Benchmark's Future, SpaceX IPO, RIP Sora | Mike Knoop, Nathan Benaich, Rohin Dhar, Eric Jorgenson, Jenny Just, and Matt Hulsizer

16:49Rohin Dhar:like a entertainment doom loop. Exactly. You could imagine it just getting so good at generating the next thing that you would want to see better than even a billion humans on Instagram could do. And that's not what we've seen so far.

17:07Mike Knoop:And so like my big question was, was like, will this actually be sticky? Will people like this? And at what rate? I mean, I read, I read LLM generated text daily, but I also read a ton of not LLM generated text. And my ratio has grown exponentially, but it hasn't gone to 100%, nowhere near it. Like probably 5 % of the text that I read is LLM generated.

17:32Rohin Dhar:I mean, we should actually revisit how we were processing it during launch when it was, you know, rocketing.

17:38Mike Knoop:We should just throw on that three hour stream and just watch than reacted to how our team was that day.

17:43Rohin Dhar:But even at the time, I remember saying, very obvious that they built a very cool creative tool. Yeah. And they have the potential to seed a network with this. There's all this novel content. They had allowing creators and people like Sam to allow people to use their IP. It was a very, very well-executed launch. But even from the beginning, it was like, okay obviously cool creative tool it's a totally different ball you know this like come for the tool stay for the network has been like an enduring strategy right chris dixon probably wrote that in like 2014 maybe or yeah like a long time ago over 10 over 10 years ago yeah uh but just because you build a tool that is attached to a network like that jump is just really really really, really tough.

18:36Mike Knoop:Especially when there are three or four or five serious networks that are at scale that can on day one support the format of the file that is produced from the model. So in a world where generative AI video came out not in a MP4 file or an MOV file, it came out in some sort of format that could never be uploaded to Instagram Reels, then you have a chance to build a network and run away with it. And this was the story of Instagram. Instagram just had better support for images than Facebook did. And then Vine had support for video literally before Instagram. So Instagram, it was like, I have a video on my phone.

19:21Mike Knoop:It's cool. I want to share it. Sharing it to Instagram was not possible. Now on day one, you generate an AI video. You want to share it, you can share it on TikTok.

19:30Rohin Dhar:Yeah, it's just the incentive. If you created an amazing video on Sora, what is the most logical thing to do if you're a creator and you want reach? Post it to Instagram. There's just naturally, there's billions of people there. There were millions of people on Sora and a lot of energy and momentum.

19:47Mike Knoop:And it's not lost on me that the same day that Sora was killed, you have a viral breakout reality TV style series putting up incredible numbers on TikTok for Fruit Love Island, I believe it's called. It's an AI generated twist on Love Island. There's romantic intrigue and plot lines and stories and consistent characters and a lot of things that have come from a variety of AI models. And we should talk to the person that's the entrepreneur behind that project because I would be interested to know what the stack is because I imagine it's not just going to a single Gen.AI app. I imagine that they have a whole pipeline of workflow in place to actually generate that.

20:33Mike Knoop:And so we're at this weird moment where Sora, the app is going away, but we're also seeing more and more AI-generated content slowly see success, whether that's the podcast that's at the top of the charts that's fully AI-generated. There's this Love Island show. There's a number of niches where they've found the right product market fit for AI-generated content. But it's not overnight we're living in infinite jest and we just can't look away. It's like for specific things, it makes a lot of sense. And so it's working there.

21:07Rohin Dhar:Yeah, it's interesting to think about Google's strategy with video. Even Google was like, we cannot operate this for free at scale. $250 a month. No, that was the discounted rate.

21:21Mike Knoop:Oh, I think I had$500 a month or something. It was like an entry.

21:24Rohin Dhar:To start, it was like$250 a month. And it was brutally weight-limited. Yeah, even with – we were laughing at this because – I would get three a day. I remember we'd be like at the gym in the morning. You would fire off a couple prompts. Yeah. And then you were like rate-limited. I hope I got it right. Yeah, if you wouldn't get it right, then you were rate-limited. And you're like, wait, I'm rate-limited? After$250. On a$250 plan that's going to jump to$500? you're probably paying, got to check the ramp. Yeah, I did. Got to check our ramp. I saw. It's probably paying$500 a month still.

21:55Mike Knoop:No, seriously. And that rate limit. And that's Google with all this cash flow.

22:00Rohin Dhar:Literally hyperscaler. It's insane data advantage with YouTube.

22:04Mike Knoop:And that, let me tell you, rate limits kill retention. Like nothing is worse. If you're in Instagram, the endless scroll exists. TikTok, you can scroll endlessly. You can use the, Imagine if TikTok was like after five minutes, you have to close the app and come back in 20 minutes. Like how successful do we think that would be? It would be a disaster. And that was the experience for both Sora and VO3 where you would fire off a prompt and it would be like, okay, come back in a couple minutes. It's going to take me a while to cook. And then you fire off five and it's like, okay, no more for today.

22:38Mike Knoop:And then the next day happens and you forget about it and you go on something else. So clearly the compute constraints are immense and there's just so much more value that can come from enterprise and can come from deep research and so many of the other models that are immediately economically valued like code gen, like enterprise workflows. And it's maybe more boring and less viral and less controversial, but it's where the compute needs to go. And so I think you're going to see the chips be moved around inside of all the labs to like compute will find the most optimal output. Like the tokens of the most value will always be the ones that the compute flows to.

23:20and as a lot of people predicted,

23:23Mike Knoop:like just endless random generations that aren't quite dialed yet, even the best video models, like they're just not there. They require a lot of work. It's not the same as where we are in terms of knowledge retrieval, where we are in terms of code gen. It's just way more valuable. So anyway, let me tell you about Okta. Okta helps you assign every AI agent a trusted identity so you get the power of AI without the risk. Secure every agent, secure any agent. Thank you guys. And let me also tell you about Cisco Critical infrastructure for the AI era Unlock seamless real-time experience is a new value with Cisco

23:56Nathan Benaich:Market clearing order inbound

23:58Rohin Dhar:You said September people overestimate how much brain rot happens in a year And underestimate how much brain rot happens in a decade So yes, we're still

24:08Mike Knoop:So I mean I'm using brain rot pejoratively there But I do think that like this move does not really bend the curve of just AI generated content, but I still think it's like a slow rollout. Like it's fast in the sense that like we went from no slop on the timeline to lots and we went from like actually zero. It was like one cool AI video, Harry Potter Balenciaga was like entertaining to general people. And now we get like five and then we get like next year we'll get like 20. And then eventually it'll be like hundreds and it'll be like, oh yeah, I'm actually into that. Like people are into cartoons and people are into CGI movies and superhero movies.

24:49Mike Knoop:Some people will be into it. Some people will never like it. Some people will always say, I want a black and white film from the 40s. That's what I want to watch. And these rollouts, the diffusion of this stuff will happen. Should we revisit one of the -

25:02Rohin Dhar:Tweet Davidson says -

25:04Mike Knoop:What is this?

25:06Rohin Dhar:Y 'all are worried about the wrong open claw.

25:08Mike Knoop:This is a good post.

25:10Rohin Dhar:This is the open claw that F. Randall was worried about in 2017. He was not thinking about Uber.

25:19Mike Knoop:Was White Claw invented in 2017? When did White Claw get founded? That's a great, I feel like it really took off. It had a fast takeoff.

25:28Rohin Dhar:Yeah, 2016. 2016, okay. Open Claw. There's a very good chance he was an early adopter of Open Claw. He might have been an early adopter of Open Claw.

25:35Mike Knoop:It truly was. I'm calling it Open Claw now. White Claw did have a fast takeoff, for sure. It went from zero to 60, and it was just everywhere all of a sudden. Anyway, let me tell you about Sentry. Sentry shows developers what's broken, helps them fix it fast. That's why 150 ,000 organizations use it to keep their apps working. I got a story for you, Jordy. Today, as I was driving into Hollywood from my hometown of Pasadena, I was driving through Hollywood and I look over and there is a new Hollywood sign. I'm not kidding about this. I actually saw this. I took a picture. I can maybe send it into the chat, but I can just show you because I'm driving and I just see this.

26:18Mike Knoop:Like -

26:18Rohin Dhar:Billy Bowman.

26:19Mike Knoop:Billy Bowman. I don't know. I'll send it into the chat so they can pull it up. Let me see. Production. Here we go. But anyway, it is a remarkable story because Fiverr is running one of the coolest out-of-home campaigns. Like just from an out-of-home inventory, I didn't know you could do this. We can pull up either my picture or we can pull up this -

26:42Rohin Dhar:from KTLA 5.

26:44Mike Knoop:KTLA 5 had a video breaking down what's going on. Let's watch this and then we'll react to this. And while the team pulls that up, I'm going to tell everyone about LabelBox, RL environments, voice robotics, evals, and expert human data. LabelBox is the data factory behind the world's leading AI teams. So let's pull up the KTLA 5 report about AI coming for Hollywood, the mysterious sign along the 101.

27:11Nathan Benaich:Underneath, a logo for Fiverr and a search box says, find the best AI directors. It's a brash, bold statement. Brash, bold statement. Coming for Hollywood. Coming for Hollywood. Fiverr has made a name for its self-connecting projects with freelancers. Now they're launching an AI video hub, which they say can make content at a fraction compared to traditional production.

27:30Jenny Just:This Billy Bowman guy is one of the directors that you can hire. He's based in Sweden. He's made AI videos for Google, Universal Music Group, and others. As you know, AI really hasn't taken over Hollywood yet, but it has certainly crept into commercials. Brands like Google and Jeep rolling out AI on national campaigns.

27:49Nathan Benaich:Many are slowing to see the 30-foot sign, which went up over the weekend. I first noticed it stuck in traffic yesterday morning after someone was so entranced, they rear-ended somebody else. It's causing accidents.

28:01Jenny Just:So interesting. AI director.

28:03Nathan Benaich:So it's basically someone who puts the prompt into the machine and chooses,

28:09Mike Knoop:is Fiverr going to pay the$500 that the vendor vendor...

28:14Rohin Dhar:That's a great question, yeah.

28:15Mike Knoop:Yeah, can they be held liable for such a distracting sign?

28:20Nathan Benaich:I didn't get a crash for something.

28:26Nathan Benaich:That's interesting because Fiverr is not one of those companies.

28:32Rohin Dhar:KTLA 5 is not prepared for it not to be a bubble.

28:36Mike Knoop:So Fiverr's market cap now is$560 million, and that's down about 95 % over the last five years.

28:45Rohin Dhar:Wait, where are you seeing that? I'm seeing 350.

28:47Mike Knoop:Sorry, yeah, 359. What did I say?

28:51Rohin Dhar:500.

28:52Mike Knoop:Oh, sorry. So it's a$360 million company today, down 95 % from five years ago. So it started selling off in 2021, sort of pre-ChatGPT. So I think the AI narrative might be a little bit overblown there. It did IPO around this price. It was a$700 million IPO, I think, maybe a billion dollars. Went through a massive boom during COVID and then sold off. But of course, the AI wave has not been kind to Fiverr because a lot of the tasks like,

29:26Rohin Dhar:you know generate AI is very very very good at five dollar creative work exactly twenty five dollar obviously yes the prices go well beyond five dollars since uh since since the early days but in terms of the kind of projects that I always use Fiverr for AI just one shots all of that and

29:45Mike Knoop:the nature of Fiverr is like you have to define your task in a prompt it's not it's not oh have like a long conversation get drinks with somebody that was often that was often the bottle yeah

29:56Rohin Dhar:That was the bottleneck. Yeah, totally. It was like, okay, I need to do this task. I need like 10 minutes to like properly define it, all these things. It's honestly way more time than you spend prompting formally because with prompting, you're just like, I'll just try it a few times. A bunch of times. Kind of iterate.

30:11Mike Knoop:Hit my rate limits and then fire back up. Yeah, I mean, it was always a bottleneck. I remember as an entrepreneur, I found out about Fiverr and I was like, this is amazing. I can get random stuff done for five bucks, but the time commitment, actually finding the right person, making sure the reviews are good, It wound up being like hours of work. And if you have a consistent flow, you're better off just hiring a person. So they got kind of squeezed in the middle.

30:33Rohin Dhar:Yeah, the market is not excited about Fiverr right now. They're being valued basically at four times EBITDA.

30:40Mike Knoop:Okay.

30:42Rohin Dhar:And so, yeah.

30:43Mike Knoop:But this is an interesting pivot for them. They're basically saying that you can come to us to hire someone who has all the tooling set up to actually sit there and sort of, you know, nanny all the AI models because it is a hassle. Like, as you described with me and VO3, I was sitting there like, okay, I fire off four prompts, then I go back. Like, it's way better if you're on the API and you have Higgs field wired up and you have, you know, runway ML and you have access to the Chinese model C dance, like, you know, the right tool for the job. And then you do fine tune on someone's face. There's a whole bunch of things that you can do to get better results, but it takes time and it's a hassle and it's more of a professional job.

31:26Mike Knoop:It's not actually at a one prompt.

31:28Rohin Dhar:Here's the main problem with the campaign. Yes. Is that Billy Bowman is a real person with his own website, with his own Instagram, and you can just go and reach out to him, which is interesting because like the primary issue with these labor marketplaces like Fiverr, it's disintermediation. If a business hires somebody on Fiverr and has an amazing experience, eventually they're just going to go direct because they build up a lot of trust and it's very different than a platform like Uber where you don't necessarily want the same driver every time because they're not around you and all these things.

32:07Rohin Dhar:And so the reason that the Fiverr's and the Upworks of the world, and there's been a bunch of other like engineering-focused marketplaces just have never reached like insane scale, like Uber, is because of the disintermediation. And this campaign is effectively an ad for Billy Bowman, who you could just go hire today.

32:28Mike Knoop:Yeah, disintermediation has always been a problem on these platforms. Anyway, let's move on. But first, let me tell you about Fin.ai, the number one AI agent for customer service. If you want AI to handle your customer support, go to Fin.ai. And let me also tell you about the New York Stock Exchange. Want to change the world? Raise capital at the New York Stock Exchange. Speaking of stocks, did you see that Bombardier, the manufacturer of private business jets, is down 10 % over the past month? A lot of people were wondering why this was happening. I think we now know why, and it's probably because of the shot across the bow from United Airlines.

