Jensen vs NYT, New Model Reactions, "You Can See Everything" Trailer, Saudi EVs | Cristiano Amon, Talia Goldberg, John & Louis Antonelli, Max Levchin, Sam Ross

You're watching TBPN. Today is Wednesday, September 23rd, 2026. We are live from the TBPN UltraDome, the temple of technology, the fortress of finance, the capital of capital. Tell you about ramp.com. Time is money. Save both. Easy-to-use corporate cards, bill pay, accounting, and a whole lot more all in one place.

What happened, John? We— the, the mallet broke.

Oh, you broke the mallet?

We broke the mallet.

I mean, does that have anything to do with the number of days until Christmas?

I think so.

Are we at 90?

Is that a round number?

So we got to hit the gong. What are we? I can't read that. Is it 90?

92 days.

Okay. Well, yeah, if it's 92 days till Christmas, you got to celebrate. Of course.

That's right.

Get ready. TBPN Road to Christmas continues. 92 more days.

Get ready.

Nvidia CEO Jensen Huang went toe to toe with Ezra Klein on the New York Times podcast, The Ezra Klein Show.

That's actually Crazy environment to go in.

Why?

As Jensen. I just think he's brave. Ezra's a real journalist.

It's like, he's brave, he engaged with a real journalist.

No, it's like, you have to imagine he was a bit traumatized after Dwarkesh.

OK, yeah.

Who isn't— I don't think of as a journalist by any means, but he's Obviously has very strong beliefs and very yeah, and and gets to like the root question for a particular audience. Yeah.

Now Dorkesh, although he was going super hard on the the open source question, on selling chips to China, on sort of AI safety and rollout, and like how the model, how the AI race should go. You know, Dorkesh is not the person to push push Jensen on like politics specifically, right? Like that's going to happen somewhere else. But yeah, it is it is a hot seat, but I think he did well too. hours almost hanging out with Ezra Klein. There's some clips and I have some reactions. And it's sort of interesting to dig into the mind of Jensen because he's simultaneously the biggest force in AI, the central bank of artificial intelligence, according to The Economist. He's the backstop of all backstops. He's backstopping everything from, you know, the biggest data centers in the world, lending investment-grade designation to the debt and the credit lines, to Like sort of acting as a soft landing for startups that get acquired at the application layer or anywhere in the stack. He's been an acquirer that's sort of underwriting. If you're a VC and you did a deal at $1 billion—

And you're kind of in trouble on it.

There's a chance that you could get out because Jensen is willing to do a $10 billion, $15 billion acquisition. Whereas like in the prior era, Apple had the money, wouldn't do it. Google really didn't do that many deals that huge. Facebook would do one big one every 5, 10 years, but Jensen's been quick on it. And then he's also been investing directly in basically every lab and basically every AI project. So he's been an incredibly important force, and yet he's now starting to stand alone in his sort of P-doom equals zero take, which was very much the consensus in the technology community.

Zuck would like a word.

True, true. Yeah, I think it still is the consensus in the business community and the finance community. Basically, anyone at the application layers, PDM zero. Anyone deeper in the stack on the semiconductor side or the energy side, the build-out side, the NeoCloud side, they're all pretty much PDM zero. But the labs, and Jensen's been playing there, he's at that level. He's as important as a voice as Dario, Sam, Elon. And so to hear him not jump on the bandwagon when Elon, Sam, and Dario all agreed on pacing the frontier, He's saying, no, we don't really need to pace the frontier. It's interesting to hear him say this. There's a couple clips. Let's play one, and then I have sort of an allegory for where I think his position is, but let's play this.

So, what I've been hearing from the labs, what they've been saying publicly, is that they are facing a hard problem.

Yeah.

Partially an engineering problem, partially an alignment problem, partially an operational excellence problem in Dario Amadei's Framing, and what they are worried about is that in competition with each other, in national competition with China, that they are being pushed to move too fast. That they all feel they're in a collective action dilemma. Now watch you on the All In podcast stage. Donald Trump, President Trump gave you a call there. Oh no!

This is not planned, but we know who it is.

Oh no, Mr.

President.

Oh, yes, sir.

And you and the president and the other members on stage were very resistant to the idea any kind of regulation or collective action was needed.

And they're just playing right into the hands of a lot of people that don't want to see it happen. And that could be political people.

It could also be China.

And we're not going to let that happen. It's a, it's a hoax.

You're right.

What I hear— If you come out as pro-regulation, it's illegal to slow down. That's a form of regulation. You'd be like, I think AI regulation is incredibly important. Acceleration is regulation. Really frustrate everyone. Yeah, it's interesting. Didn't Jensen also do Jolene Kent on CBS just recently? I saw a clip from that, but very different clips going out. The one from Ezra Klein is talking about Maybe we need to shut the labs down, a very, you know, in-the-weeds hot take about the current thing in the AI debate. I think the clip that I saw from CBS was talking about his leather jackets. It's like, I imagine that that interview will be more substantive when it gets clipped properly, but it's funny that that's the one that made it out initially. Let's play the other clip from the MIDAS Project. They said— Here's the clip of Jensen actually talking about properly slowing down. Why is there a bump?

That's the simple answer. If you're going to build a car, a self-driving car, and let's say it's a robotaxi, and there's a really difficult condition, and it just— as an engineer, we just have no idea how to solve this problem. Because these cars are not programmed, they're trained. And so we have no idea how to train these cars, and we have no idea how to align them to the safety standards that are expected on the road. And so what's the answer? Don't ship it. These products were unreleased.

What's that?

These products were unreleased. Ah, so now it comes back to engineering problem again. And so the one is, one, you have to root cause it. Second, you have to, you know, think about what's the— what you could have done, what's the solution for it. And then in the future, use improve your process so that you could avoid this from happening again? I am fairly certain, I am fairly certain they will say, yes, they know how to solve this problem. And if that's the case, then that's the problem. It's as simple as engineering. And now the alternative, the alternative is that if they say that, If they say the alternative, which is there is no way to contain our experiments, there's just no way. When we test our AI models, it will get out and it will damage the world. Then I think the answer is we have to shut the labs down.

Yeah, I mean, that is kind of what happened with self-driving cars. You know, like, they do— before they ship them, they do test them on roads and They don't test them on open roads. They test them on closed courses before they move to open roads. They sort of have their own sandboxes, their own environments to test these in. I do wonder if there's a sort of a legislation or liability gap between the liability incurred by a self-driving car company who causes property damage from a car running into another car autonomously and an AI agent that hacks and defaces or causes some economic damage? I don't think there will be. I think the courts, if there was true economic harm, like one model accidentally took down a payment system for an e-commerce website, I think it would be pretty easy to sue that company and say, you caused me to lose this much revenue, you owe me. And the courts would say, sure. And even if the lab argued, hey, we didn't tell it to take down your e-commerce system or your payment rails, the judge and the courts would say, doesn't matter. Even if you expressed a duty of care, like, you still have to pay in this scenario. But it is possible that there's a gap there, and that's where regulation could fit in. It's interesting. He spent the first, like, 20 minutes sort of steelmanning the jobs question and talking about jobs, because I think that's throwing a lot of people off. Like, we sort of moved past the job apocalypse, SaaS apocalypse narrative, which was predicted from somewhat of the same community, into actual apocalypse. And people are like, whoa, whoa, whoa, like, you were wrong about the SaaS-pocalypse. Like, Salesforce is still doing fine. Like, Slack still exists. And you were wrong about the job apocalypse. Like, the unemployment rate is like— 3% for American white-collar workers. You were predicting like 50% or 30%, something like 10% overall. And even in the Philippines, I mean, I remember seeing— I think it was Tristan Harris on Modern Wisdom. Like, he's now sounding the alarm bells about existential risk, but he was saying something like the Philippines would see like, you know, 90% of their economy go away because they're heavily dependent on Call centers. Call centers are actually only like 3.5% of the Philippines job market. They do in fact make things and have agriculture and all sorts of other economic endeavors going on in the country. But even in the Philippines, like the unemployment rate is right now in the Philippines, it's 4.9% in June of 2026. Now, it went up to 6% in August, but it still feels like the AI effect is pretty minimal. And most people were predicting that, like, the offshore call centers would be affected first. And that one seems like maybe we're there, but it's just taking so much longer that everyone feels very vindicated in saying, like, hey, let's watch that play out first before we move on to the x-risk discourse potentially. I think that's a lot of what—

Well, now with Muse floating the idea of having human in the loop on personal agents, you can imagine those people would be Oh, they could just move over.

Yeah, yeah, potentially. But yeah, I mean, it's all the same, you know, in the limit, in the exponential. Add 5 orders of magnitude, maybe things look very different. But Jensen just rejects that. I mean, he's an— is he an AI is a normal technology guy? I saw Joe Weisenthal posting about this. He said that he had to differentiate between I gotta pull it up 'cause it's funny. Weisenthal. Joe Weisenthal said he had to disaggregate— where is it? He posts a lot, so I gotta dig it up. Normal technology. Man, he posts a lot.

Weisenthal.

Okay, he said, the splintering around AI discourse is really a sight to behold. Was in a conversation yesterday with some folks during which it became necessary to distinguish the people who see AI as normal technology from the AI as normal technology people. Because there is a group of people that have rallied around a particular thesis, which is AI as normal technology. And that's different than people that are just like casually into that idea.

Yeah.

'Cause it's actually like a different ecosystem. Anyway, It does feel like Jensen is AI is normal technology. I mean, he's certainly seen plenty of technology revolutions come and go, and he's been in this industry for what, 30-odd years? And I think of the jobs on the jobs question. We were talking to Joe Weisenthal about this when he was in the studio. Like, where is the economic impact of the internet? Like, why can't you see you know, a kink in the graph of really any economic data when, like, the internet takes off. It's not like productivity went way up. There's nothing really to grab onto. You actually go back to 1970 if you want to see, like, the real trends shift. And there are other, you know, trade and globalization moves that have had bigger economic impacts than the internet, which is crazy to think because so much wealth was created, so many companies were created, and it did change the world and like the day-to-day experience, but it didn't actually show up that much in the economic data. And that's what we're seeing now where jobs are sort of changing, tasks are changing, but we're not seeing dramatically different economic statistics like the 10-year is at all-time highs or not all-time highs, but 19-year highs, you said, over 5%. And yet everyone is sort of a consensus agrees that that's because of the war. Are you rooting for people that are buying the bonds and getting higher yields now?

Yes.

OK.

I don't know. Sometimes a record-breaking number—

It's just exciting to you.

It's exciting.

Just general, just real golden retriever mind.

You understand the implications and you—

You don't even think about the implications potentially. You're just cheering for a bigger number.

Yeah.

It's like, now it begins with a 5.

Great.

I like it.

It's a higher number.

