versions of content to fill our attention in time. And so I think that's a great example.
Speaker 8:You know, it doesn't matter how it was made. It matters, you know, whether there's meaning in
Speaker 1:it. Even knew how the tools I I I knew the tools that were used to make Harry Potter Balenciaga thing, but I couldn't come up with a unique idea that would go viral. And so I went to ChatGPT and I said, here's why this worked. It worked because it was inspired and it combined two things that were so disparate. Think of another thing that could be iconic like that and it couldn't do it at all.
Speaker 1:Became Famous. Yeah. Yeah. Exactly. Exactly.
Speaker 1:It wasn't there. I know, that that inspiration still needs to strike. George, do have a last Speaking
Speaker 2:of Hollywood, did you see Mountainhead, the new Jesse Armstrong film? Have you seen it yet?
Speaker 8:I haven't seen Mountain Head yet.
Speaker 2:No. Okay. You should I mean, you if if you don't enjoy it, they're they're really cooked. But it's Jesse Armstrong from Succession. Okay.
Speaker 2:You're making this film. The the high level concept is, you know, some podcast. Yeah. You could you could say that. But the thing that the thing that I wanted to get to is the the basically the over arch part of the overarching narrative is that deepfakes have gotten so good that they're causing global chaos because people don't know what's real and then they're seeing video and and sort of acting on that video.
Speaker 2:I wanted to ask you in that context or or or just generally about the progression of video models and how you're thinking about, you know, if if v o three, you know, what do you expect from from things like v o four and Yep. You know, new runway models and any you know, I'm assuming you're looking at everything internally at at Yeah.
Speaker 8:Let me let me just well, two comments. Like, one on video models and then deep fakes real quickly. On video models, I mean, this is like a consistent slap of hand game, right, where, oh my god, this is the best model and then v o two comes out and then Sora and then runway and then v o three and it just it just keeps piling up. This is great for anyone who makes stories because these models are becoming better and increasingly commoditized. However, you know, it's would I wanna be the model, you know, that's competing and not increasingly commoditized and not as great, you know, quality sort of vector?
Speaker 8:Probably not. So that's comment number one. On the deepfake situation, it's interesting, like these new websites that are coming out where you have these, like, anyone can make a deepfake with Trump saying whatever. I actually think they're playing a secret value to society by inoculating all of
Speaker 1:us. Totally.
Speaker 8:We all get a fake Trump said something crazy video tomorrow and we're inoculated from the fact that we should no longer trust what we see, that we should instead of going from a world where we would trust but verify, go from a world, you know, to a world where we verify then trust. Yep. Like, that would be good for humanity. So I'm like, I'm actually, you know, for that inoculation because I think I think that I think that we need it and we're gonna wanna know where where stuff came from.
Speaker 2:If it didn't fly on a weird way
Speaker 1:VPN, it didn't happen.
Speaker 2:No. In a weird in a weird way, it it it might save legacy media because if legacy media orients around institutions. It orients around like, if CNN were to say, we are you know, there's a bunch of the you know, you have usernames like autism capital that are sort of de facto news on x. Right? These are accounts that get billions of impressions and they act as as, you know, news content.
Speaker 2:Yeah. But if CNB you know, CNBC and CNN and and other services can really orient around we did the you know, we were late to the punch on this, but we did the work to, you know, verify that it was real. It actually might save
Speaker 1:Totally.
Speaker 8:And there's credentials now. There's metadata through things like content credentials that go into assets that are made on certain cameras and edit in certain software and, you know, and whether it's TPPN or CNN or anyone else can surface that information in the reporting and say, we verified this is, you know, done by this so and so and was edited by so and so. And I think that adds to, you know, a layer of what people are gonna need and want in the future. Make it happen.
Speaker 1:Thanks so much.
Speaker 2:Yeah. I wish we had I wish we had ninety minutes. Yeah. This was super fun.
Speaker 1:We'll have
Speaker 8:to come back soon.
Speaker 1:Yeah. To be continued. Great talk rest of your day. We'll talk to you soon, Scott. Bye.
Speaker 1:Cheers. Really quickly, let me tell you about bezel. Go to get bezel.com. Your Bezel concierge is available now to source you any watch on the planet. Seriously, any watch.
Speaker 1:And we have our next guest already in the studio, Roy from Bloomberg beta coming in to talk about his latest fundraise. How are you doing, Roy? Great to meet you.
Speaker 7:Fresh capital in the bank or committed or something like
Speaker 1:that. What? What? What? How much how much capital did you raise?
Speaker 2:Talk to us.
Speaker 8:Okay. How much?
Speaker 7:You hit it 75 times for 75 Woah. You know, I'll take one customer sale over fresh capital in the bank. You know? No.
Speaker 2:No. Capital formation is is the highest calling of man.
Speaker 1:It is. Is.
Speaker 7:They have two guys who do not intend to form their own capital
Speaker 2:unless he's ready. That's right. But we we're in the business of
Speaker 1:covering capital formation and celebrating it. But congratulations. What are you most excited about? Where are you planning to deploy this? What is how is the money burning a hole in your pocket?
Speaker 7:Yeah. So we, twelve years ago, started this firm to say, we're gonna do day zero investing in startups and I'll just give the context because the answer's gonna be the same thing. Mhmm. Startups that future are future work oriented. Our bet at the time was our personal lives have changed a lot.
Speaker 7:Our work lives have not. Maybe that'll change. Like, people were still using Lotus Notes for email. And and now on our fund, we are doing basically exactly the same thing. The craft of day zero, work closely with the founder, and what's burning a hole in my pocket is continue to do that.
Speaker 7:You know? And I'm looking at our fund one companies and feeling like they're still midway through the journey. Replit, Flexport, Campus, you know?
Speaker 1:We love these companies. Yeah. Many most of them have been on the show. Fantastic companies.
Speaker 7:Yeah. No. I've loved watching them. That's part of what I love about the show.
Speaker 2:What what percentage of funds venture funds make it to fund five?
Speaker 7:That's an excellent question.
Speaker 2:Very gotta be like 5%.
Speaker 1:Very low.
Speaker 7:But I always feel like that's sort of like those stats about what percentage of startups like raise their series b. It's like if the starting denominator has a lot of meh in Like, I think to me the more interesting question is who gets there
Speaker 5:you go.
Speaker 7:Who gets to a there you go. Hot off the press.
Speaker 1:Printed so I printed your your post because it appears that you printed your post. I don't know if you can see this, but you printed Meta. It's a printed a LinkedIn post and you marked it up. You said, today, we're announcing our next fund, our and you just crossed it out and put And I and and we respect printing out posts here, so I just wanted to
Speaker 7:The idea was inspired by this thing I stole from congress
Speaker 1:Yeah.
Speaker 7:When the republicans blocked a democrat supreme court nominee
Speaker 1:Okay.
Speaker 7:And then it went around the other way and they literally just crossed out the names
Speaker 1:and put in like Schumer to a congressman.
Speaker 7:It is the same. So I think the more interesting question is
Speaker 1:Yes.
Speaker 7:Who gets to a fund five or whatever fund size without trying to gradually expand AUM? Like, it seems like so many of the VC firms out there, and we love working with them, are just in the AUM expansion business.
Speaker 2:Yep. The big AUM scare me personally. I I looked it up here according to Chad GPT. There's probably a 50% chance it's hallucinating, but it's estimating at less than 5% based on PitchBook and Cambridge Associates data. I
Speaker 1:mean, here here you say you're you aspire to be the most transparent investors. What does transparency mean in the context of a venture fund?
Speaker 2:Yeah. Do you tell the founder, look, we clocked you at about a 15% chance of success. It's a bet we're willing to take.
Speaker 7:If you try to tell them how exactly we're thinking about it. But here, look up go to our website right now on those two laptops you got in front of you, and then you'll tell me what but which is to say, when I was a founder, so before this, I started a company in games.
Speaker 8:Yeah.
Speaker 7:And, you know, you drive down to the 280, end up in an office on Sandhill Road.
Speaker 2:Mhmm.
Speaker 7:And in the three minutes of the meeting, the person would be like, oh, but you're not a fit for us. We don't do this. And it's like, well, why on earth do we just do that? And we're an attacker. We're coming into an established industry.
Speaker 7:We just asked, are there things the industry does that we can flip the bit and do the other way? And so the industry seemed very opaque at the time. It's a lot less true now. And we're just like, can we be as transparent as possible? Can we put in valuation?
Speaker 7:Can we put in diligence questions? You can actually get our long form actual deal documents from our website. And the point of it is not transparency for transparency's sake, although that's a very Bloomberg idea about trans Yeah. It's just founders are our customers. We want them to not waste time guessing what we do.
Speaker 7:And so if they can disqualify out by seeing we don't do that thing, great. Better for everybody.
Speaker 1:We're big fans of Bloomberg. We read a lot of Bloomberg pieces on the show. What is the actual relationship to your funds? Subscription yet? No.
Speaker 1:We gotta get one. Well, again This is time. This is my go to terminal every day as a Wall Street Journal, but, we we we do have a
Speaker 2:We gotta
Speaker 1:get a And
Speaker 2:You gotta get a terminal.
Speaker 3:We've had
Speaker 1:a bunch of Bloomberg folks in the show. You're like the Bloomberg affiliated person. We got Joe Wizenthal, Tracy Allaway. We got Sheeran Gafari coming on the show Bigger brands
Speaker 7:than me. One and all.
Speaker 1:But what is the relationship between the fund and Bloomberg as a whole? Obviously, Bloomberg does a ton of different stuff. What does that look like and how does it evolve?
Speaker 7:The company is the LP in our fund.
Speaker 1:Period. End of story. Full stop.
Speaker 7:We are not a strategic investor. So unlike a bunch of other corporate backed funds, we're not trying to find some startup that's gonna be a Bloomberg partner.
Speaker 1:Sure.
Speaker 7:Bloomberg wanted to understand what was happening in the world of startups. The argument was best way to do that is give startups what they need, which is just money.
Speaker 1:Yeah. That makes a lot of sense. Cool. Talk to me about deployment of the fund. Is is 75,000,000, that's a lot of smaller checks.
Speaker 1:Are you holding back some for pro rata and scale up? Like, what
Speaker 7:what You know the line about, like, tell me the fund size. I'll tell you the strategy.