33:05Mike Knoop:So what competes with a private jet? potentially United Airlines new product which is an entire row of economy seats we got to pull this up United Airlines says the entire row is all yours welcome to the United relax row three adjacent United economy seats with adjustable leg rests that can be raised or lowered to create a cozy lie flat space for stretching out you'll also get a mattress pad blanket and two pillows If you're traveling with kids a plushie to United relax row will be available starting next year on more than 200 of the 787 and 777 Each with up to 12 of these brand new rows So what do you think Jordy?

33:49Mike Knoop:Is this the way I was telling Tyler Cosgrove who is out of the studio today? He's in Washington DC. He's got a demo this he's got to get on one of these I don't know every time the airline announces something. It's always like five years until it actually is available I've been waiting for Starlink for a long time took a long time for that to get rolled out from the PR release.

34:05Rohin Dhar:I feel like United has pretty good pace. Haven't they been quick to startling?

34:08Mike Knoop:So you think Tyler could get on this tomorrow? Or today? He's going to the airport today.

34:11Rohin Dhar:I think if Tyler's resourceful enough, he could just, if he ended up in a row with two empty seats next to him, he could just figure out a way to detach the armrests, blocking this, and just kind of build your own. They might have to land the plane and arrest him. Yeah. But potentially worth the risk.

34:30Mike Knoop:He could also potentially negotiate with whoever's sitting next to him. Say, hey, you go and spend the entire flight in the lavatory. And in exchange, I will vibe code you a sloppy app, of which I don't understand what programming languages we use. I'll trade you an app for your seat. I'll trade you an app for your seat. And somebody might be like, that's amazing. I don't have anyone that can vibe code for me. This is too good. No, I'm sorry.

34:54Rohin Dhar:Ryan Peterson says, now we just need to put stairs on the food drink cart so you can climb over the top of them to get to the bathroom instead of holding it. Yeah, this just feels like, this just feels very, very chaotic. But it's good. This is wild. It's good.

35:12Mike Knoop:I don't know. Starlink, a relaxed row, a dream. I think that this could be a good option. United built the product that everyone who has been, who has ever been on a plane wanted, says John Collison.

35:25Rohin Dhar:John, you need to work on fixing Bombardier's stock price.

35:29Mike Knoop:I don't think it's related. Oh, apparently Air New Zealand launched this in 2010. No, it is related because he should help them build out their pipeline. Well, he's just pumping his bags because he owns a property in Ireland. How do you get there? You got to fly on United. So, you know, one hand washes the other on this. He's talking his own book. No, just kidding. Let me tell you about console.com. console builds ai agents that automate 70 of it hr and finance support giving employees instant resolution for access requests and password resets and let me also tell you about railway railway is the all-in-one intelligent cloud provider use your favorite agent to deploy web app servers databases and more while railway automatically takes care of scaling monitoring

36:09Rohin Dhar:and security and carter says if you say no to pretzels the flight attendant should give you something called a coin of restraint while worth nothing now these coins will play a major role in

36:22Mike Knoop:the afterlife the coin of restraint is very very good i like that uh well elon musk is teasing something cooler than a minivan that might come because uh elon said the cyber truck rear bench has three seats of isofix attachments and is wide enough to fit three child seats or three adults so there's been a big debate on uh the isofix attachments these are the little metal uh hooks that are installed in every car in the back seat for child seats. And so child seat requirements mean that you have to have a car that has these. And it's been called like the death of the five kid family or something like that, or like the death of the big family.

37:05Mike Knoop:Because at a certain point, in order to have another kid, you have to upgrade your car. And that has an expense associated with it. You need a three-row SUV or you need a minivan or you need something bigger that's not as affordable as just a normal sedan. They used to be able to just throw four kids across and maybe that was less safe.

37:23Rohin Dhar:You're saying regulation killed the birth rate.

37:25Mike Knoop:People actually say this. People say that child seats have saved like a million lives, but then they've stopped 10 million from being born. They talk about the relative exchange ratios. I haven't really dug into it too much, but there's clearly demand for more spacious vehicles with more seating. The Model S used to come with a third row, which I still don't understand how that was possible. The Model X came with a third row. And in China, they actually sell a Model YL, which is a long wheelbase version of the Model Y. I hope they bring that to the States.

37:58Rohin Dhar:So people are saying, make a minivan, Elon. Elon says something way cooler than a minivan is coming. What do you think it is? And people are speculating. Garcia here. I think it might be a data center. Tesla. I think he might be like, there's another data center coming. Chip Fab.

38:12Mike Knoop:Yeah, Chip Fab.

38:13Rohin Dhar:He's like you you're gonna be I'm gonna end and you're not gonna need this is gonna change the child labor law Yeah, that instead of worrying about bringing your kids around. Yeah, they'll just go work. No, they're in the fat They're in the fat clean room in the cleaner. They're fully suited up They're making chips, but now people are speculating. This is very cool I love gen AI has been amazing for car enthusiasts to create basically their own concept cars These look very very cool We were talking about a 20 of bezel about this. Make a Tesla version of the Rivian.

38:45Mike Knoop:Yeah.

38:45Rohin Dhar:Because it looks exactly like it. But let's get into some of the speculation. Okay.

38:49Mike Knoop:What are people saying?

38:50Rohin Dhar:Cyan Bannister says an RV. That could be fun. Arthur McWater says, I can't wait for the next Roadster unveil. Elon was teasing. It was on Joe Rogan, right? This concept of maybe it'll fly. And I think what Elon could be getting at is picture a Roadster, not a great family car, hard to put kids in a sports car. Some of them you technically can, but it's so uncomfortable and kind of chaotic. Very few people would. And I think what we could see is the Roadster comes with five kind of like, you know, that Fury collaborative combat aircraft from Andrel. What if it comes with like up to five little mini roadsters that are just trained to autopilot behind the primary roadster?

39:41Rohin Dhar:So you can be in your sports car. And then however many kids you have are in the mini drones following. That'd be fun.

39:48Mike Knoop:What about a Chinook heavy lift helicopter with two massive rotors that can lift your roadster off the ground? Yes. Technically a flying car then. Yes. Anyway. Let me tell you about phantom cash fund your wallet without exchanges or middleman and spend with a phantom card I have a question for you Jordy. Are you are you running the new AI model? It's on co-work. It's literally on co-pilot. You can probably find it on codex dude. It's on co-author It's a cosine exclusive. It's on cocaine. You can run it on cocaine You can literally go to cocaine and run it. What a great copy pasta. This is one of the funniest formats.

40:30Mike Knoop:But yes, the war for co-pilot and co-work is heating up. We got to find a new term, I think. People have been really, really fighting neck and neck with this.

40:39Rohin Dhar:Well, I was telling Microsoft they should just name it Coco. Coco. Microsoft co-pilot, co-work.

40:45Mike Knoop:It's just Coco. Coco would be good. There's a few different options. I think I prefer the non-anthropomorphized AI names, although they are a little bit colliding in the namespace. I have been a fan of, you know, the codexes and co-works and co-pilots. Those feel more collaborative to me and they feel more like tools than the Bards and the Ceres and the Alexas and the Rufus and the Sparkies, like that. That's just a different vibe. And I think that if we're living in a world where people are going to form strong relationships with these tools. Introducing them truly as tools is probably.

41:30Rohin Dhar:Let's see what's going on with QVC. Let's pull up this video.

41:35Mike Knoop:And we also have one of our guests joining early at 11.

41:38Rohin Dhar:No, he's going to be joining. He'll be ready to join in an hour.

41:44Mike Knoop:Are you sure?

41:44Rohin Dhar:Yeah.

41:45Mike Knoop:Okay.

41:45Rohin Dhar:Let's check with the production team. I've already texted. Okay, cool. We'll continue for the next 15 minutes.

41:51Mike Knoop:Fantastic. We'll take us through the next story.

41:53Rohin Dhar:What do you want? River says QVC basically reinvented live streaming decades, invented live streaming decades ago, goes 24-7. They invented live TV. Goes 24-7, a good 80 % of the show is just the host going on long personal digressions. People watch it as background, heavy parasocial element. Hosts know the callers. 95 % are repeat buyers. It's 100 % Twitch for grandmas. Let's pull up QVC.

42:20Eric Jorgenson:and with the suffering i wanted to tell you that i got that peasant blouse with the tassels yes and i used to wear the tassels on my pasties do you know what pasties are this is okay ridiculous what pasties are yes i'm gonna do okay well i have crazy we're moving on let me tell you about 11 laughs build intelligent real-time conversational agents

42:47Mike Knoop:reimagine human technology interaction with 11 labs. And let me also tell you about Gemini 3.1 Pro. We are going to deep dive ArcGi today. And Gemini 3.1 Pro has done very, very well. With a more capable baseline, it's great for super complex tasks like visualizing difficult concepts, synthesizing data into a single view or bringing creative projects to life.

43:10Rohin Dhar:SpaceX aims to file IPO as soon as this week. I know everyone is excited for the S1. Particularly, I think people will be focused on XAI, what they have going on. I think that... Are they going to have to break it out in the S1? I would assume so.

43:30Mike Knoop:This might be the first time we actually see the economics of inference, the economics of foundation lab, even though, yes, they are at a smaller scale.

43:38Rohin Dhar:It's hard to read too much into it because they've been investing so far ahead. Yeah.

43:44Mike Knoop:And yeah, I just think that like there is a world where we get broken out financials that you can dig through and you can understand based on grok pricing, which we see and top line revenue and cost. We can actually see, are they serving that model profitably? And there will be, you know, a lot to dig into there. Obviously, the other labs have different strategies, different vertical integration points, different economics, different pricing regimes. I mean, the true frontier, the models that are dominating ArcGIS, which we will talk about in 15 minutes, those command a premium, a price premium.

44:23Mike Knoop:And there's a wild difference between charging$15 per million tokens versus$2 per million tokens. So it will be interesting.

44:32Rohin Dhar:Yeah, and if you remember, I think it was in Q4 of last year. if you looked on open router grok was what had i think it was like grok fast yeah had a ton of usage people are like okay why is this happening and part of it at least i believe was because they were subsidizing it well um okay so here's what i think so so people were posting this as though it was fact uh but i think uh i think it's a very real possibility so uh i think elon will we'll we'll try to aim for the company to actually go out on on april 20th 420 really um and i think it is possible if he goes fast the the ticker we'll see what the ticker ends up being but i think some people would like knowing elon's very millennial sense of humor i think the ticker s e x is plus the April 20th IPO.

45:33Rohin Dhar:I would assume that - You think there's a real prediction? You're not trolling? I'm not saying I would bet on it, but I think there's, I would put the April 20th at maybe like 30 % and then the ticker maybe down at 15%.

45:54Mike Knoop:Kalshi has when will SpaceX officially announce an IPO before June 1st, which April 20th would be before June 1st. Yeah, I'm not talking about it.

46:02Rohin Dhar:I'm talking about like list actual like listing day, like the day of the IPO.

46:06Mike Knoop:Yeah, this is just announcing the IPO.

46:08Rohin Dhar:Which I don't even know if they haven't even confirmed this.

46:10Mike Knoop:This is now this is currently in the scoop in the scoop thing. So they haven't even scoop.

46:16Rohin Dhar:You said they so the wait, John, did you say scoop?

46:19Mike Knoop:Yes, this is a scoop from what is what is this? Can we go to the wide angle? We got Katie Roof, Scoop Master.

46:28Rohin Dhar:We have a new...

46:29Mike Knoop:We have to award her the first TBPN Golden Scoop.

46:32Rohin Dhar:The Golden Scoop Award. Do you want to show her the scoop? I don't want to pick it up yet. Why not? Okay, we can...

46:38Mike Knoop:We need to give the Golden Scoop Award for the best scoop of the day to Katie Roof, who moved markets with her scoop. She, of course, is the Deputy Bureau Chief of Venture Capital at The Information, and she's an absolute scoop athlete. She's Scoop Doggy Dog. and and she moved markets so uh sats is up 7.8 percent beast b bksy is up 4.8 percent uh l unr is up 4.1 percent every stock in the space we're working on is a new award award show the scoopies the scoop the tbp and scoop i think katie roof is a lock i mean she's in she's she's a front runner

47:17Rohin Dhar:for sure putting on a generational run front runner for sure yeah it's so it's so funny the the I mean, incredible moment for the retail space investor community. Yeah. Because they're just, for some reason, people, anytime you get SpaceX repricing, they're like, well, this other random company that happens to be technically on the same market map definitely deserves to be worth 7 % more.

47:45Mike Knoop:Yeah. I don't know. I was as skeptical about the rest of the lunar economy for a long time. It felt like winner take all. It felt like SpaceX was running away with it. But there have been interesting dynamics where companies that are buyers of SpaceX capacity, whether on the satellite Internet side or on the launch capacity side, they don't want a monopoly to exist. And so they're willing to throw money at competitors. And Jeff Bezos has stuck around with Blue Origin. Rocket Lab's done very well. There's been a bunch. People are saying we need to redesign the scoop. I don't know what you're talking about.

48:23Rohin Dhar:I don't even know what you could be talking about.

48:25Mike Knoop:It's an ice cream scoop. It's an ice cream scoop. People, get your mind out of the gutter. Out of the gutter, please. And head over to Shopify. Shopify is the commerce platform that grows with your business and lets you sell in seconds online, in-store, on mobile, on social, on marketplaces, and now with AI agents.

48:42Rohin Dhar:Okay, Casey Hammer is worried. What is he saying? He's worried. Why is he worried? He's stressed. Why is he stressed? He says, what I worry about is a generation of talented, experienced engineers being too rich to work.

48:53Mike Knoop:So if you're worried about being demotivated by your incredible SpaceX liquidity, you have to do what I recommend, which is the Brewster's Millions approach, where you have to spend all the money in 30 days without telling anyone why you're doing it. This is from the 1980s, 1990s comedy called Brewster's Millions, which I highly recommend you watch. In it, a man is gifted an inheritance from a wealthy uncle or father figure or grandfather. And it is conditioned on the fact that he needs to spend something like$30 million in 30 days without telling anyone why. And he can't accrue assets. So he can't go and just buy cars.