There's an interesting allegory around the effect that technology has on the labor market, at least historically. Now things might change. Stephen Covey highlighted this in First Things First, his book on time management. He said, I attended a seminar once where the instructor was lecturing on time. At one point, he said, OK, it's time for a quiz. He reached under the table and pulled out a wide-mouth gallon jar. He set it on the table next to a platter with some fist-sized rocks. How many of these rocks do you think I can get in the jar? he asked. After everyone made their guesses, he said, OK, let's find out. He set one rock in the jar, then another, then another. I don't remember how many he got in, but he got the jar full. Then he asked, is that jar full? Everyone looked at the rocks and said, yes. Then he said, ah. He reached under the table and pulled out a bucket of gravel. He dumped some gravel in and shook the jar and the gravel went in all the little spaces left by the big rocks. Then he grinned and said once more, is the jar full? By this time, people were in on him. They said, probably not. There's something else coming. Good, he said. And he reached under the table and brought out a bucket of sand.

Oh.

He started dumping the sand in. And it went in all the little spaces left by the rocks and the gravel. Once more, he said, is the jar full?

No!

Everyone roars. He said, good. And he grabbed a pitcher of water and began to pour, and the water went in between the rocks and the sand and filled up. And somebody said, well, there are gaps, and if you really work at it, you can always fit more into your life. He said, no, that's not the point. The point is this: if you hadn't put these big rocks in first, would you have ever gotten any of them in? And so the effect that Jensen's describing is that, like, at one point in human history, There were maybe only 2 jobs, hunting and gathering, something along those lines. Then we invent agriculture, industrialization. At one point, everyone's farming. Now, very few people are farming, but we still have more food than ever.

There might have been a 3rd job, singing. I could see Tyler, while everyone else was hunting and gathering, just kind of jester back thing and just singing for all the hunters and all the gatherers, kind of like providing ambient entertainment.

Yeah. Yeah.

Anyways.

But it does feel like that was the effect that the internet had. Like, it didn't dramatically reshape the labor force, but like, obviously, like, lawyers use the internet to communicate. And now, like, you see the AI agents thing. It's like every little document will go through an AI pass. Every little interaction in the economy gets this, like, small effect, at least right now. And that's what Jensen's, like, living in. He's like, I have a real business to run in the real world today. So he says he's worried about the future. Or he says he thinks about the future, but really, he's clearly very much living in the present.

It's interesting to think about how much technology-driven efficiency gains just get effectively wasted. So I would imagine today, it's faster to close a venture round post-term sheet than it was in, like, the '90s, right? You would think so with the internet and AI and all these different things. But I bet you that it's not as maybe as fast, as efficient as you might think if we can now generate docs on the fly and you can easily go back and forth on redlines, right? Like, maybe it went from 6 weeks to 4 weeks.

Sure.

But theoretically, it could have gone from 6 weeks down to 5 days.

Yeah.

And I think you're just seeing that even with AI now, people can do their jobs faster. And you've seen some management teams tell their employees, hey, I know you're getting a lot more efficiency. That doesn't mean you should just do the same. I want you to do more work in the same amount of time. Don't do the same amount of work with less time, but you're just sort of wasting a bunch of time.

Yeah, it seems like no one's really No one's saving time. Everyone's just doing more stuff. There is an interesting, like, corollary of that, which is potentially these technologies, they don't necessarily change the growth curve, but they are responsible for the growth. Like, if you don't have the internet speeding up commerce from a week to get an item to 2 days, that is actually the source of the 2% growth. And without the technology, you have no growth.

Yeah.

And so there is another side of an argument. Of course, there's like population growth and a whole bunch of other things that are affecting economic growth broadly. But there is a world where, yes, if you're compressing the timeline on everything, you're building the house faster, you're deciding to buy the house faster, you're exchanging everything faster. As things move quicker, even if you're not doing entirely like net new jobs, just the fact that you're doing them faster, you do more of them. And that's what actually creates the economic growth. I don't know. We'll figure it out. We'll get to the bottom of it tomorrow. Let me tell you about the New York Stock Exchange. Want to change the world? Raise capital at the New York Stock Exchange. The the and yeah, it's always a good time to share the Financial Times black pill white pill chart of which way things go. Either either GDP goes to zero infinity or it stays the same. It's like that Mitch Hedberg joke. I used to be in a metal band. People either loved us, they hate us, or they thought we were just okay. Stupid joke. Do you know Mitch Hedberg? Oh, he's a great, like, one-liner comedian. He's fantastic. RIP. Anyway, let's move on to some other reactions. I'll tell you about Console. Console builds AI agents that automate 70% IT, HR, and finance support, giving employees instant resolution for access requests and password resets. Claude Opus 5.5 drew every frame in this animation in JavaScript. They went all in on LLMs, on the big model, on the great model, and now it can do basically video generation, but do it in JavaScript, do it in Blender, do it in Python, do it in SVG, and you can just hill climb on SVG. And people are sharing a bunch of cool demos and good for launch. People are sick of benchmarks. People want to see visual stuff, entertain me, make a song. And yeah.

Yeah, really, really cool style. Yeah, I'm already sort of mourning it just because this is probably going to be everywhere on the internet. Yeah, like by next week. But for now, a good format I would, you know, if you see maybe a coworker doomscrolling, send them a custom animation like this saying, hey, stop doomscrolling.

Yeah.

Do some work. You could maybe send this to the, I think, the president of Syria.

Oh yeah, he was doing some work.

Caught using Instagram Reels at the UN.

So good.

Naughty, naughty, as they say. Anyway, very, very cool stuff.

Yeah, Mike Bird says, total cultural victory. Man has yet to create an ideology that can compete with short-form video-based social media scrolling. Ahmed Al-Sharaa. Spotted scrolling and sending Instagram Reels during UN General Assembly with the translator headphone on. He's scrolling. Hey, you know, you got to keep those— you got to keep those group chats going. You got to keep them. You got to keep the content flowing. You don't want to be falling off. He might be sending them to other world leaders. He might be recontextualizing what's happening at the UN with a funny reel. Like, he might— the person might be talking about some peace plan. And he might be sharing some hilarious Instagram reel that makes fun of that to let his friends know that he's not buying it, something like that.

He also could be just— his feed could be so dialed into just local political content, he could be mainlining public opinion and trying to understand what's important to voters heading into the next election.

Yeah.

Yeah, yeah. There's one more Claude post I want to show. The GIF animated in Python and rendered in Blender. And at this point, you know, I posted that AI video of you and people were asking like, what was the workflow? And I was like, it's— you just ask it to do exactly what you want it to do. And you don't— you actually don't even need to know the word Blender. Like, you can just—

You can even misspell every word and it will still—

No, you just open up the voice mode and I just talk and I'm like, you can even do multiple things now. So I was like, I have this children's story that I made up for my 5-year-old and And I was like, in one shot, I was like, take this story, turn it into a series of stories, then a series of children's books. Go find a place that can print the children's books, illustrate it, turn it into short-form video, and also make a video game. And it did it all. It was just like spawning subagents to do it. And you can just do it all in one prompt. And I didn't need to be like, well, I want you to use JavaScript for this and Blender for that. You can just ask for what you want and basically You can basically get it from all the models right now. You have an interesting thesis. You're blackpilling on the application layer now. You think the models are getting so good that people are just going to use the AI tools. Does this change anything for you? Because I see this and I still feel like these are great. There's probably a couple of revisions. When I do the prompts, I still sort of filter and review. 20 outputs, pick the best one. I actually talked to an AI video founder yesterday who's doing like AI movie production and whatnot. And he was absolutely printing using all the latest models. The business is doing fantastically. He's hiring 4 video editors like a week or a day or something. Like he's hiring lots of people because there still is a lot of— it's not even prompt engineering. It's more like processing the output, curatorial work. understanding what is the right thing to fit together. And I think that that mainly comes into picture when you're looking at something that's a bigger project. You want to go from a 1-minute thing that might have some consistency, but when you go to 2 hours, the consistency becomes much more important. The style, the pacing, matching everything matters more. I don't know. I think we might be gearing up for another application layer versus model layer debate. We saw this with the Harvey discourse. Earlier this— I think we discussed that yesterday, actually. People were sort of blackpilling because their margins went negative. But then all the models got cheaper since that released. And so you think—

Better and cheaper.

Yeah. But of course, if the models can do it at a base level, there is a world where every company just has a relationship with a foundation lab. So I don't know. We'll see. Anyway, people are feeling the AGI. The serious adult ML enjoyer at Anthropic, he said, I'm feeling the AGI. I'm going to follow this guy back. I'm feeling the AGI. He made this cool video with Opus 55. Then Sholto comes in from the top rope. We don't have AGI. The job's not finished. I love the debate even internally. People are saying they may be loosening up comms over there. I think it's cool. I like seeing different takes. Of course, these companies are not monoliths. It's nice to actually get a glimpse into everyone's different perceptions. Everyone has different definitions for AGI, and I think it's cool to actually toy with them. Early in the show, I coined, like, definition of AGI, which was just purely economics, just when AI revenues equal non-AI revenues, you have AGI. So, like, when the AI economy is as big as the human economy, Then that's AGI. And of course, that's completely arbitrary. Who knows if that's a valuable metric? Certainly interesting. But I can definitively say we're not there because AI is contributing like a quarter percent to GDP. And total lab revenues are in like the hundreds of billions while we're doing like tens of trillions in the global economy or in the US economy even. So, interesting stuff, fun. Go play around with it. Let us know what you build. I like that they put the horse riding the astronaut on the moon. And I think there's probably some Blender under the hood. But it was cool that the model was able to do the post-processing and adding grain and texture. That made it look very special. Like, it popped out on the timeline, at least to me, because of that. Very cool. I also had an interesting test. Like, you really can hill climb SVG. At one point, I just took an image that was AI-generated image of a pelican riding a bicycle, which is of course because it's AI-generated. GenAI image, like, looks amazing. And then I just told Astra, like, turn this into an SVG pixel by pixel. And I was able to send it to you. It was like a 40-megabyte SVG, but it looks exactly like a pelican riding a bicycle. And so it calls into question, like, what even matters?

Yeah.

Like, because you can use a generative AI tool to then create a Blender model to then create an After Effects file to then bake it down to a PNG or change it. Like, every format changes into every other format. Use the best tool for the job. We're definitely in the regime of, like, how much did it cost to actually get that thing done?

Yeah.

As opposed to some, like, artificial synthetic benchmark around, like, a line of code costs this much. Like, no one cares. No one cares what tools are being used under the hood. There's definitely a world where you go to a model, You ask for a thing, and if it needs to use Slack, it uses Slack. If it needs to use Photoshop, it uses Photoshop. If it needs to write its own thing in Python, it does that. It uses the right tool for the job, and it intelligently chooses things just like a real person on your team would, which is exciting.

What else?

EV news.

EV news.

From Dave over on X, he flagged this.

First, let me tell you about Codex. Codex is a powerful workspace for getting work done with AI agents, whether you're writing code, analyzing data, creating content, or automating business workflows. Codex helps you move projects forward from start to finish.