Speaker 1:Yep.
Speaker 7:Part of the reason why we've kept our fund size where it is is we wanna be as early as possible. And so Okay. I can't remember the exact number, but it's something like most funds, their check ends up being something like 75 basis points of fund size on average. And we end up a little bit around there, slightly bigger. We do you know, we reserve for follow ons, but then we also have an opportunity fund.
Speaker 7:Because what we realized is we wrote some big checks in from our core fund into some of our winners. We wrote a big check
Speaker 2:Yeah.
Speaker 7:Into Replit at one point, eight whatever. The the, you know, company up, new front. And it's like, well, if we're gonna do that, we might as well have the capital to do that reliably. So we've got an opportunity fund.
Speaker 1:Yeah. At the early stage, are you are you trying to pick a winner and then not invest in competitive companies? Like, how do you think about that?
Speaker 7:Very old school on all this stuff. My view on competition Wow. Competition is in the eye of the founder.
Speaker 2:Mhmm.
Speaker 7:Like, I have a attitude on this, which is if I back you, I want you knowing I have your back. Not that I'm thinking about which of your competitors to introduce to somebody. And so any founder we invest in, if they tell us that a company is competitive, we won't invest in that Shit still happens like
Speaker 1:Of course.
Speaker 7:You know, companies Pivot in. Pivot in. It'll kinda work it out. But that's the principle.
Speaker 1:Yeah. But yeah. That's not on you. Driving the news cycle this week, you got WWDC, Apple kind of pulling back It drove
Speaker 7:the news cycle. It drove the news cycle kind of by necessity. Yeah. Of course. If you had said, but nothing happened, would we have just nodded along politely?
Speaker 2:Well, our our in our our intern Tyler spent hours Simultaneously. Setting it
Speaker 1:Well, yeah. He assembled the American made iPhone yesterday. Today, he installed arguably a harder challenge in installing a big iOS 26. But, I mean, there is a there is a bit of a narrative for startups there in the sense that if Apple is truly pulling back and not going to steamroll the the the the startup developer community in terms of AI based apps, that could be a a potential boom for you know, we could see another rise of a mobile esque era where AI companies are building on iOS in in a little bit more friendly territory than Totally. Than it's been in the past.
Speaker 1:Obviously, there's the Fortnite decision and discussion around the App Store. What are you seeing that's interesting? Or or just what else is driving the news cycle for you?
Speaker 7:Well, no. So I I do think look. Apple has to be an attacker on AI. You've pointed out the way that the privacy philosophy makes it a lot harder for them to do AI. AI developers who go there talk about running into that internally.
Speaker 7:You know, all the big tech companies wanna be the platform on which everybody else sharecrops.
Speaker 1:Yep.
Speaker 7:And at the moment, that's OpenAI and Anthropic. It's like you have all these fast growing
Speaker 2:growth Sharecrops is such a savage but real way to
Speaker 1:describe cut. It's just 30%. 30. It's not 50?
Speaker 7:30. Of course, naturally. But the market didn't exist but for
Speaker 1:them. Yes.
Speaker 7:And and I think they're gonna try to figure out, can they disrupt some other part of the ecosystem? I feel the same way about the Scale AI acquisition, which is Meta has to attack. They need a layer that they can control that everybody else depends on, and this looks like their play at it. The other thing I think is interesting about that that I've been thinking about is how many of these big AI companies have effectively been acquired in ways that the government doesn't get to approve? It's We sell them.
Speaker 7:The big talent acquisitions. When I saw this, I was like, that looks like an acquisition the FTC doesn't get to approve. Yep. And so I don't know if that's the motivation. I have not spoken at any of the parties.
Speaker 7:We're not in Scale AI. But my sense is you're basically seeing the Game of Thrones play out, but the government is one of the houses.
Speaker 1:What's very interesting about that is that
Speaker 2:we are
Speaker 1:Yeah. Lena Con's gone.
Speaker 3:We're in a different
Speaker 9:Why can't
Speaker 3:we put this thing?
Speaker 2:Let us let us do some exudicious.
Speaker 1:Let us do
Speaker 2:some m and a.
Speaker 1:Just $28,000,000,000 acquisition. Just let us sneak it sneak it in. It's fine.
Speaker 2:Let's get it by. Let's get it Let's get Let's open let's get the m and a window master
Speaker 7:I mean, the other thing I say is when was the last time you heard a big tech company buy a company for $80,000,000? It felt like that used to happen all the time.
Speaker 1:All the time.
Speaker 7:Yep. And now, it's a lot less common for
Speaker 2:a variety They took that they took that from us.
Speaker 1:They took that from us.
Speaker 2:I think
Speaker 7:I feel the grief.
Speaker 1:Yeah. I mean, there used to be there used to be a a really great outcome for a lot of folks where, if you're a founder and you start and you still own 30% of a company and you sell it for 80,000,000, like, that's that's a house in Palo Alto and kids and generational wealth in some ways. And, yeah, that that has gone by the wayside. I don't exactly know why because those seem to be easier to get across the finish line from an FTC perspective, but I guess folks just
Speaker 2:I mean, at what point does the FTC just say, like, look, we know. We could see what you're doing.
Speaker 1:Yeah. I mean, also
Speaker 2:15,000,000,000 on this company Yep. For and and the CEO no longer works there.
Speaker 1:Works there. Yeah. I mean, the flip side yeah. I mean, the flip side is, like, when was the last time a company was valued at 80,000,000? Because every company seems to go That wasn't a pre
Speaker 7:seed cut.
Speaker 1:From 5,000,000 to 500,000,000 in two days. And so I I don't know where you're getting 80,000,000. Like, that that's just hard to hard to find. I do I do have a question for you. I don't even know if you can speak to this, but there's a lot of companies that are thinking about plugging into the terminal.
Speaker 1:We see what Perplexity is doing. We're we see, a bunch of AI agents for
Speaker 2:financial gain. Perplexity is trying to
Speaker 1:disrupt the But, are you looking at any of space without
Speaker 2:being too competitive?
Speaker 1:Is there anything interesting there that you've seen or or or heard rumblings on the other side of the of the fence?
Speaker 7:I can't speak to what's competitive Sure. With I I you know, they're my LP.
Speaker 1:Yeah. Course. Yeah.
Speaker 7:Speak for their business strategy. What I will say is when you when you run a firm that's got a name of another company on it, my guess is the Google Ventures, GV guys have this too. Yep. Every pitch that's like, we are gonna be the Bloomberg for x lands on my desk.
Speaker 1:Yep.
Speaker 7:And maybe not everyone, but many of them do because they're like, and how amazing would it be to also have Bloomberg as an investor?
Speaker 1:Yeah. Yeah.
Speaker 7:Almost all of them seem to misunderstand to me what the value of the Bloomberg terminal is.
Speaker 1:Sure.
Speaker 7:Because it packages data
Speaker 1:Yep.
Speaker 7:Community with a messaging system, outside in perspective news, etcetera. I mean, that's just some
Speaker 1:of it. So much stuff.
Speaker 7:It's more than just let's display some data. So everybody who's trying to disrupt, I think, in for a surprise when they realize what an ecosystem it is.
Speaker 2:Yep. I I think this happens constantly, especially in media. People see a media product. They like it. They don't understand why it's successful.
Speaker 2:Try to Totally. engineer it. But if you don't understand the why, you're never gonna be
Speaker 7:But can I ask you guys though? For you, you tried before. What's your hypothesis on your why of why this has been so successful for you?
Speaker 1:The main one is that most people in tech media have done it part time historically and we decided to just kind of burn all of the ships and make this the full time thing. We got some great advice from David Senra, the host of the Founders Podcast, another full time media creator. And he basically just said, you guys have something that's that's working. You should go 10 times harder at this. And what's
Speaker 2:interesting also enjoyed it a lot.
Speaker 1:We loved
Speaker 2:We liked it talking about business Yeah.
Speaker 9:We loved
Speaker 2:it. Was kind of the foundation. But but yeah, the idea that there's of Yeah. There's a lot of technology podcasts. There's a lot of business podcasts.
Speaker 2:If you actually drill down and you look at how many people are actually full time
Speaker 1:Yep.
Speaker 2:Just making media, it's very, very small.
Speaker 1:It's pretty small.
Speaker 2:And the nature the other thing is the nature of by taking something way more serious than anyone else, it can sort of morph and evolve in the way that the show has Exactly. From just us two and a printer.
Speaker 7:My my viewers look on this is it's it felt I'm obsessed with Hamilton for a variety of reasons.
Speaker 2:One of
Speaker 7:the reasons I'm obsessed with it is nobody would have said one of the great media properties of the last ten or twenty years would be a musical. Yeah. Totally. And so it defied the genre through intensity and seriousness. And you feel immersed in a world.
Speaker 7:And like before the show, they used to go out on the street and do some little ditty or something like that. Yep. Oops. My camera just froze. Okay.
Speaker 7:There we go. And and you guys have that same kind of immersion. I teach this class at Berkeley on the structure of the media industry. I will be inviting you as guest speakers.
Speaker 1:Been amazing. We'd love that.
Speaker 2:Let's do it.
Speaker 7:Not when you're live.
Speaker 2:You can I grew up I grew
Speaker 7:up in Berkeley?
Speaker 1:Yeah. Did.
Speaker 7:Fucking the other thing that you've realized is it's cheap to start a media company. So as long as you don't get too big for your britches and figure like a venture backed company, your financial aspiration, maybe this is yours, is to create one of the most financially successful businesses in the history of capitalism, which is in VC, as much as an $80,000,000 exit along the way can be magical for everybody involved. That's the hope. Yeah. Yeah.
Speaker 7:You know, is that you can produce something wildly valuable and make some money.
Speaker 1:Yeah. Yeah. Exactly. Yeah. This is super fun.
Speaker 1:This is great. Well, I'll to have you back.
Speaker 2:Congratulations. Congratulations. It's
Speaker 7:Thank you. I appreciate what you're doing. Keep us all immersed in it. We
Speaker 2:will. We will. Come back soon. Never gone 75 times. Yeah.
Speaker 2:We'll hit it. We'll we'll wait till
Speaker 1:after the show Two down 73 more to go. 73 hits.