49:33Mike Knoop:He needs to throw parties and give money away and spend money wildly. And it's to teach him that money does not bring happiness, of course. And I think that's the solution to this. Anyway, let me tell you about MongoDB. What's the only thing faster than the AI market? Your business on MongoDB. Don't just build AI. Own the data platform that powers it. Okay, here's why I'm not worried.

49:52Rohin Dhar:Why are you not worried? Because I think that these ultra-talented, hardworking engineers having some liquidity, let's say someone's been there for some number of years. They have five million liquid. They buy a nice house somewhere and then realize, hey, I've got a nice nest egg. Like, I can keep working on crazy moonshot. I don't have to go join, you know, the historical example would be like work on the hard thing or work on enterprise SaaS. And I think this just will give people more confidence to work on the hard thing, the thing that might have a 5 % chance of success. But if it's successful, you know, has a tremendous impact on our country and things like that.

50:41Mike Knoop:It might happen for some people, but in general, I do think that there is this liquidity wave coming. Dalian talked about it on the show yesterday. At the same time, SpaceX has been doing tenders for over a decade. And it's not like the early employees have never had a crumb of liquidity or secondary throughout their journey. A lot of them have had opportunities to sell at least a portion of their stake and have been able to buy houses. And there's always been a way to access some of that capital, whether through a loan from a bank. And you're obviously more credit worthy if you own a bunch of SpaceX stock and it's going up.

51:20Rohin Dhar:Yeah, a bigger issue for the kind of space economy overall is just the Blue Origin people. Didn't they have way more? They didn't really know what their equity was worth. It's not like there was regular tenders. And so why work at the number two, at least by many definitions, space company? And then that's potentially ultimately bad for competition. And that's bad for launch pricing for all these other companies that are reliant on the SpaceX's and ultimately the Blue Origin. So anyways, crazy news out of China. apparently the co-founders of manis uh are still in china and were called up uh to uh talk with the government and are now blocked have you seen the dark knight yes has everyone seen the dark knight

52:16Mike Knoop:you thinking what i'm thinking you think what i'm thinking we go there wrap our arms around him the plane comes grabs the balloon sucks him out of the back of the of the skyscraper it's one of the greatest scenes and i think that's what we got to do because we need personal super okay so

52:33Rohin Dhar:this was surprising to me because i feel like we've been messaged to for a long time that they were in singapore yes that's true it was definitely shouldn't have been seeing this it's not a chinese company they're in singapore yeah the whole team's in singapore and and you would it takes some audacity to sell your leading chinese one of the leading chinese ai companies during an AI, a global AI race, this battle between great powers and to sell to a big American hyperscaler, maybe get out of the country before you do that, because it's not at all, I mean, this doesn't, when the Manus acquisition happened, it seemed very clear that you would be, if you were China and you were competing in the AI race, even though Manus is not like a lab, you're still like, okay, they're building a powerful harness.

53:26Rohin Dhar:Yeah, we probably don't want them going to serve and the harnesses are incredibly

53:32Mike Knoop:Probably under more important now everyone. Yeah, it's super important right now. Everyone everyone, you know Obsesses over the models and the models are important But the harnesses have shown incredible promise for actual diffusion and making these models

53:44Rohin Dhar:so Josh wolf says I thought this wasn't a Chinese company and Delian goes for the jugular so much for all the arguments about man. It's not being influenced by the CCP Phil.

53:57Mike Knoop:Yeah, I'm mostly shocked just about how this is playing out. You would think that if you're the CEO of Manus and you get a call from Mark Zuckerberg and it even smells like a potential acquisition, you're like, yeah, I'd love to come see the headquarters. Why don't I come in with my team? We'll just come and hang out in Menlo Park or Miami for a couple months while we hash out the deal. And if the deal doesn't go through, we'll head back. But if it does, we'll just stay and we won't go back because if it goes through, then there's going to be pressure and we're going to wind up in this situation.

54:30Mike Knoop:This feels almost predictable. I don't know. It feels like there's something else going on here. I'm excited for this story to develop.

54:38Rohin Dhar:So the authorities are reviewing the sale and they're being asked not to leave. Seems hard to reverse at this point. But again, not sure why. I mean, when you look back at acquisitions that were blocked historically, Who knows how feasible it is to fully block the acquisition, but they can certainly block these individuals from materially benefiting from it in some way or contributing to Meta's efforts.

55:08Mike Knoop:Well, here's some advice for the CEO of Manus. When you get here to America, when you get that liquidity, that payday from Mark Zuckerberg, open an account on public.com, investing for those that take it seriously. Stocks, options, bonds, crypto, treasuries, and more with great customer service. Just do it. And then, you know, tell your story. Start restreaming. One live stream, 30-plus destinations. You should be multi-streaming. So go to restream.com. Tell your story live on the internet.

55:35Rohin Dhar:Gabriel says, Meek Mill has been going off about AI. AI is helping him organize his whole music career and other businesses in days, and it's moving his business forward at a high rate. Some tech young bull I met on LinkedIn gave me an incredible template, which is probably G-Stack. Who else can help me with Claude? Gabe says, Drake, I don't do K2. Kimmy, Deep Seek, that's more for your kind. My gal more like Demis Theme Park ting London Deepmine I quad coded Perks out of 18th and Berks I got 500 agent lawyers trying to Free Lil Durk

56:20Mike Knoop:Drake sing it

56:21Rohin Dhar:You got me loco Trying to be your shoulder

56:27Rohin Dhar:You didn't sing it Sophie chimes in Two chains Open claw on my laptop trapping off these Mac minis shout out to YC real G's want to stack with me that's good that is good I mean yeah it's not a it's not a bubble until until G stack makes it into makes it into it

56:49Mike Knoop:yeah uh uh actual hit the funny thing here is you might see there's some debate and and there's this general vibe like some people were latching on this trunk fan post about like you know are people making fun of Meek Mill? Are people like undercounting his ability to actually build something for real? And the interesting thing is that I would definitely bet on Meek Mill to build a real valuable piece of software for his audience or his life or his business over any of these tech people writing rap lyrics, even with all the powerful LLMs. Like the tools to actually build software are way better than the tools to write rap lyrics.

57:27Mike Knoop:And it's interesting because you are seeing this dynamic where where the like like it I think a lot of people are latching on to the older paradigm of like oh like you know Jeremy Renner built an Instagram clone at one point and it was just the Jeremy Renner app and it was just his feed of his photos and people were like why does this exist you can just follow Jeremy Renner on Instagram it doesn't make sense that he would like his own private Instagram and he probably spent a lot of money developing that piece of software. Uh, but, and, and I don't think it wound up working and it didn't scale and he wound up winding that project down.

58:00Mike Knoop:But, uh, if you think about like, well, what if this, what if this cost of doing that is a hundred bucks or 200 bucks or a thousand bucks, like all of a sudden the, the hurdle rate to clear something like that actually does open up the creative aspects where I wouldn't be surprised if there's a, like, maybe not like a breakout hyperscale, incredible, like generational company, but just like in terms of like you, like you can be a great musical artist and also produce great clothing. Like you will now be able to produce software at the equivalent level, like it is available. And so if you are constrained by your ideas and if you're a creative artist, you, and you have a great idea, you're no longer going to be in this world where you're like, well, I need to put a couple million bucks down for a software engineering team.

58:51Mike Knoop:And All of a sudden you get into this weird thing where like the app that they launch or is like sort of iffy and not that good So I don't know. I'm actually I'm actually coming away bullish on What meek mill winds up producing over the next few years and we are working on getting meek on the show

59:08Rohin Dhar:I really hope we can talk to us. I'll cover You're good. You're good. I'll cover meta. Okay, you want to jump for a second first?

59:15Mike Knoop:Let me tell you about CrowdStrike your business today I their business is securing it CrowdStrike secures AI and stops breaches And I'm also going to tell you about Vanta, automate compliance and security. Vanta is the leading AI trust management platform. And I'm totally good, so I can take the next intro.

59:31Rohin Dhar:I have a personal thing I'm going to run to, but I will see you guys tomorrow. Yes. Love you. Cheers.

59:36Mike Knoop:Thanks, Jordy. Up next, we have Mike from ARK Prize in the Restream Rating Room. Let's bring him into the TVP and Ultradome. I'm very excited to talk to Mike. How are you doing?

59:46Jenny Just:Here we go. Hey, good to see you again.

59:48Mike Knoop:Good to see you.

59:50Jenny Just:I'm so excited.

59:51Mike Knoop:This is always the highlight of the show. I love talking to you about everything. But what are we talking about today? Reintroduce ARC as an organization and then take us through the actual, do you even call them benchmarks challenges? What's the right term?

1:00:08Jenny Just:Yeah, I think benchmarks is a fair word.

1:00:09Mike Knoop:Okay.

1:00:10Jenny Just:Yeah, take us through. Almost three years ago now, we co-founded the ARC Prize Foundation, me and Francois Chollet. The ARC Prize Foundation has a mission to be the North Star to AGI. So our job, we have two of them. One is to help be a useful public sense-finding tool for the public to understand how close, how far are we towards AGI or not. And the second is to inspire progress towards AGI. ARC is a series of benchmarks that help highlight what are some of the large remaining gaps between what Frontier AI is capable of and what humans are capable of. And we sort of target that gap. That is sort of our definition of ultimately AGI is, you know, we produce an ongoing series of benchmarks, continually studying frontier progress.

1:00:54Jenny Just:And, you know, at some point, we are not going to be able to do that job anymore. We will run out of ideas. You know, we'll test frontier and say we can't find anything else, any more gaps. And I think that'll sort of be the moment when I think it becomes commonly accepted to say, OK, yeah, we've got AGI now. And today we are announcing and launching the newest, best version of Arc AGI 3. It's the latest in the series. This is a really large format change from the first two. ARC 3 is designed to test agentic intelligence. And it is, as far as I am aware, and I've been sort of interviewing folks all over the AIC in the last few weeks, the only unsaturated general AI agent benchmark in the world.

1:01:32Jenny Just:The headline score is human score 100 % and AI less than 1%.

1:01:37Mike Knoop:Okay. I unpack that like launch because I my conception of Arc AGI v3 is it's almost like a 2d game. It's no longer the puzzles where I'm picking colors to match a pattern. It's actual moving arrows on the keyboard. I'm stepping on triggers. I'm opening doors switches that type of thing. And I played it with you on the stream months ago.

1:02:06Jenny Just:You helped us launch our preview several months back. Okay, so that was the preview. Today we got the full data set launching today.

1:02:12Mike Knoop:Okay, so does that mean more, I'm going to call them games, more actual levels launching? Or is this that what you're launching is like you did the actual benchmark and got the four leading labs to devote the compute and actually open up their models to be able to interface with the system to get the scores?

1:02:32Jenny Just:Both things, actually. So today, on the benchmark side, the public version of the benchmark is, I guess, the overall benchmark. So over 100 games, nearly 1 ,000 different levels across these game-like environments. I think it's fair to call them games. We've designed them to be fun, and games are fun. I think you could look at them from a research standpoint more as environments, though. These environments are intended to test whether AI can effectively explore, discover its own goals, acquire strategy, develop plans, execute its plans. One of the really unique things about Arc 3 compared to the 1 and 2 format is that it is interactive now, whereas you mentioned 1 and 2 look like these kind of static IQ puzzles that were on a page.

1:03:14Jenny Just:3 challenges both humans and AI to essentially figure out the goals themselves. When you're dropped into one of these environments, your only goal explicitly is to win. And so in order to figure out how to do that, you have to actually dedicate some explanation to figure out the rules, the mechanics, the strategy. And one important thing is you're sort of playing these environments, the strategy mechanic, they grow and they evolve and they change over time. And this is one of the reasons I think ARK3 will be a really useful tool for understanding agentic intelligence this year. I think it'll be our first real test or, you know, seeing early progress on these AI systems that are able to do on-the-fly world modeling, some degree of, like, on-the-fly continual learning.

1:03:55Jenny Just:These are both, like, critical capabilities that we view as missing today that ARK3 tests for. Okay, take me a little bit deeper on,

1:04:04Mike Knoop:you said there's 1 ,000 games or 1 ,000 levels?

1:04:08Jenny Just:A few over 100 games across those 100 environments, nearly 1 ,000 levels across all of them. Yeah, it's a much larger version of the benchmark than we've ever had previously. And then, like I mentioned before, the other major thing we're announcing today is Frontier Scores. So the benchmark is launching. We're also publishing, as of today, They built the latest four models across all the four major labs. And yeah, I think Soda is currently sitting at like 0.3%, 0.4%. Yeah, I think I saw Gemini 3.1 Pro.

1:04:41Mike Knoop:Maybe there's an extra hyphenate on there. But basically, the Gemini, Anthropic, and OpenAI were all in the 0.2, 0.3 something. And then Grok was, I think it's 0%. And walk me through the actual build out of these hundred games. Is this entirely human done? Is there some sort of computer aided tooling to insert variation programmatically? Or is it important that they're all created by hand? How do you think about the creation?

1:05:15Jenny Just:I wish we could use AI to help design games. We'd be able to make the benchmark even better. The reality is like humans are still the bottleneck on creativity. And so every game has still been handcrafted and hand designed by humans. You could sort of imagine if you were embedding all these different levels on like a big manifold, you know, in an embedding, you'd want them all as far apart as possible in that sort of space. And today, still humans are kind of the limiting factor in terms of ensuring that, you know, every game is different and is novel from each other as possible.

1:05:45Mike Knoop:Yeah.

1:05:45Jenny Just:There's a few interesting design changes, actually, from a benchmark standpoint compared to one and two. Maybe the largest is, you know, our studies, the frontier progress. We have to design our future versions of the benchmark to adapt to changing frontier progress. One of the design goals with one and two was we have what's called a private and a public test split. We have a public version of the benchmark and a private holdout version, which is what we actually use to verify the performance of frontier models.

1:06:15Mike Knoop:So the frontier models get no freebies. They don't get anything from the public set. But they can train on. You can't memorize the public set, right? Or they can experiment on the public set from a prompting perspective, maybe? Yeah.

