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[music] >> You're watching TVBN.

4:35

Today is Wednesday, February 11th, 2026.

4:37

We are live from the TV to be back.

4:40

The temple of technology, the fortress of finance, the capital of capital.

4:45

Let me tell you about ramp. com. Time is money. Save both.

4:48

He's used corporate cards, bill pay, accounting, and a whole lot more all in one place.

4:51

We have a great lineup for you today.

4:55

We got Matt Schumer coming on the show to talk about something big is happening.

4:59

His viral essay, 45 million views, completely broke containment.

5:04

That has to be up there in the competition if it was posted during that $1 million challenge.

5:11

Uh, we also have Harley from Shopify coming back.

5:13

Vlad from Robin Hood's coming on.

5:15

Jeff, founder of Twilio is coming on.

5:17

Jeff Lawson, Sam Blonde, who I worked with at Founders Fund, uh, is launching a new company.

5:21

Monaco >> and John Ferrara, who's been on the show, I believe, at YC demo day and so we've only talked to him in person and he's coming to the Ultradome again.

5:29

So, we will see him in person at two.

5:31

Well, is something big happening?

5:34

This is the big question.

5:37

Um, I think it's a good essay.

5:40

I don't love the COVID comparison for a few reasons. It's good.

5:46

It's good in the macro, but I think when you dig into, you know, how much is AI and fast takeoff and the advancement of these models really like COVID?

5:54

I have trouble with that analogy in particular.

5:57

Um, so back in February of 2020, everyone in tech was aware of how quickly a virus could compound because everyone in tech had had followed exponential curves. We all knew Moore's law.

6:11

Uh, there's that funny quote, the most powerful force in the universe is compound interest.

6:17

People in tech like to attribute that to Albert Einstein.

6:19

There's actually no evidence that he ever said it.

6:21

Uh, but uh, it's it's still fun.

6:23

But everyone in tech is obsessed with exponential growth, exponential charts, you know, everything is about exponentials.

6:30

So seeing an exponential curve and maybe studying math or something like that, uh just made people much more aware that uh if COVID got out of control and wasn't contained, you would just see rapid rapid ex uh explosion in the number of cases.

6:46

And that of course held for most of COVID, but it wasn't a true exponential.

6:51

And I've said this before, um there are very few true exponentials in the real world because of course things cap out.

6:58

Uh they turn into logistic curves.

7:01

So instead of going up and to the right indefinitely, they go up and to the right and then they then they plateau. Now will AI plateau?

7:07

We've there's been a series of plateaus.

7:12

There's been a series of S-curves.

7:13

That's the story of technology really.

7:15

As you zoom out, you see smooth exponential growth.

7:17

But in the moment you see a number of of S-curves.

7:20

You see the desktop, the mainframe, then then mobile, then the internet and cloud.

7:24

You see these different these different curves.

7:28

AI is certainly one of those.

7:29

You could put LLMs, reasoning, agents, a whole bunch of different uh technologies that have grown have that have sort of if if they didn't happen, there would have been a plateau, but then we get the next thing.

7:40

And so the the the math around co the COVID exponential always bothered me because it was exponential growth for a while.

7:48

Um but you can't keep growing indefinitely exponentially because there's only 8 billion people on Earth.

7:55

Something like a billion people got reported COVID cases but you just can't 100x from there. Like it's impossible.

8:01

There's not a h 100red billion people to infect.

8:02

So eventually the growth rate has to slow down.

8:04

And of course, there's a whole bunch of other dynamics where if if a bunch of people have had COVID, they can't really infect each other anymore and all sorts of different things.

8:11

There's a great >> and just jumping in chat, we are aware of a number of audio issues, so we're working on fixing that. Thank you for flagging.

8:20

>> Um, so, uh, back to AI.

8:20

Um, if you model the power of artificial intelligence just purely as a function of energy, uh, we have plenty of room for for exponential growth.

8:33

We're we're we're truly very far away.

8:35

Uh humanity is around 13 orders of magnitude away from Cardartesev type two like full Dyson sphere capturing 100% of the energy that's produced by the sun.

8:44

Uh even just in terms of how much energy we're using uh on AI that we have the power that we generate on earth we're less than 1%.

8:52

So we can grow that significantly and that's why it feels exponential now.

8:55

But there will be a whole bunch of bottlenecks all over the place. It takes time to adjust.

8:59

place. It takes time to adjust. There are certain industries that are sticky and so I like the framing of you know it's time to talk to your friends outside of the tech world about AI but it doesn't feel exactly like co because co affected people you know older people people who were not online reading

9:18

biology Seruvasan's post about co studying the exponentials modeling the ars uh so it was very it was very advantageous to go to people who were not aware of what was coming and telling them like, hey, like you are going to need to stay inside for a little bit because it's going to get rough out there. And people didn't. It happened it And people didn't.

9:34

It happened it happened extremely fast.

9:36

Um, and a lot of people when they think about AI, they have very antiquated views.

9:40

They still think like, oh, the images of six fingers, and they don't notice that they just watched five AI generated reels that they couldn't detect.

9:48

Uh, or they talk about hallucinated facts and LLM responses, something that's basically been solved by deep research and reasoning models.

9:54

Uh, knowledge cut offs like, oh, it can't tell me what happened today.

9:57

Like, no, it can actually tell you the weather today.

9:58

can go and look that up on the internet, no problem.

10:00

Um, and so many people still use these reference points and maybe they dip their toe in, but it's definitely time for them to dip their toe in again. So, this is good. I love that.

10:10

Uh, at the same time, um, they're the coding models, as remarkable as they are, they'll reshuffle the economics of tech.

10:19

We're seeing this with the SAS apocalypse.

10:20

Certain companies will be stronger beneficiaries of AI.

10:22

Others will be damaged because maybe their only moat was that they had a complex software system that was hard to migrate off of.

10:29

All of a sudden an agent can just do it for you.

10:30

Um, and you don't want to be uninformed, especially if you're in that industry.

10:34

If you even if you're just a buyer of that industry and all of a sudden it's more competitive, hey, you should be getting a better deal.

10:40

Go get go renegotiate your contract.

10:41

But, um, when I think about telling my friends outside of tech about the coming wave, I'm just not entirely sure how helpful an understanding of coded coding agents will be for them.

10:51

I was thinking about like some of my real world friends like I'm friends with a surgeon like yes he has a SAS product that helps him book clients he should probably renegotiate that I don't I would not recommend him vibe coding his own payment system and his own you know customer relationship management system.

11:24

Yeah, compliance just a headache.

11:26

He should just maybe it's cheaper.

11:27

Um there will be more pricing pressure.

11:29

So find a better tool, find a faster, find a newer tool, >> like the humanoid robot that can operate a patient in a surgical and has the trust of the patient.

11:38

It's coming but is away and he's up to surgical tools and how surgeries are developing and that's like this month.

11:46

>> So compare him to Matt Schu Schumer. Yes.

11:48

The the guy who wrote this. >> Yes.

11:50

And Matt has been building what appears to be, we can talk to you about it, but like the thinnest possible wrapper over >> AI and other models, right?

12:00

It is >> according to the definition your AI personal assistant writing and productivity tools. >> Yeah.

12:09

So >> again, like this is I don't know.

12:10

I can see him using >> ChachiBT. Yes.

12:16

and Claude and Gemini and thinking, >> "What am I doing with my life?"

12:22

>> Well, if he used the tool to write this, it clearly worked because he got 45 million views and 65,000 likes >> like on the AI on the website.

12:33

It's the AI writing assistant with web search and citations. >> Yeah.

12:39

>> Which you can just get the models to do today. >> Yeah.

12:42

when he started this, I'm I'm sure they didn't have great search.

12:46

They probably couldn't do citations very well.

12:50

>> And so, he's been his business has been getting steamrolled >> by the labs. >> Yeah.

12:56

>> And a lot of the lab founders kind of warned about building this kind of >> Yeah.

13:01

Sam Alman famously said, "Don't build a startup that assumes the models will plateau in capability." >> Yeah.

13:08

And then [clears throat] he built Sora and if you and that was a little bit of a violation for that but sort of in line with what he was doing.

13:15

Um but at the same time uh yeah if you were just building a rapper and saying I'm going to I'm going to you know do better citations that that that was always messaged as like hey you're going to have a rough time. Yeah.

13:26

>> Um, and so I would definitely talk to any software engineers in your world about what's happening, how the level of abstraction.

13:33

I mean, just just yesterday Run posted something was like whatever level abstraction you're giving to the AI agents, you should probably be delegating one level above that.

13:40

And I think that's a good that's a good frame of mind.

13:44

And so if there's someone out there that says, "Look, my company for some reason hasn't been really on the forefront of AI adoption.

13:49

I don't really have access to the models or they're not approved."

13:54

It's like, yeah, you should probably be using these in your free time a lot to get up to speed to know how to actually use the new tools as effectively as possible because that's clearly where the future role is going.

14:05

Um, but in many areas of the economy and many areas of society and many groups of people that are outside of tech, if I sit them down like I have a friend who's a teacher and I say, "Oh, like like coding agents are here.

14:18

You need to understand that this is going to change everything.

14:22

This is going to be like co."

14:23

co." It's like well for the teacher like COVID was important because they could go there they could get sick and then they could not work and they could you know and the school could close but if the software gets better it's like yes in the far future like you might go to you might be like I want my kids to go

14:39

to the school with the humanoid robots because it's cheaper or something like that but we're not there yet and so if the software gets better then I'm talking about like grade school like it's mostly like distracted kids they'll be distracted by like better AI slot feeds basically. Yeah. Um, but the Yeah.

14:51

Um, but the actual pro process of like, you know, you want your kid to go be with other kids and that have a have a teacher there monitoring them and nurturing them, that's not immediately disrupted.

15:05

Like, yes, it will change over the next decade.

15:07

Like I'm not I'm not AI bear here.

15:10

I'm just saying like I don't know that February 2026 will be the month that like surgeons change or or what do you >> Sorry, I got to jump in.

15:18

I know everyone I know we're still having audio issues.

15:21

The team is working on it, but the chat is funny.

15:24

[laughter] God terminal says, "Tax loss harvesting my audio right now."

15:29

>> Is this the >> Someone else said, "Is this the seed dance cling sora version of TBPN?"

15:33

I asked people if they had uh kind of closed the app and reopened it.

15:38

And Trey says, "Already sold all my devices."

15:42

[laughter] >> Anyways, uh thank you for bearing with us.

15:47

>> My boy Plunger says, "We're back." So, let us know.

15:50

Let us know in the comments. >> Whoa.

15:51

The chat's saying we're back. >> Chat says we're back. Hopefully.

15:53

A agi as we're in the fast takeoff, but we can't get reliable.

16:00

>> Wait, cut to John's screen for a second.

16:02

I want to test something.

16:06

[music] >> We're so back. >> It still works.

16:10

At least the At least the graphics package works.

16:13

>> Ryan Surf says, "TBPN terrible buffering personal nightmare."

16:16

[laughter] >> Oh no, we're getting cooked.

16:17

Let me tell you about Cognition.

16:20

They're the makers of Devon, the AI software engineer, but crush your backlog with your personal AI engineering team.

16:25

Um, [snorts] >> all right.

16:27

Thank you for bearing with us back. >> Thank you.

16:29

We'll talk Yeah, we we will talk more about this with Matt.

16:31

There's a lot of interesting things.

16:33

I just I you know, I'm bullish on AI.

16:34

I do think like there's the software only singularity is super real, the singularity broadly.

16:40

I still believe in the Kerszsw Wild timelines, but it's just like I don't know that February is the year is the month.

16:45

February 2026 is the month where like everyone is changed.

16:50

Whether you're like a car mechanic or like I have a friend who operates a bunch of gas stations.

16:53

Like one of the things he had to do was like kick someone out who was trying to steal stuff.

16:59

Like there's a crazy video of him like jumping over the counter.

17:01

And like it's just like the humanoids will change a lot.

17:05

That's not quite here yet.

17:05

we're we're we're still like in this like slow takeoff in my opinion.

17:10

Uh it is remarkable and it's a lot of fun to talk about.

17:13

So I do think the recommendation of like talk to your friends about advances in AI is awesome because you can just say hey like look at this personal website let's build you this.

17:22

Oh you have a wedding coming up like here vibe code your wedding website like what do you want to do?

17:25

Like there's a whole bunch of different things you can do and you can understand how that will affect the economy and different stocks and different businesses but uh for most people it won't be like co where 100% of people were like somehow somehow affected by it you know whether it was like oh the thing that I like is closed the coffee shop I like is closed or I I don't I'm afraid to go outside.

17:47

>> The question I have is like even even five years ago there was kind of a running joke where it felt like a lot of office jobs were just fake. >> Yeah.

17:55

And >> yeah, >> and even when people kind of like started that became part of the zeicist and people were talking about it, yeah, it didn't mean all the jobs went away.

18:04

Yeah, some jobs have gone away, but again, headcounts at, you know, even a lot of these companies have have stayed >> Yeah. >> uh relatively stable.

18:10

Uh we had a good jobs report.

18:13

Uh surprisingly, >> yeah, economists expected 65,000 jobs.

18:18

The number came in at more than double at 130,000 jobs.

18:20

We'll see where it lands in terms of >> but but yeah the question is like okay the jobs have always been some email jobs a lot of email jobs have been pretty fake >> and what happens if agents can do a lot of these jobs do the fake jobs remain >> and how fast >> overall overall like I didn't uh I I I was joking I I I responded to the article and I said TLDDR freak TF out and sell all your money immediately.

18:49

People were asking what do you sell your money for? >> That's the point. I was joking around.

18:54

Uh I thought Jeffrey said it's depressing how widely shared and read this is.

18:58

It's AI generated word salad posted by someone with vested interest in spreading AI hype.

19:04

>> AI is big I guess but its effect will be much more complicated than this essay quote unquote essay implies.

19:11

>> Um so really really going really going hard.

19:13

Uh but again it it felt like something like you know send this to 10 friends or you will be in the permanent underclass forever like kind of like high school.

19:23

>> Yeah it was a little bit of like a throwback to the the permanent underclass.

19:25

Tyler, what was your interpretation of it?

19:27

>> Yeah I think my main critique is like uh I think with co it's like very destructive, right?

19:31

Um maybe you lose your job but like at the very least like you you might get sick things everything is like bad. Yeah.

19:38

>> Um with AI it's like this article is like yeah people are like going to lose their jobs.

19:42

That's like kind of what you should be aware that like your job might get automated.

19:46

>> Um but like AI is like fundamentally like it's like a productive tool, right?

19:50

So I imagine like >> we're not it's not going to cause a recession and that like GDP is not going to go down, it's going to go up. >> Yeah. Yeah. >> Um makes sense.

19:57

>> And so I think my base case is like jobs >> actually get like way more fake generally. >> Yep.

20:02

Um, like now it's like I mean there's probably like hundreds of people on X.

20:06

Their entire job like their salary is just posting like basically fake AI news and they get [clears throat] paid by it's not even like sponsored deals.

20:14

It's like they're just getting paid by X directly.

20:16

Like that's like completely fake job. >> Yeah.

20:18

>> But like that's going to go up.

20:18

There going to be more of those. [laughter] >> Yeah. Yeah. Yeah.

20:21

I mean the the the jobs have been getting faker ever since we stopped tilling the fields. Correct.

20:28

Isn't that the uh uh I mean that was the original Sam Alman formulation was like if you explained to someone 200 years ago a bunch of people will be sitting around talking about the news and and they'll be filmed it'll go over the internet.

20:41

It's like it makes no sense.

20:42

And yet here we are running a business doing ads for Octa.

20:44

Octa helps you assign every AI agent a trusted identity so you get the power of AI without the risk. Secure every agent. Secure any agent.

20:53

Um, should we keep touring the the the the takes the various takes on this article?

20:58

Uh, >> stay sassy says, "I'm exhausted by the OMG, this changes everything.

21:02

AI posts this godforsaken site that I'm planning to take my doom scrolling talents back to Instagram. I believe in AI.

21:09

I use it every day for increasingly non-trivial tasks.

21:12

My team spends a massive amount of money on it.

21:15

Vendors, tokens, acquisition, and I have pitched AI products that we built on stage.

21:18

I believe things are changing fast.

21:20

I don't care to hear some sweaty, overly online online dude's breathless panting over the latest model anymore.

21:26

I don't need to know what's changed in the last 45 seconds in AI.

21:29

I don't need some dork with a weird haircut writing condescending post like he was the first person to get the last Harry Potter book and wants to drop edgy hints about how Dumbledore dies at the end.

21:39

I'd rather miss the latest AI news and just be poor.

21:43

Tell me when the singularity is done so I can pause Singles Inferno and I'll tune back into X then.

21:47

[laughter] the logging [snorts] off.

21:51

Apparently states as he works at the NASDAQ >> apparently.

21:54

U Roberts goal I'm building an answer to exactly this problem.

21:56

Come back in a couple weeks and say is you're building ambient.

22:00

[laughter] >> Nelson says okay but this one really changes anything everything please. I promise. Please.

22:08

>> Yeah people are having fun.

22:08

Let me tell you about MongoDB.

22:10

Choose a database built for flexibility and scale with best-in-class embedding models and rerankers.