Speaker 7:Done. I'll come in and bang on that.
Speaker 4:Have a
Speaker 2:good one. You're the man.
Speaker 1:We'll talk to
Speaker 7:you later.
Speaker 2:Cheers, Roy.
Speaker 1:Bye. Up next, we have the founder of Metropolis, Alex Israel. He's in the studio, but really quickly, let me tell you about Wander. Find your happy place. Book a wander with inspiring views, hotel great amenities, dreamy beds, top tier cleaning, and twenty four seven concierge service.
Speaker 1:It's a vacation home, but better. Welcome to the stream, Alex. How are you doing today?
Speaker 9:Good. How are you guys doing?
Speaker 1:We're doing great. We've been having an awesome show.
Speaker 2:What's it like to land on the the CNBC list?
Speaker 1:You guys are on there. Right? You guys are on there. Congrats.
Speaker 2:I mean, that's gotta be your guys' biggest accomplishment ever. There's nothing there's tops that. It's
Speaker 7:not weird.
Speaker 2:No. No. I'm kidding. It's all I mean, any time, you know, I know the CEOs that land on these lists, they're like, you know, they they'll post about they'll post about it, but it's like you get back to work. Yeah.
Speaker 2:Of course.
Speaker 9:Yeah. It's, look. It's flattering. I just like being in the company of, you know, OpenAI and Yeah. It's good.
Speaker 9:But, yeah, you just gotta get back
Speaker 1:to work. Yeah. The the CEO to be like, you know, normally, CEO say job's not finished. In this case, job's finished.
Speaker 2:No. We're done.
Speaker 1:We're done. Done. This was the whole goal the whole time. The whole goal. And now we can retire.
Speaker 9:It's kinda like an exit,
Speaker 1:but better. Yeah. It's definitely better. It's definitely better. Yeah.
Speaker 1:I can pay my college
Speaker 2:tuition bills, but, you know, you can send that to a family member and maybe they'll be impressed. You
Speaker 1:know? Yeah. Yeah. You'll get some text messages. Anyway, can can you kick us off with an introduction on on on the structure of the company and what you guys are building?
Speaker 1:Because it's super interesting. And I I I know we can go a bunch of different directions, but I'd love to get your kind ground setting
Speaker 9:Yeah. Of course. So, you know, traditional, in a lot of ways, startup story. Founded the company in 2017
Speaker 1:Mhmm.
Speaker 9:And now are one of the fast growing payments companies in The United States. We talk about ourselves externally as an AI company for the real world, but it's all about how you leverage computer vision and artificial intelligence to create next generation payments and commerce everywhere you go, whether it's a retail environment, a car wash, or a gas station. How do you just walk in or walk out, or in this case, drive in and drive out?
Speaker 1:That is fascinating. Talk to me about the strategy of actual, building the business and, acquiring assets and and and actually getting like, the go to market motion is different here. Right?
Speaker 9:Yeah. It was very different. I mean, look, we started very, you know, I don't know, stereotypical. We raised the, you know, I guess, but 20,000,000 seed financing, $40,000,000 series a. We hit the Wait.
Speaker 2:$20,000,000 seed in 2017. That that that that's more than bigger than a mango seed Yeah. Which which started to become popular a bit later. I don't know. Is that a water watermelon seed round?
Speaker 2:What what what what was the catalyst there? You just you'd had a bunch of experience in the space and and so people had a lot of confidence in you, or why did why did you need 20,000,000 at the time?
Speaker 9:Yeah. It's a good question. I don't know. I guess serial tech entrepreneur. Mhmm.
Speaker 9:I don't know. My last series a in my last company was 3,500,000.0, and I, you know, I thought I was rich, you know? Yeah. And then, you know, a $20,000,000 seed financing. But look, we knew we were tackling you know, the vertical that we entered was mobility, and we wanted to go after the parking industry.
Speaker 9:And we wanted to deploy technology in the parking industry, and we knew that there were a number of companies, whether it was Standard Cognition or Amazon Go, that were leveraging computer vision to create these next generation experiences, and we knew it would take a lot of capital.
Speaker 1:Mhmm. We knew
Speaker 9:it would take a while a while to penetrate the market. So we wanted to make sure that we had the capital in place to to really go after the market.
Speaker 2:Talk about your position in in parking today. It sounds like you're you're thinking about other categories already. At what point did you decide that you could be thinking about other applications of the tech and infrastructure?
Speaker 9:Yeah, it's a good question. You know, I'd say, so after our series a, I would say we hit product market fit and unit economic fit really quickly. I'd say the problem was we hit a wall with our go to market. And that was, you know, at the time, we were scaling our technology to a number of large asset owners across The United States, and we'd effectively knock on their door, ask to take the keys for the parking experience to their $200,000,000 development, and they were like, cute startup. Come back in fifty years.
Speaker 1:So
Speaker 9:we realized we needed a different go to market motion. So we shifted strategies, and we invented what we qualified internally as a GBO, which was this idea of a growth buyout. Could we raise venture capital dollars, and could we acquire old world businesses? So we started rolling up old world parking operators that are the cost plus staffing agencies that were EBITDA positive that run parking across The United States. And we kept rolling them up to a point where now we're the largest parking operator in The United States.
Speaker 1:That's amazing. What, yeah. Yeah. But what is the structure of the of the parking market generally? I feel like, I I live in Pasadena.
Speaker 1:When I drive around, some of them are city owned, some of them validate, some of them don't. It feels very fragmented. It I I couldn't name one unified brand, but what is the is the structure of the parking owner market as fragmented as I perceive it to be?
Speaker 9:Yeah. Completely. It's I mean, it's as fragmented as the real estate owner market. Mhmm. Right?
Speaker 9:People that own real estate own parking. And there are, you know, hundreds of thousands of real estate owners from a class a perspective all the way through an airport across The United States. And we deploy our technology to facilitate that type of seamless experience where a consumer can just drive in
Speaker 1:Yeah.
Speaker 7:Get a
Speaker 9:text message when they arrive and get charged when they leave.
Speaker 1:Yeah. Is that historically just because there's no economy of scale like there is in in real estate, or is that just because the asset class is so big that you can't possibly own it all?
Speaker 9:It's just so sexy. You know? Everyone's driving over to, like, parking.
Speaker 1:Yes. Yes.
Speaker 7:Know, it's like no.
Speaker 9:It's like the last bastion of non institutionalized real estate in The United States.
Speaker 1:Yeah. Yeah. You're right.
Speaker 9:And it's everywhere. It's 15% of the surface area of our cities.
Speaker 1:Yeah.
Speaker 9:And for us, it was the touch point.
Speaker 1:Yeah.
Speaker 7:And to
Speaker 9:your comment earlier, we realized that if we can roll up parking and we can deploy a seamless seamless payment product across parking, then we can move into gas stations and car wash and quick serve retail. And then we can move past the car and into the store.
Speaker 1:Yeah. Can you talk about the, the kind of longer term vision for city parking. I feel like there's with autonomous cars, people are excited about maybe reclaiming some green space. Whenever I see a big city and there's there's just, like, one flat parking lot, I'm like, that would be way more efficient if it was, like, three of underground parking and then a massive building on top with some mixed retail and
Speaker 2:some Yeah. And the
Speaker 1:spot and this
Speaker 2:the autonomous cars, people like to say, oh, when we have autonomous cars, we'll need less parking Mhmm. In cities. And and and I can see that in some way. But at but at the same time, I'm not excited to spend every day in Waymo's, effectively taxis. I am excited to have my own autonomous car.
Speaker 1:Mhmm.
Speaker 2:And the idea that I would drive into the city and then my car would just be driving around all day. Like, it's gotta go somewhere while I'm while I'm podcasting. Right? Like, it's know, so so it's gonna be parked somewhere. And so I think this sense that autonomous driving is gonna eliminate the need for for parking is is, or or certain you know, some some of the parking in in cities is maybe off base?
Speaker 9:No. Look. I think it's an interesting question. I mean, when we founded the company, we spent a lot of time thinking about the future of autonomous vehicles. And to your point, cars are not gonna circle the block endlessly looking for their next job.
Speaker 9:They're gonna get off the road and back onto the road as quickly as possible. And that's the conversion of parking from parking lot to mobility hub, where you can facilitate the cleaning, servicing, charging, and deploying of vehicles. I mean, at this point, our underlying technology enables kind of seamless, I would say, integration or connectivity between an autonomous vehicle and old world infrastructure. I mean, at this point, we're interacting with millions of Americans every single day that are on our platform or interacting with our locations. And I think at this point, we're onboarding 50,000 Americans every single day that are signing up for the time with Metropolis.
Speaker 2:Yeah. Yeah. The idea, you know, you're not gonna a Waymo is not gonna have, like, a a a humanoid robot in it that presses the parking ticket, you know, button when it's coming in and and then is, like, feeding the ticket back in. It obviously would just happen, you know, if Metropolis can be that hub for for autonomous vehicles, that it makes makes a ton of sense.
Speaker 1:Yeah. Talk to me about, the, like, the evolution of financing. You're obviously using a lot of venture capital, but I imagine that at a certain point, you need to interface with private equity firms or banks or debt providers. How can you get creative with the different structuring financially on some of these larger deals? And can you give me kind of like a one zero one zero one on what it what it takes to get a billion dollar deal done these days?
Speaker 9:Yeah. I mean, we did you know, the last deal was a 1,800,000,000 series c. Amazing. Huge.
Speaker 1:Huge.
Speaker 9:Yeah. Listen. We took an old world, you know, 100 year old company that was publicly traded private. Yeah. And yeah.
Speaker 9:Look. It's if you look at our cap table, it's exactly that. It's venture and private equity in the same rounds.
Speaker 2:Mhmm.
Speaker 9:So last round was Eldridge, Vista, three l, Tomasek, Vista, BDTMSD. And, like, you normally don't find all of those players in one
Speaker 2:Party round.
Speaker 9:Capital. But, yeah, look, I think that you guys talk about this more than I do, but the capital markets operate very clearly in these very set boxes. It's credit, it's private equity, it's growth. And we kind of broke through that with an entirely different strategy, which is how do you take next generation technology and artificial intelligence and start acquiring old world businesses to scale into the market even faster. But in the context, to your question, in the context of our business, it's structured to a great extent like any Series C venture company would be structured.