1:06:28Jenny Just:The idea is the public set is intended to demonstrate the format. Okay. And this was similar with Arc 1 and 2. However, we held a design goal that the public sets and the private sets were what's called IDD with each other. Basically, that they are supposed to be as close as possible to each other, and it's just split along visibility. Some are private and some are public. Sure. One of the big advancements with AI reasoning is this is actually not a very useful way to run benchmarks. AI reasoning systems are so powerful now that they can actually generalize across IDD test splits. And this is what we saw with Arc 1 and 2.

1:07:01Jenny Just:So with 3, one of the big design decisions is we're actually releasing fewer games into the public demonstration set. So there's only, I think, about 25 games that are in the public set. We're actually explicitly not even calling it a training set anymore. or we're calling it a demonstration set, just to show the format to humans, be able to test your systems to make sure you can create them, get a feel for them. There's obviously fun marketing value in being able to play the games as humans too, which we really love. And on the private set, this is the set that's over 100 games. They're specifically different.

1:07:29Jenny Just:We design them with different characteristics, different goals, different intelligence capabilities required to beat them, the difficulty, the acceptance criteria is more extreme between human and AI performance, all to hopefully produce the most useful high signal benchmark towards whether we actually are getting real progress for DGI with the foundation models. So let me pitch you a strategy.

1:07:54Mike Knoop:If I have access and I'm at Google or OpenAI or Anthropic and I want to do well here, can I take the public set and create a log of all the steps and all the reasoning chains and all the keystrokes that are required to pass those levels and then sort of like dump that into the context window before I go off into the unknown.

1:08:22Jenny Just:And train your model that way, basically?

1:08:24Mike Knoop:Maybe train my model, but also I'm just wondering if that's helpful for setting up the context or like doing some sort of like pre-compaction of the strategies that are learned. I see. Maybe not even training a custom model because I feel like that would maybe be like bench hacking. I'm more thinking about just like, okay, we went and we played all the public games to completion. And we monitored them, screen recorded them, tried to extract as many learnings as possible into an MD file, basically. And then we include that in the prompt that kicks us off to sort of bootstrap the learning once we get into the unknown environment.

1:09:06Jenny Just:If we've done a good job on the benchmark, you should not be able to train a system on the public set and perform well on the private set if we've done a good job. Obviously, every benchmark release, it's an experiment. We make contact with reality. We ship these systems, put benchmarks publicly. We try to analyze the performance, understand what they're good at and bad at, and evolve future versions of the benchmark. But intentionally, no. And this actually is very closely related to another design decision that we're making with our scoring function going forward this year. And this is, again, in response to AI progress that we've seen.

1:09:35Jenny Just:Our scoring methodology is basically EGI-pilled at this point. We, going forward with V3, are using as... I kind of have this idea of basically a philosophy of having essentially no harness. We want to create a testing experience that's as similar as possible between the human and the AI test takers. When we have our human baseline, when we have literally a testing center in San Francisco had hundreds of humans play these games. All they're given is you have sensory input through your eyes and action motor output through your hands back into our testing interface. And all of the intelligence happens between those two steps.

1:10:16Jenny Just:And so we try to emulate that as close as possible for our verification function, where we have this sort of philosophy of having a very stateless client so that our scoring function basically tries not to introduce any kind of bias, any kind of help, any kind of maybe potential cheating strategy. If you go read our prompt, it's extremely simple. It's like, you know, you're playing a game. Here's your actions. Your conversation will be carried forward to the next turn, and that's it. In order to, again, kind of produce this really clear signal towards when the real progress towards AGI and the base intelligence layer were able to detect that.

1:10:46Mike Knoop:Okay. So take me back through history a little bit because I'm surprised by why AI is struggling with this in particular. because I remember it feels like almost a decade ago that OpenAI had a product, I think it was called Gym, where they were able to beat Mario and then they beat the Dota team, Dota 5. And they were able to do things that I can't do. I certainly can't beat Lisa Dahl in Go. I certainly can't win Jeopardy or any of these things. And yet AI systems were able to dominate those games. You've created new games. What's different about the games or the strategies by the AI labs where we're not matching up like we did in the past?

1:11:35Jenny Just:I think the biggest thing is the expectation of what constitutes real progress towards HCI. When labs were using games in maybe the 2016 to 2018, 2019 era when they were very popular, human researchers are studying the games, trying to understand the failure modes of machine learning, deep learning, trying to build custom search harnesses and feedback mechanisms from the environments. It's very, very handcrafted. It's loaded with what I'll call human G in the research process. We're now at a point where we want to control for that, actually. We want to control for as little human G in these systems as possible.

1:12:14Jenny Just:We want to understand, can AI do what the human researchers were doing back in that era in order to beat those games? that they had never been trained on or exposed to before.

1:12:23Mike Knoop:Oh, interesting.

1:12:23Jenny Just:So I do think it's kind of elegant that, you know, we are coming to find a full circle where games are these very minimal representations of like actually important capabilities that humans possess around exploring and developing strategy and world modeling and being able to learn on the fly. They're really, they're really elegant as far as an environment goes. But I think what's changed is our expectation of how much human crafting is needed in order to learn the games when they haven't been specifically trained on them is the big difference today, especially with Arc 3.

1:12:52Mike Knoop:Okay. Remind me of some more history, but more related to Arc. I remember with one of the Arc AGI benchmark tests, there was a version of a model from OpenAI that was running on some sort of like extra high mode. And I seem to remember like$2 ,000 per task being cited. Yeah, O3.

1:13:11Jenny Just:Is that what it was? A very big launch. Okay. Yeah, that was like a preview of O3 in December of 2024. for. So really the first, you know, there's a great chart on the ArcPrize homepage now where you can actually see those data points so clearly. I think one of the really, like I mentioned before, one of our missions of the foundation is to try and be useful public sense finding tool. And I think, you know, when we first launched Arc 1 and 2, you know, it was a very common critique. It's understandable. You know, hey, these things look like toys. Are they really economically useful? Are they going to lead to any real progress?

1:13:41Jenny Just:And now in hindsight, I actually think that's a pretty outdated view because we have pretty strong evidence that ARK held quite strong predictive power of noticing really important AI moments. We only started seeing saturation on the V1 benchmark. And remember, V1 was like five years old. We only started seeing any amount of progress from LLMs on V1 once we got AI reasoning, which was a really critical innovation, I'd argue, is as important as the original transformer innovation. And then a year later, this was four months ago now, with the November, December 2025 class of models with GPT-5.2 and Opus 4.5, we again started to see saturation on Arc v2, and it precisely correlated with this agentic coding capability that emerged.

1:14:21Jenny Just:So I'm optimistic that Arc 3 will again be a very useful predictive tool to understand when basically AI agents are capable of operating in more open-ended environments. Right now, you need a lot of human handcrafting to get these intelligence systems to work in domains, such as coding, right, with cloud codecs and code. Or, sorry, codecs and cloud code. And I basically expect that, like, when you are doing very good on V3, which will mean, by the way, 100 % score on V3 means, like, AI can sort of beat all the games as efficiently as humans can on an action basis. That will lead to economically useful systems where agents are able to operate in more open-ended environments that they have specifically trained on.

1:15:01Mike Knoop:I still remember from ArcGIS 1, you see these three by three grids, and the first time I ever tried it, I tried on my phone, and I think my phone was in some weird landscape mode or something, so it wasn't rendering correctly, and I was like -

1:15:15Jenny Just:You didn't even get all the data points.

1:15:16Mike Knoop:Yeah, no, so normally it's like you see the blocks, and then you see the blocks to the left and the right, and then I was like, wow, I'm like, I'm cooked. The fact that other people can do this, but of course, once you load it on desktop, it's very usable. I want to continue down that path of the 03 extra high. Like, what are you seeing from the labs that put forth models that did test on ARC AGI V3 in terms of just steering the models? Because we talk about GPT 5.4, but that means a lot of different things these days. Was this in the max reasoning? Should I compare this to what I'm seeing in chat GPT?

1:15:59Mike Knoop:I'm getting more and more drop downs where I can go. Oh, I can go pro and then I can go extended thinking mode Yep, is it is it an off-the-shelf model or are they able to sort of come to you and say hey We want to we want to actually Marshall ten times the amount of compute for this particular challenge

1:16:16Jenny Just:On our verification leaderboard. We have a new testing policy It's actually something we did have with one and two Introduced after the three where we limit to ten thousand dollars per verification run. Okay, this is somewhat of a practical like consideration If we actually used the most expensive, highest million context window, the most expensive model, I think testing of the full V3 private data set would be like$100 ,000, which is just kind of silly, right?

1:16:42Mike Knoop:Yeah.

1:16:42Jenny Just:So we set a reasonable limit. Humans, nowhere near as much as dollars to produce the same performance.

1:16:48Mike Knoop:I like that, too, because that is like getting AGI and it's like, yes, it can do anything, but it costs$50 million per prompt to do one hour of human labor. That's not really economically valuable. And so bounding it makes less sense. I think you want to know progress, right?

1:17:05Jenny Just:And I think$10 ,000 is a reasonable amount of money where you will actually see some degree of progress, and that will be a useful signal to start paying attention to it more. And it's like just, for practical reasons, we just can't. We're a strapped nonprofit, so we have to be sort of thoughtful on our sort of money, on how we deploy things. Well, good luck. So I think the high reasoning mode is the most we used for the official verification stuff that we used today.

1:17:26Mike Knoop:So, I mean, do you spend a lot of time thinking about your own AGI timelines? Has your work at ARK shifted your timelines at all? Or do you feel like, oh, I've always been a 2035 guy. I'm still a 2035 guy, something like that. Like, do you have an internal model of this? Or is that even useful these days?

1:17:45Jenny Just:I, instead of listening to my predictions, you should probably follow our actions as our best sign of a sort of view of progress. I think the reality is we have made tremendous progress with their reasoning over the last 12 months. Arc is operating to bring the next version of the benchmark. We've already started work on v4. We actually have plans written down already for v5 as well. Our intention is to bring these to market annually over the next two years. And so that's sort of our expectation of having the next version ready right now. Yeah. Now, like, will we actually launch them? I think we'll have to just see where Frontier Progress is.

1:18:25Jenny Just:We want the future benchmarks to be as useful as possible. And so if there's like still a lot of utility and scientific value in the current version of the benchmarks, you know, we want to keep focus on those. But to the extent that like the scientific value is starting to wane, we want to have the next version ready that has sort of like identified, hey, are there other interesting remaining large gaps between what humans can do and AI can do in order to drive that gap to zero? Again, we're a very AGI-peeled organization. We want to see progress. We actually love seeing progress. Part of our goal is to inspire as much progress as quickly as we can to get to these AGI systems.

1:18:58Jenny Just:That's the operating view. A common question would be, is V3 AGI, is V4 AGI, is V5 AGI? The honest answer, and this is something I've actually learned, I had a different view of this maybe three years ago, the honest answer is no single version of any benchmark is ever going to be AGI. I think the frontier of progress is a moving target. And our job is to understand the gap, the remaining gap. And the definition of that gap is going to change as time goes forward in order to keep chunking up what are the largest pieces of that gap that we can find that are interesting, that identify some missing important capability that humans are able to do and produce benchmarks that showcase that gap.

1:19:36Mike Knoop:Last question, I'll let you go. What's going on with the Pokemon bench? That feels somewhat related. Similar tasks. What are you learning from that? How are models becoming so good at that? It feels like they aren't specifically RL'd on Pokemon, and yet they're learning. But also, there's a massive amount of written text about what to do at every level in Pokemon. Are they just learning that from the pre-training corpus? What's your thesis on Pokemon?

1:20:05Jenny Just:It certainly seems helpful. If I use our experiencing developing ARC as a tool to draw a sense finder on this, we have seen more understanding from the latest generation of AI reasoning systems over the last three months than we saw in the first six months when we were developing Arc v3. I think you can kind of fork, you can almost split the research problem of agents into two things. You can split it into a problem that says, can an AI agent effectively perceive some kind of environment state, apply a strategy that's written down to produce actions and successfully execute a plan? That's half the equation.

1:20:49Jenny Just:The other half of the question is can you have agents that are effectively able to develop what that plan is? And to do that, you need to be able to on the fly build a world model of your task, acquire goals, create your strategy, create your plan. We've seen a lot more progress on the perception through strategy to action problem than we've seen on the the exploration problem, the strategy generation problem. And I actually think this is one of the areas that I would point interested arc three researchers at because I think it's a lot more greenfield and will unlock a lot more progress, even on, you know, things like Pokemon bench, where it's kind of coming down to like, okay, we know they can sort of, or I should say at execution, the exploration and planning step is still where there's a large degree of bottlenecking still, still happening today.

1:21:35Mike Knoop:Well, congratulations on the progress. Where can people find it? How can people participate? How can people help out?

1:21:43Jenny Just:Yeah, go to arcprize.org. You can play the games as humans. Like I said, we've got almost 25 of them, I think, on the site. They're all designed to be very fun. We were closely controlled for this, actually, when we were doing human baseline testing. So that should be fun. You can have fun. And you can also get details there. Enter ArcPrize 2026, our new$2 million prize pool this year that's on Arc2 and Arc3.

1:22:04Mike Knoop:That's amazing. Yeah, our teammate, Tyler Cosgrove, was climbing the human leaderboard for a while. I imagine he's been knocked off, but we'll have to get him back on top. Thank you so much for taking the time to come chat with me. This was fantastic. We'll talk to you soon. Have a good one. Let me tell you about Gusto, the unified platform for payroll benefits and HR built to evolve with modern, small, and medium-sized businesses. And let me also tell you about Turbo Puffer, serverless vector and full-text search built from first principles and object storage, fast, 10x cheaper, and extremely scalable.

1:22:33Mike Knoop:And without further ado, we have our next guest, Nathan from Airstreet Capital, coming in to the TBP and Ultronome. Nathan, how are you doing?

1:22:40Nathan Benaich:Great. How are you doing, John?

1:22:41Mike Knoop:Thank you so much for staying up late. What time is it there? 7.25. Okay, not too bad, but past the work day. Reintroduce yourself. It is your second time on the show, but reintroduce yourself and give us the news.