22:15

MongoDB has what you need to build what's next.

22:17

Uh Logan Bartlett was uh identifying the the the remarkable uh crazy times we are in says feels like an anonest tweet just vibe coded databick datab bricks with a screenshot in the SAS market will follow 5%. uh sephilopod.

22:36

Yeah, I mean if your job is building a wraparound chatbt like this guy, then it's not surprising that AI can automate that shot. >> Tricky.

22:46

>> Um >> what did Joe Wisenthal have to say?

22:48

>> Joe with a funny post.

22:48

He says, "Seeing a lot of posts from software engineers that are like AI is devouring my job and soon it will happen to everyone."

22:54

And it's like maybe but just because you have an easy job doesn't mean everyone else does.

22:59

[laughter] >> Such good bait. Incredible bait master. >> Incredible. [laughter] Solid bait.

23:08

>> If anyone falls for this, you really deserve it. >> Yes.

23:11

[laughter] And software engineering isn't an easy job.

23:14

And Joe says, "How hard can it be if it's the first thing a computer can do?"

23:17

[laughter] >> That's uh that's so good. That's funny.

23:23

>> Buco Capital say >> quoted it uh and said, "A great comment from a friend who's coding with these AI tools around the clock.

23:29

For the hype you read online, it's just really difficult to tell the difference between a genuine breakthrough propaganda to justify valuations and LLM psychosis.

23:41

>> Yeah, Matt Schumer's article must go incredibly hard if you have LLM psychosis.

23:45

>> I was thinking more about uh Clawed with Ads, the vibecoded drop we launched on the Super Bowl.

23:52

That was an idea that we had Friday morning.

23:53

And after the show on Friday, we sat down.

23:57

We talked about it with Tyler and said like, is this feasible?

24:02

Can we get a functional website up?

24:05

It's a clone of the chat of the of the clawed app interface.

24:08

Same color, style guides, fonts, all this stuff.

24:13

Like coding that by hand feels like a week long project.

24:16

I don't know how long it would take normally, but like it's it would be harder and it was clearly accelerated.

24:23

And I was thinking about like if we didn't have coding agents, what would we have done?

24:28

Like we could have paid a dev shop 10K to build something like that, but we probably just wouldn't have done it at all. Right. >> Disagree. >> Okay. What What do you think? How would it play out?

24:40

>> I was do I was doing kind of drops, stunts like that before coding agents were a thing. Yeah.

24:48

>> And you could just work hard and do that. >> Just grind.

24:50

like Dylan and I, you know, we we did we did one back in the day with Party Round called Helpful VCs.

24:57

This was during, you know, kind of this was, I think, like May or June. Yeah.

25:02

>> Of 2021, so it was before the crazy NFT boom had really started, but Cryptounks were popular.

25:07

And uh we made a collection of like 400 NFTTS of uh various VCs and we just put them on a website and said if you don't repost this site in the next four hours we're going to auction off your NFT. >> Yeah.

25:23

>> And uh and so you had like 400 VCs reposted it very quickly.

25:28

>> Uh and that was an example of like a funny idea like clawed with ads where we just had the idea, we worked on it for a few days, shipped it and that was it.

25:34

So this kind of thing was >> how how long was it? a couple days.

25:39

>> It was definitely no more than than five business days.

25:44

>> We got this done in like one day.

25:44

It's f >> Friday to Sunday.

25:47

Tyler was still shipping. >> Yeah.

25:50

>> Like like obviously like I'm extremely bullish on these tools and they're like incredible, but it's still like I was spent like most like almost all my Saturday like building out.

25:56

It's not like it's like [laughter] you took one for the team.

26:02

You you you sacrificed your weekend.

26:04

>> No, like like these tools are like employee of the month. Employee of the month.

26:07

I still I still you know they're not so incredible that like it can't like literally oneshot it in in 5 minutes.

26:14

You can't just tell cloud code build exact replica >> and it it's not it can't actually like do that yet. >> Yeah.

26:19

W- without you it would not have happened because I was busy on Saturday with a bunch of different uh I had a a friend's birthday party and stuff and I wasn't able to lock in even if I understood the tools as well as Tyler does.

26:33

And so it just feels like >> and I just like comparing it to the new Yeah.

26:38

to comparing it to the helpful VCs drop like we had to create original artwork for 400 VCs that you would have actually that would have been much easier with with uh Genai. >> Totally.

26:49

>> Uh so that was a factor too.

26:51

>> But you're talking about >> anyway. >> Yeah. I Yeah.

26:54

I'm just wondering like you know there's the Jebans paradox.

26:55

We go back to Jevven's paradox here is like is is this an example of intelligence getting cheaper to meter and then more ideas flourishing, more projects being built, more things happening uh versus um versus something that we would have done anyway and it's more just like a cost savings thing. I don't know.

27:15

It it goes back and forth but people are people are debating and people are enjoying the uh the AGI.

27:19

Megan [snorts] Fritz says, "Bro, you got to listen. AGI is here. It's smarter than me.

27:24

smarter than Neil Degrasse Tyson.

27:26

Bro, there is literally no escaping it.

27:28

They're putting AI in your shoes.

27:30

They're going to put AI in your cereal, bro. Bro, listen.

27:34

The only way to survive this is to buy a premium AI subscription, bro.

27:35

I swear hardly make a commission. Please, bro, buy it.

27:41

>> That was a funny thing.

27:43

>> Call to action to what was the >> What is the call to action?

27:45

I I actually missed that part.

27:47

Um it's like buy a subscription uh to OpenAI or to his app because if this is content marketing like genius like >> no he just said sign up for the paid version of Claude or Chad GBT. >> Okay. Yeah. Yeah.

27:59

And I mean anyone who's saying that like this is like spawn con for the found for the AI labs. Like that's ridiculous.

28:04

Like that's not that's not what's going on here.

28:06

This all feels very genuine.

28:07

Uh it's just it's just how nuanced is it?

28:09

So yeah start start using AI seriously.

28:12

It's not just a search engine.

28:14

just a search engine. uh sign up for the paid version of cler chat gbt like you don't you don't post that if you're for economic gain so I don't know anyway graphite code review for the age of AI graphite helps teams on GitHub ship

28:27

higher quality software faster [applause] uh delicious tacos favorite account says moratorium on AI CEOs using AI to write long-winded articles on how scared they are of AI very true there's a lot but I wonder this didn't trigger my this is AI writ slop uh you know vibes. Maybe there was

28:45

Maybe there was AI involved somehow, but it felt like it was sort of just I don't know very readable.

28:53

I I it didn't it didn't throw me off.

28:55

Um anything else you want to cover on this or should we move on to a different story because there's a lot going on in the news today. >> Uh we can move on. >> Okay.

29:04

I want to talk about Tai Lopez.

29:07

Tai Lopez, the retail investor, retail rival, retail revival vow, burned investors.

29:13

The Wall Street Journal has a has a deep dive on Tai Lopez.

29:15

He pitched Radio Shack tier One turnarounds.

29:18

Now, the SEC alleges a Ponzi scheme.

29:20

Uh Tai Lopez was living proof of the American the American dream was still attainable for young men willing to bet on themselves.

29:29

The entrepreneur hosted parties at a mansion in Beverly Hills and boasted about the black Lamborghini in his garage.

29:36

The college dropout had made a name for himself on social media by offering get-richqu advice and self-help courses.

29:42

He also had a book subscription company.

29:45

You would pay $30 a month and he would send you just a box of books, which was like not that scammy.

29:52

Like kind of a funny cool thing.

29:54

I mean, the books were like very like >> he was automating book buying.

29:58

>> Basically, >> a lot of people are popping on to Amazon to buy books they don't read.

30:02

>> He's like, "Why don't I why don't we just set this up on a subscription? Save you the time." >> Yeah.

30:05

He had this whole he had this whole thing about um uh knowledge and how like uh the the original pitch for here in my garage was like look at all my supercars that grabs your attention.

30:17

He's like but you know what's more important?

30:18

Turning around a bunch of airport non-fiction.

30:22

[laughter] It was like you know a bunch of these like books behind him and he was like this book wall is more important than anything.

30:27

Um where where is the actual article in the timeline? Here it is. The Wall Street Journal.

30:31

Uh, [snorts] so the college dropout had made a name for himself on social media by offering get-richqu advice and self-help courses.

30:39

He was one of the first people to really understand the economics of YouTube ads that when he went live with his YouTube ad campaign, he had the LTV to CAC so dialed that he was able to spin it up and just spend millions and millions of dollars on YouTube ads.

30:54

And I don't know if he owned the Ferraris or rented them, but like it clearly worked.

31:01

It was like the first real breakout uh not influencer campaign but direct YouTube ad network campaign.

31:08

Very broad, not didn't need to be super hyperargeted or anything like that, but it it clearly worked.

31:15

So he urged his followers to invest in a new company he had started that was scooping up distressed retailers on the cheap.

31:21

RadioShack, Pier 1 Imports, Dress Barn, Modell Sporting Goods, and Linens and Things with a promise to turn them into e-commerce winners.

31:31

>> That was always a weird >> weird crazy pitch. >> It was a crazy pitch.

31:38

>> And it's crazy how quickly the brand recognition drops off. Yeah. Radio Shack. All right. I know that one.

31:42

Pier One Imports, I know that one. Yeah.

31:46

Dress Barn, do not know that one.

31:46

Modell Sporting Goods, do not know that one. Linens and things. Do not know that one.

31:53

>> At least linens and things.

31:53

I can guess what they sell.

31:55

[laughter] Uh I don't know what Pier One sells. I I Pier One imports.

32:01

>> And it's crazy because almost every single every single item that that these retailers sell >> sells on Amazon and Walmart. com. Yep.

32:09

>> At at extremely thin margins. >> Yeah.

32:12

I mean it's really like a referendum on the on aggregation theory and and if you're not aggregating customers um you are just getting >> maybe that was a deeper level of the pitch.

32:22

[snorts] >> What was that?

32:24

>> One customer database. >> Yeah.

32:27

>> Leading retailer brand. >> That was sort of it. Yeah. Yeah.

32:29

One one unified e-commerce front end but uh little late to be going after.

32:33

I mean there was there were some successful um you know come from behind stories.

32:39

Uh what was the company that sold to Walmart for a billion dollars or a couple billion dollars?

32:44

That one did pretty well.

32:45

I forget what that was called, but Walmart made an acquisition of an e-commerce infrastructure provider that did have an e-commerce front end, but it never reached escape escaped velocity, but it was like the perfect plug-in uh add-on to Walmart's infrastructure.

33:00

And now Walmart's a trillion dollar company.

33:01

I think it might might be a little bit off today, but we'll [snorts] see.

33:04

Uh so Shawn Murphy is an example of someone here.

33:06

He saw Lopez's posts on his Facebook and Instagram feeds and was drawn in by the brand names and the promise of 20% returns.

33:15

Always odd to pitch a promised return.

33:18

Um but I think >> and this is called uh you know first kind of major error.

33:22

Having a bad business idea like buying old retailers and trying to revive them. Yes. >> Is not illegal. Yes.

33:30

>> But general solicitation. >> Yes. Very very >> No. No.

33:34

and and and we'll get into specifically what he was promising and then what he was delivered and the gap >> and you see you see some startup founders try to get around this by like generally signaling on X that they're amazing >> uh but uh I feel like the industry does a pretty good job of not doing this. >> Totally. Totally.

33:52

Really quickly, Phantom Cash fund your wallet without exchanges or middlemen and spend with the Phantom Card.

33:57

So, he invested, Sean Murphy invested $175,000 into the company called Retail Commerce Ventures, E-commerce Ventures, Rev and Related Lopez Ventures.

34:08

All told, Lopez raised more than $230 million from hundreds of mostly small investors.

34:15

You know, we we we talk about these big funding rounds and we're like, oh, like, how did this person get this much money?

34:22

And we hear about the SPVS and the layered SPVS and all the all the bringing retail into the private markets, but like he really did it like that the power, you know, we a lot of people have seen the Tai Lopez takedowns and sort of don't don't have a ton of respect for him in in the business community, but uh he really does have a serious audience of people that have, you know, money that they need to invest.

34:46

So, one way or another, and if they get caught in the wrong place, they might uh write a check that they wind up going on to regret.

34:52

So, Murphy is another example.

34:54

He's an Illinois grandfather.

34:56

He got a $10,000 Pier1 gift card and monthly checks of about $1,000 for two years.

35:01

What he didn't know was that his payouts allegedly were funded mostly by other investors. >> Second mistake. >> Second mistake. These guys lied. He said they conspired. They led people on. Uh, poor Murphy here. uh Sean Murphy.

35:15

Um the payments stopped abruptly in late 2022 and the struggling retailers were then taken over by some of the company's creditors.

35:25

>> So he had the 230 million of equity and then he also left >> that. Yeah.

35:29

Uh and so the creditors got uh you know control of of the assets.

35:32

Uh last September the SEC filed a civil lawsuit against Lopez and his partners accusing them of running a Ponzi scheme, misleading investors and misappropriating $16. 1 million.

35:41

The FBI has been contacting investors as part of a criminal investigation into what happened.

35:48

According to people familiar, no charges have been filed yet, so innocent until proven guilty here, but the Wall Street Journal has some good data here.

35:54

Uh, Lopez and his lawyer, Marty Ready, didn't respond to requests for comments.

35:59

Court filings indicate that lawyers for Lopez and other defendants are in settlement talks.

36:02

So, on his podcast, The Tai Lopez Show, and in his social media posts, Lopez, who's 48 years old now, hasn't addressed the company's collapse and the heavy losses incurred by his investors.

36:12

The day [snorts] the SEC filed suit, he posted on X, "Never doom.

36:15

No matter how horrible the situation, don't ever think you're doomed unless you are dead.

36:19

All defeat is psychological."

36:22

Was he talking to himself there? I don't know.

36:26

>> Yeah, I guess staying staying in character.

36:28

>> So, uh, >> I just can't believe how much like the the check sizes for some of the people that he was bringing in.

36:33

Uh, apparent Nelson Row says, "Lope seemed credible.

36:39

an 82-year-old retired real estate broker who invested $300,000.

36:41

The story sounded so good.

36:44

They had all these brands. >> Yeah.

36:46

Imag like you can imagine somebody like this like >> goes offline for 10 years >> and then just like logs onto the internet and it's like wait this guy has Radio Shack one imports linens and goods.

36:59

>> Yeah, linens and things.

37:01

>> Linens [laughter] linens and things.

37:03

>> I mean this seems like a winner. Uh so yeah. Yeah.

37:05

quick quick Google search could have could have helped to avoid this.

37:08

I mean, it's I I feel like it's under discussed how Tai Lopez effectively drove an entire seemingly a generation of young men to inspire to aspire to build like a personal brand. >> Sure.

37:24

and and he Tai Lopez's greatest contribution which I would say is not very great is he inspired tens of thousands of young people to try to make their money in info products which is like still perpetuating itself because it's sort of like a it's kind of like a virus >> because >> somebody starts doing it they get people down their funnel the people get down their funnel they realize like hey like this guy's actually making money courses.

37:54

I should learn from him how to do courses.

37:56

And it just kind of creates this web of >> people selling um info products and and you know flaunting uh >> uh bunch of uh of their lifestyle. So >> yeah. Yeah.

38:07

Anyways, there's so many layers.

38:09

The you know the course that teaches you e-commerce or drop shipping and then the course that teaches you to sell courses on e-commerce and we need to do the final boss.

38:17

a course that teaches you how to sell courses about how to sell courses about how to sell courses about how to sell e-commerce or something like that.

38:25

Anyway, before we move on, let me tell you about reream one live stream 30 plus destinations.

38:29

If you want to multiream, go to reream. com.

38:33

So, uh in podcast, Lopez has described growing up with his mother in a mobile home in California while his father was in prison for selling cocaine.

38:39

Uh after high school, he said he spent several years working on farms, including with the Amish in Lancaster, Pennsylvania.

38:45

He had about $47 in his bank account and was living in a mobile home in Raleigh, North Carolina.

38:51

He said when on the advice of his uncle, he started looking for a sales job.

38:55

He landed in an insurance company where he cold called clients.

38:59

Lopez has said that his breakthrough came out when he figured out how to write snappy copy for Google ads, which generated quality leads that produced substantial sales commissions for for an for an insurance company and later at a financial services company he founded.

39:12

He went viral in 2015 with a series of YouTube videos titled Here in My Garage in the first >> So crazy that that was 2015 in my head. This was like 2005. >> Completely agree. I completely agree.

39:24

I can't believe it's 2015. It feels much older.

39:28

It feels like the first ad I ever saw on YouTube. >> I know. >> I don't know. Uh yeah, it is. It is retro.

39:35

Uh, in the first Lopez wearing a crew neck shirt, glasses, and a scruffy beard stands in his garage in front of a black Lamborghini.

39:42

What he uh what he likes a lot more than material things, he tells viewers, is knowledge.

39:46

That was the famous line. Knowledge.

39:48

The camera swings to the other side of the garage.

39:53

In fact, he says, "I'm a lot more proud of these seven new bookshelves that I had to get installed to hold the 2,000 new books that I bought."

40:00

That video spawned a slew of parodies.