We are one week out from the Roadster reveal.

Yeah.

And I'm excited.

Did you listen to the end of the show when we bounced— when you bounced? We went deep on the Roadster. We got a scoop. We got a scoop from our guest who was next to a Tesla employee on a plane and was like pulling facts about him just to go leak it on TVPN. Yeah.

Crazy.

No, no. I mean, I don't know how real this was because the guy could have been messing with them. I don't know. It's all rumor mill stuff, but the guy was basically like, yeah, I was next to a Tesla employee and he was saying that the jets are not to make it fly. It's actually for downforce. It's going to suck it to the ground and it's going to go 0 to 60 in 1 second. Very cool prediction. Very different from what we were saying.

So who had the lowest number?

Yeah, the only thing is it doesn't track with—

Who had the lowest number? So you're closer to win if that's what happened.

Well, it doesn't track with what Elon was saying on Rogan, which is that Yeah, it should be able to leave the ground. Fly.

And that's what I was getting at. I was like, if you can have a fan or a jet that sucks you to the ground for one purpose, you can probably reverse those and boost up at least for a little bit, for a little jump. But we'll see. We're counting it down.

Well, in other news, the road to Christmas, road to Roadster.

But we're still keeping an eye on it.

Saudi Arabia is aiming to disrupt the auto industry with these radical EVs.

They're wedges.

They have a brand called C-E-R, Exobot. It's coming as a sedan and an SUV. It looks like sort of a futuristic, like, Lamborghini offshoot.

Yeah, there's a little bit of Huracán wedge in there, a little Cybertruck in there. Is that—

This is Saudi Arabia's first true production car brand. So they're going to be making these.

There's such a hard trade-off between the wedge looks great. but it's a terrible use of space. Like, the optimal use of space is like the new Waymo vehicle, which is basically just a box or like a bus, right?

Oh, so you just care about utility now?

I'm just saying it's a trade-off. Like, the more wedgie you get, the less utilitarian the vehicle space is. Of course, you need to have—

This one looks like somebody broke up with the new generation of Prius.

Yeah.

Now they've leveled up again.

Ooh.

That was the original read on the Prius is like, who hurt you? You, you know, because the, the new Prius is looking pretty, pretty stanced.

Yeah, it is.

It is a level up. Yeah, but this is a level up.

Is it the Prime? Prius Prime looks pretty good. Yeah, they've done a good job. Anyways, uh, 850 horsepower, tri-motor electric powertrain.

Uh, this thing looks insane.

It does look insane. It, it— I wonder where they'll hit in terms of price. That'll be, that'll be interesting to see. Um, I mean, it's cool. Saudi Arabia, obviously known for, you know, pretty outrageous car culture in many places.

John, what if I could— what if they could make this the performance of the Luce at only 60% of the cost?

Yeah.

Still hundreds of thousands of dollars. Hopefully not that, but it will be interesting.

Yeah, I have no idea where they would price this because it could be sort of like a national treasure a point of pride. It could come in at a very high price. At the same time, EV is a tough sell when you're in the, when you're in the 6 figures. Should we watch the trailer, the official trailer?

Let's do it.

Where you can see everything. We watched the preview clip. Now we get the full trailer. And I want you to pay attention to the quotes because the reviewers were floored by this movie. I've never seen quotes like this on a movie.

I know.

It's crazy. People really, really enjoyed this.

Triple glaze.

Yeah, seriously. While they pull that up, let me tell you about public.com. Investing for those who take it seriously. They got stocks, options, bonds, crypto, treasuries, and more with great customer service. I feel you did nothing wrong.

I did not.

So where did things get lost?

Like, how are you where you are right now?

I wish I knew. I don't know.

I don't—

I don't feel like I understand that. So I know you guys invited me to stay here. Does any part of you worry about me being here 24/7? I don't think so.

Okay, so pause.

But what if I see—

24/7.

He's actually, I think—

Living there.

Living with Elizabeth Holmes.

Yeah.

And it's crazy because only Nathan Fielder would even think to throw out an idea of, hey, would you mind if I moved into your house before you go to prison and documented the entire process? Because you would think that there would be no circumstances where that would I think it's just pure upside.

There's, there's very little downside to doing this. I mean, you're going to prison. Like, worst case, you look worse, but you're in prison either way.

Yeah.

The only thing you— the only way you can go is up and actually endear some people to you, which is the attempt. We'll see how it lands. Let's keep watching. And that makes you look bad. I think this is the moment in time when no other film I've ever experienced captures this story before I'm gone. I fell in love in that first conversation. Before or after that she revealed she was the founder of Theranos? Probably before. I mean, weren't you worried she was sort of scamming you? 100%.

But what did she have to gain from it?

Well, isn't your family rich?

Yeah, I think that there's like a lot of different levels of wealth.

Come jump in with me. You're asking me to go?

Yeah.

You've never—

What is this for? Why are they doing a 3D scan of her?

That's just something Nathan would do. Do you mind if I have a 3D scan of your body?

I saw that. I was like, this has nothing to do with Thanos or going to prison. I know what you can prepare you.

No, you don't.

I may think about this movie for the rest of my life. That is a crazy quote.

Be okay with—

It feels like there's going to be some twist or something. Something very interesting, but I'm hooked.

No, I think the whole thing is going to make the viewer feel like they're in a really bad acid trip. Like all these scenes.

Yeah.

The pauses, the silence, the way the lighting, the sort of sense of impending doom, right? Because she's about to go to prison.

Yeah.

The kids, you know, being present in these scenes, like the whole thing is just like incredibly dark and weird.

I feel like it has to break expectations in some way because the average viewer is gonna sit down and believe that she is guilty and that she lied and is like a sociopath because like that's sort of her brand, right? Is that like she never admitted any guilt and was guilty in the John Kerry retelling of the story and obviously the court findings. And so, for it to be like that, I feel like there has to be some twist or something.

I don't know.

I would be shocked if it's just like, yep, like she defrauded investors and didn't really build a good blood testing device and now she's in jail. Like, the end. Like, would that be—

I don't think it would get those quotes.

I don't think it would get those quotes. So, I feel like there's gonna be something crazy that happens, some complete twist, like maybe she's innocent or something, or maybe she's like, I don't know, guilty of something else. There's gotta be something else.

Well, the question is how does the— who's the guy that she would call Tiger?

Oh, yeah. I actually don't know. Yeah, yeah. Like, because there has— during the court case, there was a question about his responsibility. Should he bear more of the responsibility? And so— but he doesn't seem to be in the trailer, so I don't know. Because one weird, like, twist would be if you came away being like, that guy's more responsible than I thought, you know? But anyway, 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. We have the president and CEO of Qualcomm, Cristiano Amon, in the waiting room.

Let's bring him in. Here we go.

TVP and UltraDome. Cristiano, how are you doing?

Very good. How about yourself?

We're doing fantastically. Where are you calling in from?

From Maui, Hawaii. It's our Snapdragon Summit. This is day 2.

How long have you been doing Hawaii? Why Hawaii?

It's probably more than 10 years. I think it's— we have a lot of, you know, global press that come here from all over countries, a lot of partners. Nobody complains about coming to Hawaii.

Yeah, I can imagine. Yeah, it's a good place to be. What are the highlights? What are the messages that you're trying to drive home today and with this conference?

Look, at the Snapdragon Summit, we always announce our latest Snapdragon flagship processor for smartphones. But this one's— it's special because for the past couple of years we have been seeing— we have a clarity of vision. We have seen how smartphones are going to change to an AI smartphone. And I think that's actually started to happen right now.

Yes. What— how does your business actually change in an era of folks wanting to do more on-device inference and AI on something like an Android phone, one of your big partners? How do you think you need to adapt? Is there something you need to change or has this been years in the works? You think you're ready?

No, years in the work. Look, we— if you— we were kind of a long time ago. It feels like a long time ago when we're kind of showing, you know, multi-billion parameter model running on devices. Look, there's this whole conversation about AI running on the cloud and on the edge. And people often ask the question, why the edge? Why the cloud? And I think that's probably the wrong question. It's almost— I like to go back and, and say, okay, everybody get their phone out of their pockets, get your 200, 300 apps that you have, and let's go have a conversation about what part of your app runs on the device or runs on the cloud. And if you— and I know even though we build incredible processors, if you put it on airplane mode, you don't use your phone. So at the end of the day, AI is no different than that. It's going to be running on the device and on the cloud. It's going to be all transparent to you.

Yeah. How, how are you viewing what the next couple of years will look like in automotive? It feels like the demands for AI on device at the edge are even more important potentially, but maybe it's equally important. How are you seeing the automotive business develop?

Well, automotive has been ahead of that. Like, we, we've been very fortunate. Automotive was a new business for Qualcomm and, and we now serve all the car companies in the world. And what has been interesting about that is AI on the edge actually is being very big in automotive because of assisted driving and autonomous driving. That's kind of AI running on a processor in the car. But what's happening with the car right now is when you're behind the wheel and you don't have any legacy of OSs and apps, agentic experience is very natural when you're behind the wheel. We also see now the fusion of the systems in the car that was designed for navigation, like the cameras, for example, being also being used for see what I see and have an agentic experience.

Yeah.

Like, you know, people are in their car and they say, well, it gets the agent. This restaurant on the right, what's the Yelp review and do they have availability for lunch right now? Those are kind of some of the experience we're seeing and that's accelerating for us.

Got it. How are you processing the narrative around like the CPU crunch? We saw the, the agentic era boom and, you there were whole websites that were going down because so much code was getting pushed. It feels like agents— like, the idea that everything would be done at the model layer on a GPU is not the way things are playing out. CPUs are incredibly important, especially in the data center. I'm wondering if— are we going to experience another CPU crunch as we enter the era of personal agents? Because we saw the effect that the enterprise agents and software coding agents had on the CPU demand. What does the next couple months even look like for CPU demand in the data center?

Okay, let me separate that conversation into— I think one topic is there's so much more demand for compute than availability right now and across the board. So I think what we've seen this right now, and by the way, as a semiconductor company, I'll tell you, this supply chain, it's operating at 100% capacity. Everything, everything is short because there's so much more demand than the availability of compute. Now, the second part is the way we see it, and we're just entering the data center, but we kind of see that also on devices at the edge.

You—

the data center is going to have to evolve and it's already on its way to do that into heterogeneous compute. You have different engines to do different things. CPUs are going to be Very important for orchestrator and agents, and CPU demand will continue to rise. And that's also true on the other side of data center phones. As those agents get deployed on devices, they have a lot of CPU demand, but you're going to have different engines for different things, right? For example, for inference, we see there's engine now for prefill, engine for decode, decode attention, and so forth.