1:22:55Nathan Benaich:Yeah, I'm Nathan. I started a venture capital firm called Airstreet Capital in 2019 to invest in AI-first companies. and uh what year were you investing in ai well so i started the firm in 2019 but started investing in ai in 2013 which was probably around the time that like deep learning was still definitely cooking only in the lab and yeah most people didn't really care too much outside of it yeah

1:23:18Mike Knoop:what were the median deal like what was the median deal like in 2013 was that like uh recommender systems like we're gonna bring netflix recommendations to everyone like that type of thing?

1:23:32Nathan Benaich:Yeah. Well, it was e-commerce, recommendation systems, ad tech. Big data was the buzzword back then. Sure. A little bit in finance, like insurance underwriting, like loan prediction, credit score, fraud detection.

1:23:48Mike Knoop:Just like a big I guess it was like, were they doing deep learning yet? Or was it mostly just like... Yeah, they were.

1:23:56Nathan Benaich:I mean, it was 2013 was the year that computers started to be able to recognize images better than humans. Andre Carpathi was the infamous human benchmark on ImageNet in 2013, PhD. That's right. So that was the year when basically Alex at the University of Toronto built AlexNet, which was the first deep learning system running on NVIDIA card.

1:24:21Mike Knoop:Yeah, what a remarkable time. So has it been easy? I mean, you just raised a new fund. Has it been easier to pitch this to LPs? What have been the challenges and opportunities over the last few years?

1:24:35Nathan Benaich:Yeah, I mean, it's been a sea change. Like in 2018, when I started for AirStreet, it was like I'm by myself. So solo GP, super contrarian, starting in Europe where risk aversion is extremely high, trying to focus on AI, which most people didn't really care too much about. And then first time fun. Those are sort of like all the worst, like buying. selection criteria that one would have. And then, yeah, I think this is very much like a long-term journey. I set out with Amadie's early-stage investments, be high conviction, invest in biotech, defense, vertical software, dev infra. I stuck with what I said, so investing in Synthesia, 11, Black Forest, and others.

1:25:20Nathan Benaich:I'd like six exits to recursion and a company I went public and Amazon, et cetera. And then, yeah, first fund was like$27 million. Fund two was$121 million. About three years later, again, pre-chat GPT. And then this one's$232 million, which at this point makes us the largest solo GP in Europe.

1:25:42Mike Knoop:That's amazing. So us, you said solo GP, but you said us. Who else is on the team?

1:25:48Nathan Benaich:You know what? I'm kind of guilty with the Royal We thing. Okay. But I have two colleagues who run talent and operations and then a pretty sizable back office for like admin.

1:25:59Mike Knoop:Sure.

1:26:00Nathan Benaich:But everything that comes along with like building brand, finding founders, investing, fundraising, that's all me. And the decisions are at the plate.

1:26:07Mike Knoop:And then also, is it the annual report, state of AI? I mean, it's sort of a huge project. Do you bring in collaborators on that?

1:26:18Nathan Benaich:Yeah, that started in 2018 to basically create like a kind of canonical open access document covering research industry, politics and talent. There are a number of contributors every year who are sort of like at the coalface during their PhD or like transitioning between roles in AI labs who help us kind of stay smart on things. And also folks who've been working on policy because it's become increasingly important as we see in the news almost every day. and then the cool thing is like I get contributions from companies and labs and researchers every year and like I think this last year when we last talked there was like 50 people in the Google Doc kind of like leaving comments being like hey I tried this implementation this paper like I had this problem and then some other person's like that was my paper this is what I tried and it's like cool like community document basically where we can kind of get to the center of truth

1:27:08Mike Knoop:not to call you like lucky on timing it's very fortunate that you have the size of fund that you do for where we are in the market cycle but how hard would it be to do what you're doing today with a 27 million dollar fund because it feels like a 20 27 million dollars like a seed round for like a you know startup with just an idea sometimes that's like one one one percent of the of the seed round uh but like is it can you even make plays with that size fund if that's what you were constrained to today

1:27:40Nathan Benaich:I think you have to decide like what I did which is either you want to be like a main player and lead rounds and express your conviction and be early etc or you play the like large portfolio model and then you have checks and a lot of opportunities and for me that job is like much more of like a network SDR style job and less of like I can make my own opinions like do the research be there early and then when I like something like really make the bet. I don't think you can do the former. Be a lead investor in$27 million, no chance. I think you can do the larger portfolio, chipping into a variety of rounds and still have good performance.

1:28:17Nathan Benaich:But it's just a different job that I don't particularly enjoy and doesn't maximize my strengths and my interests as much. I think at the end of the day, you've got to pick what flavor is good for you and then try as best as you can to bring the best product to the market given your circumstances. And I was fortunate with Fund 3 to be able to really come with a blank slate with long-term partners and say, this is what I think is going to be the most convincing model, right up to$15 million in first checks and do a couple of growth stage rounds up to$25 million. But still, high conviction, 20 companies.

1:28:52Nathan Benaich:And of course, I'm mostly based in Europe, but still invest in the U.S. and spend decent time there as well.

1:28:58Mike Knoop:Yeah, I mean, I know you're in Europe, but you're not an exclusive European investor by any means. But I am interested in the thought exercise of like, where is the AI opportunity internationally? If I were to just back of the envelope bit, I've seen some of the sovereign AI efforts. It sort of makes sense that like a certain government might want to buy from a particular local lab. But at the same time, like, you know, Google has been very successful internationally. And, you know, China got the Google of China, but many other European countries didn't get the local Google competitor or the local Amazon competitor or the local Microsoft or Apple competitor just because, like, they were consumer products and consumers kind of flow wherever they want.

1:29:46Mike Knoop:But at the same time, I can imagine if Google or OpenAI or Anthropics are going to build a data center, they might want to go to a local neocloud. Or there might be opportunities for the Harvey of some other country that has different laws and different rules. So how are you seeing the shape of opportunity outside of America in AI?

1:30:07Nathan Benaich:I think you covered it really well. And I would generally agree with you on this. Europe doesn't need its own Google, per se. And in fact, historically, like the government has tried, there was Quero and one or two other initiatives that, you know, had hundreds of millions of dollars pumped into them so they could capture European culture better than Google could. And I think that's a bit bizarre when you're talking about a learning machine. But so there's certainly some sectors where I think like the sovereignty like really matters and it's not just marketing speak. So, you know, defense and security is clearly one where, you know, Europe woke up to this like two years ago and now even more so with the Middle Eastern war that's ongoing.

1:30:45Nathan Benaich:You know, as an example, I got invested in a business called Delhi and Alliance Industries doing defense, autonomous defense systems, right, in Greece. And one of the number one things we got from people outside of Greece, particularly in the U.S., is like, why are you investing or building a company in a vacation resort that I go sailing in, you know?

1:31:01Mike Knoop:Yeah.

1:31:02Nathan Benaich:And then that narrative changes significantly once you start seeing Shahid drones hit UK bases in Cyprus and you realize, okay, the border to southern Europe actually comes over the Mediterranean, Greece. I think the other part, which is interesting, is ambitions change. And I think in Europe where traditionally there's been fewer role models that one can look to and say, I'm going to be like that person and I know the path. some companies grow and you know for example I think Legora originally started as Leia like started in Sweden right and it was the idea hey we should do this locally in Sweden and and now like clearly that company's ambitions are like now we can go head to head with Harvey

1:31:45Mike Knoop:yeah yeah it does feel like in Europe like the the entrepreneurs that break out they're not saying I'm building x for Europe it's like I'm building 11 labs I'm gonna go everywhere I'm building Spotify and I'm going to go everywhere. And yes, I happen to be from some other country and I'm going to have a headquarters there, but get ready in New York because we're going to have a headquarters there and we're going to have an engineering hub in SF and like, we're just going to be an international company and have our roots there. Uh, and that's the right path.

1:32:10Nathan Benaich:Yeah. So this is why I think if you're going to invest in Europe, it's really important to have this foothold and knowledge of the U S market so that you can apply the same quality distribution that you see in the U S over in Europe. And either there are people who start from day one being that ambitious or there's others that grow and kind of, yeah, just like fuel their batteries with ambition as they see and experience it. You know, like when you get success, you want more of it. And so that's like the kind of recursive cycle of the content is going through. Yeah.

1:32:39Mike Knoop:I mean, with all the progress from the big labs and they're at such incredible scale now, like how are you processing the SaaSpocalypse and just advice for founders of like what gets steamrolled versus what doesn't? I mean, there was some founder, we've had a couple founders on the show that have been like, we're doing an AI-generated video social network. And then it was like, you're getting steamrolled. And then it was like, actually, like, you know, Sora's not going to be in the App Store anymore. So, like, maybe that was a good bet. I don't know. I'm not on that particular app. But it feels harder and harder.

1:33:08Mike Knoop:It used to be just like, don't do an app that's just a prompt around the foundation model. Like, that's done. But now we're talking about, oh, is there pressure on CRMs? Is there pressure on databases? is there pressure? What will the labs do? It's unpredictable, but how are you working through it?

1:33:25Nathan Benaich:I think one thing you could say is what are the problem sets and areas that the smartest AI people want to work on? And don't do that. Okay, that's a good one. Don't do coding. After coding, it seems like AI researchers really like AI for science, so don't do that either.

1:33:43Mike Knoop:Totally, totally. We have a friend from the show that does like, yeah, it's an AI company, but it's for like small businesses, like HVAC owners and helping them. It's like, yeah, I don't think that's on the roadmap.

1:33:58Nathan Benaich:That's really good. Yeah, like, you know, I think it comes down to like this tacit knowledge and like where you can capture how people do a task and taste. Like I see this a bit with our job, like, you know, I'm using like, I'm Claude Maxing as well and like Codex Maxing. It's amazing how you can imbue it with your taste and you're like, at some point you realize, okay, we built a learning machine that basically is like a sieve. You can pour as much as you want into it and it'll still learn stuff. Or before it was only one task at a time and forget accumulating multiple tasks. So at this point, if you're really AGI pilled, you have a call, you pipe the feedback in, you ask, hey, how did I do?

1:34:37Nathan Benaich:You get suggestions, you do that on the next one, you pipe it back in, and then you make a skill file, and then next time here's a new opportunity. I'm like, dude, if you're not doing that, it's game over. and so I really do think especially for our job there is a point at which you're like solo GP with like 200 or 300 million dollars with a bunch of AIs so I'll call you in 10 years and see if it works

1:34:59Mike Knoop:I'm excited I'm excited well I want to hit the gong for the new fundraise congratulations

1:35:08Mike Knoop:thank you for coming on the show have a fantastic rest of your day and I will talk to you soon have a good one thanks goodbye let me tell you about vibe.co where ddc brands b2b startups and ai companies advertise on streaming tv pick channels target audiences and measure sales just like on meta and let me also tell you about plaid plaid powers the apps you use to spend save borrow and invest securely connecting bank accounts to move money fight fraud and improve lending now with ai and without further ado our next guest is in the restream waiting room we have rohan dar he is uh a real estate expert thank you so much for joining

1:35:39Matt Hulsizer:the show how are you doing rohan good to meet you yeah happy to be here uh since this is your first

1:35:44Mike Knoop:time on the show, would you mind kicking it off with an introduction on yourself? And I'd love to know some of your background, how you got to where you are today.

1:35:51Matt Hulsizer:Yeah, I am. I'm a San Francisco real estate agent. And I'm, you know, among the highest producers by volume in the city. And I came from a little bit of a traditional background. I did a YC startup. I went to Stanford Business School. I did a bunch of startups and then got into real estate when and kind of learning about Airbnb early on and built a small portfolio of that and then learned the real estate craft from that.

1:36:16Mike Knoop:Did you have to get a license at some point? Did you join a big firm or did you just sort of strike that on your own?

1:36:22Matt Hulsizer:My Twitter account started growing because I was posting interesting houses that I was just kind of curious about. And then people were messaging me like, oh, I actually bought that house you posted about. And so I was like, dang, like someone's making a lot of money off of this and it's not me. So then I like decided to get licensed. And originally I was going to focus on like Airbnb markets and short-term rentals and vacation areas. But I live in San Francisco and I could see the prices were like after the pandemic, just like crashing here while they were shooting up everywhere else in the country.

1:36:57Matt Hulsizer:And I was like, oh, they're converging. And that's, that's like odd to me. And so I was like, okay, well, YC moved here. OpenAI is just sort of like getting traction and the city's getting better. I think everyone was sort of agreeing to that. And then I was like, well, this is the opportunity and I'm getting licensed and like, this is what I'm going to focus on. And then, uh, and then I had a lot of traction with it. So I just sort of got sucked in to be sort of a, you know, full service, like, you know, Rohan in your corner, real estate agent when you're trying to buy or sell a place.

1:37:26Mike Knoop:I love it. Uh, when did the actual rebound start? Where, where, where was the trough after COVID?

1:37:33Matt Hulsizer:um so the interesting thing about like covid was 2020 2021 everyone was leaving san francisco but the prices kept going up because interest rates were like practically zero and there were always liquidity events so prices were rising even though things were looking like a little bit desperate in the city and then when interest rates rose that sort of like tampered the liquidity in the market. And then sort of at very end of 2022, things like abruptly dropped. So 2022, end of 2022, 2023, 2024, prices were way down. And then 2024, by the end of it, there was like a little trickle and 2025, you sort of hit, had come out of the bottom, but it was like a slow, you know, like, pretty stable market, but on the upward trajectory.

1:38:24Matt Hulsizer:And then end of 2025, then it just sort of started booming like crazy in terms of pricing. And then even from like, you know, March, 2026 is like way up compared to like two months ago.

1:38:36Mike Knoop:So, so yeah, what does it actually take to raise a family if you're working at a tech company in San Francisco? Because I think a lot of people will move to suburbs, but walk me through, you know, if you're coaching someone that has a couple kids, they want schools, they want access to their employer. How should they be thinking about what it takes to find a great place in San Francisco these days?