Speaker 1:Talk to me about what the the communications challenge of taking over a 100 year old company. It feels like you're fortunate that you don't have the the stench of maybe like, oh, we're going to buy and lay everyone off. But it is change management. It is new structure in the organization. I'm sure there's some communication that you have to do when you buy a company.
Speaker 1:What has that been like and what are kind of the best practices?
Speaker 9:Yeah. It's a great question. I mean, look, I think that we went from a 200 person company organically to a 2,000 person company with our inorganic acquisition and then to a 23,000 person company with employees in 400 cities. So, yeah, there's massive change management. There's massive internal communication protocols.
Speaker 9:But I'd say and foremost, it's like how do we put our employees and our team And you're right. We were lucky because this was not a turnaround. This was not a structure where we're looking for cost synergy. Metropolis and this strategy of taking these old world companies private was all about revenue synergy. It was how can we drive more revenue and more value, not only to real estate owners, but to our employees and our team members.
Speaker 9:So it's been exciting. And what we found is it's really interesting. You see cultural friction on both sides. You see cultural friction in the engineer that's worked at Amazon for ten years that now works for Metropolis, and then you see friction on the parking attendant. But you find people that are really excited about building a hyperscaler and really excited about how they can leverage and build on the existing infrastructure of this 100 year old company.
Speaker 1:It's great. Well, thank you so much for stopping by.
Speaker 2:This is great.
Speaker 1:This is fantastic.
Speaker 2:Come back on when you're, when you have a a good reason for us to hit the size gong.
Speaker 1:Yeah. We'd love you'll have,
Speaker 2:I'm sure you'll have many more in the near future. This is great.
Speaker 9:Great. Looking forward to it. Thanks for taking the time, guys.
Speaker 1:Talk to you soon.
Speaker 2:Cheers.
Speaker 1:Bye. Next up, we have Andrew Huberman joining the stream. We'll bring him in in just a We have some breaking news too. Scott Wu has posted about the new model from OpenAI o three price drop makes it 15 times cheaper than g t GPT four thirty two k, the state of the art model from two years ago. Meanwhile, the number of use cases is probably up 1,000,000 x.
Speaker 1:Kudos to the OpenAI team for dropping the price. So congratulations to everyone over there. And welcome to the stream, Andrew. How are you doing?
Speaker 6:Great. Great to see you.
Speaker 1:Thanks so much
Speaker 2:for joining. Yeah.
Speaker 1:What's new in your world?
Speaker 6:What's new? Goodness. This week, we have a big episode of the Huberman Lab Podcast out with the current NIH director, doctor Jay Bhattacharya, who's a MD and a PhD. He has a unique background because he has a background in medicine, obviously, the MD, but he also has a background in economics.
Speaker 1:Yep.
Speaker 6:And, incidentally, did his undergraduate, master's, PhD, and medical school training and then was a professor of medicine at Stanford.
Speaker 1:So Stanford.
Speaker 6:You know, he's he's Stanford the whole way. And as NIH director, right, he he holds a ton of power over what happens for the future of basic and, clinical research, and he looks at all that through the lens of an economist, but mostly through the lens of a, you know, public health official. So it's a very unique, perspective, and folks on x will recognize James.
Speaker 1:Yeah. Yeah.
Speaker 6:Vocal. I don't wanna speak for him and and label. We have to be careful with labels, but
Speaker 1:Totally.
Speaker 6:Anti lockdown. I don't know.
Speaker 8:Yeah. You know?
Speaker 6:Know? Not not a huge fan of the lockdowns for most people. Right? He he does say that there are certain populations that he felt should have been, kept indoors, but other other folks probably, in his view, should have more options.
Speaker 2:Yeah. Well, it's a long episode. I wanted to basically get a preview of it. You guys focus on a couple of things. One, how to fix the issues with science.
Speaker 2:And two, the importance of funding research, both sorry, basic research and then applied research. So why don't we kind of cover a couple of those
Speaker 1:different areas and My question was, like, the narrative right now is that, research funding is being cut, like, immensely. And I was wondering if you got a feel for how severe the cuts are. Is the narrative overblown? What is the balance of cuts between applied and basic research? And then we can kind of go into some of the implications of that.
Speaker 6:Sure. Okay. So there is an an upcoming vote in congress in September, I believe, and it's on the table to cut the overall budget for research for NIH by 40%, four zero.
Speaker 1:That's huge.
Speaker 6:Which is huge.
Speaker 1:That's huge.
Speaker 6:I want the the budget for research at NIH, there there are multiple dimensions to NIH, and I don't wanna get lost in the weeds of it. It's a you know, NIH is something I'm very familiar with. I was on grants panels for, you know, over a decade. My lab was funded by NIH. We could go really deep into the weeds, but let's just keep it pretty simple.
Speaker 6:NIH funds basic research, which is research that it's not specifically geared toward understanding the or trying to solve a particular cure or treatment for a disease. So think all everything we understand about cell biology, everything, but much of what we understand about cell biology
Speaker 2:Yeah.
Speaker 6:Was it was because of NIH funded research into the functioning of the cell over the course of, you know, fifty or more years, and that led to important implications for treatments and cures for cancer. We don't have a quote unquote cure for all cancers, but many cancers now can be cured.
Speaker 2:And to be clear, these are noncommercial this is like noncommercial research. So things that a candidate patent. Right? Yeah. We cover a lot of Right.
Speaker 6:Cannot be patented.
Speaker 7:So Yeah.
Speaker 6:Basic research is, you know, a laboratory wants to understand how cells work, how neurons work, how the immune system functions, gut brain access, studies on, you know, how stress impacts health, sleep, etcetera, then the applied work is also funded by NIH. So clinical trials are funded by NIH. This is an enormous portion of the overall budget. Mhmm. The exact division between basic and, clinical trial funding is hard to demarcate, but let's just, for sake of this conversation, just agree because it's true that most of the basic research and clinical trials that are run-in The United States are funded by the NIH.
Speaker 6:The NSF is a separate entity. Right? But NIH's its specific goal is to improve the health and longevity of American citizens, and by extension, the rest of the world. Right? Because Yeah.
Speaker 6:It it is fair to say that while there are excellent, you know, research funding bodies in The UK and Germany and Switzerland and all over Asia and around the world, that the NIH, when people say it's the crown jewel, it's the one that's devoted the most billions of dollars Mhmm. To basic and applied research. And it's no coincidence that the majority of Nobel Prizes, has in physiology and medicine, and chemistry and related fields have come from work that was either initially seeded by or certainly supported by the NIH. So you can't overstate the importance of NIH funding basic and applied research.
Speaker 5:Mhmm.
Speaker 6:That overall budget is facing a 40% cut in September. Now, you know, I'm hearing two things out there. Right? I I wear many hats. One is my lab ran on NIH money.
Speaker 6:It no longer depends on NIH money. They're, I'm a podcaster, so I have the ear of folks who are like, this is really scary. Right? That it gets very political because the current administration seems to be taking a more, like, they're gonna revise the way that NIH is structured potentially, 20 plus institutes down to eight. So all of it looks like downsizing.
Speaker 6:There are lot of people who are terrified about this. Okay? There's another camp that I hear from a lot, and I can't even say particularly on x, and I wanna be very clear. This camp doesn't always lean right. It's it's pretty even across the board that are saying, wait a Why are we giving so much money to these universities to do research
Speaker 1:Yeah.
Speaker 6:From our tax dollars? And I know this will upset people who are very science minded as I am, who care about science, but they're saying, why why are we doing this? Right? Some of these universities, not all, but some of them, Stanford, Harvard, Yale, Princeton, UT Austin, etcetera, the private universities often, although some public ones too, have very large endowments. And they're thinking, why are we funding so much of this work?
Speaker 6:Maybe these tax dollars should go elsewhere. There's another key issue, and this came up during the discussion with doctor Bhattacharya, which is there are many, many people, okay, I'm just who voiced to me that they don't want to give their tax dollars to basic or applied research at all. Okay? This is a large and growing crowd because they feel that there needs to be, for lack of a better way to put it, some truth and reconciliation. Right?
Speaker 6:They want two things acknowledged, and I've I've and I've actually heard this from many of the let's just say that the highly recognizable names in the in the world of Silicon Valley super tech or or founders and funders and Yeah.
Speaker 1:Sure.
Speaker 6:And investors, etcetera. And those two things are the following. One, they want the NIH to acknowledge or CDC and or others in government to acknowledge that there were, in their mind, failures during the pandemic, in particular, lockdowns that impacted the non laptop class. Okay? We're talking about janitors, staff, teachers, kids, etcetera, that basically had to halt their work and their income.
Speaker 6:They're they're they're pissed off about this, right, that no one's kind of acknowledged this. The other thing that they're very angry about is the lack of acknowledgment from the scientific community that the science community makes errors. Sometimes errors that for instance, in the field of Alzheimer's research I wanna point out not all the work in the in the field of Alzheimer's is bad. Much of it is is very solid or or excellent. But they they are frustrated by some recent, kind of unveiling of the fact that there were findings that later were found to be fraudulent, basically, and that it was never checked up on.
Speaker 6:And then that opens up a whole discussion, which I also discussed with doctor Bhattachary about what's being done to solve the so called replication crisis. So they're upset about the about the public messaging around health and science. Right? They would have preferred, it sounds like, that people in government say, hey. Listen.
Speaker 6:You know, we have a virus that we don't understand, and we we have ideas about what might control it, but we don't fully understand this. So it was very iterative, and a lot of people are pissed off. Kinda like when you're, you know, 15 or 16, and you're being told you can't stay out late, and then your parents are staying up late, or, you know, you've or, like, we had governors who were saying you had to wear a mask, but then were taped in fancy restaurants on the Northern Coast, you know, at restaurants. And, like, much in the way that a teenager goes, wait a Like, you smoked pot in college, and you're telling me not to smoke pot. Like, this there's a logical flaw here, and we at least need to talk about it.
Speaker 6:So there's this kind of notion that, that this this isn't my stance necessarily. I'd be happy to share my stance, but that the scientific community has kind of cloaked its errors.
Speaker 1:Yep.