40:05

Uh, around the same time, wait, around the same time, 2015, Tai Lopez launches 67 steps. 67 steps. >> He did this in 2015. He created the 67 meme.

40:18

Apparently, >> this is crazy.

40:20

67 Steps, an online course designed to help people find what he calls the good life by focusing on health, wealth, love, and happiness.

40:29

Lopez ran conferences where he shared what he said were the secrets for getting rich.

40:33

Uh 67 steps is fascinating because it's this odd number.

40:37

We were talking to Brandon about this how you know 19 details you missed in the Super Bowl halftime show.

40:43

Like the odd number is like oh okay that's like feasible.

40:47

There's also a little bit of sticker thing.

40:48

If I say uh you know 99 cents that's different than a dollar, right?

40:53

Uh >> I was gonna say so so in that video when he when he pans to the bookshelf Yeah.

40:56

One of the books is called a thousand1 books.

40:58

So it really has he has 30,0001 books. >> There we go. There we go.

41:01

Books inside of books layered.

41:04

>> I guess where Mosi took this to the next level where his new info product is selling like tens of thousands of books at the same time.

41:13

>> There I I believe there was a a checkout purchase that I saw a screenshot of was that was that you could buy like a box of copies of the book or something.

41:19

I think that's very good for ranking on the New York Times bestseller list.

41:23

And I believe he didn't he set a world record for most books sold or something like that. Wild.

41:28

Uh so uh you know all all sorts of different book marketing strategies out there.

41:35

Uh our biggest mistake is almost always thinking too small, he said in a social media post.

41:40

He hosted influencerfueled parties at a Beverly Hills mansion he rented with a pool and basketball court.

41:44

In one 2015 video, billionaire Mark Cuban visited Lopez at the house.

41:48

Two, the two shot hoops and talked life lessons.

41:50

For those who want to be an entrepreneur, "What's the best advice?"

41:54

Lopez asked, "Find something you love to do.

41:56

Be great at it and sell it." Cuban responded. Honestly, good advice. Um, icky guy.

42:01

There's been a bunch of different ways to say that from very high.

42:07

>> I should have turned that sentence into a course.

42:09

He should have put that sentence behind a paper.

42:10

This he's like, "This is such good advice.

42:12

I can't I can't just I got to charge behind the table."

42:16

A lot of the courses it is just like it's already been distilled into a 60-cond reel.

42:21

You pay for the course and you're just getting that 60 seconds repeated 25 times, right? It's uh it's rough.

42:27

So, let's go into the shopping spree.

42:31

>> Did you ever buy a course? >> Yes.

42:33

>> That that actually changed your life. >> Yes. Yes. Yes, I did.

42:35

I bought a course on Houdini.

42:37

On Houdini, which is a uh a motion graphics tool used in Hollywood.

42:43

Uh if you've watched Game of Thrones and you see galloping. Here's the thing.

42:47

What was the course title?

42:48

Was it like how to get rich quick with Houdini?

42:51

>> No, it was like it was like it was like you know like like using Houdini and advanced VFX pipelines.

42:59

>> So you weren't deep you didn't you didn't just the course creator was not driving a Lamborghini. >> No. No.

43:03

The course creator was like I worked on Westworld.

43:06

You want to learn how they did Westworld graphics?

43:07

And I'm like absolutely I would love to pay you $1,000 to teach me how to do that.

43:13

That's really cool and I want to learn that tool.

43:15

I I I I I paid for a number of uh of courses related to content creation.

43:20

Cinema 4D, After Effects, like any like skit even when you see me like edit something, you know, all of that is is I did I did needed to learn it.

43:27

I watched a lot of YouTube videos for free.

43:30

I was also paying for stuff, but none of them were about to learn how to you paid to learn how to fish. Yes.

43:35

>> And now you're feeding yourself for a lifetime. >> Exactly.

43:37

Because I mean courses are good if it's a narrow skill. Yeah.

43:39

I definitely bought at least one workout course when I was probably like 18 or 19. Yep.

43:46

And I de even though it was like effectively advertising a bro split. >> Yeah.

43:54

>> Just learn from >> any Arnold >> Yeah.

43:57

>> video, any quick Google search certainly can get it from Chad GBT.

44:00

It was opinionated and I just followed it. Yeah.

44:04

And it it was well worth the money. Yeah.

44:06

Even though the information was like there there's something about if you pay for something, >> you're much more likely to take it seriously and actually try to follow it. >> Yeah.

44:15

>> And so I won't say even though we're kind of poking fun here, I don't think all all information products are bad.

44:22

>> No, I completely agree.

44:22

P90X that was the workout course that was that was going viral when I was in college.

44:27

The ones I do, the ones I do think are the ones I do think are are like really really really bad >> are when they advertise like trading courses >> to like young younger audiences. >> Yeah.

44:42

>> Because it's like, okay, you have $300 in your bank account. >> Yeah. >> I'm sorry.

44:46

Like you're not you're not going to change you're not going to change your life.

44:51

The crazy thing is that there is a reasonable trading course which would be like like buy ETFs, right?

44:55

Like like there is good financial advice that you could give someone to trade, right?

45:01

And it would be basically like don't trade like buy and hold, right?

45:04

Uh dollar cost average invest a little bit every month. >> Investment firm. >> Yeah.

45:09

Or or go pro and go work at Jane Street or Citadel if you have the chops.

45:14

>> Turn at a wealth management firm. >> Sure.

45:16

Uh the flip side is like a lot of the courses they weren't even they weren't even teaching you how to okay well there's this big AI trend maybe you want to increase exposure to Nvidia, Google, Apple, you know the big companies like that would be maybe a little financial advicey but totally reasonable.

45:33

They were like foreign exchange like ch uh like forex courses.

45:39

So you were trading but it was like essentially on top of a random number generator.

45:42

generator. like it's like the most complex like understanding the trade flows for for proper forex trading is not something you can just like pick up on a weekend like that that is a life's work as opposed to just being like oh well like I'm a kid I'm I'm I'm using

45:56

Uber all the time maybe I should buy some Uber shares like that's a much more reasonable philosophy around financial investing in my opinion than okay well the candlestick went up and it's a camel pattern so it's got to go up like chart yeah uh chartlogy or something what's that called >> anyway live.co, where DTOC brands, B2B

46:11

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46:20

>> Lopez teamed up with Alex Mayer, mechanical engineer, who had co-founded an online dating app that sold for 255 million. Not bad.

46:27

In 2019, they formed Miami based retail e-commerce ventures to snap up distress retail brands.

46:32

Lopez was CEO and Mayor was president.

46:35

Lopez's younger cousin was chief operating officer.

46:39

Uh, according to the SEC complaint, she had previously worked as a substitute preschool teacher, a radio station promoter, and as an assistant uh to the online educational company that Lopez had started.

46:51

The spokesperson for mayor said he believed in Rev's business models, put over 5 million of his own money into the company, and suffered substantial losses when the business was hit with a so-called severe post-pandemic macroeconomic headwinds.

47:04

Burken Road is represented by blah blah blah.

47:07

Uh, Rev's first notable notable acquisition came in 2019 when it paid five million for the e-commerce rights to the Dress Barn name.

47:13

Has anyone in this room heard of Dress Barn? [laughter] >> Crickets.

47:21

[clears throat] Where's the crickets? >> We need it. >> Where's the crickets? >> That's a good one. Team crickets. Crickets sound effects. We got to add it.

47:27

Uh, after the COVID pandemic hit, Rev went on a shopping spree.

47:30

In July 2020, it purchased home furnishing retailer Pier 1 Imports out of bankruptcy for about 31 million, followed later that year by two more bankrupt chains.

47:39

Sporting goods retailer Mo mod Modell's modals for 3. 6 mill.

47:41

Has anyone heard of modals? [snorts] >> Yes. >> No. No. Oh, no.

47:52

>> Uh, and discounter Steinmart.

47:52

Has anyone heard of Stein Mart 6 million? And we got another no.

47:57

I I feel like this is this is we got people from all over the country.

48:02

So I think I think this is uh somewhat representative of the average American.

48:06

And of course Radio Radio Shack undisclosed.

48:09

I wonder how much they got Radio Shack for. I have no idea. Okay.

48:13

Uh there's a there's an interesting tidbit here about Alex Mayer. I had to hunt it down. I'm sorry. I was I was distracted.

48:20

First I'm gonna tell everyone about Label Box.

48:23

Reinforcement learning environments, voice robotics, evals, and expert human data.

48:26

Labelbox is the data factory behind the world's leading AI team.

48:28

So tell me uh so Alex Mayer is you know controversially included in this uh Wall Street Journal article about this uh you know potentially disastrous uh deal.

48:36

Um Jessica Livingston coh founder of Y Combinator is the author of Founders at Work: Stories of Startups Early Days.

48:48

It's a fascinating book with interviews.

48:51

It's basically a whole bunch of podcast type interviews combined.

48:53

So 37 signals, uh, Hotmail, Lotus, PayPal, there's they the the interviews in here are are remarkable.

49:02

Steve Waznjak, uh, Katrina Fake from Flickr, Max Lebch at PayPal.

49:07

This founders at work template, if you see, it has this like we should pull it up, but it's like this very iconic book with just a bunch of names on it and then in orange, Founders at Work, and then Jessica Livingston wrote it. It turned into a series.

49:19

Uh there's coders at work about software engineers and there's venture capitalists at work and venture capitalist at work is a different book not written by Jessica Livingston but Alex Mayer's in it because he founded Zeus which was a dating site and and it's just like a funny like fun fact that he's in this like like book that is sort of tangentially like extremely legit.

49:39

Um anyway, we can move on. Sorry.

49:42

Uh during weekly Zoom calls for investors, Lopez and Mayor pitched new investment opportunities by touting the success of earlier Rev deals.

49:50

According to former employees, at his self-help conferences, Lopez would tell audiences they could share in his success by investing in Rev brands.

50:00

>> Uh Joseph Bertau, a 44year-old who works in construction sales, went to an investor meeting at a Los Angeles hotel.

50:07

Bertau recalled the message, "Give us as much money as you can.

50:09

These deals are popping off and we can't get them fast enough."

50:13

He invested about $350,000. >> So much money. I I I don't know.

50:15

I mean, maybe people are >> at the same time when I when I look back at like my first angel investments, which granted I was like 22. >> Yeah.

50:25

>> I would I I thought that I was seeing good enough opportunities. >> Sure.

50:31

>> That I would happily >> invest half of my like liquid net worth.

50:37

[laughter] >> You say 10% >> which I mean it wasn't that much at the time.

50:40

I was like building my first company. I was like very young.

50:42

I was down to take a lot of risk.

50:44

I was like, "Hey, this is >> But it's got to be different for these folks because this is clearly like retirement money." >> Yeah.

50:50

But but part of it is like when you start seeing >> Yeah.

50:54

>> when you start seeing private deals for the first time, >> it feels special. >> It feels special. You look at the chart. >> Yeah.

51:00

And you know, and in hindsight, I'm like most of the worst, like there's certainly some people that have come on the show.

51:09

Justin Mars is a good example.

51:11

Like you look at the first like three deals Justin did and they were all like at least two were unicorns. Like he's he's insane.

51:16

But for me, I look at the worst investments I've ever made were like >> probably in the first five. >> Yeah.

51:23

>> And so >> people just don't realize how many companies are out there, how many private companies are out there.

51:27

like you see this one deal, you talk to this one founder and you're like this is everything.

51:32

everything. And I and and some of the early uh early angel investments that I made that were didn't go well were um were like okay great team coming out of a great university on a super interesting uh category and what I just didn't realize was that there was like they were coming out of uh waterlue but there was a team at MIT that was six

51:53

months ahead and there was a team at Stanford that was nine months ahead and Sequoia had already backed this one but they hadn't announced and then the you know Andreesa had backed that one and so I is in the one that didn't have any of the backing and was just going to be third in the category, which was just going to create this like power law difference. And if you don't have full

52:08

And if you don't have full coverage, you don't even know that those deals are happening.

52:11

And so you you wind up uh even if you get like the idea correct and like the team is good, you can still wind up in a really rough.

52:18

The other thing here is in one tier 1 pitch deck, investors were told they would receive 200,000 after their first year if they invested 1 million, which again is 20% uh return, which is insane.

52:33

>> Uh if somebody tells you they're >> any sort of like return is usually a huge red flag. Huge red flag.

52:41

>> Anyways, >> before we move on, let me tell you about Shopify.

52:42

Shopify is the commerce platform that grows with your business and lets you sell in seconds online, in store, on mobile, on social, on marketplaces, and now with AI agents.

52:51

>> Uh anyways, I think we can move on.

52:51

This this uh story is still unfolding.

52:53

It is very sad, and I hope that uh the investors that were duped uh can recoup as much of their investment as possible. >> Indeed.

53:06

>> Uh getting into the jobs report. jobs report. Big beat 130,000 jobs.

53:13

Economists expected 65,000 jobs and a 4. 4% unemployment rate.

53:17

Uh Bloomberg has a live blog here uh breaking it all down.

53:23

There's some interesting things.

53:23

So traders pushed Fed rate cut expectations to July and revisions trimmed the US 2025 payroll gain to 181,000.

53:33

Um from Bloomberg, >> it's it's interesting.

53:35

I think everyone there were kind of delays with the report, right?

53:40

Everyone was expecting this to be absolutely abysmal. >> Yeah.

53:44

>> And now I think the reaction is >> can we trust can we trust the data, right?

53:49

There's just been so much kind of like >> FUD thrown around the data and and the job market in general that >> yeah, >> it's hard to believe your own eyes.

53:58

I was debating with a friend about uh he was he was sending me some economic data and he was saying like like AI is the only thing holding up the economy and I was like I don't know that that's the right phrase.

54:10

I almost prefer AI is holding up the stock market, but healthc care is holding up the economy because that's where we're seeing job gains and and that's where like the real economy like there's always this disconnect between what's happening in the markets.

54:27

That's very forward-looking.

54:27

You're valuing things based on, you know, 2050 cash flow and being like, "Yeah, I'll pay for that right now because this company's going to be around."

54:34

You're buying a Google bond that doesn't mature for a hundred years, right?

54:36

Um, and then there's like the on the ground like do people have jobs or not?

54:40

And the question of like do people have jobs or not is much more in the health care and services sector.

54:45

And so uh Bloomberg has been breaking down.

54:48

US payrolls rose in January by the most in a more than a year and the unemployment rate unexpectedly fell suggesting the labor market continued to stabilize at the start of 2026.

54:58

And now there's going to be some debate over you know how real is this? Will it be revised down?

55:03

But there are other economic statistics that we can look at.

55:06

We're having Harley from Shopify on the show and we'll ask him about the health of the consumer because he sees a lot of a lot of commerce data and if people are even just worried about losing their jobs.

55:15

Usually they're pulling back on spending, discretionary spending.

55:19

>> Revisions came out today as well uh showed job growth was almost 900,000 lower in the 12 months through March 2025 than initially reported.

55:27

So again, like we announce these big numbers >> and then we kind of move on and then revise them.

55:37

>> This is pretty big though.

55:37

You'd be surprised if this re if this if this flipped negative like maybe it goes back to 65 or half as much, but um it still seems like like there is job growth broadly.

55:50

This seems at least directionally correct.

55:51

Uh employers added 130,000 jobs last month and the unemployment rate declined to 4. 3% according to the BLS.

55:58

Uh the that followed revisions to the prior year which showed market slowdown in hiring.

56:04

Um jobs gains averaged 15,000 a month last year down from the initially reported 49,000 pace. >> Just a bit off.

56:12

[laughter] >> Uh the report suggests the labor market is finding its footing after a year marked by rising unemployment and minimal hiring.

56:20

While economists expected hiring to remain generally sluggish in 2026, more clarity around the impact of President Donald Trump's economic policies and lower borrowing costs could encourage some employers to boost headcount.

56:31

The January data reinforces Federal Reserve's officials inclination to keep interest rates on hold.

56:38

Now, yeah, I mean there there is this interesting tension, right, between even if the job numbers are inflated, that puts pressure on the Fed to not cut rates, which is another stated objective of the administration.

56:47

So you have these like two things like if you're if you're pushing for hey let's let's count every possible job that could potentially you know fit in this category that well then it's going to be harder to make the case that you should cut rates um in leaving rates unchanged last last month chair Jerome Powell cited signs of steadying in the job market.

57:07

So Jerome Powell saw this as well uh coming off a hiring recession in 2026.

57:12

This is welcome news, said Heather Long, chief economist at the Navy Federal Credit Union.

57:17

I think Fed Chair Powell was right.

57:19

The labor market appears to be stabilizing.

57:22

So Trump praised the numbers in a social media post Wednesday said that the US should have the lowest interest rates globally, adding to previous calls for for rate reductions.

57:31

Great job numbers, far greater than expected, he wrote in all caps.

57:35

With the release of each January employment report, BLS benchmarks payrolls to a more accurate but slightly less timely series called the quarterly census of employment wages.

57:45

That data is based on state unemployment insurance t tax records and covers most US jobs.

57:50

That adjustment showed job growth was nearly 900,000 lower in the 12 months through March than initially reported.

57:57

The figure roughly aligned with that of the BL.