1:39:01Matt Hulsizer:I don't even know if people think of it that way. I think it's like San Francisco is just such a scarce place in all ways. There's not enough housing, there's not enough restaurants, There's not enough this or that. And it's sort of like, if you want a place like in San Francisco, you're like so convicted on the idea of it, of the city, of like the tech industry. You're like, you know what? I'm just going to like do this and then I'll figure the rest of it out. And so like, I don't think people are like, oh, now I have to figure out like what school my kids are going to go to or like what my commute will be or this or that.

1:39:36Matt Hulsizer:It's like, if you're sort of like dilly dally around the edges, you sort of end up never really sort of being so committed and that kind of ends up being like what makes it hard to buy a place but like the people that like actually win these uh homes whether they're like you know any price point it's it's like there's something mentally inside them that's like this is the place for me and what does the the like the down the fairway place in san francisco look like these

1:40:03Mike Knoop:days is everything over two million three million like where are we in terms of like single family

1:40:09Matt Hulsizer:Kind of trying to find a place that would fit four people and might have parking and a second bathroom and two or three bedrooms. Say like a year ago, it was like around$2 million. And then if you were slightly above that price, there'd be like a big drop off in competition. And now it's like that level has sort of definitely moved up to like$3-ish million. But the bigger change, too, is that there's a huge level of competitions at any price point now. If it's like one that sort of checks the box for buyers.

1:40:42Mike Knoop:So give me some advice if I'm trying to win one of those competitions. What do I have to do? I have to show up with all cash, just put the cash in the bag. What do I have to do?

1:40:50Matt Hulsizer:I mean, in any given offer process, there'll be a decent number of all cash buyers. So it's not like you can walk in and be like, oh, I'm going to win this because I'm all cash. Assume like a third or half might be over a certain price point. And like, I think what you sort of have to realize is there's going to be a range of competition on any given house. So like some houses, you know, this could be like a five or six million dollar house, so pretty expensive house. And there might be like 15 offers. Whoa. And like the seller's not like going to just sell it to you because you're a cool guy.

1:41:25Matt Hulsizer:Like they're they the market will sort of dictate the price. And unfortunately for buyers, you just have to say, you know, the highest price in the best terms to win. OK. And so what you're sort of trying to navigate is the level of competition any one house is going to have. So say it doesn't have as many bathrooms as you want, but you could figure out how to add one. Or say it's off-market and only a few people know about it, so there's less competition. So your lever of getting a good deal on a house isn't just participating in a massive auction. It's trying to participate in an auction only you know about or a smaller, a different kind of property.

1:42:04Mike Knoop:And you're probably expecting it to go a lot higher, I imagine, with IPOs. The labs are getting bigger. There's more liquidity. There's new investment rounds happening. What's your forecast? Well, obviously, it's hard to predict the future.

1:42:21Matt Hulsizer:But I wasn't like, oh, I'm a San Francisco real estate agent. I'm going to say whatever. I decided to get into the market because I thought this was going to happen. I was like, oh, these scarce homes are going to become more valuable and people will wish they bought them and I should focus on this. Personally, I'm convicted. The city is on the right trajectory now, so it's not contrarian to buy a place here at the moment. Then there are liquidity rounds, and that has made a big impact on the market. If the liquidity rounds get bigger, like there's, it's a fixed number of homes that the, you know, that money goes into.

1:43:01Matt Hulsizer:So.

1:43:02Mike Knoop:What do you think, uh, expansion looks like over the next few years? Are we going to, I know Mill Valley's booming. There's other suburbs. Is Oakland going to happen? There's this California forever development that's happening. That's further out. Like, uh, are you starting to broaden your horizons or do you want to stay focused? And what do you think the real estate buyer will want to do in the near future?

1:43:21Matt Hulsizer:So I solely focus on San Francisco, like buyers and sellers. Because I found that every time, especially on the buyer side to win, it's sort of like pulling off this mission impossible heist where it's so elaborate. And you have to know every detail about the market. And so for me personally, I feel very strongly that I can really help people in San Francisco. That makes sense. And then if you put me in Mill Valley, it's like, oh, I mean, maybe it's good for me to help serve Mill Valley customers, but it's not good for them. So I think if you're going to use a real estate agent, you should use one that really knows a particular market really well.

1:44:01Matt Hulsizer:So for me, I want that to be San Francisco. Yeah.

1:44:04Mike Knoop:How much of the San Francisco boom is attributable to the labs being based in San Francisco, like specifically, as opposed to the previous generation of tech boom times happening in Menlo Park, Cupertino, sort of on the peninsula?

1:44:22Matt Hulsizer:Yeah, I'd say it's about 50-50 explaining what's going on. On one hand, what's really driving it is the perception that the city is on the right track with the mayor and walking around. It just feels better, and it feels fun, and people are moving there. It sort of regained the zeitgeist of a place you move to invent the future. So I think that's half of it. And then the other half of it is, yeah, we've had very successful companies in San Francisco, tech companies, but we never had the big one like Meta or Google or Apple. And now we have two that just started that are within that range. And it's somewhat unprecedented, I think, even though we've had$100 billion companies before.

1:45:06Mike Knoop:Yeah, there's been Salesforce and Twitter, but this is at a different level, an order of magnitude. And so that's just going to drive up attention and excitement and all sorts of things. What are the most underrated neighborhoods? What's on the come up right now?

1:45:21Matt Hulsizer:You know, everyone sort of really wants like Noe Valley, Pack Heights. Like I think if like if you're sort of like looking in the Noe area, like Bernal, like the kind of the hills right next to it, Glen Park, like, you know, Sunnyside is like dramatically less expensive. And like Pack Heights is now like getting to be like back to its sort of premier level pricing. But Russian Hill is like right next to it and like a little bit less like walkable and this, you know, but like, you know, just as great. But now the prices are up there and then like Knob Hill is next to that and the prices are still a little bit down there.

1:46:00Matt Hulsizer:So maybe I'd say Knob Hill and, you know, Bernal Heights.

1:46:06Mike Knoop:Well, where can people get in touch with you? How do people reach out if they're looking to?

1:46:11Matt Hulsizer:Yeah, I mean, they can Google me, Rohan Dar, and then find my email or just reach out to me on Twitter. And I'm pretty active there. And generally, I just share what's going on in the market over there. Fantastic.

1:46:22Mike Knoop:Well, we appreciate you taking the time to come chat. Thanks so much.

1:46:25Matt Hulsizer:Yeah. Have a great rest of your day.

1:46:26Mike Knoop:We'll talk to you soon. Thank you.

1:46:27Matt Hulsizer:You too.

1:46:28Mike Knoop:Goodbye. Let me tell you about Cognition. They're the makers of Devin, the AI software engineer. Crush your backlog with your personal AI engineering team. And let me also tell you about Graphite. Code review for the age of AI. Graphite helps teams on GitHub ship higher quality software faster. And without further ado, we have Eric Jorgensen, good friend of mine. He is the author, the publisher of the book of Elon. Thank you so much for sending me this. It looks fantastic. And I was particularly, I want to get into the book, but I think partnering up with Jack Butcher on this, deeply underrated.

1:47:03Mike Knoop:He is an incredibly special illustrator, designer. I don't even know what you call Jack Butcher, but obviously he was helpful in this. But thank you so much for taking the time to join the show. How are you doing?

1:47:15Nathan Benaich:Thank you for having me. I'm honored to be here and extremely excited to put this thing out into the world.

1:47:21Mike Knoop:Yeah. Listen to that voice. You got a voice for live streaming. Let's go. The microphone's helping. You got a good setup. It's good to have you.

1:47:29Nathan Benaich:Am I about to get discovered right now?

1:47:30Mike Knoop:I think so. No, of course, you've been online a million times. Everyone knows you. But maybe take me back to a little bit of how you got into publishing, your business overall, the Naval book, and then we can go into the Elon book.

1:47:48Nathan Benaich:Yeah, that's an amazing setup because then I get to shout out Jack Butcher again. Basically, I was tweeting and blogging happily in 2017, and I had been following Naval. I learned so much from him over the years. and I felt like he was putting out this timeless wisdom that was just dissolving into the stream every day. And it just broke my heart that it was going to get lost, get buried so quickly. Yeah, yeah.

1:48:13Mike Knoop:This is the thing with Twitter. It's ephemeral, which is amazing, but there's no rediscoverability. We actually put out this account once, Banger Archive, where we would just share screenshots of old tweets and they would go viral again. But Twitter doesn't, X isn't set up to resurface stuff like that, like YouTube is, like Netflix is. And so the back catalog really goes stale, but you were able to obviously repurpose it.

1:48:36Nathan Benaich:Yeah. I think so many of the great books have this like long fat tale of timeless wisdom that we keep needing to revisit. And Naval was, you know, obviously has done an incredible job distilling that wisdom and articulating it for sort of our era. And I wanted to preserve that in a permanent format. And that side project that I did on nights and weekends and published, you know, hoping to sell a few thousand copies has gone on to sell. I think we're coming up on 2 million and I've given away 5 million more digital versions and 40 languages.

1:49:09Mike Knoop:It's crazy. That's such a huge number. I feel like it's hard to sell a thousand books and you've sold 2 million.

1:49:16Nathan Benaich:That is a, that is an unbelievable number for those that don't have like inside context in the book industry. Like I think the median outcome is like a few hundred and like 10 ,000 is top fraction of a percent.

1:49:26Mike Knoop:Yeah, absolutely incredible. What was the strategy? I mean, Naval has a big audience, but I don't see him pumping this book constantly on his Twitter feed or his X feed. Like how did this book actually get in the hands of customers? Is it like top of Amazon? Is it on the New York times bestseller list? Like how do you even sell that many books?

1:49:46Nathan Benaich:I cannot explain it other than to say it has become like a word of mouth phenomenon. I think it is just so many people tell me they buy it as gifts or they recommend it or they give it to, you know, I know teachers that give it to every class that comes through and it's just sort of, um, it's, you know, who doesn't, the subtitle of the book is a guide to wealth and happiness, like big Tam, right? Like universal human desires. Um, and, and new people graduate into like trying to figure that out for themselves every day. And, uh, I think it is, you know, this really rich, dense collection of Naval, who's a really, really gifted sort of a distiller and articulator of some of the most important principles that make life, make lives successful.

1:50:30Mike Knoop:What, what principles from that book either stick out to you are timeless or maybe even underrated, uh, that you keep coming back to you?

1:50:39Nathan Benaich:I think, uh, I mean the, on the wealth side, like leverage, um, is, is still an underrated one. I mean, you guys are living examples of this. Uh, authenticity is another one that like that word is thrown around so much that it becomes sort of a cliche. Uh, but the people that we tend to admire the most or that are doing the best are a really interesting combination of like excellent, authentic and leveraged, right? Like Jack Butcher is an incredible example. You don't even really know how to describe him. He's like, he's an artist, but he's a contemporary artist in the digital era and he's a really gifted designer.

1:51:14Nathan Benaich:He's kind of like inventing this category of networked art, but whatever he is, is him and it's awesome and it's massively leveraged. And you know, he's doing things that nobody else is doing in the art game. Do you think that being controversial is correlated with authenticity?

1:51:33Mike Knoop:Because if you're not authentic, you can be this very polished one side, you know, many faced thing. You interact with one person in a certain way, another person, another way, you make everyone happy. You're less controversial. As soon as you start wearing your heart on your sleeve, being authentic, you're going to attract some people that don't like what you're showing them because you're showing them the true self. Is there anything there?

1:51:58Nathan Benaich:It's a great question. I bet there's two opposing archetypes. I bet there is a type of person that is extremely inauthentic in how they court controversy for the benefit of the algorithm or just being elevated by being attacked. And I bet there's another set of people that are authentic despite any headwinds or controversy that might come up. And I think the only way to probably tell the difference is to just zoom out and see who's been doing what for how long and in under what contexts.

1:52:29Mike Knoop:So how obvious was it that Elon was going to be the next subject? I imagine that the playbook that you ran, the process that you ran with the Naval book could apply to a lot of entrepreneurs. It's a very interesting style where it's high leverage. I can only think, I can only describe it as high leverage because you're standing on the shoulders of giants, which is like all of the work that they've produced, all of the podcasts that they've done, everything that they have written. There's a lot of primary research there that doesn't necessarily require the same, you know, access and permission.

1:53:11Mike Knoop:And you can do a lot of pre-work, uh, independent before you actually go in. Whereas some other books, it's like, okay, this author didn't even get the interview with the person that they're writing about. Like they could sort of, you know, no one wanted this book to happen and that's a lot harder, right? So, so, so I imagine that the list was pretty long. How did you narrow it down? How did you land on Elon? Why this person? Why this time?

1:53:37Nathan Benaich:Yeah, this is an interesting, it's an interesting type of book. Cause as you point out, like I'm not writing about someone, I'm trying to get out of the way. It's not about my opinion of them. Yeah. My North star with these books is to just be as for the book to be as useful as possible to the reader. I want the reader on every single page to be like, oh my God, this is a great use of time. I got a highlight on every page. I'm getting so much out of this. I feel like I'm getting personally mentored by Elon Musk through a few hours of reading about his most valuable and timeless ideas, right? And I think for those of us in tech, Elon's been interesting for a very long time.

1:54:10Nathan Benaich:And over the last five, six years, he's become more controversial. but inside tech, before he was a household name, he was the most ambitious person in tech, and nobody knew how that story was going to end. He was running on a very thin tightrope for a really long time with both Tesla and SpaceX. And more recently, people have started, I mean, Mark Andreessen and Brian Armstrong, maybe most famously, have started asking the question, how does Elon do it? Why is he an outlier among outliers? And I wanted to answer that question, And I think this book does that in more ways than I anticipated at the outset.

1:54:52Nathan Benaich:Right. Like there was some interesting stuff that everybody kind of knew would come in and there's like the greatest hits and then there's the back catalog and then how it all comes together is actually like what's really interesting. Yeah.

1:55:03Mike Knoop:I remember in college, someone called me and was like, oh, I heard about this, this entrepreneur named Elon Musk and he runs two companies, SpaceX and Tesla. And I was like, of course I know about that. I'd learned about it like three months earlier. But it really was a very controversial thing to do. The timeless wisdom is like focus, focus, focus. How have you perceived Elon's ability to be like the exception that proves the rule versus a pattern that might actually be more replicable than people think if they just adopt a particular stance in how they leverage what they're capable of to build multiple companies simultaneously.