Speaker 6:And and so there are a lot of people in the general public who are like, don't give these universities a dime. Let them dip into their endowments. And the last thing I wanna say about that is not every university has large endowments. Yeah. Most public universities do not have large endowments.
Speaker 6:It's also true that universities don't like to spend their endowments.
Speaker 1:Mhmm.
Speaker 6:And the typical way that they hide behind, their their endowments or endowment spending is to say that money is earmarked for other things. Right? So it's which is not to say that it isn't. But and then the the last thing, and I know I'm going kind of fire hose here, but I wanna make sure this comes out, is that that the big issue that is really on the table as well is this notion of indirect costs.
Speaker 1:Mhmm.
Speaker 6:You guys are finance guys. So, basically, a laboratory get might get a grant of a million dollars across four years, so $2.50 a year for four years. The university then gets what are called indirect costs. They get, let's say, 500 k, typically. It's anywhere from 300 k on the million to up to 750 k on the million.
Speaker 6:There are a few cases of even more than that. The so called indirect funds that take care of administrative costs and the the basic cost of doing research. And earlier this year, the Trump administration said we're cutting that to 15% across the board for all universities. And that was very prominent on x because Elon retweeted it and a number of other people retweeted it. And I would say, while the indirects have been very controversial, I I would just personally it's my view.
Speaker 6:K. This is my personal view, is that a a severe cut to the indirects, while on the face of it might sound good, that's going to disproportionately hurt the public schools without large endowments. Okay? Because they don't have money to dip into. And, you know, something more in the range of 30% seemed reasonable to me based on my understanding of what those funds are used for.
Speaker 6:But, historically, there have been some challenges with indirects. You know, there were universities, I won't mention which, caught for spending some indirects on things that were unrelated to the science, you know, perhaps keeping the lights on in the English department. That's typically not the case now. It's for disposal of radioactive waste. It's for, yes, generators.
Speaker 6:It's for painting the walls of the building, but it's not for making, you know, a lavish lifestyle for the administrators. Right? If administrators have a lavish lifestyle, it's presumably through some other mechanism, not IDC.
Speaker 2:Yeah. There were some example. I don't know if it was UCSF or some school where they had like a multi $100,000,000 administrative budget and I think people really wanted to push on that.
Speaker 1:Yeah. And
Speaker 2:but I I I think your concern is like, obviously, there's like this massive trust issue between the public and new parts of the administration and science. And how do we rebuild that trust without destroying the entire system? Right? Is that is that kind of
Speaker 6:You nailed it. And and I I would like to just highlight in the backdrop of all of this, there there are is one very major emotional issue that I I'm gonna catch a lot of heat for this, but I don't really care anymore. Know? And we're on x.
Speaker 2:So Yeah.
Speaker 1:You know,
Speaker 6:a lot of I put out a a a post recently that said, hey. Listen. I I I'm I'm very concerned about this 40% overall cut as the most severe, damage to to science. We're not talking about allocation. We're not talking about indirects.
Speaker 6:We're you know, we're we're not talking about what's gonna happen with that with that body of money. We're just accept this 40% cut.
Speaker 2:Mhmm.
Speaker 6:And I'm very concerned about this, but I don't wanna talk about, for instance, the fact that federal funding to Harvard or to Columbia has been frozen. And a lot of people said, well, why not? I have a lot of friends at Harvard Med and at Columbia and elsewhere, and they're like, wait. This is why why won't you talk about that? Well, that's actually a different issue.
Speaker 6:Right? The reason that money has been frozen is that in the eyes of the administration, they are Harvard and Columbia are violating civil rights laws. Until that's resolved, there's no discussion about NIH to be had. It's not an NIH issue. It it funnels through NIH money.
Speaker 1:Yeah. People are tying the issue even though Yeah. Just because it it has some of the same buzzwords. Yeah. That's interesting.
Speaker 1:I I have a question about the 40%. I I mean, there is a world where where, like, where what becomes important is the ranking of what gets cut. And so my question is, like, the within the basic research that you're seeing, what should we be fighting for hardest to keep? What basic science or applied science research are you most optimistic about going forward? Because we saw this with GLP-1s.
Speaker 1:I mean, I'm sure CRISPR, These stuff lay this stuff was NIH funded at one point. There was a ton of research, and then we get this big boom, like but it's ten years later. What's on the frontier? What are you most excited about, and what should we be fighting for? Let's keep the funding there no matter what.
Speaker 6:Yeah. Great great question. In fact, the most important question. So regardless of whether or not this 40% cut happens, if it's less, if it's kept the same Mhmm. A couple of things.
Speaker 6:of all, despite the fact that NIH funds basic research and that many laboratories, including my own for for many years, focus on basic research, like, how does the visual system work? We always had an eye every laboratory has an eye toward, you know, what what the translational implications could be. Okay. So we were actively involved in trying to solve, you know, blindness due to glaucoma even though we were focusing on some basic questions.
Speaker 1:So Sure.
Speaker 6:I think it it it's a statistical issue. If you step back and you say, okay. In the field of, let's just say, vision, my my former field, what is the leading cause of blindness? Cataract. But you know what?
Speaker 6:You can fix cataract. You can slide out the lens and you put in a new lens. That's being done now. Great. What's the leading cause of blindness?
Speaker 6:More than seventy million people worldwide. Glaucoma.
Speaker 7:You can
Speaker 6:test for eye pressures, but once the cells in the eyes start deteriorating, people go blind, there's no recovering those cells.
Speaker 1:Mhmm.
Speaker 6:So you could say, wow. So okay. So let's take the top let let's take the the statistically, the the the the the top causes of blindness, and let's let's fund those. Okay? Retinitis, pigmentosa, etcetera.
Speaker 6:You could do this for pretty much any field. So in the field of of brain health, you'd say, okay, dementia, you'd say, major depression, you'd say a stroke, you'd say, you know, I'm gonna piss off some people because I'm not gonna mention their their particular suffering, you know, here. But it's not hard to find Parkinson's. Right? Yeah.
Speaker 6:Yeah. MS. I mean, it's not hard to know what the problems are to tackle. The problem is deciding what the targets are.
Speaker 1:Sure.
Speaker 6:And as you mentioned, like, with CRISPR, I mean, in in many ways, it was a fortuitous thing. Right? Down in the lab was worrying on bacteria. I mean, it's you know, it's very hard to predict what basic research is gonna lead into these different areas, but we we know what the critical areas are. So I'm not trying to dodge your question.
Speaker 6:I do wanna say that the emphasis from MAHA on chronic disease and chronic health issues, I think, has concerned some of the people in the scientific community because listen. I, as a podcaster that covers science and health, will be the to say that if you're not sleeping well, your mental health and physical health is not going to be good. You can miss a few nights sleep, but if you're chronically sleep deprived Yeah. You're sicker than you normally would be. If your gut health isn't proper, if you're not getting exercise, if you're not getting sunlight, if you're not doing these things, of course.
Speaker 6:Right? But I think that people who are in the the kind of hardcore mechanistic science community are like, great. We're all gonna strive to do those things, and we should, but not at the exclusion of figuring out signaling pathways that are vital for, like, the GLP ones are a beautiful example. Right? This peptide acts at the level of the brain and the gut to make people feel more full.
Speaker 6:It also, by the way, shut down the debate as to why people are fat. It's because they eat too much. Right? Is it they eat more than they burn. Remember if we used to argue about it?
Speaker 1:Yeah. Yeah. Totally.
Speaker 6:No. No. GLP one silenced that. It's
Speaker 1:a good one. That's really true.
Speaker 6:But Now are they eating too much because of a hormone issue related to having too much fat? Maybe there's some depression. If you sure. Like, I fully acknowledge, like, I'm not trying to be completely insensitive, but, like but we we isolated the problem by understanding that this peptide discovered in heal the discovery of this is worth spending two sentences on.
Speaker 1:Please. Yeah.
Speaker 6:Gila monster, a reptile that doesn't need to eat very often, makes a lot of this peptide that it turns out is manufactured by humans too, and
Speaker 5:if you increase your pounds,
Speaker 6:it's cold in humans, you know, you're not hungry anymore. And so, I think that, you know, the guy studying the Gila monster, I doubt was thinking about curing obesity
Speaker 7:Mhmm.
Speaker 6:But there you go. Now, and and of course, there's a debate to every one of these things. No medication should ever replace lifestyle factors. Right?
Speaker 1:Yep.
Speaker 6:There are many I think we've sometimes fail as healthy fit people. We fail to understand that lifestyle factors are very hard for people to implement, even if they have copious amounts of disposable income
Speaker 7:Yeah.
Speaker 6:And some free time. It's it's just tough. Yeah. It's just tough. It's hard to do.
Speaker 6:And so I think that the the emphasis on nutrition and exercise is wonderful. I think I I don't think anyone on either side of the political debate would argue that MAHA in principle, make America healthy again, isn't a great thing.
Speaker 1:Yeah.
Speaker 6:I think what they probably would appreciate hearing, now I'm speaking for kind of the more science mechanistic biology minded folks, they'd probably like to hear a little bit more about, hey, you know, they're probably signaling pathways in the brain that are relevant to, you know, to depression, that maybe a a next class of antidepressant drugs are probably good. I don't think anyone would say there's no need to develop antidepressant drugs. We'd probably take too many of the ones that don't work and have too many side effects, but as a country but when so when you say what are the most important things, what we really need is a is a very rationally grounded planning committee, a sit back and say, you know what? We're gonna put x number of dollars towards x number of dollars towards that, x number of dollars towards this. And this is where I think doctor Bhattacharya really, shined on the podcast.
Speaker 6:He said, and I would totally agree, and I got I have already my phone's been blowing up with some anger from colleagues about this. Much of the work that's funded by NIH, here's the dirty secret, is already completed. Because they tend to fund things that are very certain to be completed. And so people put forward grants based on work and preliminary data showing, I can do this, and it's already kinda worked out, then they use the money for the next iteration. This is the dirty secret of every NIH funded lab.
Speaker 6:And it tends to favor a kind of pedestrian more pedestrian science. Then they use foundation money, and they use other sources to kinda do the the high risk stuff.
Speaker 1:Mhmm.
Speaker 6:But if you were to look at, like, one of the the more impressive funding bodies in science, like the Howard Hughes Medical Institute, right, gives the equivalent HHMI folks, as they're called, never they always say it's not that much money, but let me many we can do the test. We can take away their money, and we can see how well they do or don't do.