58:00

Overall, I think I think uh you know the team that had to revise last year down by almost a million now coming out and saying like you know everything's great and we crushed it. Yeah.

58:12

>> It doesn't give you uh >> I don't have any comp like >> a smart person might might think like okay a year from now we're going to figure out that this none of this was real. >> Maybe. Yeah.

58:23

Uh I mean the market's not moving on it. The Dow Jones is down. 1%. The S&P 500's up. 1%.

58:29

The Nasdaq's completely flat.

58:32

I guess technically up 0. 01%.

58:37

>> Comments on Joe's post >> says, >> "And you take these numbers at face value."

58:44

Joe, I know you don't believe these numbers, lol.

58:48

>> Almost every single person responding just like >> um anyways. >> Oh well.

58:52

Um what what did Khi have to say? Jobs numbers. This is for February. This is for February.

58:57

Most people are expecting, you know, uh, more than 60k.

59:02

>> The current forecast is 68,000 and, uh, it and it jumped in the last, uh, couple days on this.

59:11

>> Well, you know what is real? >> What?

59:13

>> Bite dance, sea dance.

59:16

The model's very good >> according to Ethan Mllik.

59:17

Uh, I wish we could have asked uh uh Chris from Runway about Sea Dance yesterday. Yeah.

59:25

And how he's thinking about competition from Bite Dance.

59:28

Um, but we can next time. Let's play this video.

59:31

This is uh a nature documentary about an otter flying an airplane, which if you ask me is worth the two trillion of capex is photo real.

59:41

>> In the world of marvels, some creatures defy all expectations.

59:46

This is the incredible story of the pilot otter. >> That's cute. [laughter] I like that.

59:50

12 seconds, longer than most 8 seconds.

59:56

Um, and someone in the in the replies um shared a Grock version of this that it just has a little bit more I don't even know how to describe it.

1:00:06

It's a little bit more blurry maybe this video.

1:00:08

I don't know if you can see it up close, but it it it it's close, but it's not as real. This is >> Grock. Okay.

1:00:15

The audio is also much worse. I think I I watch this. >> Yeah.

1:00:19

Um, >> in the skies above Alaska, a river otter pilots its plane.

1:00:22

Its paws expertly handle the controls.

1:00:25

>> Yeah, you instantly clock the audio.

1:00:27

Yeah, you don't see on sea dance.

1:00:27

It sounds It sounds for sure real. Um, >> Otter Maxing.

1:00:32

Lucas is firing shots at actors. >> Okay.

1:00:36

>> Uh, but we can pull this up. >> Let's see. Let's get some audio.

1:00:42

>> You killed Jeffrey Epstein, you animal. >> He was a good man.

1:00:49

>> He knew too much about our Russia operations. He had to die. And now you die, too. >> All right. Insane. Insane audio.

1:00:54

But [laughter] but the uh the video the video look I mean I can't you you've watched a handful of movies more than me.

1:01:06

>> Does this look like it could be in a film? It's close. It's pretty close. >> What are you missing?

1:01:15

>> I mean, just the length of the shot.

1:01:15

It It's not It It's not fully like modern in the sense of the way the way Hollywood shoots an action scene like this.

1:01:26

It's either like way more cuts and uh just way more like detail shots like cutting in and out or they'll try and turn it into more of like a cinematic set piece and have like a drone shot or sweeping shot like it's very rare that you're just sort of sitting there watching that in most of like the most modern movies.

1:01:46

But it's but sitting there prompting and splicing it together from different angles.

1:01:52

>> For sure >> you could. >> For sure. What do you think?

1:01:54

>> For sure. What do you think? Yeah, I I think um I I do wonder if there's like an interesting comparison to the the kind of Cloudbot stuff where like I think one of my main takeaways from the Cloudbot thing was that um it's going to

1:02:04

be hard for for big labs to kind of replicate that just because of like you can't get the the WhatsApp integration like stuff like this where I think with the Chinese models, the image models, the video models, um they're very clearly like training on stuff they're not supposed to be training on. Like the

1:02:17

Like the the otter flying like that's David Atenboroough's voice, right?

1:02:20

Like you're not supposed to be able to to do that. Yeah. Yeah.

1:02:24

>> Where um like can Sora can open release Sora with with that exact voice? Like probably not.

1:02:29

Like maybe they can try to do it, but like they're clearly going to face some legal repercussions. Yeah.

1:02:36

>> Where like China can actually just kind of do it because they don't really have those. >> Yeah.

1:02:39

A lot of the American labs, it feels like they've been launching very aggressively and sort of making a fair use claim and probably engaging with lawyers from the big IP holders immediately and just sort of saying like look yes like we know you can prompt Disney characters.

1:02:57

We are happy to pull that out but also can you want to talk to our business development team?

1:03:01

Um, and >> yeah, like with Open Eye, you saw them actually do like a Disney deal where China is not like I'm pretty sure that you can go and see uh Sea Dance >> and just prompt like Mickey Mouse, you know, doing a little dance or whatever.

1:03:15

>> Yeah, let's look at this.

1:03:15

Let's look at this other Sea Dance 2. 0 uh post.

1:03:17

Will Smith fighting a spaghetti monster. Epic action film scene. Different cuts. >> There you go, John.

1:03:26

You wanted all you had to do is ask. >> This is pretty real.

1:03:32

I like that Will Smith is just the benchmark forever.

1:03:35

>> And I have the old Will Smith spaghetti AI ready to go after this. >> Okay. >> All right.

1:03:41

So, this is February 2026.

1:03:45

>> Yeah, this is >> Let's go back in time. >> That is a great shot.

1:03:47

That's something you need to do in Houdini. No longer. >> Yeah, this is good. This is very good.

1:03:55

>> All right, pull up this next one.

1:03:55

We got going back to 2023. We can see the progress.

1:04:01

>> China can oneshot AI crime. Wow.

1:04:08

>> This is the progression or was this >> I remember I remember people used to post this exact same thing and be like this is going to change everything and it did >> and they were right.

1:04:16

>> Yeah, they were right. >> But it's still funny.

1:04:18

>> And now it's just I'm sitting there enjoying spaghetti, I suppose. Yeah.

1:04:24

Wow, that looks cinematic.

1:04:30

This is good for Will Smith, right?

1:04:30

Like they he'll license his his likeness and it's just more more attention.

1:04:37

I mean, this is like Jake Paul's strategy.

1:04:39

He really wanted to be all over Sora.

1:04:41

Got a billion impressions or something like that.

1:04:45

>> Daniel in the chat says, "China can oneshot AI crime."

1:04:49

>> Who do you think launches the next turn of the video model?

1:04:52

Do you think we get V4, Sora 3, or the next meta model first?

1:05:04

>> And while you're thinking about, let me tell you about 11 Labs.

1:05:05

Build intelligent real-time conversational agents.

1:05:08

Reimagine human technology interaction with 11 Labs.

1:05:10

[applause] >> What do you think, Tyler? >> I'm hoping it's meta.

1:05:13

I really want to see their model.

1:05:15

It should I'm expecting it to be like super super good.

1:05:18

>> I think it'll be this this quality. It it has to be.

1:05:20

This is like the standard.

1:05:22

You can't launch something that's behind the frontier. >> Yeah.

1:05:24

Also, shortage of content.

1:05:26

>> No shortage of content for sure. >> Yeah.

1:05:28

I I'm I'm curious what they'll do with Sora if they'll actually like keep working on the app or or if they're just going to kind of try to just keep like making the model better and then Yeah, they put it in the app, but they're it's not a as big of a push this time. >> I don't know.

1:05:43

Well, >> um yeah, >> another news. >> Which one?

1:05:47

>> We got to talk about M. M's cooking.

1:05:51

They're cooking >> and they're investing 1.

1:05:51

4 billion to build out AI infrastructure in Sweden. >> Wow.

1:05:57

>> Let's head over to Bloomberg.

1:05:59

>> French AI startup Mistral is investing 1.

1:06:02

4 billion US dollars to build AI infrastructure in Sweden as it pushes to become the go-to AI supplier for governments and enterprises in Europe.

1:06:09

The data center will be located in a place that I can not pronounce, Borlange.

1:06:14

Borlange in partnership with uh Echo Data Center AB.

1:06:17

Mistral said in a statement, "The facility will will house the advanced computing power to train and run Mistral's AI models and is scheduled to be operational from 2027." So, at least a year out.

1:06:31

This is Mistral's first data center investment outside of France, and the company is built uh billing the buildout as a move to strengthen European tech sovereignty.

1:06:42

As political ties with Washington Frey, governments in the region are increasingly wary of relying on Amazon, Microsoft, and Alphabet, which dominate a infrastructure, data storage, and cloud computing.

1:06:52

Mral, which develops AI models and hopes to be Europe's answer to OpenAI, says it can offer customers a fully European AI stack with data processed and stored locally.

1:07:00

This [snorts] investment is a concrete step toward building independent capabilities in Europe dedicated to AI, says Arthur Mench. >> Mench.

1:07:10

Yeah, their last round was led by ASML. $1.

1:07:12

3 billion from the Dutch chip maker. That's a good deal. >> They're cooking. They're cooking.

1:07:18

This is the kind of thing that uh Mcronone should be highlighting. >> Yeah, for sure.

1:07:23

I mean, I guess it's old news.

1:07:25

They need to launch a new project and >> you can't just fully focus on >> and they're announcing in the Financial Times that their revenue is now uh similar to Grock. >> Mr.

1:07:36

Al's revenue soarses uh over 400 million. Interesting. That's pretty high.

1:07:41

400 million as Europe seeks AI independence.

1:07:44

Well, they've certainly carved out a nice niche.

1:07:45

Um, let's go over to the Gro team and GR and the XAI departures.

1:07:53

First, I'll tell you about Finn.

1:07:54

ai, the number one AI agent for customer service.

1:07:56

If you want AI to handle your customer support, go to Finn. ai.

1:08:01

Um, >> John in the chat says Jordy discusses dissing Mcronone caused domino effect. Mr.

1:08:07

[laughter] Rolling, >> you manifested it. >> I did it.

1:08:10

I inspired them to grind harder.

1:08:12

Uh, now of course I was one of many who was having a little bit of fun last Friday.

1:08:18

>> Uh, so Jimmy Ba said uh, bye-bye yesterday. He said last day at XAI.

1:08:25

>> Uh, and Tanish says with Jimmy Ba's departure, half of the XAI founding team has left. Mhm.

1:08:32

>> Uh I my a lot of people have been trying to figure out like why is this happening? >> Yes.

1:08:38

>> And my current uh belief is that uh and this is based on some news that last week >> XAI executives were given the option take cash. Yep.

1:08:51

>> As part of the SpaceX >> uh merger.

1:08:53

Take cash today and you can just move on. Yep.

1:08:55

or you can take equity in SpaceX and stay with us for the next leg.

1:09:00

And so I think a lot of the executives which are just the founding team, some of the co-founders are just saying like, "Hey, I'm gonna go work on something else."

1:09:07

And so we saw >> some other posts, some of these people are >> teaming up to work on something new together.

1:09:14

>> I'm sure some of them, you know, will just join other labs.

1:09:16

But um yeah, the big question is like what is is XAI's strategy going to change at all with the merger?

1:09:25

uh or is it going to be more of the same?

1:09:27

I keep kind of wondering, you know, will they get into uh you know, actually get into the Neocloud business? I could see it.

1:09:34

I could see it happening.

1:09:35

Uh but uh for now, I think this is maybe like people want it to be more dramatic than it actually is, >> I think. But >> yeah, it is. It isn't.

1:09:45

I mean, when when the when the SpaceX merger happened with XAI, a lot of people were like like you got preIPO shares in SpaceX, like you you should ride it out and then sell post uh post IPO because the stock will probably pop, etc.

1:10:00

probably pop, etc. And yeah, this feels like a quick exodus of people which is aggressive and it it feels um like sure you're behind the frontier on a few different vectors but you it is a place where you're sort of GPU rich very

1:10:18

intense environment though so if you want something that's a little bit more exploratory a little bit more researchoriented you know having the CEO say we're not doing research we're doing engineering that's not exactly a rallying cry if you're like But I want to do research. I don't want to do

1:10:31

I don't want to do engineering.

1:10:33

It's like, >> but I'm a researcher, sir. But I'm a researcher. >> You're an engineer.

1:10:37

>> You're an engineer now. And so, yeah.

1:10:39

Well, well, it'll be interesting to see where people land.

1:10:40

Tyler, what's your take on all the the departures from XAI? >> Yeah.

1:10:45

I mean, it it probably just seems like more evidence um that that X is going to be some sort of like GPU reseller or neocloud market.

1:10:51

like maybe um it's like okay Elon is extremely bullish on space data centers because it can just allow you to put like so much like you know terra terowatts of of compute in space.

1:11:05

>> Um >> it's like okay that if you're engineering versus research maybe um he's just like so scaling pill that you don't you don't actually need to do that much research.

1:11:13

You can just build up massive data center and then you just use the same paradigm of models.

1:11:16

You just train the biggest model.

1:11:19

>> It's 10x bigger than everyone else.

1:11:19

You just have the best model.

1:11:20

So you don't actually need like the insane like moonshot research projects.

1:11:24

>> Yeah, >> maybe there's something like that going on.

1:11:26

>> Yeah, >> I a lot of the researchers they said they're leaving.

1:11:28

[laughter] >> That's all folks.

1:11:34

>> They said they're leaving because they're so excited about um this kind of recursive self-improvement learning type cycle.

1:11:41

>> It's like a very moon moonshot research project.

1:11:44

>> That feels something you wouldn't want to leave. That seems fun. That seems interesting.

1:11:46

Yeah, but if XAI's whole path is now just we're going to scale up the data center so much that we don't actually need to work on these things. Okay.

1:11:53

Maybe it's something like directionally kind of in that lane. >> Yeah.

1:11:56

What was the uh what was the original Elon Musk prediction about XAI's progress around like solving something fundamental in physics or or one of those like one of those like major math challenges. >> Yeah.

1:12:09

I think he said that at the Grock 4 launch. >> Yeah. Was that Nalia Strokes?

1:12:14

>> Yeah, it was something like that.

1:12:14

It was it's going to develop some novel novel physics theory.

1:12:17

>> The most impressive product that I've seen from XAI is their voice mode integrated into Tesla.

1:12:22

It seems to be wildly entertaining to a lot of people.

1:12:28

And I've been seeing posts this week that have like 200,000 likes, meaning that it's incredibly mainstream on Instagram.

1:12:36

>> And testing out the product, it's it's like very quick, very low latency.

1:12:38

It it's as it feels like pretty much as close to talking to somebody like in a Google Hangout or Zoom as you can get. >> Yep.

1:12:48

>> Uh and so I think maybe maybe their voice mode is underrated. >> I think so.

1:12:52

I have a friend who has a Tesla with a long commute.

1:12:55

>> The question is is there value beyond comedy?

1:12:57

Not saying there needs to be right now, but if Grock can actually get good at doing things for you and you're driving in your Tesla and you can say, >> "Hey, book me a haircut, you know, for next week."

1:13:09

and you can like do that or hey, I need to get some groceries.

1:13:11

Can you order some groceries to the house?

1:13:14

And you're actually just getting that kind of like ambient assistant experience.

1:13:18

>> I think that uh they could get some traction there.

1:13:20

They do have an insane amount of cars on the road. That's a big user base.

1:13:25

>> Yeah, I have a friend who has a Tesla with long commute and he talks to Grock voice mode.

1:13:29

not the crazy mode, just the normal mode about, you know, putting together to-do lists, planning out the day, researching things, answering questions, getting up to speed while he's commuting.

1:13:39

I've done that a few times where I've just kind of sort of opened up not the voice mode specifically, but the record my voice and and transcribe it and I'll sort of talk about what's on the agenda for today and then try and put it into just a sort of, you know, annotated note format that I can work.

1:13:56

>> Uh, we uh breaking news from Elon. What's that?

1:13:59

>> He shared uh XAI was reorganized a few days ago to improve speed of execution as a company grows, especially as quickly as XAI.

1:14:06

The structure must evolve just like any living organism.

1:14:10

This unfortunately required parting ways with some people and we wish them well in future endeavors.

1:14:13

We are hiring aggressively.

1:14:15

Join XAI if the idea of mass drivers on the moon appeals to you.

1:14:20

[laughter] >> That's funny. I like that.

1:14:22

>> Yeah, but like mass drivers is like not an AI thing, right?

1:14:24

So it's very clear that like if if you want to work on these crazy like moonshot AI like this weird yeah machine learning concept like maybe it's it's not actually that aligned with with XAI anymore. >> Sure.

1:14:36

Well uh I mean yeah it's like what type of moonshot do you want to work on?

1:14:42

ASI that lives in a data center or the infrastructure that will power humanoids and the mass driver on the moon that's making endless satellites that you know build the Dyson sphere.

1:14:52

It's like it's a different direction, maybe even longer term moonshot, but it is a different. >> Yeah.

1:14:58

I mean, they still have like the macro hard project, right?

1:14:59

Which is like still I'm I'm very excited to see what comes out of that, but >> yeah. Yeah.

1:15:04

I mean, do they do they have a CLI tool yet for Grock?