1:55:49Nathan Benaich:Yeah, there was a period where Jack Dorsey was running two companies. There was a period where Steve Jobs was running two companies. And there's plenty of companies that are collections of meaningfully different companies kind of under one name. I think it's kind of hard to extricate what does run the company mean? really, on a day-to-day basis. And who is around and who's running different functions? Like Elon running a company probably looks a lot different than Steve Jobs running a company or than Bill Gates running a company or Mark Benioff. The motions that he dives deeply into are very different kind of on a per-leader basis.

1:56:31And there's an element of this that like,

1:56:35Nathan Benaich:Naval points this out, I think it's super interesting. He's like, you are probably working harder on your company than Naval is or than Elon is working on any one of his companies just because he has this divided attention. So let's just say he's working 80 hours a week, but he's only working 30 hours a week on SpaceX.

1:56:50Mike Knoop:Yeah.

1:56:50Nathan Benaich:Like, how is he able to have orders of magnitude more impact in those 30 hours than you're having with your 70?

1:56:58Mike Knoop:Well, it is sort of interesting, maybe ironic that his main competitor over the last two decades has been Jeff Bezos at Blue Origin, who's also running two companies. Yeah, and retired. Yeah, I mean, now maybe more focused, he's retired. But there was a long time, like a full decade, where Jeff Bezos was running Amazon full-time, and then Blue Origin was the halftime or side project. And Elon sort of didn't have a direct, like, full-time, you know, by-the-book entrepreneur just building a direct competitor in that one space fully focused. So, I don't know. Maybe that's luck. Maybe things play out differently if there was someone in that space.

1:57:38Mike Knoop:But it's clearly worked out.

1:57:42Nathan Benaich:We kind of end up conflating, like, Elon the person. Yeah. Like, Elon the core team around him and Elon the symbol, frankly. and especially at this point in his career he's one of the most leveraged people alive right so we are ascribing to like quote unquote Elon what is actually the effort of tens of thousands of engineers and you know plenty of other employees and fans and supporters and there's beauty to that right like we are humans we rally around people kind of better than we do with symbols but that becomes this rallying like this, uh, this rallying point for people to like organize around the values exemplified by this person.

1:58:26Nathan Benaich:And I think that's, uh, that's beautiful and magical and part of the formula. Uh, but it does tend to like, if you conflate the conversation about the guy with the conversation about the symbol, you end up in this really weird kind of arguments with people. You're not even really talking about the same thing.

1:58:41Mike Knoop:How do you think about the, the thinking in decades concept? You know, it's something that everyone's Silicon Valley says, Oh, you got to think in decades. and then Elon comes out with something that's like 20, 30, 40 years away. And everyone's like, no, we didn't actually want thinking in decades. I want to know something that's going to happen for sure in like five years tops. I'm thinking about this mass driver question. And I'm wondering, now that you've written this book, you've studied Elon, is this a departure? Is he thinking even farther in the future? or has he always been thinking around this time horizon?

1:59:18Mike Knoop:Like how similar is this crazy mass driver on the moon pitch compared to previous eras? I think.

1:59:27Nathan Benaich:It's difficult to predict as are many things, but if his theory that in his acting principle is that the future is arriving ever faster, right? And so things that at our previous growth rate or technology trajectory seemed like they were 30 years away are actually now maybe 10. It is really difficult to adjust for that like recursion factor.

1:59:48Mike Knoop:Yeah. Yeah, that makes sense. Yeah. Well, where can people find the book?

1:59:55Nathan Benaich:Anywhere you buy books. Amazon, barnesandnoble.com, Target. It just came out like yesterday.

2:00:02Mike Knoop:Are you going to do an audio book?

2:00:05Nathan Benaich:Yeah, the audio book's out. I didn't read it. Oh, you got to read it.

2:00:08Mike Knoop:You got this. We'll be up with pipes. Put them to work. Well, Eric Jorgensen, thank you for joining. The book is The Book of Elon. You can go find it everywhere books are sold. And we will talk to you soon, Eric. Thank you so much. Appreciate you. To join the show. Let me tell you about Figma. Agents, meet the canvas. Your AI agents can now create and modify your Figma files with design system context in beta starting today. And our next guests are live here with us in the TBP and Ultradome. Thank you so much for taking the time to join us. How are you doing? Please, since this is your first time on the show, introduce yourself for everyone.

2:00:44Eric Jorgenson:I am Jenny Just, co-founder of Peak Six. Yes.

2:00:47Nathan Benaich:And I'm Matt Holsizer. I'm Jenny's husband and also co-founder. Fantastic.

2:00:51Mike Knoop:Take us back in time. I want to hear the founding story.

2:00:56Eric Jorgenson:Founding story. Yeah. We both grew up on the option trading floor of Chicago and New York. Yeah. And we were at an sort of infamous options trading firm called O 'Connor Associates.

2:01:09Mike Knoop:You were both at the same firm.

2:01:11Eric Jorgenson:We were both at the same firm. But in different cities. Okay. Yeah. So super lucky to be trained there when they did their merger acquisition, UBS. Who was in Chicago?

2:01:20Mike Knoop:I was. Did you ever go to Ceres? Oh, of course.

2:01:23Eric Jorgenson:Still go to Ceres. Ceres is amazing. Yeah. Anyway, it's a bar. It's even kind of modern these days. Oh, yeah? Oh, yeah.

2:01:28Mike Knoop:I worked at Citadel in college, and that was the place where we'd go and hang out, and they'd give you, you'd order like a rum and Coke, and it would just be a full glass of rum. It was crazy. That's right. It was a really good greasy sandwich to go with it. Yeah, yeah, yeah.

2:01:41Eric Jorgenson:Really good. Good fries.

2:01:42Mike Knoop:Okay, so you're in Chicago.

2:01:43Eric Jorgenson:Yeah, so we're in Chicago. Yeah. Yeah. We decided, we started working together. Yeah. Pretty early on. What were you trading at the time? Equity options, both of us were. Equity options. Yeah. And then when they did the original Swiss bank joint venture, we were part of the team that went to start the OTC derivative desk. So there was just three of us. There's a gentleman from Goldman who came in. And so we're like, oh, this is cool. We're in our mid 20s starting a business, you know, an entrepreneur. And when things started going really well and then UBS came in and they were moving to the East Coast, we're like, well, we're not moving.

2:02:16Eric Jorgenson:He had actually just come from New York and my family's in the Midwest. So we're like, we'll just do that thing again. So that thing was to partner with a bank. That was our plan A. And do over-the-counter derivatives. We, 28 and a half years later, we've still never done it. But we did invest really early in tech and education. And so we created a proprietary options trading firm, which is 28 and a half years old that has never had a losing year. Wow. And it allowed us to self-fund all the things we've done since then.

2:02:52Mike Knoop:And what's the secret to such an incredible run with no losing years? Is that risk management? Is that the particular strategy? How does that come together? Because I can't think of another investor who's ever done that.

2:03:06Eric Jorgenson:It's unusual, for sure. Go ahead.

2:03:08Nathan Benaich:It's a secret. I think it tends to be about our approach. Our approach was not to be smarter with our algorithms. It was smarter with our business model. So there are plenty of businesses that haven't had losing years in the last 29 years. They tend to be technology firms that are basically providing a service into the market, which is the approach that we, I mean, we talked about ourselves as Wendy's or Walmart, Walgreens. We're merchandisers. We carry inventory and then deliver it to customers. We're not trying to take the, we're not disagreeing with customers. We're providing a service.

2:03:45Mike Knoop:And then on the investment side, what is out further on the risk curve for you?

2:03:51Nathan Benaich:I mean, I think we've lost money in more ways than anyone you've ever had on this show.

2:03:57Mike Knoop:Collectively. What is the nature of an investment that doesn't pan out? Is it just it's high risk and you know that going in?

2:04:07Eric Jorgenson:Well, there's a wide range. Obviously, in our trading business, it's really systematic. We have an amazing team. We educate kids right out of school into our model. It's really rare that they would leave and be able to do the same thing because it is about the collective. But we started a whole bunch of other businesses, of course. So Peak Six today, based on what Eric was saying in your previous interview, it's a company of companies. So we have started or bought and turned around 15-ish companies at this point. and primarily in the back-end technology space, in fintech, definitely, in insurtech, which is relatively new to us, and edutech.

2:04:48Eric Jorgenson:So those are the biggest risks we're taking. And then fast forward, as we built those businesses over the years, we started an investing side of the business, which is quite large because it's all AI stuff now. And we started early enough, so it grew really fast.

2:05:02Nathan Benaich:We have some doozies. I mean, I'll... I don't want to dwell on it. I don't know. Well, refer. This is a callback to your previous person. In 2008, we had, it was a good year for us, not because we were smart and short the market. Yeah. Jenny was like, she's like, things are confusing. We should be in cash. And we were. Wow. So I was lucky. Well, she was right. The market goes crazy. And then we have a lot of cash. Everybody starts knocking on your door in the fall. And she's like, well, why don't we do something good for humanity? We'll do electric vehicles. Sure. So we are early. Yeah. So we interview two different people.

2:05:37Eric Jorgenson:And we're not investors at this point. We are traders. Yeah. So it's two different things. We are operators, traders.

2:05:43Nathan Benaich:I still don't know if we're investors. Investors, yeah. We're just knuckleheads. Yeah, yeah. We get two people. We're going to interview the two companies at the time. Yeah. One is this PayPal guy who's trying to do it. And the other is the guy who was the chief architect at BMW.

2:05:58Mike Knoop:Yeah.

2:05:59Nathan Benaich:The PayPal guy gets on a call with us. With you. With me.

2:06:04Eric Jorgenson:Just to be clear. Okay.

2:06:09Eric Jorgenson:I mean,

2:06:11Nathan Benaich:if he listens to this, I don't know if he'll remember, because I think he was stoned out of his mind. It was the worst presentation I've ever heard. Like, this guy's never going to build a car. It wasn't about cars.

2:06:21Eric Jorgenson:It was about the train. He was talking about trains. Trains. Between LA and Tampa.

2:06:27Nathan Benaich:Electromagnetic trains. Yeah, yeah, yeah. To also be useful. I was like, what the hell are we talking about here?

2:06:32Mike Knoop:It's supposed to be a business investment. Yes.

2:06:33Nathan Benaich:I want to hear the business pitch. And the other person comes in buttoned up, right? German engineer. Yep. Amazing.

2:06:41Mike Knoop:I've built these my entire career. 100%.

2:06:44Nathan Benaich:So we go with that person. Wow. And then nine months later, we find out that the one we invested in, when it rains, the cars catch on fire and explode. What? That's the craziest downside. So not a good one. Yeah, that's not a good, that's not a good business. That's a bad downside, yeah.

2:06:59Mike Knoop:Yeah, that makes a lot of sense. I think a lot of investors have had to really come around to the other pattern of thinking. I know some investors that, I mean, even on the other side, I know an investor that passed on Tesla, but not because Elon was thinking too futuristic. He was thinking, well, all the cars are going to be self-driving and no one's going to need a car anymore. So if this guy's just building cars, why should I invest in this? And of course, Tesla was going to be the one to do that, but that was too hard to predict. And it just gets very, very hard when you think that far out.

2:07:31Mike Knoop:So walk me through a deal that is in the wheelhouse. What's the structure? Are you looking for a particular vintage and age, a size of like, you know, meat on the bones of the company? And then what are you looking to do? Because there's when you come into a new company, you can be transforming the business with AI. You can be focused on cost reduction, back office rationalization. There's so many different techniques that you can use to drive value.

2:07:59Eric Jorgenson:Yeah. I'll start maybe. I'll start with Peak Six Trials. Please. So at its core, we're entrepreneurs, right? That's what we do. Yeah. So we're comfortable with that risk. Ironically, it doesn't make us super comfortable doing venture because we're not doing it. Yeah. So we have to find really special people. We've been lucky in the universe of Peak Six to have some of those special people along the way. Yeah. We just started something called Peak Six Trials, which is, think about entrepreneurship and residence. We have, it's like previous accelerators, except for that we have the capital. It's already there.

2:08:32Eric Jorgenson:We have the resources, the tech resources, for example, legal, compliance, whatever it is, already there. And then we also have the customers because of Apex FinTech Solutions. So that's our back-end tech. Powers 40 million customers today. And consumers were B2B. Yeah. So there's a unique opportunity for fintech and sure tech type of young entrepreneurs who want to do something. That's how we want to make those bets. That will go into our operating company scenario. And then I know you want to talk about the investment side where we take what kind of what kind of investments we're looking for.

2:09:10Mike Knoop:Yeah, sure. Or even just the story of Apex. I'd love to know how that came into the portfolio, what the process was like. I can tell it's already going to be a good story. Yeah.

2:09:21Nathan Benaich:So there was a public company called Penson. We owned and operated a brokerage called Options House at the time. This predates Wealthfront Betterment and Robinhood, et cetera. And that business custody kept the assets at Penson along with a million other customers, retail customers.

2:09:41Eric Jorgenson:So we're in 2012 at this point. Sure.

2:09:43Nathan Benaich:And we get a call from the CEO of the bank. This is the bank that holds our money, calls on a Friday. He's like, hey, you guys have some money, and could you lend us some money for a little bit? It would help us a lot. Sure. I'm like, let me think about it. I've got to talk to Jenny. Yeah. She's like, that's not a good sign. For your listeners or your viewers, if your bank calls you and asks to borrow more money, Yeah, that's the risk. So Monday morning, we get a call from the SEC. There's fraud, announced fraud at the clearing firm.

2:10:24Mike Knoop:Wow.

2:10:25Nathan Benaich:And we want you to put$70 million into the business by Friday. Wow. Or we're going to liquidate everybody.

2:10:32Eric Jorgenson:And that's everybody in the market. So think pre-generation Robinhood for context. Sure. All those names out there. Yeah. Those middle tier names besides the big names. Yeah. Options House, our firm was one of them. Sure. They're all going to go.

2:10:43Mike Knoop:Yeah.

2:10:44Eric Jorgenson:So 13 days later, we bought it. Amazing. Yeah.

2:10:47Nathan Benaich:And now it's fraud and all.