Speaker 1:They don't like
Speaker 6:doing that. Yeah. It's it's like being on academic steroids. Right?
Speaker 2:Yeah.
Speaker 6:The equivalent of three grants per year, basically, NIH grants per year. Yeah. And more money translates to when when it's excess money. Mhmm. I know that word excess money, you know, scares investors, especially if they're taxpayers.
Speaker 6:But if that money is being used to fund really, like, really bold hypotheses, like, it's my opinion that every single peptide, not just GLP one, every single peptide shouldn't be getting tested in the gray market of, like, gyms and, like, biohacking.
Speaker 1:That's Yeah.
Speaker 6:Frankly, that's bullshit.
Speaker 2:Yeah. And isn't the reason that there we don't have good studies on a lot of peptides is it's not profitable to study them because they're effectively naturally occurring, and you can't patent as, like
Speaker 7:Is it
Speaker 6:too late?
Speaker 2:Correct there?
Speaker 6:Like like BPC one five seven. Right? You hear about that all the time is, will it accelerate healing? You know, the animal studies are solid. There's no human studies.
Speaker 6:My good friend Peter Atia is like, I'm not gonna touch that stuff. There's no clinical data in humans. And the rest of us are like, well, I take it and it works, and there's there's no reason for a for a drug company to take it. I'll take it, transiently for for if like a like a joint
Speaker 2:issue. But the the core issue and and I
Speaker 6:patent it.
Speaker 2:There's no a Yeah. I've I've I've taken it too. I've benefited from it. I recommended it to John a couple weeks ago. He had a he had an injury.
Speaker 2:I just said, hey, I'm I'm not gonna like, this is not something I'm gonna take Yeah. You know, weekly for my entire life but in in certain instances.
Speaker 1:I mean
Speaker 2:But but break down that specifically that you're saying because it's because it's effectively science, there's not there's no real ability. Would would a drug company have to create some variation of it in order to patent it? Is that is that
Speaker 6:Yeah. In fact, and I here, I'm gonna catch heat from everybody, but, you know, the pharma companies that make GLP ones mean, most people have realized that GLP ones are very expensive, and the dosages that they're typically prescribed, people get some discomfort.
Speaker 1:Mhmm.
Speaker 6:And so the new thing is people get it compounded at a compounding pharmacy, and they're micro they're micro dosing GLP ones. Mhmm. I the number of women that I know who are micro dosing GLP one, in service to the spring and summer, outrageous. Right?
Speaker 2:Yeah. Outrageous.
Speaker 6:Yeah. It's outrageous. And and the idea is that it's GLP one is a good example. I mean, again, insulin's a peptide, you know, but but there are many peptides. Like for instance, I'm very excited about this peptide pinealine for for sleep.
Speaker 6:Right? And it's for some other properties too. But there's no reason why a drug company would go patent pinealine. They're busy patenting drugs like the recent class of drugs, the Doras. This is an interesting story.
Speaker 6:Work on on a peptide called hypocretin. This peptide is involved in generating wakefulness. It's also in the feeding pathway, and there's a new class of sleep drugs that suppresses the wakefulness pathway as opposed to making you more sleepy, so lower abuse potential. The DORAs have been released. Right?
Speaker 6:They maintain the the architecture sleep pretty well compared to other sleep drugs like Ambien, etcetera. Here's the issue. They're about $325 a month. So for a lot of people, that's prohibitively expensive, and they're patented.
Speaker 2:Yeah. To put it in context, that's that's a luxury gym membership. Yeah. Right. You know, it's which is
Speaker 6:a Pinealine probably cost you, and I'm not suggesting people take Pinealine. I'm not a physician, so talk to your physician and then ignore him or her. If you choose, don't don't do what don't do that on my on my suggestion. But, you know, it costs you about $15 a month. Right?
Speaker 6:And and, you know, it's it's for for me personally, it's allowed me to I get two and a half hours of REM sleep a night in a six hour sleep bout. So I've shortened my sleep bout to about six hours a night with a lot of deep sleep. And the pinealine, is it completely safe? Reasonably, but we don't know. We don't have clinical trials.
Speaker 6:Now, I'm willing to run that experiment on
Speaker 7:me. Yeah.
Speaker 6:But are you willing to run that experiment on you is the question, and that's where it gets down to personal freedoms, and and that's a know, I don't wanna cover too many things here, but the I will say that Robert Kennedy has been pretty vocal about at least before the election, about wanting things like peptides and stem cells and supplements to be more widely available. The truth is they're pretty widely available now. Mhmm. And I will put an asterisk on stem cells. I know a very prominent public facing physician who is almost paralyzed permanently from a stem cell injection into the disc of his back.
Speaker 6:I talked to a neurosurgeon friend who ultimately saved his life, by the way. This is a well known story within the the the wellness community. And he said, yeah. You know, the discs can't accept stem cell injections. But if you go down to Mexico or you go out of country and you say, you know, my back is hurting, they'll inject stem cells into the disc of your back.
Speaker 6:So is this to say that stem cells are bad? No. They're not ready for clinical use yet. And The United States has been very careful about things like this because before they were careful, there was a clinic in, down in Florida that injected some stem cells into the eyes of people with macular degeneration who were worried about going blind, and guess what? They all went blind right away, permanently.
Speaker 6:So I do want any discussion about peptides and these kind of things. When you get into the realm of stem cells, it starts getting to be a serious matter. So I don't wanna give the the impression that I'm like, yeah. Try this. Do that.
Speaker 6:You know, shoulder hurt. Put some stem cells in.
Speaker 1:Yeah. When you're talking
Speaker 6:about stem cells, you're talking about cells that can become essentially anything, including tumors.
Speaker 2:Yeah. Talk about I'm curious. I mean, you you and and Rob, I feel like, do such a good job of of threading the sort of needle around having conversations without giving endorsements Mhmm. For specific things that are untested and and really focused on on understanding helping people understand the world, the science themselves, and then take the actions that they themselves as well as, you know, their their doctors believe they should take. Do you think that podcasters generally in health don't really understand broadly the responsibility they have?
Speaker 2:I I remember when I was in college, there was a popular tech podcaster at the time that would pretty much widely endorse microdosing. Right? And I I looked up I looked up to this guy. Right?
Speaker 1:Psychedelics.
Speaker 2:Right? Yeah. Psychedelics. Right? And and in hindsight, I look back on that and I'm like, is so wide wildly irresponsible to to basically recommend, you know, that the there's mic micro dosing for some people report tremendous benefits, but to sort of broadly endorse something in hindsight feels insane.
Speaker 2:And I don't think people fully grasp the responsibility that they have and just how much impact they can have on an individual or or or how a community thinks about something.
Speaker 6:Yeah. I mean, Rob and I, we take it super seriously. I mean, I've probably taken I've taken heat for a bunch of things in the larger science community, but probably one of the things I've taken the most heat for is, my belief that certain supplements can be helpful, not as a replacement for for, you know, good behaviors and for prescription drugs. I'm a fan of certain prescription drugs. Listen, I've read an episode on ADHD
Speaker 2:Mhmm.
Speaker 6:And talked about the prescription drugs and took a ton of heat from the kind of natural, folks. And then I did one on behavioral tools for ADHD and took a lot of heat from the folks who said, hey. Listen. My kid got a lot of benefit from taking stimulants for ADHD. So we we do weave back and in on that kind of knife edge, and it can be tricky.
Speaker 6:In terms of microdosing, because I saw it come up in the comments before today's discussion, and so it's kinda flagged in my mind. There the data on microdosing psilocybin are basically clear that it it's not known to have any major effect on major depression or some of the other things that psilocybin is being tested for clinically, including major depression, PTSD, etcetera. The data from clinical trials out of Robin Cartard Harris's lab at UCSF and elsewhere on high dose psilocybin, so macro dose. Right? You know, two two and a half grams.
Speaker 6:Four grams is the, quote, unquote, heroic dose if you're speaking Northern California language. You know, those dosages done in in pretty, maybe, you know, two two weeks apart or so with the support of a clinical staff going into it, through it, out of it, etcetera, have been very successful in those trials for the treatment of of depression. Microdosing has shown very little effect.
Speaker 1:Mhmm.
Speaker 6:MDMA was was put up to the FDA last year as a potential treatment for PTSD. It has not been approved. It did not pass approval. Unfortunately, as a component of those trials, there were some sexual improprieties in one of the clinical conditions that you know, all it takes is is, you know, one bad incident. Right?
Speaker 6:And then it was very but it cued people to this larger theme. How are you going to protect patients who are really in they're not incapacitated, but they're not in a position to really advocate for themselves, that you need probably multiple clinicians in the room and checks and balances? So I think, ultimately, it will be approved. The remission rates on PTSD, by the way, from properly dosed and spaced MDMA, is remarkable up to somewhere between sixty and seventy percent remission rates on PTSD. Mhmm.
Speaker 6:And the new thing that people are very excited about is Ibogaine or Iboga, a twenty two hour psychedelic journey. This has been tested largely from, Nolan, Williams' lab at Stanford, for the it seems to in one or two sessions, it has, led to a significant number of veterans essentially ceasing their alcohol use disorder, what is typically called alcoholism and opioid use disorder. But it you need to be heart rate monitored while you do this. The point here is that any discussion that we have on the podcast is, as you can tell, like, I'm not known for being very succinct. It's and it's for a reason.
Speaker 6:Right? You have to flush out the conversation around these things. You can't just say psilocybin is good. MDMA, yeah, like, works great. Permission.
Speaker 6:You know? People can really get hurt. Yeah. And I think, discussions around whether or not you take magnesium threonate or bisglycinate be before sleep, like, okay. You can probably speed through those a little more quickly.
Speaker 6:But when you get down to things about psychoactive drugs, in particular, schedule one illegal psychoactive drugs, you when you get down to things about hormone therapies, you know, you're just trying to get into the into the realm of where people can really screw themselves up. That said, there's you know, there are a number of things that I hope that the NIH and the and the public health messaging, going forward will be more expansive about, which are drugs that are currently prescribed at at enormous rates in The United States and elsewhere for which there are very severe side effects. Like like, they there's this whole thing about people taking finasteride and dutasteride, men, to to keep their hair and getting permanent sexual dysfunction. Right? Permanent sexual dysfunction.