1:15:09

>> I I want to say there's there is a Grock code. Okay. >> Um >> yeah.

1:15:12

Um >> uh anyways, XI posted a >> 45minute all hands >> uh outlining their accomplishments and a bunch of other stuff.

1:15:21

So today >> we will watch that right now in silence. >> Yes.

1:15:25

>> No, we're not going to watch it.

1:15:25

But >> no, we'll tell you about public. com.

1:15:28

Investing for those who take it seriously.

1:15:30

Stocks, options, bonds, crypto, treasuries, and more with great customer service. >> So >> um let's see.

1:15:36

A lot of people like a number of researchers have just been uh doom posting on the timeline.

1:15:41

Uh Hugh Fam says, "Today I finally feel the existential threat that AI is posing.

1:15:49

When AI becomes overly good and disrupts everything, what what will be left for humans to do?" >> Yeah.

1:15:54

>> And it's when, not if.

1:15:54

So this is somebody who's actively at open AI. >> Yeah.

1:16:00

>> And so it's significant, but it's also great marketing for >> Yeah.

1:16:08

I >> investing in Open AI.

1:16:08

I think people are are more skeptical when it comes from the CEOs who are actually out on the fundraising trail than from staff engineers who have less of an incentive. >> I don't know.

1:16:20

>> Yeah, but this post has been up for 19 hours and it has 384,000 views.

1:16:22

So, you can assure you can I would say OpenAI comms has seen this post and has not asked them to take it down. >> Yeah.

1:16:31

Well, they probably genuinely feel that way.

1:16:33

The question is just like how real is it and how how diffuse will this be and how fast will it be?

1:16:37

Is it February of 2020 or is it I don't know some other time 1995.

1:16:47

Uh there's someone on X who has figured out a massive viral hack to go viral with AI slop constantly.

1:16:55

I thought it was very funny because I I looked up the account and I already had them I already had them muted.

1:17:01

Um but the formula is as is as such trunk fan laid it out. Find a viral post.

1:17:07

AI generates a take of 400 to 800 words as a quote.

1:17:09

You do 10 plus quotes in quick in a row and hope a few hit.

1:17:16

Between 10:30 and 8 and 10 p. m.

1:17:19

yesterday, cranked out 13 of them, 10,000 words total, all AI slop every day. Unreal.

1:17:23

And the and so uh Trunk fact checked or spot checked them with Pangram and you'd see that it's fully AI generated.

1:17:30

But apparently he blocked Panggram Labs.

1:17:32

Uh, I was laughing because the there's this interesting divergence in the performance.

1:17:38

Some of the posts have tens of thousands of likes and some of them will just sit there with like one like, two likes, no likes.

1:17:48

Um, and so it's it's this odd case of 300,000 followers on LinkedIn, something like almost 200,000 followers on X.

1:17:58

like it's working, but there's no real audience because if you post something that's just that only gets one like, it feels like there's no like real audience there, real fans.

1:18:10

So, I'm wondering like how this monetizes. Is this a real business? Where is this going?

1:18:15

Um, but uh certainly frustrating some people at the trough.

1:18:22

>> Aman makes $2 billion bet on Meta.

1:18:22

Bill Aman's Persing Square revealed a major new stake in Meta, making up up 10% of its portfolio or about 2 billion.

1:18:30

The firm sees Meta as a top beneficiary of AI, boosting ads, content, and future products like wearables and digital assistance.

1:18:39

I saw somebody had wired up, I don't think we got to it in the show, but they wired up OpenClaw with their Meta headset. >> Okay. And >> which one?

1:18:47

>> Uh >> VR AR or the AR one, >> the display, >> but effectively saying like, "Hey, buy this product."

1:18:52

And it would it would go to Amazon and buy the product. >> Wow.

1:18:56

>> And that is that is the vision we've been talking about. That is the opportunity.

1:18:59

Zach wants you to be able to just be in the world shopping. >> Yep.

1:19:03

And for a lot of people that don't want to wire up an open source project, he will slowly do all the bisdev deals to, you know, drive traffic.

1:19:08

Although Meta has tried to get into commerce so many times, and we can talk to Harley about this as well.

1:19:15

Um there's been there's been a lot of back and forth about you know should you be able to just click and check out directly on meta properties.

1:19:23

It's never fully developed and you have to imagine that they have all the bisdev horsepower in the world to try and go and do that but um for some reason that has that has continued to live in the domain of brands in Amazon on Shopify sites etc.

1:19:37

Quickly Vanta automate compliance and security.

1:19:39

Vanta is the leading AI trust management platform and Scott Woo is sharing some news from Cognition.

1:19:48

Your PR should fix themselves with autofix.

1:19:50

Devon now closes the loop on its own PRs if Devon review or GitHub bot flags bugs.

1:19:55

Devon automatically fixes the PR.

1:19:58

Devon also tackles CI lint issues until all checks pass.

1:20:02

And so there's autofix and uh and Scott just says one step closer to the recursive uh ever improving AI coding system. >> Uh Jb on X says cool.

1:20:12

So now Meta is Enron uh being being a little dramatic.

1:20:21

Uh but Meta's plat Meta Platforms auditor >> Ernston Young raised a red flag over the financial engineering Meta used to keep 20 a 27 billion data center project off its balance sheet.

1:20:31

Meta moved the data center project into a new joint venture with Blue Oow Capital and said it isn't the primary beneficiary of this entity so it didn't have to put the ventures assets and liabilities on its own balance sheet.

1:20:42

>> Uh four Democratic senators asked the Financial Stability Oversight Council to investigate the risk that AI related debt posed to the financial system citing Meta Meta's joint venture with Blue as an example of a convoluted and opaque financing.

1:20:56

>> This is this is sort of old news.

1:20:56

We talked about the blue out deal and how it was structured as as its own entity. It's its own business.

1:21:02

It just has meta as a as a tenant. >> Yeah.

1:21:06

But >> I think I think for me >> I would probably need to see them doing like copy and pasting this like, you know, 10 more times to the point where I'd be like, >> you know, maybe Meta is not good for it, right?

1:21:18

But >> I mean, it still shows up in uh in the cash flow if they're paying for the data center.

1:21:24

They need to monetize it properly.

1:21:25

So, >> uh, Nas on a roll says, "Apparently, Walter Bloomberg has no vocal cords left because of all the uppercase shouting on X [laughter] constantly."

1:21:36

[sighs] >> Walter, >> I bet a lot of people out there think he's just works for Bloomberg. >> They probably do. >> Oh, yeah.

1:21:44

Walter Bloomberg, the founder of Bloomberg, Joe Weisenthal's boss. >> Definitely.

1:21:49

>> We got Harley [snorts] >> in the waiting room.

1:21:51

Let's bring him in >> to the TV.

1:21:53

Harley, how you doing, >> gentlemen?

1:21:58

Great to be here as always.

1:21:59

Love being here on earnings day.

1:22:01

>> Yeah, always good to have you. Great to have you back.

1:22:02

>> Uh yeah, give us the update on earnings and then I want to dig into, you know, what you can tell us about the economy broadly, 2025, the jobs numbers, everything about what's happening in the world, help us understand it. >> All right, let's go.

1:22:16

All right, let's start with the headlines.

1:22:17

Um, >> last time uh we were on together, I think it was Black Friday, Cyber Monday.

1:22:23

It was I think I came to you live from the middle of the national retail or maybe it was it was January actually national retail federation and I told you that uh you asked about how things are with Shopify I said wait for the earnings.

1:22:34

So >> uh so here are the earnings we we announced earlier this morning.

1:22:36

GMBB was up 29% to $370 billion which is >> incredible.

1:22:42

Revenue was up 30% to 11.

1:22:42

5 billion which is a decade of growth of over 20%.

1:22:48

>> The number that actually is I've been in Shopify for almost half my life.

1:22:50

Um, and this number is I know it hits hard, which is that we now power more than 14% of the entire US e-commerce market, which is uh which is >> you guys did the you did the 1% of the TAM meme and then you 14xed it.

1:23:07

>> That's exactly that's exactly right.

1:23:07

Um, and uh and actually, you know, one of the cool parts is that we also did it with I think with incredible discipline.

1:23:14

Uh cash flow for the year was about $2 billion for 20 uh 2025.

1:23:16

billion for 20 uh 2025. Beyond that, one of the things that I think uh I'm certainly most proud of is that we really spent kind of 2025 building the rails for AI shopping and we we did things like announce the universal

1:23:30

commerce protocol that we co-developed with Google which effectively means that every single brand will be able to sell on every major AI platform with our aentic storefronts and we have partnerships with chatbt, Google Gemini, AI mode and Microsoft co-pilot. Um, and

1:23:42

Um, and so I think if you if you kind of think about 2025 is the year that we kind of laid the rails for Aentic.

1:23:48

I think 2026 is the year that we scale what runs on them.

1:23:52

And um, and so that I think is is really incredible.

1:23:55

Back to what we were talking about at NRF, we're talking about some of the brands and and how the velocity of growth.

1:24:01

We can talk about consumer as well, but just in terms of the merchants entrepreneurs we see, I I'm beginning to think that 2026 is is really going to be kind of year one for this next generation of these billion dollar brands.

1:24:12

I think there's going to be more billion dollar brands created in the next 10 years than the last 100 years.

1:24:16

And um and in terms of, you know, if you're looking for kind of a proxy for how the consumer is doing, I mean, we we talked, you know, we talked during BFCM, of course, we did that um you know, I sort of became a a couple of hours exactly.

1:24:29

Um but look, GMV for the quarter was 124 billion.

1:24:34

I mentioned, you know, for the year was almost $400 billion.

1:24:36

And so if you if you think about that as a as a proxy for, you know, how consumers are doing, consumers are buying.

1:24:42

They're buying from brands they love.

1:24:44

They're being incredibly thoughtful about where they're spending their dollars.

1:24:48

But for the brands that they care about, they're voting with their wallets to support them.

1:24:54

>> Uh talk about agentic commerce.

1:24:54

Is there any activity that's happening yet?

1:24:57

Is the uh ads launch from ChachiPT going to be an important moment in driving that?

1:25:06

uh what are you looking forward to this quarter in terms of agentic?

1:25:10

>> So we do have some merchants live already uh merchants like Glossier, Spanx, Viori, Stanley, Steve Madden already live.

1:25:16

Actually if you just look from Jan 2025 to Jan 2026, we actually have seen um approximately um AI searches.

1:25:24

So if you look at your Shopify admin in terms of sources, it's up like 15x.

1:25:28

It's still very early, but it's certainly beginning to evolve.

1:25:30

And one of the things that we're trying to do for the merchants on Shopify is that if you're with us, you can sell everywhere commerce is happening, whether that's online or offline or certainly on on Agentic.

1:25:41

And I I think, you know, you guys have discussed this many times, but I think there's going to be a bunch of like there's going to be a bunch of diff different permutations of exactly how Agentic Commerce evolves.

1:25:51

What we're doing is we're preparing for whichever path wins.

1:25:55

Shopify is going to be well set up there.

1:25:57

Um, in terms of ads, I mean, that's not, you know, ads are not a new thing.

1:26:01

I think ads have always been part of the commerce experience in some form, sort of natural evolution.

1:26:04

I think consumers expect this.

1:26:07

I think the key though is going to be there has to be a clear distinction between kind of ads and organic content.

1:26:12

Um, and so far that's what we're seeing as well.

1:26:15

But generally and and you know I I think you know we're in the early stage of 2026 but it does certainly feel like there is a massive I know you were talking earlier about you know how a bunch of young people became kind of drop shippers based on certain influence.

1:26:32

>> In many ways it does feel like there are more people starting businesses but the velocity of those businesses is just insane right now.

1:26:38

And and like because like they can access global markets like right away.

1:26:42

They have incredible resources.

1:26:44

Yeah, it feels like a really really important time to be an entrepreneur right now and a very exciting time. >> Yeah.

1:26:50

What's the moat for DTOC entrepreneurs? Is it changing? Is it brand? Is it distribution? Marketing chops?

1:26:58

>> I mean, look, I I think let me I'll give you a quick example.

1:26:59

We launched Shopify Sidekick um about a year ago or so, which is our we we sort of call it your your co-founder.

1:27:05

It lives inside of Shopify.

1:27:07

It knows everything about your business and everything about commerce and Shopify.

1:27:11

We added to this thing called Shopify Pulse recently, which is this new feature that effectively it proactively helps merchants grow their business.

1:27:18

It works in the background.

1:27:18

It surfaces like these tailored recommendations for things you can do to grow your business and then if you agree to them, it actually goes and executes.

1:27:28

I heard this story last week of a of a jewelry merchant who was actually who got a recommendation from Pulse to rather than having four separate SKUs to actually bundle them into a stack and create a bundle.

1:27:39

And immediately that that particular merchant like immediately saw more sales happen.

1:27:45

>> If you are meeting these great merchants with great ambition and great products and adding this like personalized data analysis with great intelligence, I don't know it it's it's bespoke, it's intuitive, but it it really will allow

1:27:57

more of these direct to consumer brands to access I think more customers and this idea of you know like initially it was like online only for DTC then it was like let's try offline as well have online and offline working simultaneously. It feels like we've evolved well past

1:28:10

It feels like we've evolved well past that that and this is kind of what we're doing at Shoplet which is that regardless of where consumers are spending their time make it really easy for merchants and entrepreneurs to access those markets and simple something as simple as like the agentic storefronts where with a couple clicks you can push products to chat GBT and to Gemini that's only going to increase the velocity even further. uh SAS Apocalypse. How are you guys?

1:28:35

Uh I I'm just going to say the word uh that [laughter] that's been on everybody's mind the last like, you know, 10 days or so or 10 months if if for for kind of our corner of the internet.

1:28:48

I look at Shopify, it's a system of record, it's payments, it's a cons, you know, consumer buying network.

1:28:55

it's battle tested infrastructure that uh that needs to be you know have you know insane uptime like I don't see the I don't see the vibe coding risk at all but how are you guys answering that uh kind of question uh with analysts >> yeah it it's look I I we did our call this morning 8:30 and um we basically

1:29:17

have been with analysts and investors the entire day the question does come up I mean first of all let me just say this um people have been underestimating Shopify pretty pretty much since day one we've sort of made it a habit of proving them wrong which is which is kind of fun. I think a couple things. I think AI I think a couple things.

1:29:29

I think AI for on the agentic side, I think AI will change how people discover products and potentially even how they buy.

1:29:38

>> That's what we're building for.

1:29:38

We are building for these agentic storefront experiences and and making sure tools like Sidekick make it so that if you're on Shop, you're just better positioned. >> Mhm.

1:29:47

>> But, [clears throat] you know, the the truth is like AI is going to rewrite interfaces.

1:29:51

>> It's not it will not rewrite the transaction contract.

1:29:54

And and one of the things that we've been building on Shopify, you know, everyone talks about the online store, like your, you know, the the e-commerce component of Shopify.

1:30:03

The killer feature of Shopify for a very long time has actually been the back office, the retail operating system.

1:30:09

That's where you go to do inventory and and you do taxes and you do analytics and reporting.

1:30:14

You launch marketing campaigns and you create loyalty and you do payment authorizations and fraud prevention.

1:30:19

Ultimately, I think the companies that are going to continue to do really well, notwithstanding some of this vibe coding, the ones that will do well will be the ones that are system of records, the ones that are actually operating like operating systems and and you know that's that's Shopify. Yeah.

1:30:34

And some other companies. Yeah. >> Yeah.

1:30:36

>> Yeah. But just jumping in like I do think that there when when uh throughout my history, you know, being being a Shopify, you know, customer and and user over the years, I would be if I was operating like a tiny Shopify plugin that one engineer had built and they were charging $30 a month, I would be a little bit worried about vibe coding because I do remember in throughout history using a plugin where I was like,

1:31:02

"Okay, this is a nice little feature that I can bolt on and I'm happy to pay for this because it doesn't make sense for me to go hire an engineer to build some custom uh you know yeah whatever whatever that is so I think >> but again that is a that is a uh that's a tailwind for Shopify as a platform because you have the system of record and it's like hey now we can allow you to add these kind of like Lego blocks on top of it. So

1:31:24

So >> yeah I you know one of the things we're noticing actually one of the uh questions I got on the earnings call this morning was um the growth of the app ecosystem that there's now more people building apps for us.

1:31:33

So, one of the things we're seeing app developers, but also merchants themselves who historically would hire, you know, a third party to build a tool do it themselves.

1:31:43

And part of the reason that we're putting out all these new APIs and SDKs and and these new tools to build on top of is because we actually think having more people build on on top of Shopify, you know, benefits benefits merchants.

1:31:54

merchants. But back to that whole like if you were just a feature I mean you you know you guys uh if I had to word cloud you know your show the word rapper probably comes up as much as uh as as anything I think you actually have to create something of real value and if all you're really doing is wrapping

1:32:10

something you're going to struggle but companies and if you look at the apps on I mean you know take some of the larger apps on Shopify like the Clavios of the world you know who are who built this incredible in their own ways their own >> rails around email marketing that is very very difficult to disrupt. So I I

1:32:24

So I I think the idea of like we want to invite more people to build incredible tools on top of Shopify and also give merchant tools to build it themselves.