How are you thinking about the changing landscape of consumer devices? I mean, Meta Connect is today. I'm sure that they're going to announce some new consumer devices. But we talk to founders all day long that are building just really cool small robotics projects, wearables devices. There's rings and wristbands and ankle bands And anything you can wear or put on your body, it's happening. And I'm wondering if you're seeing that actually start to move up your to-do list as like you got to engage with that smaller community, even though it might be nascent. And are you actually trying to engage with like the smaller device community on the consumer side at a conference like this?

Yeah.

Look, and I'm going to say this in all humility, but the majority of those new classes of devices are actually using our chip.

Of course.

And there it is. Now, there's a multitude of those products now, and there's big companies and small companies. And the reason is because when you think about agents, and agents are not bound by OSs or applications, applications and you have multimodal. Like, think about glasses, for example. I'm actually a big believer that glasses is going to see an inflection point. The glass is a prime real estate close to your eyes, to your mouth, to your ears. Your head turns, your cameras see it.

Yeah.

And then those things like see what I see, read what I read, hear what I hear are going to come up. But we've seen all sorts of form factors. We've seen earbuds with cameras, jewelry, pins, buttons. And, and this is kind of the new personal AI category. And I think that would be a very big category.

How are you grappling with the open source ecosystem versus closed source tooling to enable the next generation of devices to integrate? I mean, obviously you've already won a huge portion of them over, but You want to keep that forever, right?

Oh, thank you for asking this question. I think it's maybe a great opportunity for me to, to make a plug about what we're doing with Modular. So I don't know if you heard about what we're doing with Modular. Look, we made an acquisition of a company and that's a great team. It's the Modular team. I think the founder is Chris Lattner. I think he's probably a legend within the computer science world. He was the inventor of the Apple Swift programming language. He was the inventor of LLVM. And he built a stack which is like CUDA, but it's designed to work on any hardware. Doesn't matter, you know, CPU accelerators. It will run on, on NVIDIA, on AMD, on, on Qualcomm, or on any hardware whatsoever. So we bought that company and we're making that open source. That's what we're doing because we actually believe that the industry will benefit from an open-source stack that scales from the data center across different hardware and the edge. And it doesn't matter. I'm going to celebrate that stack in each and every one of my competitors because we probably need an open stack to drive innovation in AI. Otherwise, it's just one company doing most of the innovation.

Thank you. That's a very helpful explanation. We were just earlier in the show talking about Jensen Huang sitting down with Ezra Klein, engaging with some of the very deep questions about AI jobs and existential risk. Is this something— is this conversation that we're seeing bubble up in the public sphere actually making its way to the C-suite of your customers that you engage with, or are you sort of in a mode of put one foot in front of the other and let those conversations take place in other platforms? Have you been engaging with all these debates around slowdowns and open-source AI versus closed-source AI? It feels like every week there's a new big hot topic and meaty, almost sci-fi scenario to engage with. But what has your been approach—

what has your approach been as the CEO of an important company in this Well, I wish we have like at least like half an hour to have this conversation. This is a very big topic. It's a very big topic. But look, in 1 minute that we have, I'm going to try to maybe give you an answer.

Please solve the whole problem.

Solve it all.

Solve the whole problem.

In 1 minute.

In 1 minute.

I think there's a lot of different conversations. And look, in any kind of changes, for example, in the United States, you see a lot of conversation about safety of the models. I look, I think people talk about safety in general, but they are— there are very specific things. I think cybersecurity is actually a big one. And I think it's really important. It's important to have products that are done responsibly. I think that nobody's going to— nobody's going to argue against that. Hey, do you want me to build a product that is going to go crazy? No, no, I don't want you to do that. I think that's kind of a logical thing. And cybersecurity is actually a serious issue. You know, there's a big surface area. But if you go to places like China, the conversation is very different. It's about putting AI in every car and every phone, every PC, every industrial, and it's kind of very different.

Yeah, yeah, it is. Yeah, we were talking about that, how there's just such a wide gap in the discourse between the impact putting AI in all these little places, and then you have like the bigger questions. But we'll get to that next time. We'd love to have you back on the show. We can spend a full hour solving this thing.

Yeah, 30 minutes, we can get to the bottom of it.

Yeah, yeah, then we'll solve it. It will be solved.

But congratulations. Thanks for calling in from Uruguay.

Thanks so much for taking a couple minutes today to come chat with us. Have a great rest of your day. We'll talk to you soon.

Cheers.

You too.

Great talking to you guys.

Thank you.

Goodbye. 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. Coming back on the show, we got Talia Goldberg, partner at Bessemer Venture Partners. We very much enjoyed her last appearance.

What's going on?

How you doing? Hey, great to see you guys. You had a hot take last time that went very viral and proved true. Everyone thought, everyone was like, no, it's about to collapse. And you were like, no, I think like, It's okay if there's some, you know, margin compression in the short term. Things will iron out. Models are going to get cheaper. And everyone was like, she's not taking finance seriously. And here you are, vindicated. Vindicated. So congratulations. Victory lap.

Your margin is my opportunity.

There we go. There we go. How are you processing the current moment? What's exciting to you? Is the lab trade over? Opportunity above the fold at the application layer, below the fold at the semiconductor, neo-cloud build-out level? Like, what's exciting to you personally?

I mean, yes and yes. I'll say a few things I've been thinking about lately. One is physical AI and one is this new concept that a portfolio company, Mindfall, coined called token market fit.

Yeah.

And I'll talk about, like, I love this idea of token market fit. I wish I had invented it, but they did.

Yeah.

And the idea of token market fit is, like, simply put, like, what are the areas and the categories where we've found the ability to productively use the average end user, like, $10,000 a month of tokens? And if you actually look at where a lot of the spend has gone, it's really like there are basically only 3 categories I can think of right now. that have like real token market fit. One is in coding, like, you know, enormous spend in coding. The second is in, is in video and in media and in your line of work where you can very productively spend, you know, huge amounts of money creating great content.

Yep.

And then maybe the third is in high-frequency trading. But if you look at like on average, you know, legal, customer support, sales, like we actually haven't really hit like product market fit. In a real way in a lot of those areas, and we will. And I think the bottlenecks are moving away from things like code and video.

Is it possible that you can have product-market fit without massive costs? Because like, I would argue that you have like token-market fit in something like a legal, but it's just not— you're not going to see massive spend in the way due to the nature of the work, right? So, it's like possible that you can have— I'm just— this is maybe a question. It's like, can you have token market fit with just like relatively modest per person spend at a company?

Is this sort of the argument that like we need a lot more software, but maybe we don't need that many more legal briefs or something? Like the market size is small?

Is that what you're saying?

Yeah, there's in some ways almost like infinite software. Like a product is never finished.

Okay.

But in legal work, like you do a deal and then it's sort of like done and there's not, you know, I don't know. Yeah, but I didn't say that's what we're doing. My question is like, I believe there's gonna be some categories where like AI is incredible, it transforms like the task or the job, but you just don't end up with that much. It's just very efficient and you don't end up with like, you know, exceptional spend, right? You're saying like $10,000 a month per company. in a category?

It's possible. I mean, I think like, I guess, yeah, there's difference between product market fit and token market fit. But legal is like a really interesting example. Bessemer's been a longtime investor in Legora, which is like a great example of this. And I think they're still very early actually in this transition towards what's possible and what spend even for their customers is possible. So I think legal is like yet to be unlocked in a lot of ways. And In a lot of use cases, Legora is still copilot. It's not really autopilot. It's not like truly doing the work of lawyers. And, you know, you don't see like large law firms like, you know, massively changing their, their team compositions yet. I think that is still to come and that's on the come. And as we can give and figure out how to productively leverage models to give more work to, to agents, like we will be spending more on agents than on models in fields like legal too.

Yeah.

Yeah. I mean, we saw that transition maybe last year, earlier this year with like the software engineer who says like, I don't read the code anymore. And that can sometimes be a little bit risky. But in a lot of places, the lawyer who's like, I don't even read the contract, that would be token market fit. Like if I heard a, you know, a star lawyer say, yeah, I don't even read the filing anymore, the document, I'd be like, OK, yeah, superintelligence is here. It's working.

Yeah, well, the difference is software, you can ship a feature and it can be broken 1% of the time, where in legal, if you have a 1% major error rate in contracts, it's— Could be bad. A lot of money on the line.

Yeah, maybe you've got to be a little bit higher up.

Yeah, look, there are these categories that like, I guess the point is like they're still to come and like they're still growing. And so like what are those next areas with token market fit from an investment perspective are interesting because while you're right, there will be some that are maybe a lot more efficient. A lot of the dollars are in the token flow.

Yeah. How important do you think it is to be the entry point to a, to a certain token flow, to be an aggregator in the strategy Parlayance. I was just thinking about Fall and Higgsfield. They have access to incredible models. There's a few other companies in the category, but a lot of people, the workflow is like, go to their preferred AI agent, then send an API key over, and they've already put some credits in an account, and then they're using another tool to sort of access that inference. And there's a world where that billing relationship lives within Claude Code or lives within Codex and they're taking sort of an app store cut. Is that a nightmare? Is that a death knell for the inference provider? Or could that actually be the future way of these companies working together in a positive way that actually grows the market and the distribution so much that it offsets whatever rent the model labs and like the front doors are taking?

Yeah, look, I think it's probably not like black and white in every single category. And so it's somewhat different, like even in, you know, in the case of FAAL as an example, like they are the front door. And so, you know, that you can even access a model like, you know, in the past models like Nano Banana and Google's models even through FAAL. So you didn't have to go to Google. So like they have their cake and eat it too. But we do see this playing out and I think like Instinct and Muse and what's happening with Meta or Amazon and Shopify are other really interesting analogies of this aggregation disaggregation theory. And at a high level, like, I am a believer, like, there will be places for both and like both exist. Amazon exists and Shopify exists and like the tension between the two is real.

Yeah.

Personal agent predictions. How are you thinking about the category?

Well, we're very small seed investors in Instinct, so we're, you know, very bullish on, on their— on their— I don't know if I should be offended by that sound or—

No, no, no, that's the error.

No, no, no, it was a small check, but now it's— because you went in the seed, it's big now.

I wish we were bigger. I wish we were bigger investors. But like, it is such a magical experience. I'm obsessed with these products. Like, Other than when ChatGPT launched, like, this is the second oh my God moment that I've had. And like, my parents are having this moment and my sister's having this moment and they don't even use technology. And so it's kind of crazy.

Like, it is much broader than what we saw with the Claude Code Codex boom, where it was this magical experience for people in tech and for people who knew how to open up a terminal and then were familiar with code and had the these tasks that sort of fit neatly in that world. This is something that you can give to a family member who doesn't have a GitHub account, and they'll have fun, and they'll get some value out of it, and sort of see the progress, which they might not have updated on in 3 years or something.