2:10:49Mike Knoop:That's wild. Yeah, yeah. I've heard a number of these stories of like turning around a company when there is fraud. I mean, Strauss Zelnick sort of did this with Take Two. It was a fantastic turnaround of that business. It feels like an incredible cultural challenge to actually not just clean up the legal documents and make this SEC happy with whatever happened. And it's actually a cultural problem sometimes that led the company down that path. That's right. How are you thinking about cultural development generally? I feel like when I dig into different funds, there's fascinatingly different approaches.

2:11:23Mike Knoop:You know, Ray Dalio is recording everything. There's like so many different. But you mentioned that like when you train a new grad, they come out with skills that are uniquely just synergistic with the rest of the firm. And so how do you think about the cultural values that you want to instill in the next generation?

2:11:46Eric Jorgenson:They are critical, really difficult in times of COVID and changing work from home and all those things. And as we continue to build new companies, right? So, you know, at our firm that's over 28 years old, they are ingrained. It is a sense of urgency. It's a work ethic. Like, it's just high. And even when the market is telling you, you know, we ought to be different or nicer or something, like, people are so engaged. It's really fun to be in the markets. So it makes that easy. It's fun to be part of an entrepreneurial culture. So that makes that easy. So how do I, and if you don't fit, it actually, they weed out pretty quickly.

2:12:29Eric Jorgenson:We've had that benefit over the years. But every time we take on a new company, it is a challenge for us to try and integrate or have them stand in their own culture, which is also fine with us, right? So if we sit at the top and we have CEOs of each of these businesses, they are dependent quite a bit on the peak six core because it's facilitating the financial stuff. It's facilitating the HR stuff. And if they want to sort of ignore that and not join the club, it's a hard road. Because we've figured out such a rhythm. When you get in the rhythm, it makes the acceleration go so much faster. The leverage we get with our people, with the culture, is just really exponential.

2:13:17Mike Knoop:Yeah, some people refer to it as like you stress, the good type of stress. It's a stressful scenario, but it gives you energy. It doesn't actually drain you. And I feel like if people get, you know, the runner's high. So running is very stressful for some people, but for some people it's invigorating. And I feel like if, you know, being in the market at a tumultuous time gives you more energy during that day, that's something where you'll probably thrive.

2:13:41Eric Jorgenson:Yeah, I was going to say taking risk, right? starting as traders and becoming operators and then investors like at its core that that that trading that heart and soul of trading and taking risk every day all day getting used to it that isn't in everybody's dna yeah um it is part of the reason why we like poker so much we're trying to teach a million girls and women to play poker that's cool solely to get these male dominated areas for the women to feel more welcome but you have to be able to take that risk every day yeah And the organization thrives on it.

2:14:14Mike Knoop:It's a little scary. I know like 10 amazing female venture investors, and they're all incredible poker players. Are they really? I would never sit down with them. They would absolutely smoke me.

2:14:22Eric Jorgenson:Well, the funny thing is I didn't play all these years. When I started playing in 2019, it was a conversation we had. It was about our daughter, et cetera. But I realized I was like, wait, I've been playing poker my whole career. Sure. I just didn't know it. Yeah. It's the closest thing I'd ever seen to options trading. Yeah. So I was like, wait, is this what's missing? Because if we get, who cares how people come into the puzzle? The more differentiated their backgrounds are for us, right? If you look at 1997 and he and I were partners, that's what, by the way, we weren't married at the time.

2:14:55Eric Jorgenson:We were together 10 years before we did. So making that decision, that was a highly unusual decision to be made. She chased me.

2:15:04Mike Knoop:I love it. I love it. Yeah, you wish. What are you looking for in a CEO? if I want to come work for you and work for one of your portfolio companies, what does it take to make it as a CEO?

2:15:15Nathan Benaich:I don't think there's any, like there's no one thing, there's no prescriptive formula. The number one thing we've learned, because we've dealt with thousands of employees, CEOs, etc., invested in, I don't know, hundreds, not thousands of businesses. Self-awareness is probably the most important thing, because it can get you in trouble. If you think you're really smart, like you, you better be really smart. Poker teaches you a lot of that. That's a good callback there for you. The self-awareness, like you control effort, you control attitude. Those two things you really do control. Like it's a hard work, right?

2:15:55Nathan Benaich:You're going to be positive, optimist, but awareness, like, like, Hey, we're the best.

2:16:02Mike Knoop:Yeah.

2:16:02Nathan Benaich:You know, by the way, these other people aren't that good. Like you should think about it, like constantly questioning where you're at and being humble.

2:16:09Mike Knoop:Yeah. Is self-awareness around intelligence the main flaw for CEOs or are there CEOs that are overconfident in their dealmaking ability and their emotional intelligence and their managerial ability and their ability to public speak and do? There's so many different things. The CEO is a bundle of traits. I feel like intelligence is obviously super important. and making good strategic decisions, executing. But there's so much else that goes into actually running a company.

2:16:40Nathan Benaich:I wouldn't say, I would not say lack of confidence is not necessarily an issue. Overconfidence is disaster. Interesting, interesting. You get yourself in a lot of trouble because you know for sure that this is gonna happen. And when it doesn't, you're in a world of hurt.

2:16:57Mike Knoop:That happens. So what are the signs that you're looking for to suss out if someone is self-actualized in that way, aware of their flaws, aware of their strengths, their weaknesses. How are you interrogating that in an interview?

2:17:15Eric Jorgenson:We hate interviews.

2:17:16Mike Knoop:Okay. How do you recruit that?

2:17:18Eric Jorgenson:It's hard. It's hard. We've actually tried to build tech over the years. We've done all different things to try and figure it out. We try and have, without being inefficient, as long of a process as we can to see somebody. So if we can get a student in December for two weeks during their break and see them, or we have a women's trading experience that's eight weeks in the summer, anytime we get an extension of time, if we can, I mean, the CEOs is the hardest. They often come from within for us. Now, some of our CEOs did not, but it is what our hit ratio, I think on just cold interview, making it right, I think is really hard.

2:18:01Eric Jorgenson:So then, of course, it's connections and recommendations and all those things because you don't know all of the different pieces of the puzzle. I think people get snowed all the time.

2:18:11Mike Knoop:Yeah. Do you have a bright line between deal team, operating team, like those who evaluate a great company to join the portfolio versus those who will be going and operating the businesses?

2:18:24Nathan Benaich:We have a very, very small evaluating team. OK. Like this is the team. OK.

2:18:30Eric Jorgenson:No, we have some really smart, some lawyers and some analysts in there. Yeah. But at the end of the day, so we don't have outside money. Sure. So it's ours and then our employees who have become partners over the years. So that's who we're investing on behalf. And so, but we are looking for any guidance. We are just, we know we're not the smartest, right? That's what trading does for you. It humbles you really quickly. So how do we connect? How do we partner with great people on the outside and then with the best people internally to make a decision? But we're also willing, we're willing to take probably more risk on average, I would say, with some of these investments.

2:19:06Eric Jorgenson:I mean, we're not, you know, on the energy side or on the power side or on that infrastructure side for us is new. But we started early and we try and get smart and try and be surrounded by smart people.

2:19:16Mike Knoop:I want to get to energy. That sounds fascinating. I want to first ask about sourcing. Are you close to a lot of investment banks or are you cold calling people saying, I want to buy the company? Like if you're into the deal team, where are the ideas coming from?

2:19:30Nathan Benaich:Yeah, I'd say the good ones come from interpersonal relations. relations. Which is why in the age of AI, everything's going to be automated and everything, this really matters. Showing up in a studio where you'll hopefully send us, you'll say, hey, I have an idea for you guys. That's what happens. And vice versa. Yeah, of course. I would say that's 99 % of our sources.

2:19:52Mike Knoop:That's 99 % of it. But it's worked pretty well. That's so interesting. We talk to investors across the category. There's some that are doing tons of outbound. They have a price for every company in their CRM. They have an army of deal associates that are getting out there, pounding the pavement. There's other folks who, yeah, just wildly different strategies. It's fascinating.

2:20:13Eric Jorgenson:Well, for being a very quiet firm for a very long time, it didn't allow us to have what we now realize we probably should have been doing for a while. It's building those relationships. But it's been quick coming out and building those relationships and figuring out how to make it work. We're more mature doing it. We know what we're looking for. We made a shit ton of mistakes. So, like, you know, it's easy to start. You know, they're not perfect, but they rhyme with the past, right? So we're good at saying no, I would say.

2:20:50Mike Knoop:Yeah. Let's talk about the energy side. What's interesting there? It's a very broad category. We talked to a founder yesterday who's refining uranium to go into nuclear power plants that won't come online for five years. on the good side. Then at the same time, we talked to, you know, Chase Lockmiller from Crusoe. He's building data center, putting up power plants today. There's so many other pieces of infrastructure. So many, the supply chain is so complicated. Where is the opportunity? You want to go ahead?

2:21:23Nathan Benaich:We like Crusoe. We're investors in Crusoe. Oh, really? No way. Oh, yeah. That's amazing. We've got a lot of investments. Okay. And what is interesting in energy is it tends to be this. there's some individuals or individual companies that are doing some stuff that's that we see as transformational yeah so everybody's very worried about energy yeah whatever happens with the war we don't have any thoughts on that yeah but assuming that things are peaceful like hey is it going to be nuclear is it going to be solar solar etc um geothermal is really interesting so we're big investors in a company called fervo okay based in utah yeah it's uh your your viewers should look it up.

2:22:02Nathan Benaich:It's transformational. And it's today.

2:22:05Mike Knoop:So it's built.

2:22:06Nathan Benaich:They're going to deliver, I don't know, 500 megs in - Wow. That's serious energy. That's a 2027. Wow. Okay. Yeah, that's enough.

2:22:16Mike Knoop:That's the average Metacampus right now. Okay.

2:22:18Nathan Benaich:And remember, it's fracking. It's traditional drilling, but not in traditional areas. Okay. So I think more remote areas. Sure. Are there side effects? It's unclear. I don't think there are necessarily, but maybe there could be some seismic. But that's super interesting. And the people

2:22:35Mike Knoop:who are doing that, by the way, there's plenty of

2:22:37Nathan Benaich:heat down there. It doesn't heat the planet. There's a bunch of physics around that. But it won't make the planet hotter.

2:22:43Mike Knoop:Yeah, because it's net zero.

2:22:45Nathan Benaich:So that's a good one. I think there's another company in Utah that we like a lot. We were talking to them earlier. It's Taurus Energy. And that is what, effectively what you saw in cloud. Compute is cloud energy. And so So Taurus is a, it's basically a, it's a flywheel business. Okay. Like actually a flywheel. Okay. Like a physical, like this table. Like a literal flywheel. Okay. Except it weighs about 3 ,500 pounds. Power. Okay. But it spins. Remember, the issue with power is that it's, everybody draws at the same time. If you're Snow Basin in Utah and you draw on power to run your tram at the same time that everybody's, hey, by the way, OpenAI is going to run one of their, you know, one of their loops, then you're going to end up drawing tons of power, and that's expensive for the grid.

2:23:30Nathan Benaich:So what Nate has done and his team at Taurus is they're a balancer. The load balancer. It's the load balancer. And you realize there's actually quite a bit of power. How you actually balance the power is the hard part, and he solved it. So they are operating today. We talked to him earlier. He's in a bunch of different states, and he's coming to a state near you.

2:23:56Mike Knoop:Yeah, I love it. Well, tell me more about Peak Six Trials. Where can people get started? How do people apply or join?

2:24:04Eric Jorgenson:Yeah, so peak6trials.com. Okay. And we're looking for entrepreneurs who have ideas. Cool. And everything else is sort of there. You don't have to go and raise money. You have to spend time doing that. Think about the things that where your specialty is, is your idea. Yeah. Right? This is a place with AI. Like, we can do a bunch of stuff around you. Yeah. And interestingly, like with Apex, we have these 40 million customers. They might want your product. And if they don't want your product, that's also really good news. So we short circuit all these things that take to say, like, is this a good idea or not?

2:24:37Eric Jorgenson:You don't have to worry about the capital. You don't have to worry about paying your rent. We actually pay your salary. No way. Yeah. So it's really nicely packaged for someone. I wish we had it at the time. It would have made me feel better. Yeah. Maybe we were better off because we took so much risk, you never know. But the balance here is we want the people who bring the ideas, and we help support and build it, ultimately to own the majority of things, not for us to own the majority of things. So the way we've structured the deals are really creative, I think, and different than the marketplace has seen so far.

2:25:12Eric Jorgenson:So finding those people, those young entrepreneurs, or they may not be so young entrepreneurs. They can be anywhere. But it's really, I mean, I think it's super broad with the fintech sort of space is like everything's money. Every large CPG company who has a bunch of customers, there's some money product that exists or could exist in that ecosystem. So there's a lot of ideas, I think, that are out there. We're going to pick 12 to 15 for the first year and we're going to see what we can do and see what we can pump through.

2:25:43Mike Knoop:That's great. Last question. What's the best way? I'm terrible at poker. What's the best way for me to learn and get better?

2:25:51Eric Jorgenson:Well, we have amazing teachers around the country, which is kind of crazy. We're like at 28 teachers. We have taught at like 360 companies. So you can actually bring us to your company. Oh, really? The banks, the technology firms, the law firms.

2:26:03Mike Knoop:I think they might like it.

2:26:04Eric Jorgenson:It's been wild how people have picked it up, right? Because first of all, we're not playing for money. We're actually teaching because these are people who know nothing. But, you know, 94 % of poker players on the planet are men. So, yeah, it's really extreme. So, I mean, after a couple hundred years of this game coming around, it's probably time for women to be doing this. We're in 70 countries. We're in rural villages in Kenya, for example. So we are super quick, turnkey events, best events that are on the... Pokerpower.com. Yes, Pokerpower.com.

2:26:41Mike Knoop:I love it. Well, thank you both for taking the time to come chat with us. Yeah, of course. We will close the show here on this camera. Leave us five stars on Apple Podcasts and Spotify. We'll be live tomorrow at 11 a.m. Pacific, sharp. Sign up for our newsletter at tbpn.com, and we'll see you tomorrow. Goodbye. Thank you.