1:32:32

But I think that you know AI rewrite interfaces will never rewrite like real infrastructure.

1:32:38

Yeah, Clavio is a great example because you could have a somebody could could build something that can send an email, but then if your delivery is just terrible, it's just going to be you might like save a little bit a little bit using the fivecoded solution, but then you're like losing tens or hundreds of thousands of dollars because you're not actually getting through to your customers.

1:32:57

So there's there's uh any like e-commerce operator like getting you guys know this too like you've spent like you guys have had a better solution in the market for how many years and you're still you know how hard it is to convert a legacy brand to even trust a new platform because they're like our current system is not great but we know we know how critical this infrastructure is and and what a big step it is.

1:33:21

big step it is. So I >> it is interesting you know even on the enterprise side one of the things that I've noticed coming out of NRF which effectively is is like all the major the largest retailers are all there is that even the largest retailers who feel like they have something that's good enough they're getting pushed by their exec team or their board to think about like

1:33:37

unified commerce this idea that you know think about the metaphor of like a browser with 12 tabs open online offline agentic um cross-ell on social media platforms B2B even the most traditional of of retailers and businesses we are finding now are coming to Shopify for simplicity that they don't want to run this like you know this Rube Goldberg

1:33:58

machine in commerce they actually want to create this centralized back office that runs all of it that's been amazing for us in fact one of the biggest areas of growth for us has been the enterprise and companies that traditionally did not come to shop like General Motors for example or Estee Lauder for example are now migrating to us as well so I I think

1:34:15

you know it's an exciting time to be a new entrepreneur getting started because the resources and the tools are insane But even some of the largest retailers, the next few years are going to be incredible for them because they're going to access these tools and be able to operate at a pace that frankly some of them have never been able to operate at. >> Yeah. >> Yeah.

1:34:31

>> Do you have a hard stop at 12:30?

1:34:33

>> I can keep going for a bit. >> Okay.

1:34:34

>> Okay. Uh uh I want to talk about uh evolution of UI sort of uh tactical like uh when I had an e-commerce site that was not on Shopify regrettably uh launching a new product was like how are we going to literally Django go in the back end what's the database schema is

1:34:53

it a boolean right like all these different things right then you go to Shopify and it's very easy >> Yahoo stores or something like what was it >> no it was literally Django like like Python like it was like hosted on Heroku I Um, and so, uh, yeah, homegrown disaster. Uh, huge, huge waste of

1:35:07

Uh, huge, huge waste of resources.

1:35:09

Um, you go to Shopify, you get a an HTML page with a bunch of fields that you can fill in when you have a new product and it fills into the templates, right?

1:35:17

Is the future I talk to Shopify in natural language?

1:35:22

Is that actually better than defining my product variance in HTML UI?

1:35:28

Like do you think that like Shopify will have an agent that where I'm I'm I'm making changes within the Shopify ecosystem but in in natural language or is HTML dropdowns are there sort of like more lindy than we'd think?

1:35:46

>> So I think uh the good news you can do both right like the idea is can we make the important things really easy and everything else possible.

1:35:52

There are merchants right now that we have a product we just announced um in in December at our at our edition called SimJim. >> Mhm.

1:35:59

Simjim effectively simulates what any task might be.

1:36:02

So you can say if I change this particular design or I try this particular campaign, what does SimJim simulate will be the results of that and we're seeing a lot of our merchants begin to adopt it now and try it out.

1:36:15

I think the idea should be you can do both.

1:36:17

If ultimately what you do best is you are an artisan.

1:36:19

You make beautiful products.

1:36:21

you make some sort of like children's toys and they're amazing and and you actually do not know anything about digital commerce or digital marketing.

1:36:29

I think you can use Sidekick as really your your CMO and your your your co-founder that helps you become a lot more um you know internet native when it comes to commerce and retail.

1:36:41

>> In other cases, the idea that you know some of our our brands like Skiims for example uh or or Alo Yoga for example, I mean they want to do some really customizable stuff. They're very technical.

1:36:51

They have an amazing engineering team.

1:36:53

They want to go into the code and really make it so their particular store is exactly what they want.

1:36:59

That ability where you know at some point you had to either build your own stack if you wanted massive customization or if you didn't know how to use anything when it came to e-commerce, you had to go and hire, you know, some sort of like company to go build everything on your behalf. I think all that's gone.

1:37:14

I think the net result of that's going to be you're going to have way more people starting businesses and way more companies getting larger at a much faster clip and sidekick is a really good example of that and so is Simjam.

1:37:24

I think beyond that the other thing is like this idea that you start with one particular channel I think will will very quickly go away.

1:37:30

We're already starting to see that where immediately you know you may start with your online store as your online hub but very quickly you're going to activate an Instagram channel or a Tik Tok channel or you may decide hey I want to try this agentic thing.

1:37:41

I think this idea that I am an ex kind of merchant, I'm an online merchant, offline merchant.

1:37:46

I think that's going to be something that like it's going to be like talking about the color TV.

1:37:49

It makes no sense in the future.

1:37:52

Um, but all that coming together is is what we've been building in Shopify for two decades.

1:37:56

And the end result of it is that, you know, we're seeing way more entrepreneurship than ever before.

1:38:01

>> Yeah, makes a lot of sense.

1:38:01

But Jordy, anything else?

1:38:03

Uh, how are you talking to, Last question, how are you talking to, uh, friends, family outside of the tech bubble about AI on X?

1:38:10

You were busy with earnings, but on X there's a there's an essay with like 50 million views basically telling everyone to freak out.

1:38:20

[laughter] >> Uh, I'm curious how your >> I saw I saw the essay before I before I started my day.

1:38:25

I actually sent the essay to my wife um just because I wanted to substantiate that I'm not an insane person talking about this stuff every single day. Yeah.

1:38:33

>> Um I think that essay I think you guys said or someone said like that essay feels like it crossed the chasm. >> It did. Yeah.

1:38:39

>> Like it it like >> containment. >> Exactly.

1:38:42

It it went kind of well beyond just like our kind of little, you know, world circle of the internet.

1:38:50

>> I think ultimately uh the the idea of being reflexive with AI, you know, Toby wrote this letter a couple months ago, you guys probably remember it that got leaked.

1:39:00

Um, and it really, you know, the reason it got leaked was it talked about that if you want to hire someone at Shopify for your team, first you have to substantiate why AI can do it better.

1:39:09

But if you actually looked at like the the meta message in the in in email, right? >> Yeah.

1:39:16

>> Definitely cannot do it better. Exactly. That AI cannot that.

1:39:18

That AI cannot that. So if you can't do it better then you like you can hire but like if AI can do it better you're you know we're not we're not you know the headcount doesn't get allocated which >> what it really suggested was this idea of like AI reflex that >> rather than sort of use it as a tool how

1:39:36

do you kind of use it as part of your day-to-day life you know when I'm preparing for an earnings call with Jeff our our CFO we used to go around and meet a ton of different product leaders around the company to kind of glean uh and figure out and summarize like what are the most exciting things happening at Shopify. It was an like it was part

1:39:49

It was an like it was part of the process for I don't know like 10 quarters.

1:39:53

Now effectively we go to Shopify's vault.

1:39:55

We have like a dozen MCPs running.

1:39:57

We're able to pull way more information we can.

1:39:59

So when we do meet with those product leaders, the conversations are way richer.

1:40:03

They're not spending a bunch of time explaining to us on on a you know at a very abstract level or a you know at a macro level what they're working on.

1:40:10

We can ask specific questions.

1:40:12

I think companies that become more reflexive and individuals that become more reflexive, especially entrepreneurs, there's no doubt it's going to make you more, you know, it's going to make you more effective and more efficient.

1:40:22

But I think articles like this, it invites the non- tech community into what we're seeing in a way that I think is is important.

1:40:30

I think the reason it's getting so much traction is because it felt like it was um it felt like it was written for my wife as opposed to for me.

1:40:39

me. and not a but she needed someone who isn't really seriously >> but that's different >> then I think a lot of people are sharing it saying you should take this seriously it's really cool I think a lot of people have been processing this as like you should take this seriously and it's like

1:40:58

get your financial house in order like you know this is like a you're going to get steamrololled >> um >> yeah look I I I'm not like I like I don't believe in the doom of I'm an eternal optimist I think I think what it's done for Shopify, for our merchants, for our business has been incredible. I think what it's doing for

1:41:12

I think what it's doing for individual entrepreneurs is incredible.

1:41:16

My daughter, you know, we we recently moved to uh we moved to Montreal, which is a French city.

1:41:19

My my kids, we moved from an English city.

1:41:21

My kids are learning French right now.

1:41:23

There's homework that comes that I just cannot help them with.

1:41:26

I I would have had to hire a tutor.

1:41:28

I still may have to at some point, but the fact that I'm able to do so much more on my own, even in my own like dad role, makes my life better. Totally. So, yeah.

1:41:36

And what's so cool about that is for for for you, you can you you can go hire a tutor.

1:41:40

You could hire 10 tutors, but there's a lot of there's a lot of families that just never would have been able to do that.

1:41:47

The kids would have been struggling optimistic. That's what I'm saying.

1:41:48

I mean, sometimes like my my four-year-old will ask me just why why why, you know, the 10 ws of like why like why is the sky blue?

1:41:57

And I'll be like, I think I know why, but I I even if I even with the money, I can't hire a tutor to come buy the house at 9:00 p. m.

1:42:03

on a Tuesday in 2 seconds, but I can go and look it up and then relay a story and I can tell that story.

1:42:10

>> How can you not be optimistic when you have those tools available to you?

1:42:12

The key though is looking at them as these incredible tools, looking at them as a way for you to create like some sort of exoskeleton in for all of our lives.

1:42:19

And um and there's going to be some lagards.

1:42:24

I mean it's going to be like I think it's was Jeffrey Moore crossing the chasm like we will cross the chasm where in the mainstream we'll use it. >> Yeah.

1:42:30

>> My mom's using uh AI right now mostly for like things like recipes but that's sort of like a gateway drug I think for her using it for things like questions about I don't know banking or whatever my mom does daily.

1:42:40

So I I it's tough not to be optimistic and and certainly from a Shopify perspective it's been incredibly valuable for us.

1:42:46

Aentic shopping hasn't even started yet, but like we're prepared for it.

1:42:50

And I think um I don't know, this sounds like Yeah, even even for entrepreneurship.

1:42:55

>> I think we're still underelling the opportunity with AI. >> Yeah.

1:42:58

When when I look back in my early days of entrepreneurship, luckily I had people around that I could call and say, "Hey, how do you do this?"

1:43:04

Or what kind of contract do I need for this?

1:43:05

Uh how do I set this thing up?

1:43:07

How do I what should I use a safe note?

1:43:10

Should I use this or that?

1:43:11

And now it's, you know, hopefully entrepreneurs can build a network quickly, but you don't need a network to get like customized advice on pretty much any situation.

1:43:19

And yes, it could still be wrong sometimes, but it's usually directionally correct and helps you be more informed. And it's amazing.

1:43:28

Uh, >> it feels also like we as humans, we don't often want to ask someone else um the question that we deem as being like a silly question or a d a stupid question.

1:43:37

>> Um, >> that's one of my favorite parts of AI, right?

1:43:39

Just like ask a dumb question.

1:43:41

Yeah, >> totally totally agree.

1:43:42

I remember when we raised our first our series A, this is I don't know, literally almost 20 years ago.

1:43:47

I had to look up what a liquidation preference was and I call around >> and and I felt like, you know, I like we were raising a series A and it was a $25 million round let it and um and I remember thinking like I I I went to I was already a lawyer like I wasn't a very good lawyer, but I finished law school.

1:44:02

I didn't went to business school and I wasn't exactly sure what it meant.

1:44:06

I just sort of think back of now the like the amount of information I could have taken.

1:44:10

I could have got all these case studies.

1:44:11

I could have understood it in in a much deeper way.

1:44:12

That is where I think so it's not surprising that this >> you could have dropped the term sheet into any LLM and instantly gotten like pretty deep.

1:44:23

>> Tell me what's wrong with pull out all the main terms. Here's what's market.

1:44:27

Here's what you can push back on. >> Anyway, it's amazing. No more doom.

1:44:30

Thank you for not >> No more doom, guys. Come on.

1:44:31

Appreciate you taking the extra time.

1:44:32

This is going to be great.

1:44:34

We kept a great rest of your day. We'll talk to you soon. Goodbye, Harley.

1:44:38

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1:44:52

Nikita Beer has a prediction.

1:44:54

I want your take on Nikita Beer's prediction.

1:44:56

And he says, "In less than 90 days, all channels that we thought were safe from spam and automation will be so flooded that they will no longer be usable in any functional sense.

1:45:08

iMessage, phone calls, Gmail, and we will have no way to stop it." What do you think?

1:45:16

>> Yeah, I don't Yeah, I mean, he he must be seeing something.

1:45:18

I would assume he's seeing something at >> Acts.

1:45:21

He's been fighting this for a long time.

1:45:22

In the trenches, for sure. >> Fighting the bots. >> Yes.

1:45:25

Uh, I got a I got a a pretty good AI phone call yesterday that was somebody leaving me a voicemail that was just like, "Hey, just have a few questions. Give me a call back. >> That's that."

1:45:36

>> And I was Yeah, it was a good >> Yeah.

1:45:38

No, no, sometimes like the the text messages like >> But I listened to the voicemail. >> Yeah.

1:45:43

>> And I could clock it as AI, but when I just got the like kind of like summary of it, >> but if it's David Atenboroough, you're going to be like, "David, >> I would love to do a documentary about a flying beaver with you. Sign me up.

1:45:56

>> So, >> uh, hack that sort of solves this.

1:45:57

Uh, on X, you go into the settings and you turn off notifications from anyone that you're not mutuals with, that's not verified, that doesn't have a phone number.

1:46:07

You just make it really, you will miss some stuff, but you will see way less spam.

1:46:10

Uh, on iMessage and and and the iPhone, I I just don't accept calls from unknown numbers.

1:46:15

And so, like, you have to be in my contacts book.

1:46:19

>> And so, how do I actually meet people?

1:46:21

Well, I get mutually introduced. I add their contact.

1:46:24

We get into a group chat and it's just it's just a game of chain linking one chain to the next.

1:46:28

So if you >> for me there's already there's already a pretty there's a small number of people who are free to call me out of the blue whenever and I will pick up if I'm if I'm available and then there's another big group of people that I'd be happy to have a phone call with, but I'm not just going to pick up out of nowhere because you know uh whatever you talk about it before.

1:46:47

The typical spam functionality for a long time has been deny lists or blacklists where you have a list of spam accounts and you deny those. You block those numbers.

1:46:56

Uh I think everyone everything is shifting to allow lists or whitelists where you have a have an approved list of people that can get through to your messaging apps and basically uh cold cold messages, cold DMs are going to be a lot harder to break through.

1:47:11

So the era of the reply guy who gets retweeted and ratios and you know gets surfaced.

1:47:16

Maybe that's the maybe that's the alpha these days >> or you just have to grind harder.

1:47:19

I have a post that I want to read >> about turbuffer first.

1:47:22

Serverless vector and full text search build from first principles and object storage fast 10x cheaper and extremely scalable.

1:47:29

>> Shopify alumni I have a post I want your reaction. >> Okay. >> From delicious tacos. >> Yes.

1:47:35

>> I'm the CEO of a hot dog company.

1:47:35

I've worked on hot dogs for 10 years and I wasn't prepared for what I've just seen.

1:47:43

Your life is about to change. So, what can you do?

1:47:45

Buy as many hot dogs as you can.

1:47:48

Buy stock in hot dog companies.

1:47:51

>> Uh I I I think it's a little different, but it is [laughter] funny. It is very funny. >> I mean, who knows?

1:47:57

Hot dogs might change everything. >> Okay.

1:48:00

Well, you got you got uh you got quote tweeted here.

1:48:02

You said just in horses say we may be in a car bubble which is funny because that's a pro AAI take right?

1:48:09

>> Yeah I was confused by this and then AI not kill everyone is a memes responded kind of saying horse says the real risk is what happens to the economy when the car bubble pops.

1:48:19

So it's kind of it's it's uh this is a technoptimist account now.

1:48:25

>> Uh no I think it's a doomer account right?

1:48:28

>> No no I don't think so.

1:48:29

>> Wait really >> they say technoptimist in their bio. >> Okay. Huh.

1:48:32

I thought they were always like pause AIS, pause the progress.

1:48:33

Um, but maybe the maybe the bubble is a is a bigger issue as well.

1:48:39

Well, we can continue to dig into that.

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1:48:51

>> Uh, the We got the We got a Bugatti Turbion, >> the Luch >> uh post here.

1:48:58

>> Yes, >> the Bugatti's mogging.

1:48:59

So, the post says, "The Ferrari Luche makes the interior of the Bugatti Bugatti Turbion look like an absolute masterclass.

1:49:06

Bravo Ferrari, it's pure genius to be this bad."

1:49:11

>> People are still going back and forth on this.

1:49:13

The turbion, this is a this is a driving machine.

1:49:17

My take my take away from all the reactions this week in my personal view is I think the Johnny I Ferrari will be popular in specific bubbles on the West Coast and generally not be very loved. >> The only Yeah.