And so, yeah, everyone is going to need to own this, and there's going to be a major war. And every large lab, every large company is going to be out there trying to figure out, how do I create, like, similarly such a delightful experience? And how do you bring this to enterprise? I think it's just like the interaction modes, the delightful proactivity, the simplicity of the interaction is something that could absolutely be ported over to the enterprise use cases as well. And so I think this is not a winner-take-all market. There will be multiple agents and different angles on it. And I think this is about to be arguably the most important next category in AI.

It's another knife fight too, which is fun. Yeah. Give us the update on Bessemer. Raise some more funds. But what's the structure of the fund? What's the structure of the—

of—

Yeah.

And how is the strategy evolving? Yeah, all that good stuff.

Yeah. Look, so we have exciting news that we just raised $5.75 billion.

$1.0—

That sounds good.

That's how we feel. We're, we're so excited. We have $1.75 billion of that is dedicated to early-stage companies, which lets us write really meaningful investments in companies at their earliest days when conviction matters a lot, when it's not, you know, very obvious.

$200 million seed rounds. Let's do it. Get it done in 2 deals.

And it looked like 70% of our investments have started early, often way before there's even revenue or sometimes even a company name. And we're going to continue to do that. And then $4 billion for growth, which lets us keep backing companies as they're at their inflection points and not just participate or let others kind of invest in them. We're going to be leading these rounds. Returns are concentrating, as you all know, in fewer larger winners. And so the right move for us is to be a meaningful investor and have meaningful positions in the companies that really, really matter. And we don't want to spread it thin and be peanut buttering across our growth dollars across a bunch of companies. We want to be super disciplined, but disciplined not by taking small checks in growth companies, by making big checks, being highly selective, and really committing fully to a smaller subset of companies. So, that's the strategy.

That's exciting.

Amazing.

Very exciting times. Well, thank you so much for coming on the show.

It is so funny to rewind like 10 years and if somebody from the future came and they're like, Talia, like you're going to have a $5.75 billion fund, and you would be like, so, we're the biggest venture investor in the world, right? It's like, well, you know, this is now like if you want to be like a real fund, you got to have—

Companies are staying private so much longer. I mean, yeah, the trillion-dollar IPOs are unthinkable years ago.

And now here we are.

It's crazy.

Wild time.

And yeah, a lot to come. Well, thank you guys for having me.

Great to see you. Great update.

We'll talk to you soon.

Cheers.

Have a good one. Goodbye. Let me tell you about Cisco. Critical infrastructure for the AI era unlocks seamless real-time experiences and new value with Cisco. We have Our next guest in person. Welcome to the show. How you guys doing? Sorry, let me get this out of here. Welcome, welcome. Introduce yourselves for those. Hi. Introduce yourselves.

Yeah, great name as well.

Uh, introduce yourselves for the audience. Tell us about the company.

Yeah, yeah.

I'm, uh, my name is Louis Antonelli.

I'm John Antonelli. Um, we're brothers if you haven't—

there we go.

Um, but yeah, we're— so we started Real 6 years ago. It's a score stat tracking app. It's very social, engaging, and it caters towards those fantasy players, bettors, just avid fans that want to know what's happening in sports.

Is it the ultimate second screen experience? Is that the trend, or is this actually like a third screen now? How do you, how do you think about this?

Yeah, I think it's the ultimate second screen. And then, I mean, it's the penultimate first screen. So like when you're not watching the game, it's the fastest way to know what's happening in sports.

Okay.

We started like, when we started live data, it was kind of play-by-play data was kind of this concept that was kind of shoved on a 5th tab on ESPN. You'd have to like tab over to the play-by-play. You'd have to look at like really tiny Excel-looking rows of data to try to find those small numbers and see, you know, what's happening. So we wanted to bring engagement, you know, comments, reactions, a bunch of community around data. And then the latency too at the time with gambling companies, like low latency data is super important, right?

Sure.

So, we brought that more from a media perspective to show people, bring people that knowledge in real time about what's happening.

Yeah. What is the data source? Are there like sort of open APIs and companies that are comfortable sharing the raw data? At some point, like someone has to write down what happened in the stadium, I imagine.

It's pretty commoditized. Genius Sports, Sport Radar scrape a lot of the data as well. So it's pretty like the fact that Steph created a 3 isn't owned by the leagues or anyone. So we've kind of taken a spin on it. That's our content.

Public ball knowledge.

Exactly. And then, but so the magic, like the secret sauce is really transforming that into a feed that is intelligible, not an Excel sheet. More like a Twitter type of context.

And contextual too. Like, I think we add, like, we started to add historical milestones.

Okay.

This is a player's 500th career 3, or like a player's 12th straight point in a row.

Yeah.

A lot of the times when you're on these products, like, you won't know, or even when you're watching or you're just tuning into a game, like, you won't know how well a player is performing or what they did in the first or second quarter. And this kind of brings them that, like, adds like what an announcer might tell you.

Yeah.

Okay.

So you guys have one 1.5 million monthly actives. And it sounds like the social product is actually like working and real.

Yeah.

Which is notable because I feel like so many people think about this idea of like, I'm going to create a data product and there's going to be a social layer. And then for every 100 pitches like that or people that take a shot, like, yeah, maybe less than one are going to actually build something where there's like tons of highly engaged users? Just because I think about where these sports communities pop up, it's on Instagram, on X, on Reddit, on all these existing social platforms. So, how was that? Like, how did you actually make that happen?

Yeah, I think so. From my perspective, and John can touch on his, but we basically on Twitter, for example, have a million people who are all separately leaving the same comment about some big play, we take that play as the piece of content and then underneath that you'll have the million people. So we've kind of inverted it a little bit. So instead of like one-to-many, it's like kind of, yeah, just flipped.

And then— And it's more ephemeral. So people feel like instead of posting on Twitter, it's more like sometimes when I see somebody in tech will post like, it's over.

Like, and you're like, oh, this is what it's about.

Yeah.

They'll be like, you're like, no, it's actually about the game. Yeah. Yeah. And so, like, I didn't realize that you liked AI discourse and also basketball.

Yeah.

Because the issue is super fragmented across, like, tons of different— I mean, there's only a few people that control the conversation, like meme pages and fan pages for every sport, team, and player. And we kind of built for those fan pages and meme pages.

Yeah.

People used to use sort of hashtags on X to sort of organize around a particular game or something, but that has gone so far out of fashion. The algorithm sort replaced a lot of that, but you lost in that place the ability to actually tell the app, today I only want to focus on the Lakers game.

Exactly.

And so even if there's something—

Or a specific player.

Yeah, yeah, exactly.

And you'll see X has added like a live chat now at the game level. So we break down our chats to box scores. So instead of just everyone in one massive chat, we're like, oh, I'm talking about Steph Curry's box score or his most recent 3 or his block shots. So like you can dive into these very deeper places. A cool stat too is like 30% of our monthly users leave comments, which is crazy. It's like an order of mag— couple orders of magnitude.

Yeah, normally it's like 99% lurkers.

Just lurk, yeah. So we bring that like really cool global community feel to everything, yeah.

Did you get your start on Vine?

I started on Vine, yeah.

What were you making on Vine?

So I was taking highlights and putting songs to them. I was like one of 30 people that were like the OBJ catch that went viral. I put a song to it, it went viral on when I posted it.

That's awesome.

Um, and then I grew a page, it was close to 100,000 followers in 6 months.

Okay, so no, no front-facing, no personality, like original faceless content.

Wow.

Yeah, exactly.

I was—

and I still know like a decade later a lot of the same. And this is partly why real— why we were able to grow is through these meme fan pages.

Sure, sure.

A page on Instagram close to a million followers.

Yeah.

And I would just curate content. Yeah. But we noticed, we're like, why do millions of people go to Instagram and follow hundreds of basketball pages, NFL pages?

Yeah.

Super fragmented and sensationalized. We— I would pull like the top 3 stats in a game and like make a graphic out of it. And so a lot of what we've done is we've codified that content so people share real— it's the most shareable score app.

Sure.

So it feels like— I mean, you see it all over. That's how we growing is people are using it as a means to like slander or praise players.

Slander.

Like in the first quarter, you can see like, oh, Tatum went like 0 for 11 or whatever.

Yeah.

And people will screenshot that and, you know, use it as a fueling of like narratives.

Yeah. Yeah. What's been the mix of top of funnel awareness? And I guess how has it changed amongst, I can imagine using, you know, paid partnerships with creators, we want you to, you want, we want you to promote us, uh, versus in-house clippers or even like distributed clippers like WAP, uh, like, like what's been, what's worked in the past, what's working now, uh, how has it changed?

I like, we just started to seed, like we started with just the NBA.

Yeah.

But the way that we started to grow is like we added, now we have 18 leagues, um, but we seed this content among like, there's creators that talk about the game.

Sure.

And they might use like a score in the background or whatever. We encourage them or pay them to use the scoreboard of Real or whatever.

Yeah.

And our first 1,000 users were all my friends that run these meme fan pages. And there's like thousands of these meme fan pages. They have— some have like hundreds of thousands to millions of followers.

Yep.

The NBA Centels or NBA Centrals of the world, Legion Hoops. Like, it would take their— I would just like encourage them to use it or naturally weave Real into the conversation.

Sure.

Because they might just— I mean, they're already posting like, oh, LeBron had a sick game. Yeah, might as well add that, like, yeah, zero of the past.

Yeah, whatever.

How do you make money?

It's a great question.

Yeah, so we started with a kind of virtual bucks model like Roblox or Fortnite, um, that users could, you know, earn and then also collect different moments. So, you know, instead of collecting like a player, collect his home run or his 3 or his touchdown. And build your fandom kind of based on how many you've, how many cards you've collected.

And you have to be like in the app when a play happens in order to collect it.

Yeah. There's like real-time raffles and then there's also just like general packs. So it's cool. Cause like as soon as every touchdown right now in the NFL happens, you can kind of get like a digital representation of it. It's a stat-based representation. Like this is a 30-yard touchdown. And a really cool thing we do is we rate everything between 0 and 10, or it can actually go above 10. So we don't become like it.

Let's go.

Let's go. So we don't want to become like it.

How high can it go?

Not the dunk contest.

Sometimes you're like 14.

14?

So Shohei's, yeah, so Shohei's like 10 RBI, that like legendary 10 RBI, 6 for 6, 50-50 game was like, yeah, 15 or something. So Ashton Gente regularly was sitting in his college days at like 12.

So it's sort of logarithmic. Like 15 is 10 times better than 14.

It's like the dunk contest is the worst back when it was like everything was a 10.

It was stupid.

So we didn't want that.

Yeah.

But people actually now reference our scores and it's really good for like rookie ladders for MVP. Like usually it reflects really well without us needing to like subjectively say like, this is just a, it's a cool—

Do players like this?

A lot of them, a lot of them use it.

Yeah.

Cause it's just fast. I think that's like the difference.

They're opening up during the game.

How many points?

Whoa.

Really?

Yeah.

At halftime? Like Trey Jones, they open up at Every single game.

That's crazy.