Speaker 6:Some of them killing themselves as a consequence of this. I mean, these are young guys. It's clear those drugs have very different effects in young people versus old. Some people can use them safely. Some people can't.
Speaker 6:These are FDA approved drugs, as well as, you know, I think we're finally coming around to the idea that the SSRIs can be very useful for things like OCD in certain cases for depression, but it's it's a double edged blade. A lot of people suffered it, as a consequence. So I I hope that, there I hope really strongly for three things. One, as a scientist who essentially has my podcasting job because of the way the NIH supported me coming up through graduate school, postdoc, my lab, I think a 40% cut would be too severe. Regardless of the IDC issue, I I think it's just too severe.
Speaker 6:It's gonna kneecap science throughout the world and health, the growth of new discoveries throughout the world. I'd like to keep that funding level. I really would. What happens to IDC? What happens to Harvard and Columbia?
Speaker 6:Separate matter within there. But then I would very much like a a very thoughtful committee to go in and look at every single grant. Every single grant by area
Speaker 2:You have to have a scalpel, not
Speaker 6:a You've got a scalpel. And you could say, I mean, listen. In the field of neuroscience, am I the most qualified to decide what grant should be funded or not funded? No. But I can tell you that I sat on study section for a long time, and I can tell you there were clusters of grants that didn't solve what we call what good labs call the deletion test.
Speaker 6:If this laboratory didn't exist, would it change the direction of science? You have to pass the deletion test. Mhmm. It's not solve. You have to pass the deletion test.
Speaker 6:If you didn't exist, would it matter? That's a harsh test. Nobody wants to be subject to that test. But anyone that's getting millions and millions of taxpayer dollars and by the way, millions of taxpayer dollars often to work on and kill, and we could argue about the I think most people are speciesist. They'd rather see a mouse or a rat life or a nonhuman primate life.
Speaker 6:You know, we're we're killing animals. We're, we're occupying the lives of graduate students and postdocs with taxpayer dollars. The the work needs to be justified by passing the deletion test. And the idea that AI could, you know, do that, maybe, but the idea that a jury of close peers are gonna decide the deletion test, and if you pass, that's flawed in my opinion. Because the in culture we don't have time for this, but the in culture of science is, you know, people aren't, like, helping each other out just to help each other out.
Speaker 6:But when you're very close to something, it's very hard to make a really clear decision about it. And when you're too far from it, you're not you're not qualified to. So we need people that are in the middle who can really go in and say, okay, in the field of of, let's say, visual repair and neuroscience, give me a scalpel. I hate to do it, but also, you know, some are gonna pass. And then Yeah.
Speaker 6:I do think that instead of cutting people's funding entirely, there should be initiatives saying, hey, listen. If if you wanna run a laboratory, would you be interested in working on these important projects that maybe the Americans paying for this research ought to be able to to vote upvote? Why not? I mean, it's 2025, and the the NIH has done beautiful work over the last funded beautiful work over the last hundred years, but I think an update in the way these things are handled is great. As I say that, every single one of my colleagues is probably quaking that they're not gonna pass the deletion test except the ones that know they would absolutely pass the deletion test.
Speaker 6:And then the question is who's making the decision? And I'm not saying I should be making that decision, although I have some strong opinions about what's great, what's meh, and and what's, like, lousy. But I do think, we need we need to be more discerning the same way that a a bunch of VCs would sit around and say, like, hey. What are we getting for this investment?
Speaker 2:Well, yeah. I think the question they ask is if we don't make this investment, is the is the world gonna be, you know, worse off? Like, does this company, you know, I think it's not the quite the same test, but I think it's important for investors to run that Yeah. That process and understand, are we really funding the future that we want or is this kind of a rounding error and and the dollars would be better elsewhere? Can you
Speaker 1:give us a white pill? Like, are there any other organizations that can come in and help? I I I always think of, what happened in computer science and artificial intelligence. Google created the transformer architecture, not patentable. It created large language models, and we got ChatGPT, and we got all this great stuff.
Speaker 1:It would be amazing if we could find a way that the big pharma companies that are big and profitable wind up stepping in and funding some of the gap. Maybe there's non profits. Maybe we just, you know, the the sheer will of the American people. We wind up voting for more funding. But how do we really make science amazing and ensure really strong progression over the next few decades?
Speaker 6:Yeah. I mean, it's it that's the the key question. Right? So, I mean, listen, I grew I was born at Stanford Hospital. You know, did my training, much of it at Stanford.
Speaker 6:I'd say, I'll probably die at Stanford. Hopefully, I don't Wow. I'm the hospital. I'd like to die in in morning sunlight or something. But Oh, great.
Speaker 6:My dad's a physicist turned computer scientist. Right? Worked at Xerox PARC, which was an incubator for ideas, right, for many years. So I grew up in that landscape.
Speaker 1:Yeah.
Speaker 6:And, you know, he always said, you know, eventually, degrees in computer science will be important for starting companies. Right? But when I was young, that wasn't the case. Right? People dorked around on computers and made video games.
Speaker 6:Yeah. And then we saw cell biology migrate into the world of biotech and for the treatment of certain diseases. It has been, I mean, we can't forget that there are certain basic discoveries, going back to our earlier discussion, that have led to tremendous treatments, like the drops to lower eye pressure in glaucoma. If you catch your eye pressure elevation early and you take those drops, you will keep your vision.
Speaker 1:Wow.
Speaker 2:Okay?
Speaker 6:Right? You'll keep your vision. So it's not like we can't cure glaucoma, but you have to that's based on basic work. So the real key here is to ask, you know, so where has it been done successfully before? It's been done successfully in in the world of computer science and AI.
Speaker 6:Right? Growing up, I heard about AI, it was kind of like like no one no one took AI seriously growing up. Our brain machine interface was like
Speaker 2:Yeah. Like sci fi. That
Speaker 1:was so
Speaker 6:sci Seriously. Now, my good friend from from childhood, Eddie Chang, who's the chair of neurosurgery at UCSF, I mean, he's using BMI, brain machine interface, and AI to get peep with locked in syndrome to to speak and to and Elon's gonna get them to move. I fully believe that Neuralink is gonna solve paralysis.
Speaker 1:Yeah.
Speaker 6:I really do. I'm not saying that because we're on X. It's I know I know the head neurosurgeon there. They're well on their way. Right?
Speaker 2:Yeah.
Speaker 6:So the question is, what when should it move into biotech? And, you know, Peter Thiel had the breakthrough labs idea. He was paying people to not go pursue graduate degrees in labs to get the PI like me papers and advance their careers and then maybe go get their own lab, but to take great ideas and go to through breakthrough labs. I don't know what happened to breakthrough labs, but I do think that incubators like that
Speaker 1:Mhmm.
Speaker 6:Where you have enough money to test, you know, to move fast. Right? You know, move fast, break things, model, figure out whether or not something is promising, and then advance advance that. And here's the key. As soon as something looks promising, you want to be able to pour human power onto that.
Speaker 6:And the problem in academia is every graduate student and postdoc needs a first author paper in order to have the potential to get a job. Mhmm. And so one thing that I'm I've, you know, been in Jay Bhattacharya's ear about is, you know, I think I think the the independent investigator model of science in this country, where it's the Huberman lab or it's the whatever lab named after the PI, I think that's a flawed model. This is gonna really upset some people. There should be labs named after a particular mission, like curing blindness laboratory or solving Alzheimer's laboratory.
Speaker 6:And then people can collaborate within that lab without the idea that they're necessarily gonna go start their own lab. In in Europe, typically, there's a lab head, and it's it's very hierarchical, but people who get PhDs often stay in those labs as permanent careers. They get paid better and better. The NIH has not had a mode to keep paying people as staff scientists, and most people don't wanna go off and run their own labs. So I think the ability to iterate more quickly, much like a a tech company funded by NIH, would be enormously beneficial.
Speaker 6:And I I could be wrong, but I think it's gonna be music to most people who would like to go to graduate school. Because what it means is that you can be on the bench next to someone, and they get the thing that's really interesting, and rather than feel like, shit, I got nothing. You can now start working together to accelerate the progress of that work. And so you now who can go off and run a lab becomes a separate issue, but it really becomes discovery based science. And and we can't forget that the taxpayers are funding this.
Speaker 6:Right? So this is like, we as much as we'd all like it, the next generation of scientists to all have their own labs, I think what we really want is for the next generation of scientists to have the opportunity to make fundamental discoveries that seed health and cures and treatments for disease. Right?
Speaker 2:Yeah.
Speaker 6:Mean, do we really care about the careers of scientists? No. That we care about treatments for cure treatments and cures for disease. The careerist models
Speaker 2:Well, I do think it I do think it matters that that young people aspire to be scientists.
Speaker 6:Yes.
Speaker 7:And I
Speaker 2:and that is a concern that I have about the destruction of of trust between the public and the science community via COVID. The concern is that you'll have a a, you know, a ten year period, a a decade, you know, a decade where young young people say, well, I'm not gonna go into science because they have some and I and I think that that's the work that that you do with Huberman Lab has potential to heal that divide between the public and the science community and and one of the reasons why I think it's so important.
Speaker 6:Yeah. Yeah. I mean, I listen. One of the most the three most gratifying things I can hear, as feedback for the podcast are, I can't believe this is free. You know, that that feels good.
Speaker 6:That people are sleeping better. Like, oh goodness. I made a few morning sunlight and dim the lights and a few things in the evening and, like, I'm sleeping better because I know that catalyzes many, many other positive changes. And then the one and the one that's most heartening to me as a scientist less as a, you know, a health podcaster is when people say, like, you really turned me on to, like, neuroscience or, you know, or I'm going into the field of psychology. I wanna be a therapist, but I'm really starting to incorporate some physiological tools with my patients.
Speaker 6:That to me is those are the three most gratifying things. You know, I as you can probably tell, I'm very impassioned by this. Right? Folks close to me know this is how I talk all the time. No.
Speaker 6:I haven't had any caffeine in the last, you know, four or five hours. Just kinda
Speaker 2:We we have we have
Speaker 8:I heard you run off. Yeah.