1:49:31

The only thing that that really jumps out to me about the about the design is the is the rounded rectangle display in the center.

1:49:37

It just is it does feel iPadish.

1:49:40

It feels like there's the tactile buttons, but the the just that block of like there's a screen.

1:49:49

>> There's also like a leather kind of lunchbox looking thing that you can pull out. >> Cool.

1:49:55

>> Which I think is weird. >> Odd.

1:49:57

>> I don't I don't love it.

1:49:59

>> Take it on the go, I suppose.

1:50:01

>> Rat limit on X says, "People who back into parking spots cannot be truly present.

1:50:06

You envisualized [laughter] your departure the moment you arrived."

1:50:11

In visualize isn't even a word for it, is it? Envisioned. >> This is hilarious. >> Still doing numbers. >> 50k likes. I love it.

1:50:16

You envisioned your departure.

1:50:20

The moment you arrive, [laughter] you're not truly present. >> Do you back in ever?

1:50:27

>> I back in every once in a while, but mostly I'm I'm angling for uh the the room for the doors.

1:50:32

So if there's a if there's a pillar in the parking garage that will block the passenger door and I have a passenger. >> It's strategic. It's not default. >> Exactly.

1:50:42

So I am extra I'm extra present. I'm extremely present.

1:50:44

I'm locked in trying to give my passenger the best possible vehicle exiting experience there could possibly be.

1:50:49

Let me tell you about Figma.

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1:51:00

Toma Bravo executives fielded queries and held conversations with investors to discuss the impact of AI on their software portfolios.

1:51:08

Vista Equities chief executives sent an email to clients and plans to follow up with a webinar.

1:51:13

Don't worry, I'm following up with a webinar to discuss the state of the firm's portfolio saying that we believe that AI will enhance software not replace it.

1:51:21

L uh leaders of several firms including KKR, Blackstone, and Aries reported that their exposure to the sector are limited and that the sell-off is overblown with some saying that AI will not significantly impact their wellestablished portfolio companies.

1:51:36

Uh it's hard to say that it won't impact it at all.

1:51:39

You kind of got to kind of got to pick a side in most cases.

1:51:43

But yeah, it's interesting.

1:51:44

You've got like, you know, PE like PE firms that only own software and they're like, "No big deal.

1:51:49

We're excited about this. were not worried at all.

1:51:54

>> Uh but they're having to do kind of like, you know, >> it's the what kind of American and are you meme?

1:51:58

It's what kind of software did you did you but then on the other side you have firms that have some exposure saying well we don't have very much exposure. >> Yes. Yes. Yes.

1:52:06

And so these are, you know, the messaging is >> and so this is what we were we were talking about this morning.

1:52:10

This uh you know I I think there will need to be a in many ways a reclassification of who the AI winners and who the AI losers are in the software world because there truly are platforms where yes, you could vibe code it, but the value in the asset is the liquidity on that platform.

1:52:25

like you can vibe code an Airbnb marketplace competitor, but if there's no houses on there and they're all AI generated, you can't actually go to the beach house, like you don't actually compete with Airbnb.

1:52:37

And so there's a lot of software companies that fit in that world where there's liquidity or some other network effect or some scale economy, but purely just having okay, we spent a bunch of money on R&D.

1:52:50

We have a bunch of lines of code written and it would cost you a billion dollars to write the same amount of code and compete with us.

1:52:57

So you're not going to do that because you're going to take a billion dollars to raise all the money and then you're just going to be competing with us.

1:53:04

Well, now that billion dollars is shrinking down.

1:53:06

Maybe it's $100 million, maybe it's $10 million, maybe it's less and less and less.

1:53:10

less. And so they there will be need in many ways it's just a return to form of like where are the true moes >> and and then and you know intellectual property obviously uh network effects scale economies there's a few >> regulatory regulatory so yeah there will

1:53:25

be some software companies some SAS companies where you find out that it it's like duolingo with like oh it's actually a game and people love the brand and so that's been much more resilient relative to a che that was basically just data that was scraped and put into chatbt and the stock's down 90%. Pythia cap responded to the uh

1:53:42

90%. Pythia cap responded to the uh comments from tomo bravo and vista equities saying breaking 6x levered long software investors who can't exit thinks software is okay actually >> u so >> let me tell you about console console builds AI agents that automates 70% of

1:53:58

IT HR and finance support giving employees instant resolution for access requests and password resets and let me also uh Pat Grady from Sequoia Capital has quote tweeted my article and he chimes in sort of agrees He says AI I the title of my article was AI is not COVID. And he says AI is not COVID in

1:54:15

And he says AI is not COVID in three key ways.

1:54:18

And I wish I put this in the article because it's pretty good analysis.

1:54:21

He says it's bigger, much bigger. And I agree with that.

1:54:23

COVID, you look at the numbers and it goes up.

1:54:26

It was crazy world changing.

1:54:26

But then now we've moved on and there's a whole different set of stories. Uh it's durable. COVID was a wave. It came and went. AI will compound.

1:54:34

And so you never go back to not using the internet.

1:54:36

You never go back to not using a mobile device.

1:54:39

You never go back to not having AI in the world.

1:54:41

You do go back to a world where you can walk around and not feel sick if you don't wear a mask. That happened.

1:54:47

Uh and then third, he says, "We have a choice."

1:54:48

This is important and the main reason to read the article with COVID. Everyone play defense.

1:54:52

With AI, we can choose to play offense.

1:54:54

Don't let AI wash over you. Put it to work.

1:54:58

And this is what Harley was saying as well. There's an opportunity.

1:54:59

And Pat Grady says, "The best time to make that choice is right now." And I agree.

1:55:03

It's an optimistic message.

1:55:05

Uh, Alex Sue, >> yes, >> says, "At this point, I can't tell if Harvey is in the business of selling technology to lawyers or equity to VCs."

1:55:16

>> He, of course, is in >> What business is he in?

1:55:20

>> He's in works for a company called Attitude, who specialize in providing high and flexible legal talent to corporate legal departments.

1:55:25

So, he's in a a legal a lawyer staffing firm. >> Oh, okay.

1:55:31

>> Uh, so uh hard to take this post. Uh, two. >> Guess what? News flash.

1:55:37

If you're the CEO of a startup, you're in both businesses, buddy. Always. No matter what. You got to raise.

1:55:43

You got to outraise your competitors.

1:55:45

If you're in a competitive space, if you're in a high growth industry, you have to be selling equity to VCs.

1:55:49

And you also got to be selling your product to customers. Get used to it.

1:55:54

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1:56:05

>> Jer ticket says knew a dude who emailed the IT guy directly instead of submitting a ticket and they blew his head. Smooth off.

1:56:15

I can't believe how mainstream this this is.

1:56:18

5 million views, 167,000 likes.

1:56:22

Andrea console says, "Should I use console?"

1:56:24

It does does solve that exact issue.

1:56:28

Uh, Sofh over on X says, "Going to name my son Garrett, short short for cigarette."

1:56:38

[laughter] I never put that together.

1:56:41

>> I I used to have >> Garrett would be a beautiful name.

1:56:43

>> I used to have this joke with Christian Garrett from 137 Ventures because uh the his first initial is C.

1:56:48

So if it's C Garrett, it's Cigarette.

1:56:54

It's like he has the name.

1:56:54

Anyway, Black Rockck's getting into DeFi.

1:56:57

Totally unimaginable five years ago, but they're doing it. Uh, we should talk.

1:57:04

>> This will be interesting.

1:57:04

Um, yes, they're Yes, they're buying unis swap tokens.

1:57:08

So, Fortune has a story here.

1:57:10

Uh, in the latest sign of the rapid convergence of Wall Street and crypto, the world's biggest asset manager is moving into decentralized finance or DeFi, Black Rockck on Wednesday revealed it will be bringing its treasurybacked digital token called Build with Misspelled.

1:57:25

that's very online for Black Rockck um onto Uniswap, a leading D5 platform where it will be bought and sold by institutional traders.

1:57:32

As part of the tie-up, Black Rockck is also purchasing an undisclosed amount of unis swap's own token, Uni.

1:57:37

Uh the new arrangement, which is being undertaken with tokenization firm securitize, is a significant milestone for the DeFi sector, which many view is one of the most useful applications in crypto.

1:57:50

Unlike traditional trading which relies on centralized intermediaries to record and settle trades, platforms like unis swap rely on smart rely on smart contracts to match buyers and sellers via liquidity pools and automated market makers.

1:58:02

Uh currently there are around hundred billion dollars worth of capital sitting on DeFi platforms. I remember DeFi summer.

1:58:07

Were you deep in the trenches during DeFi summer?

1:58:09

It was uh it was a big what was that 2022 right? 2021. It was before the crash.

1:58:18

>> It was the era of like Thor Chain and like and like >> 2020 2020 or 2021. >> Yeah, something.

1:58:25

>> But I think but 2021 was the Salana summer.

1:58:28

>> Yeah, DeFi summer was was >> must have been >> major FOMO basically for anyone who didn't participate and major heartache for many people that did.

1:58:35

It was it was a wild time.

1:58:37

Uh a lot of people having fun.

1:58:39

uh and interesting from a you know it it had it had some of the same feelings as the as the open claw thing.

1:58:50

It was like you you had to set up you had to know the terminal a little bit.

1:58:53

You had to be comfortable sort of you know installing these tools understanding oh don't send your money to the wrong address.

1:58:57

The address itself looks like a hash and so it's like a little bit like lightly technical.

1:59:02

You didn't have to write any software, but you had to be able to use different wallets that were very >> I it does feel like there was a little bit of nerd sniping.

1:59:10

There was also a lot of real businesses built and you know obviously there's still a hundred billion dollars sitting in DeFi and DeFi survived the DeFi winter that followed DeFi summer of course sort of bad nominative determinism.

1:59:22

The DeFi summer sort of implied that a winter was around the corner and it was but Black Rockck's now going into DeFi.

1:59:29

Uh so they're listing their build token which launched in 2024 and boasts a total market value of around $1.

1:59:35

8 billion and it reflects a major vote of confidence confidence in DeFi from one of the finance industry's most inf influential firms.

1:59:41

The practical impact of unifi of unis swap adding build to its platform is likely to be minor at first though since the arrangement involves securitize creating a white list of ed eligible institutions that can participate in the defy trading.

1:59:56

The firm is also whitelisting a handful of market makers, including longtime crypto liquidity provider Wintermute, uh, to facilitate trading.

2:00:04

Meanwhile, access to build is restricted to qualified purchasers, a legal designation for those with assets of more than 5 million or more.

2:00:10

So, they're getting into DeFi, but they're just dipping their toes in the water.

2:00:14

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2:00:27

So, uh there are lots of essays that everyone it's like essay week in AI.

2:00:34

People are writing essays about is AI like COVID is you need to talk to your family.

2:00:39

Uh Zoe resigned from OpenAI on Monday.

2:00:43

The same day they started testing ads and chatbt. She quit in protest. >> She did. >> Yes.

2:00:48

>> And she dropped an guest essay.

2:00:48

guest essay in the New York Times.

2:00:52

>> In the New York Times.

2:00:53

>> That is a crazy thing to do. >> Open.

2:00:54

I feel like a company hasn't fully arrived until an employee quits and they have the opportunity just to go immediately write uh like an opinion essay on said business.

2:01:05

>> Pretty soon you're going to quit and drop a whole Mr. Beast video. That's the future.

2:01:09

You drop you drop a drop a 10part hourong miniseries.

2:01:12

Just just raise the stakes.

2:01:15

go with the the the the biggest the biggest splash you can possibly make.

2:01:21

>> So, first makes the bull case for uh KGBT as a business.

2:01:24

OpenAI is the most detailed record of private human thought ever assembled.

2:01:29

Can we trust them to resist the title forces pushing them to abuse it again?

2:01:34

Uh so far the ads will effectively be display ads. Yeah.

2:01:38

not not uh integrated into the content and not uh yeah not not uh influencing the content.

2:01:48

And uh but again she's arguing that you know you can sort of start by doing that and then there there there's an incentive there's a business incentive to um you know up the ante a little bit.

2:02:01

Hopes revenge says I don't mean to be rude but I feel like this article says very little.

2:02:06

I think everyone will agree data privacy is good.

2:02:09

two tech companies have a bad track record of resisting their incentives to misuse this data.

2:02:12

You kind of vaguely gesture towards certain kinds of oversight, mostly niche and European, but I think we both suspect that pro that's probably not going to happen in this case.

2:02:22

That's really there really isn't a model here.

2:02:23

I'm a lot more interested in why you joined OpenAI and stayed for 2 years and what you would slash wouldn't do in the AI space.

2:02:29

I do think you're right to draw attention to what is special about the intersection of AI and advertising, which is that the data set being created and the product itself has a much higher potential for abuse and other familiar tech models of admonetized platforms.

2:02:41

This feels like fairly obvious point that I don't see enough of.

2:02:45

You're also right to draw attention to the fact that people don't necessarily have a problem with the fact that Chad GBT is doing ads now like this, but that they likely don't think it will actually stop their slippery slope. Thanks.

2:02:56

There's a very funny uh paragraph in uh Ben Thompson's certy piece on Google earnings that is basically the flip side of this that I thought was very funny.

2:03:08

Uh now uh he says this is probably the least important of the three benefits of LLMs for Google search business.

2:03:14

He's he's covering Google earnings and what uh what ads are doing for Google.

2:03:20

Everything's going very well.

2:03:20

Uh and he says, "What's notable about that ranking, however, is that this is basically OpenAI's entire proposed advertising business.

2:03:29

Google has the luxury of not putting ads in Gemini.

2:03:31

But that doesn't mean they aren't experimenting with ads in conversational AI.

2:03:37

They're just doing it in AI mode."

2:03:41

And their initial offering sounds a lot like what OpenAI is going to do in chatbt.

2:03:45

Put ads put in ads based on the content of the current conversation. Meh.

2:03:50

It's the meh that is scaring.

2:03:53

Google's upside re revenue potential from LLMs is so large that its side project, which is OpenAI's entire proposed business, hardly merits a mention in terms of justifying capex.

2:04:02

So Google's saying, "Hey, we're going to spend so much money on capex, but analysts, shareholders, don't worry because we have really great applications."

2:04:12

And the great applications that like they put ads in LLM responses really, really low.

2:04:17

And so Ben Thompson's like it's this like s this thing is happening and everyone's very focused in this chat GPT ads thing but Google's doing it and it's like meh like not a even big deal for them.

2:04:28

like not a even big deal for them. And they're like, "Of course, yeah, we just stuffed some ads in the thing because we're doing AI search and we'll keep them out of Gemini, but we're, you know, display and and search ads and YouTube ads are going to be way better and we're

2:04:37

making so much money over here that this this thing that's like causing so much drama and people are doing Super Bowl ads about like yeah, we just did it and it's minor to the financials and you know, if you're an analyst or shareholder like don't even stress about it and also no one's paying attention." So, it was just very funny that uh says

2:04:50

So, it was just very funny that uh says there there are plenty of justifications elsewhere while everyone else is going to have to keep have to spend to keep up without nearly the obvious high margin benefit.

2:05:00

So, Google has a bunch of different places to put ads and so much surface area, so many users um and uh and so little push back.

2:05:07

You know, I I don't think anyone at Google is going to be quitting over ads in AI mode um because they it's an advertising company and everyone's used to it.

2:05:15

We have our next guest in the reream waiting room.

2:05:18

Let me tell you about CrowdStrike first. Your business is AI.

2:05:20

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2:05:25

And without further ado, we have Matt Schumer in the recent waiting room.

2:05:29

Welcome to the show, Matt.

2:05:31

>> The Schuminator, >> the man of the hour. Welcome to the show.

2:05:33

Thank you so much for taking the time.

2:05:34

>> The most viral essay ever, maybe.

2:05:34

Has there ever been a more viral?

2:05:38

>> Would you have won the million dollars if you posted this a week ago? >> I think so.

2:05:42

>> I don't know, but I do wish I posted this a week ago.

2:05:43

[laughter] >> Well, fantastic response.

2:05:45

What has the response been like to the essay from non- tech people?

2:05:51

I imagine that you have friends, family friends that have been texting you screenshots or something like walk me through the experience of this. >> It's been crazy.

2:06:00

Uh I I wrote this with that in mind, but still I didn't expect it to actually happen.

2:06:06

You know what I mean, right?

2:06:08

I I originally wrote this for my parents.

2:06:10

I was trying to explain to them what was going on while I was actually home for Super Bowl Sunday with them, some family, friends.

2:06:14

And frankly, I couldn't find anything that was both clear and accurate, but also understandable for them. >> Right?

2:06:23

I was looking at Dario Mod's essays, and when you read them, they're [clears throat] perfect. They're amazing.

2:06:29

But you have to be in tech to understand them.

2:06:32

And I just wanted to find a way to communicate this in a way that allowed them to actually understand it without having to know all the jargon, the industry dynamics, everything.

2:06:40

because I think it's important for people to know this, but there's just not much out there for the person that's not in tech.

2:06:45

Um, so yeah, it did take off.

2:06:47

It's been surprising and exciting.