Don't tell like Microsoft Surface or whatever because I think they're supposed to use that. It's all good though.

They're like, damn, damn, I've gone 0 for 15. Wow, I really thought I was on a hot streak. It's so funny, it's the opposite approach of like the score takes care of itself. Oh yeah, it's literally just like obsessing over the score.

Yeah, I think another thing we do different too is a lot of like the ESPNs, Bleacher Reports, their score apps would never send real-time notifications. Only like halftime, end of game moments.

Sure, sure, sure.

So we'll inform you like this is like Tatum's 12th straight point in a row or like this touchdown just happened. We'll take you straight to that moment.

Yeah.

And I think that we send like 50 million notifications a day on average.

Is that sort of like predictive? Like you can—

it's based on the rating.

AI model or— okay, so you have the rating and then if something's happening You can be like, oh, you should really tune into this game. Something cool is happening.

Yeah, we'll tell you when it happens.

Okay.

We do some like cycle watches are the coolest ones. So like when a player is about to hit a cycle in baseball and they have like 3 of the 4 things, we won't tell you when they need a triple because that's very unlikely. So we'll only bring you in when they need a single, double, or homer.

Oh, okay.

So we'll bring people together for kind of more of that, like expected things to build that hype. But most of the time, most people, there's so much going on in sports. They just want to know kind of what happened. Yeah.

Is Real replacing like sports radio in some ways? Because I guess when I was a kid, I would, I would be like, you know, cycling through the radio and I'd hear like a baseball game on. And as a kid, like, you kind of grew up on the internet. I'm like, who's, who's like tuning into like just the rate? Like, who's watching sports? You know, who's—

Listening to radio?

Listening to radio. But it's just sort of that you're kind of like passively following game or, or, you know, a team that you care about. And this feels like that.

And now people can stream the video on their phone. Like, I feel like that's probably more dominant.

It is fast. I like to think of it as like written radio and Twitch. Like, it's faster to read than it is to watch, than it is to even listen.

Especially when there's like 15 games on at once. Like, you're not streaming 15 games on like an NBA Wednesday, right? So like, this is like kind of the red zone of every league.

Okay.

Yeah. Yeah. Um, it's kind of like how we—

What's the, what's the smallest league you support currently? Um, you like curling?

We just added— it's a good question because like every league technically can be considered big. I mean, we added— we're starting to add like golf, tennis, some of the more longer tails that we haven't had. F1 is going to be coming on the product as well. Um, but we cover— we have tons of like soccer, karate.

You've seen that one?

Ping pong.

We're considering putting Putting a community vote for like some obscure, some crazy one, like hot dog eating.

Hot dog eating would be fun.

Joey's people ask for everything, I'm sure. And we have this like pretty strong Australian fan base, so like I get every like 3 AM every day, it's like, add the AFL.

Oh yeah, okay, the Down Under group.

Okay, it's like our third biggest city.

How cyclical is the business? Is the— I mean, I imagine the Super Bowl is your Super Bowl, but NBA Finals is big. Yeah. But, but in general, is there like a pretty stable demand for this across—

It's definitely cyclic. I mean, like summer when it's just baseball, it's just like natural cycles.

Sure, sure.

But World Cup was big for us.

Oh, sure.

As we continue to add more things in the summer.

Are you thinking about Olympics?

We were talking about like Olympic basketball. The tough thing is like it's 4 months out of the year.

Sure.

So like Put engineering time into it.

A lot of work.

But I think now that, I mean, our team hasn't really grown from like a, I mean, our engineers are outputting because of like AI and everything.

A lot more.

We used to be outputting updates every 3 to 4 months. Now it's every like 2 to 3 weeks.

That's great.

And so like we're just continuing to add more insights, make the data more contextual.

Sure.

Sure.

I think that's how we continue to stay like ahead is like, how do we, like we've added next gen stats to NFL. You can see like telemetry data. And then we're also seeing, you can see like Personnel, like personnel coverages and like things you wouldn't like while you're watching, like you wouldn't be able to conceptualize. We're just trying to bake it in and into a very digestible way because then that makes it more shareable. You'll tell your friend more, like it's all that helps is that helps like the growth flow.

Yeah, you can go really deep on live still. Like live for us is like everything. That's most of our usage is live. So just keep being, just go as deep as we can.

What's the house philosophy? What's your philosophy on prediction markets? Partner, roll your own, stay away from? How do you puzzle it out?

Yeah, we have an engagement feature we launched kind of with the virtual bucks, kind of more of a kind of fun play thing to build your profile and compete with others on that dimension. We've considered kind of the prediction markets.

Yeah, a lot of our, I mean, our recent, I mean, in the last year and a half, 2 years, a lot of our usage has come from fantasy players and bettors, um, and people just like sweating their bets basically, like around the money. Comment sections are like, oh, I need another 12Ks or 10Ks or whatever, um, or like another touchdown. Um, and so we were like, how do we play into like more of a real, real money gaming spit, the real money gaming space? Um, and we've talked across the board from the Calshys to, yeah, Parley Market and all them. Um, we, we ended up landing on FanDuel as like a partner for us. Um, so that's another revenue stream.

Okay.

I was like, how do we bring odds to the product?

Yeah.

I mean, we were talking about it. It's like we have so many bettors and we can't even serve them with live odds.

Sure.

And so it's another data source.

Yeah.

The data layer of live odds too, like it adds a dimension that people kind of expect. Now you see it on every broadcast now. It has live odds and what people like, what Vegas thinks, what the people think. So I think there's like a lot of cool things we can do with like real-time charts about how the lines are moving for Everything. People can discuss every market. They can kind of just like have it where they expect it with, especially with our, we've signed up millions and millions of the, of the gamblers in the last couple years.

So a lot.

And I mean, use for the people that are interested in it. I mean, we, if we've just been missing that as like a source of data and it's a good conversational piece too.

And you can turn it off. Like obviously there's people that don't want to see that so they can just toggle it off.

That's cool.

So do you think AI is allowing people more time to just watch sports.

I think the thing that's missing though, which I think we separate ourselves even across Instagram and Twitter and TikTok, is they don't have deeper community. Like, I can spend 6 hours a day on NBA Twitter and get nothing from my fandom. Like, I don't get badges, I don't get like anything related to like, you know, viewing these games. We build up your profile, and I think that's something we want to continue to like triple down on is that community side. Because a lot of these, I mean, you look at like There's hundreds of millions of Taylor Swift fans. Yeah, well, there's no— like, I still think there's these communal things that can be built for like tons of different niches.

Yeah, a lot of it's offline. Like, you have the tour merch or the signed, you know, album or the jersey that's signed. But in the digital world, uh, there was— I mean, there was some movement towards this with like NFTs, but it sort of died off.

I mean, think about it with Belly. And yeah, even like the letterboxes of the world.

Like, sure, yeah, same thing. Pockets. Yeah, clout.

People like, they want that like community profile that they're building, focused thing.

Yeah, yeah.

I think sports is pretty safe though, and AI, because it's like the last kind of human thing that people value. I mean, that sounds dystopian. I don't know, it's like the art, more than family, more than your children. If you think about it, it's like the only live thing. And that's why you see these ticket prices are going up.

Yeah, ticket prices are high. And of course a bunch of venture capitalists that are creating AI.

There's a kid more than anything too. Yeah, humans.

Yeah, yeah, yeah, yeah. Um, uh, community building, uh, how do you deal with moderation? Do you have an in-house team, an AI system, hybrid? I imagine that like culling the most disruptive folks in— or there's probably a dance there.

Yeah, it's very— it's a huge dance because our demographic is like that 18th So you definitely want to keep some of that edginess. Yeah, you want to be able to go and talk some trash. Exactly. Yeah. And not—

when you say libel or slander, there needs to be an appropriate level of slander.

But we use— yeah, we've been using AI for moderation from day one and just building that up over time. So we've— it's always going to be a dance and a balance.

Sure, sure.

We're pretty confident now. We actually scan like every single reply in real time.

Okay.

Um, just to make sure We catch like the really, really bad stuff.

Do you use like a really cheap commodity open source model for that? Are you actually passing that through AI or is it just like lookup table if bad word?

Yeah, well, we use the lookup table. It catches like 80%, 85%. And then we have like a classifier that's super fast that catches another 10%. And then anything that falls through there will hit like any of the latest models.

And then you can escalate.

So we have a couple layers there and escalate if we need to. Generally, it's worked super well, and I think it's something that's missing on a lot of these kind of live chats. There's a lot— some of these live chat streams, like, you just have to close the chat.

So, like, we don't want that.

So, yeah, it's a dance, but I think it's important.

What's stopping you guys from having 1.5 billion monthly actives? Right now, you have 1.5 million.

Yeah. question. I think the— I think we just need more sports, more content.

More sports. Start creating more sports.

Just more data within the product.

Sure, sure.

Also live events in general.

Yeah, most— I mean, if we want to go for like the billion users, say we could have every like live show, The Bachelor, from The Bachelor to like Love Island.

Oh, that's interesting.

Yeah. Take data. I mean, you can talk about what you've seen.

Yeah, the original idea came So my now wife and I, we built like a fantasy Bachelor app where we would sit and type in everything that was happening, every kiss, every hug. And we had like, we built it, it was just us two.

We had like—

That's the funniest.

Yeah, we had like 50,000 weekly users.

Just locking in for The Bachelor.

50,000 weekly users for every kiss and every hug.

So I watched, we watched 4 years.

So you're sitting there like, rizz 'em up.

4 years, and we had to be on live because if we weren't on live, people would just be like, where's the data? But the most used screen of the app was the live feed with people commenting and watching as their second screen. And of course, like, John at the time was building his like incredible social media properties and I knew what he could do. And like, it was just like a perfect mix with play-by-play in sports and like this live feed concept.

So that's kind of it.

And him not having to type in the data every time.

Yeah, not having to type it in, even though some of these third-party providers aren't—

Yes. But you look at like politics, there's tons of like—

Yeah, you have mention markets and stuff.

Yeah, especially around like the elections. It's like, would be cool in theory. We don't want to go down that path before we dominate. I think sports are still like a 10x with what we have.

People do ask for elections like a lot, and it kind of does— it has similar feel to like a prediction market with like the—

Yeah, everyone's watched like the election map populate and go red and And that's sort of like a similar visualization for sure.

We are a daily use product though. Okay. And I love talking about like monthly actives, but we peaked at like 1.1 million daily.

Yeah, it's really good.

Yeah, our download was like 70% at its peak, like during moments you would think people would be watching. Sure. But they're almost like people want to also see, because a lot of people watch alone, like, like just at home or whatever. They just want that community. or that second screen. Like during the Bam Adebayo game, we had like 200,000 concurrent people like tracking his like every point towards his 83 points. So we see like during big moments like that or even just like the NBA Finals or the Super Bowl, we have like very concurrent usage, like high concurrent usage.

Yeah.