Speaker 9:I do.
Speaker 1:I do. I'm glad
Speaker 6:you love this stuff.
Speaker 1:Alright. We love it. We drink it every day.
Speaker 2:We debated. I I we didn't have time, but I debated having you join the call, and it was just stacks of cans so you couldn't even see I get
Speaker 6:four of these a morning minutes. Okay.
Speaker 7:But I
Speaker 6:have a very high caffeine tolerance and Yeah.
Speaker 1:You know, in Fast metabolizer.
Speaker 6:The fast metabolizer. And and, you know, there are many issues I care deeply about, but what you just put your finger on is so key. If this 40 per I know people are like, don't give them this money. They fucked up during the pandemic. Excuse my language.
Speaker 6:They lied. Listen, these kids that would potentially become scientists, we can harness their energy, they didn't lie. They didn't do anything wrong. And if you if we train them properly and we put them into an environment where where the spirit of that environment is just discovery based, maybe a little less careerist, a little more discovery based, you know, and we really fund the most important work, it we can really transform the treatment and cures for all these diseases that everyone is so concerned about. I I know that because it's proved to be the case every single time.
Speaker 6:If you look at AIDS, there are two things that led to the treatments, you know, AIDS isn't fully cured, but it's a very different landscape now than in the eighties. Two things. Right? Money and emotion. And it came emotion and money, and then a bunch of scientists and labs and a bunch of funding.
Speaker 6:Okay? So where the reason we don't have a cure for schizophrenia, even though it's one percent of the world's population, is sadly, it tends to run-in families. There's not a strong lobby for for research on schizophrenia. The director of NIMH told me that, former director, Bob Desimone. The reason there's so much interest in autism is that any human being with half a heart looks at a kid, and I'm not talking about kids that are on the spectrum or a little neurodivergent who you know, I I work with those people.
Speaker 6:Like, we're not talking about that. I'm talking about kids that have, like, stereotype motion, can't be in an open environment, will forever need support. I'm not I'm not trying to, like, split the spectrum, but there there are kids on the spectrum that really struggle. Right? Right.
Speaker 6:And so the reason there's so much interest in in finding treatments for things like that or for major depression is because many, many people suffer. Right? And what's required is money and scientists working on the right problems and ditching the things that aren't promising. The faster you can iterate, the better. And so I do think the Silicon Valley model has something to offer, and I don't know what the latest update is on Breakthrough Labs and if Peter's moved on from that.
Speaker 6:I haven't heard much about it, but that doesn't mean that they don't have something interesting. But Yeah. Look, I as you can
Speaker 2:tell key is, like, if if you have one, you know, one car that that comes out, it's not so great. You don't destroy the car industry. You know? You don't you don't, like, basically, just dismantle the entire system. This car, you know, hurt people, so we should just eliminate all cars.
Speaker 2:Yep. You know?
Speaker 6:Yeah. Look, I think in in engineering, we're on x after all. Like, engineering, more of an engineering stance on on basic research is helpful.
Speaker 7:Mhmm.
Speaker 6:It's also true that, you know, I can name off countless discoveries in biology where, you know, an accident of leaving something, you know, on the shelf too long or something led to an interesting discovery. I mean, there is some fortuitous aspect to it. But now with AI, you can also run lots of hypotheses in silico. More in vitro, then move to in vivo models. I mean, there is a way to make the the money go further, but ultimately, there's no replacement for great ideas, and there's no replacement for the for human energy.
Speaker 6:And the the best source of human energy that I know is youth. And so you you need to catch people when they're coming out of college, not send them to work in a lab for three years before they might go to graduate school, then realize that they can't make a good living compared to their friends in finance. Like, you're not gonna get rich doing science, although some scientists do get rich. Right? I mean, Genentech was started by scientists.
Speaker 6:I mean, are companies. You know? But ultimately, you want to harness that that energy of youth and the spirit of discovery and give people the resources. Now, I had wonderful mentors, and and one of the most important things they taught me was you get money, you give it to young people, and you get the fuck out of their way and let them try. And and then when they don't work, you you guide them and you say, listen, like you're wasting your time, move on.
Speaker 6:Like, no, no, no, no, and they get down to it. No. Move on. It's like a bad relationship. Cut and run.
Speaker 6:And then then you just start the next thing. And so and eventually, you get hits. And then if you can pile human power onto those hits right? I'm just describing what everyone knows to be true, but this is not the way that the system has been designed. It is it is old and clunky, and it doesn't need to be scraped or, you know, hacked in half almost Yeah.
Speaker 6:At a 40% cut, but it does need to be revised. It really does.
Speaker 2:Yep. Makes a lot of sense. Well, this is fantastic.
Speaker 1:I wanna hit the gong for you. Can you give us a stat? How big is the Huberman Huberman Lab Podcast now? Can you give us an idea of the scale of the impact you've had? We like to hit the gong when we hear big numbers.
Speaker 2:He's looking rough.
Speaker 1:He's like, no. No. Don't leave any Even some rough numbers. Any number, maybe just one episode hit a million downloads. Give us some number, something Those rookie numbers.
Speaker 1:Those are rookie numbers.
Speaker 3:Yeah.
Speaker 6:So well, can I say one thing
Speaker 1:Please, anything.
Speaker 6:That that you know, rankings reflect acceleration not absolute reach.
Speaker 1:Yes. Yeah.
Speaker 6:Like Rogan like when people go like Rogan's not in a Rogan's reach is like beyond. I know the numbers. I I'm not gonna talk about his numbers, but it's it's like it's an order of magnitude greater than all the other major news hubs combined.
Speaker 3:Oh, yeah. Yes.
Speaker 6:It's unbelievable. We're but, no, we we are very blessed to reach, you know, 20,000,000 people.
Speaker 1:20,000,000 Let's go. Let's hit the gong. Thank you so much for coming on. Goodness. Was,
Speaker 2:an important conversation
Speaker 1:This is fantastic.
Speaker 2:Excited for people to get the, get into the entire episode.
Speaker 1:Yes. Yeah. It's fantastic. It's over four hours long.
Speaker 2:No. Is. I nothing else,
Speaker 6:you know, with the Hebrew in the Lab Podcast, I I always say, if nothing else, I'll cure insomnia. But no. The, in all seriousness, I you know, it's time stamps so you can break it down. If you wanna get right to the vaccine stuff, skip to that.
Speaker 1:Bounce fantastic. I listened to it last night.
Speaker 9:Was great.
Speaker 6:Can be digested however you want. Yep. I wanna say thanks to you guys. I started watching your show since you had Rob on.
Speaker 1:Fantastic.
Speaker 6:What you guys do is great. I also think that you're transforming the way that media is is, you know, dispersed each week and, you know, and and it's awesome. Yeah. You guys are on x doing what you do and elsewhere. Thanks so much.
Speaker 1:We appreciate it.
Speaker 2:Yeah. You guys are both welcome anytime. Yeah. Anytime. This is really fun.
Speaker 1:If you ever
Speaker 6:need more Matina, let us know.
Speaker 1:Oh, yeah. We got a fridge coming. We got a fridge coming.
Speaker 2:We're gonna park a fridge right here. We're gonna
Speaker 1:do it. The guys the whole the whole crew back there is is cheering.
Speaker 8:Where are
Speaker 6:you guys based?
Speaker 1:We're in Los Angeles in Hollywood.
Speaker 2:Yeah. Alright. Yeah.
Speaker 1:We'll come right over.
Speaker 6:It's a nice day.
Speaker 1:We'll see you soon. Alright. Thanks so much for hopping up. Awesome.
Speaker 2:You're the man.
Speaker 1:Cheers. Alright. Fantastic episode. Very fun.
Speaker 2:Well, folks, we had thirty minutes scheduled with Andrew, and we just
Speaker 1:We went longer for But we have some breaking news. We can go to the breaking news camera.
Speaker 2:Hopefully The breaking news printer.
Speaker 1:The breaking news printer. If you
Speaker 2:want breaking news.
Speaker 1:Watch it live as it comes out. I gotta note that it's slightly out of
Speaker 2:I see the laser working.
Speaker 1:There we go. What is this? What is this?
Speaker 2:What do we got? Woah.
Speaker 1:Shane Copeland. Shane Copeland. Polymarket says x and x AI are live on Polymarket. When I check Polymarket to get a gist of what's going on in the world, I always wish there was more context. Now there is the of many x AI partners with Polymarket to blend market predictions with x data and Grox analysis.
Speaker 1:Hardcore truth engine. See what shapes the world.
Speaker 2:The truth engine. Let's give it up for truth engines.
Speaker 1:We love truth engines. This has been a fantastic show. We will be at YC demo day tomorrow. We have a flight to catch. We covered most of the news.
Speaker 1:You've heard it. We talked about it yesterday. OpenAI hit 10,000,000,000 in ARR, almost two x Yeah.
Speaker 2:We hardly touched that.
Speaker 1:End of twenty twenty four. Yeah. It's just it's just casual 10,000,000,000 ARR. You know? It happens.
Speaker 2:Happens all the time.
Speaker 1:Yep. And, yeah, I think that's pretty much it for the timeline. I don't know if there's anything else you wanna cover. But, I mean, maybe we can close it out with this, fantastic post from Mert who's been on the show from Helios. He says, having $300,000,000 liquid is truly an interesting limbo.
Speaker 1:Golden handcuffs in a way. You have almost infinite money for daily expenses like groceries, Amazon binges, and chill little vacations, but you can't really splurge on anything sick. You have just enough money to think about making a real boy amount, but a razor thin margin for air if you screw it up. You're also at the exact amount where it becomes cozy and hard to motivate yourself to go that much harder. Tough spot, TBH.
Speaker 2:Tough spot. Oh, I feel you know?
Speaker 1:He's an all time poster. I love him. We gotta get him back on the show. He's so fun.
Speaker 2:Banger.
Speaker 1:Banger. Great place to with a banger. Anyway
Speaker 2:Thanks so forward to tomorrow.
Speaker 1:We have five stars on Apple Podcast and Spotify. If you're in SF and you're at demo day, come by and say hi. We'd love to talk to you.
Speaker 2:Looking forward to it.
Speaker 6:A great
Speaker 2:one, folks.
Speaker 1:We'll talk to you soon. Bye.