Just like figuring out how to make that more engaging and then also more fun with your friends, I think is a big growth Man, all the betting and prediction market companies must be so pissed off that they don't have this product because it's like actually like all they care about is user acquisition and figuring out how to get engagement and deep usage. And you guys feel like you built something that's going to be very hard to actually replicate, but would be very valuable to them.

Yeah. Are there like— walk me through how a subculture emerges. I'm thinking about like on Twitter, it's just one big global chat room, but then there's like Teapot, like that part of Twitter, like these, like the SF tech insider community has created its own little subcommunity. Are there groups of people that break out and build like a Discord further, or do you have the functionality? Is there an opportunity to create like a group of people that are all commenting on similar games and then they become friends on the app and can interact more communally outside of a particular event?

Yeah. We have groups in the app so people can create groups and it's kind of nested under any piece of content. You can kind of talk in that group. I think most of the sub-communities though are still global, but they're around kind of those meme moments. So like when Brandon Podziemski was trying to hit 30 points, for example, like everyone, every game was just this community and then they would grow for people discovering.

Who were like rooting for that moment.

Yeah, like we need the 30 and he would get like 28 and everyone would just be devastated. So like tracking those type of moments when they pop up is really big. Like the meatball sub thing with the interceptions right now in NFL, like there's like random stuff.

It almost, it feels like you're just making up stuff for that ad. I don't know any of these references.

You could just throw one in that doesn't exist and we'd be like, damn, that's crazy.

But they happen all the time. It's like crazy.

But we don't create them. It's kind of like they're already a known, like people are already talking about like, yeah, like, um, like the Brandon Pusemski 30-point or like it comes from NBA Twitter almost.

Yeah, sure.

I think we can do a, like, we haven't really been at this scale before. So I think we can start curating those like subgroups or encouraging them beyond just like teams or players or whatever. Yeah.

It's awesome. Well, thanks for coming by.

Thanks for stopping by. Yeah, great to meet you guys.

Thank you. Have a great rest of your day. We'll talk to you soon. Let me tell you about Railway. Railway is the all-in-one intelligent cloud provider. Use your favorite agent to deploy web apps, servers, databases, and more while Railway automatically takes care of scaling, monitoring, and security. Our next guest is coming We have Max Levchin from Affirm coming back on the show. Always fun to talk to Max about his role as CEO, how he's adopting AI, what he's seeing in the consumer markets and debt markets and all sorts of things. While we are waiting for him, let's talk about another electric vehicle, another international electric vehicle, the, the Geely EV that can charge under 5 minutes. Is this fast enough? How long does it take to get gas? 2 minutes? 4 minutes? 5 minutes? This feels like maybe a tipping point where people will be more likely to adopt this. It does make me wonder about the Roadster. Is that gonna be a new— will they roll out a new charging technology that allows them to charge faster? They've been sort of— Tesla has not moved fast into the Like sort of wireless charging. The actual Porsche, the Cayenne EV, does wireless charging. You just put a mat down on your garage floor, drive over it, and then it charges. That seems like a no-brainer. I'm surprised that Tesla hasn't done that, especially since they were working on that crazy robotic snake arm. Yeah.

Well, I'm hoping the Roadster will just send the battery out the side with rocket engines.

Oh, you want that to be the future?

OK.

But we'll see. But yeah, it's an interesting trade right now. Charging at these charging stations can cost in the tens of dollars. It takes quite a bit longer than gas, obviously. So dropping that down, I think, is going to be pretty key.

Well, Nikita Beer is— oh, do we have our next guest? It's red.

It was green for a second.

Let's wait. Nikita Beer has a— oh, I guess we do have Max. Is that correct? OK, great. Let's bring in Max Latchem, the founder and CEO of Afora. Welcome back to the show, Max. How you doing?

It's been too long.

It has been too long. Let's start with the latest and greatest in your world, in Affirm. And then, as always, I have so many questions about how you're running the company, what you're seeing, what's working managerially on the new technology, on adoption side. But first, what's the biggest news in Affirm world?

Today's news: we are available in the UK on Amazon. That's a massive announcement.

Huge. Not everyone can get an Amazon deal done these days. Congratulations. Do you have to go straight to the top? Are you negotiating with Jassy?

No, no, no, no, no.

Amazon does feel like a company that might build this themselves. Like, what is your pitch to a big company with a lot of engineers and they have AI tooling. What do you bring to the table when you're partnering with another company at that scale? It's a huge company.

But it doesn't hurt that we've been partners for quite some time in the US. And so we're, we're definitely no strangers to working with the Amazon engineering team. They're excellent. They're very capable of building things. We are a specialist. We know what we're doing in things like underwriting. We have extraordinarily diverse capital markets program that allows us to fund the loans that we, we do for, for them and for all our other merchants. And so I think every company that's not a financial service specialist at some point or another flirts with the idea of like, hey, maybe we should do this ourselves. And if they're not serious about it, then sometimes stick with it. If they're very serious about it and they're of a certain scale, they usually say, wait a second, we should partner with the very best and You know, I'm obviously biased, but I think we've demonstrated that we're pretty great. So this is a great continuation of the relationship we've built with them over the years here. And UK is certainly a super important market for us. We're very excited to be there. Also, we came there a little while ago with Shopify, but been meaning to expand the relationship and are excited to be live with Costco and now with Amazon and many others.

Having already worked with Amazon for so many years, I imagine that the hurdle to rolling this out is not technical. It's not the actual integration. They probably have a great team. You have a great team in place. Where are you seeing technical challenges emerge? Where are you seeing acceleration in your ability to deliver a better product? Is it on the underwriting side? Is AI helping there, or is it on productization conversion, all the downstream customer service? Like, there's so much in the business. What's really moving the needle for you?

It's like you read our press releases. So I'll answer a bunch of them. There's actually a lot of really cool stuff in the question you just posed. The thing that I was referring to, especially— so we just announced we launched an entire new family of underwriting models. And this has been a long, long time coming. So we are a buyout and appealator specialist, financial services specialist. We've been underwriting, building underwriting models for 15 years with, you know, umpteen petabytes of data that we train on.

Yeah.

So we've been an ML/AI specialist for a very long time. But up until recently, we primarily stuck to tree-based models. They're deterministic, they're easier to audit, they're easier to explain to regulators, which we have to do every year. And so all of that has been kind of the stronghold of a firm. And about 3-ish years ago, we said, This attention idea that you see in LLMs and the transformer architecture is really compelling because it just opens up new ways of capturing complex patterns in a way that humans actually cannot. And fundamentally improving underwriting models for things like underwriting is expressing patterns you see in behaviors over and over again in a way that can be reused across multiple humans. And so We started an internal research project into using attention-based modeling to understand behaviors, to surface these patterns, all in the service of underwriting people better, figuring out a little bit more about them. And so about a year ago, we had something we thought was really compelling and we've been testing it quite obsessively. We're finally live as of a few days ago with a full suite of these attention-driven models that outperform our own Gradient boosted tree-based models. And the way— I mean, just to give you a sense for just how compelling this breakthrough is, so every quarter we launch a minor addition to the model. Every year or so we launch a brand new approach to the core model, all using these tree-based architectures. We measure the improvement, and that's what we report to ourselves and our shareholders on. The improvement For this new— we call it Arc. It's the code name for the architecture. The Arc-based model outperformed the next planned improvement by a factor of 2. I don't remember the last time I've seen a factor of 2 implementation improvement. So it's just very hard to overstate how compelling this is. And so I'm very, very proud of the team. And this was a very, very large-scale project that was just unbelievably successful.

That's awesome.

Talk about what you've learned about the timelines it takes for basically like the difference in execution between 2 companies to become obvious to the market. And when I say that right now, there's a bunch of new like AI companies, for example, let's say 2 vertical AI companies, they both have $500 million in funding. Right now, it seems like Maybe there's 2-ish years where it's unclear just how much better is one company versus the other. But over time, you know that one will surface to the top. And then I would say we've also— you can basically see that in every category where there's a category like prediction markets last year, there was 2 heavily funded companies and then you saw difference in execution and they bifurcated. over time. But I'm just wondering from your view how you work with your team. Like, when I'm talking to you, you just get this sense that like competing with you would be like living hell. And it's because of the just like the experience level and then the approach to all these different layers of the stack and the understanding of the category and your business. And like, it just feels like, you know, Affirm is just pulling away very, very strongly from other players in the market, whereas it looked like it was a pretty even race in many ways, like, you know, 5 years ago.

Thank you, first of all.

That's a—

I mean, I happen to agree, but I'm obviously biased. I do agree that these things take a while to play out. And who knows which inning we're in and sort of how many more sort of ups and downs we're going to see in kind of the superficial judgment AKA the stock price.

But private markets seem to muddy this a lot. It's almost like companies have to get public and then have to actually—

I'm not even sure public markets make it that much better. Public markets force you to be very transparent about a quarterly check-in. One of the things that I think we did really well as a public company, if I do say so myself, is we put a timeline of getting profitable out on the map and said, we're going to get there. And we did it quite far out. So 24 months before we were profitable, we said we're going to be profitable 24 months from now. And we just printed quarter after quarter after quarter showing like, look, we are that much closer. And then on the dot, actually a couple of, couple of months prior, said, yep, profitable now. Here it is. And I think that was a big credibility thing that private companies don't get to have because the only people who know their internal metrics intimately are their venture capitalists. And even if they publish metrics, they wouldn't be held to the sort of a standard GAAP accounting, SEC-regulated way of communicating. So in that sense, public companies have it probably a little bit easier, but you also get slapped around if you miss on a metric or the market thinks that you messed up one of your metrics. But I think the way you know who's pulling away kind of early. If I were, you know, putting on my occasional investor hat, I think, you know, I'm feeding your compliment to me back to myself, but I kind of happen to agree with it. I think you can tell operator to operator, people who are, quote unquote, for lack of a better term, serious people. You can tell, like, people who know their metrics, people that understand the entirety of their stack, that don't just say, well, you know, I have a great team. And so my AI engineers told me to say these words, and those are the words I'm going to repeat now obsessively.

Yeah.

Maybe the shortest answer is, like, companies run by engineers, we are skilled in not BSing. And so that may be like a good 1A predictor. Like, how likely are they to do what they say they will? Like, if the person running it has an engineering degree and whatever engineering, probably going to be pretty truthful.

Evergreen, evergreen. I had one more follow-up question. I'm very curious to get your point of view. We've heard a million pitches on this show about how agents are going to need to pay agents and we need all of this new financial infrastructure. And I've been consistently incredibly bearish on that just because we have a bunch of really robust financial infrastructure that's regulated. We even have companies that like Think about Stripe, for an example.

Yeah.

They've built for developers at the core from the very beginning, which means that they're inherently well set up to work with agents. And using an example, we see new personal agents like Instinct and Muse, and there's a bunch of others coming. And there's no point where— I'm sure somebody's pitched like Affirm for agents or some silly pitch like that. But with all these new sort of applications, the agent will just go and tell the user, do you want to pay cash or do you want to use Affirm? And they'll just get to select like they would as a consumer. And so, there's no new financial infrastructure needed. And I feel like agentic payments, like net new agentic payments might be an entire mirage. And we may have gotten a bunch of posts online and blog posts and all this stuff, and then really nothing new happens. But what do you think?

I'm going to make a bold claim.

There we go.

Affirm for agents will be the firm. I'm going to put it out there.

I know it's risky.

I know what I'm saying. No, I happen to agree with you. I think there are definitely Many really cool, exciting developments in agentic. I am trying out all the same agents myself. Some of them are surprisingly good. Some of them are still lumbering through the same problems you see with some of the earlier attempts. But it's very clear that we will get— we will all have agents doing our chores for us. I happen to believe that quite a lot of shopping isn't actually a chore. In fact, it's a form of entertainment. And so human in the loop will not just be a requirement. It will be a loss to humanity if we are not allowed or if we're not participating in some of the shopping choices, which includes, by the way, the way you pay. But some of these things will go to the agent. The underlying plumbing— and by that I mean everything from deciding the best way to pay all the way down to figuring out the smartest choice of a plan most rewarding transaction, best 0% loan, etc., I think that's going to primarily accrete to people who know what they're doing, who are specialists in the space. And that's why we have to continuously work on improving underwriting. We want to be more inclusive, as in say yes to more people while maintaining the same level of credit performance. And so all of that is still like the work we have to do, and we have to do it faster, and we have to pull away from the competition as aggressively as we can. But I don't think there's an opportunity to dislodge Affirm by showing up and saying, we are just like Affirm, but smaller, less profitable, with less credibility in the market, in the capital markets in particular. But we are agentic. We are agentic too. We're pretty, pretty agentic ourselves.

Yeah, I know. I love it.

That's a great take. How have you been approaching leveraging open source models in various employee use cases and workflows? I think it's been— you guys are such an incredible engineering culture. I'm sure a lot of your team has been using open models in a bunch of different ways. Yet at the same time, if you were focused maybe 5 months ago about building your own harness or using these harnesses and open-source models, and then the cost of the frontiers drops so dramatically to the point where you now have frontier-ish models that are cheaper than open source. In some cases, maybe that wasn't the best use of time. So, how are you thinking about allocating time to getting the most out of open models where it makes sense versus trying to avoid just wasting time when the cost of intelligence will continue to fall?

So, we actually did something pretty smart If I do say so myself, pretty early on. So, I'd sort of predicted that we're going to go through these moments where, like, oh my God, the best harness, the best model, the best— the combination of harness, model, user interface is going to change. And there's so much money, there's so much innovation, there's so many really brilliant people who are working all day, every day, and making AI useful specifically for software engineers. It is foolish to commit to a configuration today. You know someone else is looking at it and saying, wait a second, that is the best way of writing software, except I have a better idea. And writing software just became the best it's ever been by the hands of the company I'm about to compete with. So, like, the whole recursive self-improvement that everybody's sort of either excited or terrified about, it hasn't come to the models yet, but it's certainly come to the development industry. through recursive self-improvement of software engineering for humans and agents together. And so sometime around January of this year, we split off a team of about 12 people and basically said, your job is to make our development experience the absolute best for the current state of the art in a way that is easy to take advantage of now, but switch out to the next best thing later with a thoughtful, continuous—

Mm-hmm.

matter. So, we don't want to have this disruptive moment where everybody stops, we're all gonna switch to product X. Oh, wait a second, product Y is available. So, we've had this team and it's run really, really well by a bunch of very, very smart engineers who love their craft and know what they're doing as practitioners, but also great thinkers when it comes to developer experience. They have been keeping us at almost the cutting edge of Both the commercial Frontier models as well as open weight models, harnesses, etc., where we organize the entire process through their hands. And whatever it is they offer to the entire company is usually within a hot second of whatever is considered cutting edge. But it's thoughtful enough where if you yesterday you were on harness A and today we really believe harness B is better. They will make the transition really simple. So just having a dedicated team that gives us the best possible developer experience without having to do a handbrake turn every 3 months has been an unbelievably good investment. When we blocked off this team and said, we're going to have this big group of people whose only job is to make us more productive at the meta level, I think some people were kind of doubting the validity of the idea.

Yeah, it's interesting because the alternative is similarly sized companies, you have hundreds of people that are experimenting in real time and be like, well, I think I found the best way to do it. And the other person's like, well, I'm using this thing. And then it's just whiplash.

So, I'll give you real stats on this one since I'm a fan of numbers. So, we were in the experiment-away mode until we had this developer experience team, developer productivity team. And we were probably, I think the percentage of code written by machines and humans together versus Prior to this team's arrival increased by a factor of 10 when we organized the team and said, look, here are the prescriptive approaches we're going to take. And there's always a menu. You can use Cursor, you can also use Claude. We support all sorts of different harnesses and models. But we have a menu versus go figure out what works for you best. The tyranny of choice is a terrible thing. And telling a software engineer, go explore over the weekend your favorite of writing code with an agent, it's not gonna be a weekend project. It's gonna be a 6-month-long project. So, lopping that off into a separate area where you have a rigorous approach, and then we constantly produce, here's the best way according to this team, and here's some of the choices you have in there, has been really, really useful. We know it's doing well for us. So, we measure productivity long before AI in PRs, pull requests, per engineer per unit time. The cost per PR, fully loaded, everything from salaries all the way down to AWS costs, has come down 30% since we created this developer productivity team. And so, not only are we increasing the amount of code we're writing because we're able to leverage all these agents, the true cost per pull request is coming down quite steadily and has been for a while. And so, I'm—

Very cool.

Very excited about what's to come there. But I love the fact that we have this really Well-constrained approach.

Makes a lot of sense. One word answer for the next one. Since you like numbers, what's your P/E?

No answer.

No answer. All right, we'll get to it next time.

Thanks.

Thanks so much for coming on the show. Great day. We'll talk to you soon. Goodbye. Let me tell you about CrowdStrike. Your business is AI. Their business is securing it. CrowdStrike secures Here's AI and stops breaches. We got Sam Ross from Numeral, the co-founder and CEO, in the waiting room.

Is that gong ready?

Sorry for keeping you waiting. Sam, how you doing?

Welcome to the show.

Big dog.

Doing well.

Big dog.

We got a fresh gong now. Jordi already broke one, I think because he was celebrating that it's only 92 days till Christmas.

That's right.

But we got some bigger news than that, a number that's bigger than 92.

Most boring—

How much did you raise?

The most boring AI company in the world, which—

Whoa!

Which— no, no, no. They ran that as an ad.

Oh yeah, that's our ad.

That's our campaign.

Oh, yeah.

And you guys trigger a bunch of people.

You triggered me. I don't find it boring at all.

Anyways, let's talk about the round.

How much did you raise?

We raised $100 million with Jordi.

Insight Partners. You got Salesforce Ventures. You're being careful if you shake hands with Mark Benny off in the wrong place. You don't want to get frame-mogged. That's a big risk when partnering up.

I know he's already mogged you guys.

Yeah, we were early.

Jordi more than you, I guess.

Yeah, both of us.

Absolutely brutal.

What unlocked the round? What was the most exciting thing that Insight latched onto? Is it just top-line growth? Are the margins better than what we're seeing in other companies? Like, what was the thing that they were like, okay, let's Let's back up the truck.

Yes. Well, we solved sales tax, RSI. Beyond that, I think ultimately this is— this business is, you know, sales tax is not going anywhere. In fact, it's growing in California. Starting in January, all businesses selling software have to collect and remit tax on software. So there's just a growing trend where as the world— as AI takes up a bigger share of of the economy. This is going to be more and more of the tax dollars are going to be taxing things like AI. On top of that, I think you look at the world of accounting and really our space is like tax advisory and AI has not penetrated that space as much as areas like law. And so there's a, you know, there's some really large potential there to build a really large business. And so I think, you know, we've been building this business for about 3 years. We've had You know, phenomenal growth. And I think just, yeah, with a great engineering team and great customers, that's what gets the investors excited.

Here we go. What are the most valuable growth channels for you? Are you able to sell through tax accounting firms and then the accountants tell their clients, hey, you should be using Numai? Or do you go direct to the CEO of the biggest software companies in the world and say, you got to use Numai?

Yeah, look, we do all of the above. More and more, partnerships with firms is getting important for us, especially as you move upmarket, and these complex businesses really trust their advisors.

Sure.

I've always been someone who has— before this, I was running e-commerce businesses, so I love the world of growth. And so, you know, a lot of direct sales as well, all the things you'd imagine that most SaaS companies are doing, a lot of marketing.

Oh yeah. Sorry, Jordi.

Go for it.

I was just wondering about $100 million. Are you staffing up? Are you hiring a lot of salespeople? Are you just going to run even bigger ad campaigns? Like, how are you seeing deploying this capital?

Yeah, I think for this money, it's primarily focused on R&D. So again, There's a lot to be building in the space around building things in the tax advisory space for firms, for companies directly. And I think the space is heating up. You see companies like SponsorRamp building in the space as well. And so, I don't see them as competitors. This is a big space with a lot of different sub-verticals. We're really focused right now on the indirect tax space. things like sales tax, VAT, we file in 80+ countries. And so, there's a lot of low-level grunt work that gets done by armies of tax workers throughout the globe, and that's what we get excited about, going and making their lives easier so people can be more strategic.

Last question, and it's a choose-your-own-adventure. You can answer either of these questions. You don't have to answer both. One, what's your P doom? Two, what's the biggest fish you've ever caught?

Ooh, P doom. That that's that's based on time. Well, we already we already solved we we already solved RSI. Sales tax RSI.

Okay, and we're and you guys are fine, and we're fine.

We're living in the future. Live to tell the tale. Yeah, P doom zero. A vote of confidence. I love to see it. Well, congrats on the new round. Thanks so much for hopping on the show.

We're gonna close out the show with you. We did have a hard stop. Sorry for the little running late on the schedule, but I wanted to close out the show with you.

Well, then I gotta tell him about Shopify. Shopify is the commerce platform that grows with your business and lets you sell in seconds online, in-store, on mobile, on social, on marketplaces, and now with AI.

Sam, I wanted to throw a flashbang with you as an early partner of the show and friend. So I'm gonna throw it, and then we'll sign off. And congrats to the whole Numeral team on an awesome milestone.

Yes.

Thank you. I wanted to also give a shout out to our customer Lucy.

Oh yeah, that's right. Thank you. I don't have it here.

Aurora Water Filter is another customer of ours.

So, you know, the Shopify Numeral ecosystem is cooking.

It's powerful.

Everyone's working together.

Let's hit it.

Well, thank you for tuning in to TPBN. We'll see you tomorrow. Good luck.

Bye.