2:06:49

Um, frankly, I've been getting texts from friends who I haven't heard from in years, and they're like, "My boss is sending this around the office. It's it's it's surreal.

2:06:57

I thought it would go a little viral.

2:07:01

I didn't think it would go mega viral, and certainly not this level."

2:07:05

Um, so I'm kind of taking it all in.

2:07:07

I've slept like two whole hours since I posted this.

2:07:10

I'm exhausted, but it's been it's been crazy and I'm glad that the message was received.

2:07:14

I think that's the most important part, right?

2:07:16

People did not happen the way I'm expecting, but it's good that people know that there's a chance >> and the message is just something big is happening.

2:07:23

You just want people to pay attention because I think people are going to debate like how how you presented different things.

2:07:28

Is the COVID comparison really that accurate?

2:07:30

But, uh, is that is that specifically you're just trying to wake people up? Exactly right.

2:07:37

I if I knew how viral this was going to go, I think I would have spent more time thinking through some of the parts and how I presented them.

2:07:44

them. But >> is part of is part of why you why you you're maybe sort of worried or you want people to pay attention is is your experience as as an entrepreneur here because it feels like in many ways hyp hyperight like you know uh probably made more sense as a product two years ago and as all the different LLM have gotten

2:08:06

better and the products have gotten better I imagine uh it has been great uh and sounds like maybe you're you're moving on to focus on investing But uh is part of this is it's been kind of very personal experience of just kind of waking up to the to the power of the the base models and and and the labs in general. >> It has and I I'll share more on the

2:08:24

>> It has and I I'll share more on the company side soon.

2:08:26

Um but I've been in this industry since 2019.

2:08:29

I got in when I was in college working on a VR startup and I realized that like if I didn't drop everything to jump into AI, I'd regret it for the rest of my life. And I'm glad I did.

2:08:38

Um but seeing the progression is is kind of freaky.

2:08:41

I mean, you know, it couldn't write a sentence accurately in 2019, much less a line of code.

2:08:49

>> Now, we're looking at models that can build autonomously for many hours.

2:08:51

I had early access to GPD 5. 3 codecs.

2:08:53

And that was a very eye openening experience getting used to that.

2:09:00

At first, I was prompting and using it like I use any other model, little things at a time, iterating back and forth until I realized, wait, this isn't screwing up.

2:09:08

I started pushing it forward and pushing it further and just saying, "Hey, here's the big spec I want.

2:09:12

Don't come back to me until it's perfect and get it deployed on a server and it it did." >> Yeah.

2:09:19

>> Um, and I'm not saying every industry is going to go just like that.

2:09:21

I don't think it's going to look like that in every industry.

2:09:23

But if that's a sign of things to come, I think people should be paying attention. >> Yeah. Yeah.

2:09:29

I mean the the VR example is so interesting because like completely agree with you on just the power of the models like that it's it's so real.

2:09:37

It's it's so legitimate and it does and truly a lot of people are like oh it still hallucinates or six fingers in the images.

2:09:46

It's like that that that is antiquated like you need to get up to speed.

2:09:49

But at the same time like if if I was you know we see Mark Zuckerberg like cutting back on on virtual reality spending and plans there like and it doesn't and it feels like if AI is like going to advance everything you'd be like great like I I can invest 10 times less in reality labs and the headsets are going to get 10 times better.

2:10:08

But there's a lot of these things in like the they're not even it's not even physical world.

2:10:13

I'm not even talking about doctors.

2:10:14

I'm talking about VR headsets.

2:10:16

But even that doesn't feel like maybe like AI doesn't really pull that forward.

2:10:21

And I'm just wondering like when I go to my friends and family, how many of them will actually be like, yes, this is going to change my life in whatever I do versus like, yeah, software will get better, but software is a small piece of what I do.

2:10:36

But how how are you thinking about about people that where software is like a more minor piece of their world?

2:10:45

Yeah, this is something that again, hindsight is 2020.

2:10:46

I wish I had spent more time on knowing what was to come.

2:10:51

>> I try to address it a little bit in the article and I'll hopefully provide more color here.

2:10:53

Um >> my dad's a lawyer as an example. >> Yeah.

2:10:57

>> Like it's not going to stand in court uh anytime soon. Yeah. >> Right.

2:11:01

>> It can help with writing.

2:11:01

It can help with reviewing things that he's he's working on.

2:11:05

It's essentially an associate and it's getting better every year. >> Yeah.

2:11:09

>> But it's not going to stand in court.

2:11:09

>> But it's not going to stand in court. I think the ideal thing here is people read this and they kind of take it in their own unique way for their own unique needs um for what they're doing right if you're somebody who's very very exposed and I think there are a lot of people who are who kind of are denying it >> I think it's worth paying attention and

2:11:25

saying okay what is the world going to look like in two three years how do I prepare myself because it's it's worth it just in case there are industries where I think it will take longer though even in those industries for example let's say legal those that are just getting started today might have a bit of a rough time whereas a partner might do quite well actually. >> So, I think it's very contextual for

2:11:43

>> So, I think it's very contextual for each person and that's what I wish I kind of got across a bit better.

2:11:47

Um, >> maybe I'll do a follow or something like that.

2:11:50

But >> yeah, >> yeah, I I I I think it's really tricky to give sort of like a silver bullet one-sizefits-all answer for everybody. Totally.

2:11:57

>> The goal is to just say, hey, look, this is happening.

2:11:59

Can you try to think of it about it a little bit for your industry?

2:12:02

Because even if it's going to change an industry and there's like like the ability for it to happen, it's not going to happen overnight even if technology is there.

2:12:09

Though I do think for a lot of these industries the technology will be there relatively soon.

2:12:12

It's just a matter of how long it takes to proliferate proliferate through society. >> Yeah. Yeah.

2:12:18

>> Lawyers don't tend to post as much as software engineers. >> Uh true.

2:12:22

But you can imagine >> lawyers out there thinking I don't even write contracts anymore. I just review.

2:12:30

Which is like kind of what you're seeing. >> Yeah.

2:12:31

most engineers saying, >> but at the same time, so so part of the I I will I'll be interested to see what happens with like the general legal job market, >> but we've just been hearing examples from companies being like, I need to hire hundreds of interns that are just going to come and work >> in a new way and and use the tools sort of natively.

2:12:50

And you can imagine that happening, but but again, there's just >> I don't know. >> Yeah.

2:12:55

what what advice uh or what what recommendation would you make to a new grad right now?

2:13:04

>> It's really tough and it's one of those areas in the article that I don't think I had a clear answer on but that's because there is no clear answer.

2:13:09

I have a lot of people in my life that have asked me this and part of my thinking on this article was like >> can I answer some of these questions and there are parts of this that got clear parts that didn't.

2:13:20

This is one of the parts I don't think I have full clarity on.

2:13:23

I think knowing the tools is better than not knowing the tools. >> Yeah.

2:13:28

>> Focusing on industries that maybe will take a little bit longer to be disrupted so you can entrench yourself a bit first is valuable and there are people better than I at knowing which ones those might be.

2:13:39

>> Um but really I think it's just getting used to using this because this is the new world.

2:13:42

It's like you know if a calculator is is available you should probably be learning how to use it.

2:13:46

This is this is that times a thousand. >> Yeah.

2:13:49

>> Um so I think it's just learning to be adaptable.

2:13:51

I think there probably is.

2:13:54

We'll look back in 10 years and there will be clearly like this is what you should have done. Totally.

2:13:57

I don't think anybody knows today. >> Yeah.

2:14:00

>> But it's also been very contextual.

2:14:00

It's going to depend on what your goals are as a person. >> Yeah.

2:14:04

I mean obviously like there's those posts about like it's the last moment to join a lab before the takeoff and like it'll be fun to join and and that makes a ton of sense.

2:14:12

At the same time, I I love the idea of being a young person becoming a a hacker, like lightly technical, but really fluid in the tools, and then going and working at like an oil and gas company and just being like the most cracked, most productive person at this company that has like assets, and you're going to be able to just do so much more across the organization and and be that like, you know, thousandx intern basically.

2:14:34

Uh Jordy, where do you want to go?

2:14:38

>> A lot of uh comments from people asking if AI wrote the essay. Oh, yeah.

2:14:41

What's your what's your writing process actually like these days?

2:14:47

>> It didn't stick out to me as AI, but >> you definitely I didn't you probably if you did use AI, you pulled out a lot of the M dashes. >> Yeah.

2:14:53

>> So, [laughter] >> it did help a lot and I think that's kind of point a lot of people are like dunking on me for saying that and I posted that I I used AI. >> Yeah.

2:15:01

It's not really a gotcha if if if it >> did insane numbers like whatever whatever whatever the like if you're upfront about it, it's fine. Yeah.

2:15:11

>> It's like proving the point.

2:15:11

It's like people are saying this thing sucks at X Y and Z, but like look, it's 50 million views.

2:15:16

Like there's a reason that I'm talking about this stuff.

2:15:20

>> Um, and you know, I think there's like little details I get wrong here because this has been a crazy couple of days.

2:15:25

But >> the way that I approached it was again, I wanted to write sort of like a Daario style essay, but for the average person.

2:15:34

So what I started doing is I have like lists of like all the things that have like sort of made me think over the years that I agree with and I've sort of points on what I agree with in each of those articles, what I disagree with, what I think has well and what hasn't.

2:15:44

And I've kind of dumped this all in and I used Claude for this.

2:15:46

Even though I think Codeex is way better for engineering, Claude is better for um this sort of stuff.

2:15:51

>> I dumped all those articles in and I said, "Okay, here's what I agree with. Here's what I don't."

2:15:54

Um, and then I basically spoke to it for like an hour with my own thoughts and my own feelings and how I wanted to present it and what I think actually makes sense because a lot of these things past kind of are somewhat accurate, somewhat not.

2:16:04

And I iterated with the AI for for many many hours going back and forth until I finally felt like, okay, it's time to write.

2:16:11

And I kind of had to put out a whole sheet on how to do this.

2:16:14

>> And then I actually went and I uh took that and wrote the first draft myself.

2:16:18

And then there were obviously parts I struggled with.

2:16:19

I had the AI come and help.

2:16:22

>> Um, I hel I had it kind of like work on the wording with me.

2:16:23

And then once I had a first draft, I brought it back and I had it critiqued it.

2:16:26

Um, and that's kind of there's there's obviously more details than >> I mean I I I think when people lob the like this is AI, they think that you that your prompt was like write a essay that will get 50 million views and and it just like oneshots it.

2:16:42

It's like no, this is a collaborative back and forth. Yeah, of course. Um Yeah. Yeah. >> We tried that on X. >> Yeah.

2:16:49

[laughter] >> There's a lot of hashtags. >> Yeah. Yeah. Oh yeah.

2:16:51

It can be can be a little rough. >> Um yeah. Yeah. Fascinating. Um Jordy, anything else? >> Uh no.

2:16:59

What are you What are you What are you going to do next? >> Yeah. Yeah.

2:17:01

I mean, I I've noticed from your portfolio that there's a lot of uh chip companies, hard tech investments, like what are you most excited about just in the economy broadly?

2:17:12

>> I mean, in terms of what I'm investing in, and I intentionally tried to leave this out of the article because I wanted the article to be just purely my message, not sort of like kind of like have to deal with the sort of interplay of that.

2:17:21

But in terms of what I actually believe in, I think the chip companies are very interesting.

2:17:25

Um, I was, you know, I don't know if you saw a couple years ago, I kind of helped Grock blow up and that that's worked out quite well.

2:17:32

Um, I'm in Etched a few others like that.

2:17:35

I also think the rails are going to be very important.

2:17:38

Um, I tend to invest in, you know, I just started my fund around this thesis that there are going to be sort of these things that AI needs to proliferate, right?

2:17:43

not just the the model itself and the weights itself, but it's the >> uh you know the rails for them to communicate with each other.

2:17:50

And I just invested in a new company uh agent relay that's about to come out that I think is going to be really exciting there.

2:17:55

Um I also did the agent mail so very very similar.

2:17:59

Uh Daytona >> um >> SF Computes a little different, but I think they're going to be Evan is a killer.

2:18:05

Um, I'm sort of interested in that sort of stuff.

2:18:07

Like how do you take the models and then bring them out of their boxes because this is obviously happening and you just kind of want to put your money where where uh it's going to grow. Uh, obviously. >> Yeah.

2:18:17

It feels like there's whenever something crazy happens, there's a lot of like h it's almost like nerve-wracking panic, but I I do think we're in this moment right now where there's going to be a re-evaluation of how value acres in tech because tech has [clears throat] become everything.

2:18:31

Like, you know, car companies are tech companies now.

2:18:33

Everything's a tech company.

2:18:35

Uh and but the business models are wildly different and you know you know the the software agents are going to accelerate some companies.

2:18:42

They're going to damage some companies and uh we're we're going to be following it all right here.

2:18:47

But we appreciate you taking the time to come chat with us. >> Yeah. Get some sleep.

2:18:51

>> Congratulations on the massive article.

2:18:53

I mean it it it I definitely agree with the point of like we we're not talking about the the latest updates to AI uh broadly enough.

2:19:04

>> I do think [snorts] it's interesting some people will read this let's say they're a firefighter or a school teacher. >> Yeah.

2:19:10

>> And be like wait I'm going to have to do less paperwork. >> Oh yeah.

2:19:13

[laughter] >> There's actually a lot of people that should be >> but that's but that's a good thing there.

2:19:18

There are some there are some beautiful white pills.

2:19:19

There's some there's obviously some quagmires and some quake sand you want to avoid.

2:19:22

But this is how technology is is rolled out and adopted and so you want to you want to skate where the puck is.

2:19:28

But we appreciate you coming on the show and breaking it down for us. Thanks so much, Matt. >> Yep.

2:19:33

>> We'll talk to you soon. Have a good one. Good to see you.

2:19:35

>> Let me tell you about Gemini 3 Pro, Google's most intelligent model yet.

2:19:39

State-of-the-art reasoning, next level vibe coding, and deep multimodal understanding.

2:19:43

And without further ado, we have Vlad Tennv from Robin Hood in the reream waiting room.

2:19:47

Let's bring Vlad into the TV Ultra. Vlad, how you doing? >> Whoa. Cactus. [music] >> Cactus. >> How you doing?

2:19:54

>> I like the Is the cactus symbolic of something.

2:19:59

>> Uh, well, I love succulents.

2:19:59

And I think we're we live in a dangerous world, gentlemen.

2:20:04

You know, you turn around, you just got to be careful.

2:20:06

So, it's a constant reminder that you just have to watch your back >> with a physical cactus behind you.

2:20:11

Yes, you need to physically watch your back.

2:20:14

Don't don't back up during this interview.

2:20:16

>> I have to really be careful here. Love cactuses, too.

2:20:18

This is probably going to inspire us to get some cacti. Cacti, right? >> Sorry to be pathetic.

2:20:24

>> No, no, you're you're right.

2:20:24

We'll get some cacti around around this, too.

2:20:28

>> I'm more of a Christmas tree guy. I like big Christmas.

2:20:30

>> No, but I've been missing having some some plants in the >> Yes.

2:20:32

Anyway, [laughter] sorry.

2:20:32

We're not here to talk about >> You know what's the thing about this cactuses? Yes.

2:20:36

>> You think that it's very dangerous, but you can train yourself to actually like >> No way. Whoa. >> Yeah. Yeah. >> Alpha right here. >> Yeah.

2:20:45

It's all about the angle. >> Amazing.

2:20:46

All about the I had no idea that you could do that.

2:20:49

>> Bandaid on my hand last year. Let's see.

2:20:51

>> Fearless CEO touches cactus.

2:20:51

[laughter] >> That's great. How's business?

2:20:53

What's new in your world?

2:20:57

>> Well, we've got a lot of things going going down.

2:20:59

You know, I know I know it's the day after earnings, but we're always looking forward to the future.

2:21:03

And >> what I did at earnings outlined our path for 2026.

2:21:07

So, couple interesting things.

2:21:11

uh number one in active traders.

2:21:11

We're pushing hard on prediction markets.

2:21:13

We think that we're in the midst of a prediction market super cycle and eventually this asset class is going to go from tens of billions to trillions in annual volume.

2:21:27

>> So, we're in the thicks of that.

2:21:29

>> We're also pushing on a bunch of initiatives that I care about super personally.

2:21:33

Um private markets >> and family finance.

2:21:36

So through this year, if if you look at the end of the year, Robin Hood should be better for you.

2:21:44

The more family members use it, we want to get your partners on Robin Hood, your children, your parents, grandparents, the whole family.

2:21:50

And we're building tools accordingly with that.

2:21:53

And then private markets.

2:21:53

Um I think access to private markets is one of the biggest inequities in uh financial services today.

2:22:02

So we're we're just working really hard to solve that for people. uh very very urgently. >> Yeah.

2:22:10

More specifically, you guys have a fund set up like I imagine there's more going on like where where where where's like private markets as a category going on the platform. >> Mhm. >> Yes.

2:22:23

>> Yes. Cuz like fundamentally fundamentally the problem of like a lot of people have been excited about these billion dollar companies and watch them go from singledigit billion to you know hundreds of billions of dollars and having to just sit on the sidelines and

2:22:37

hold SAS has been a rough rough for a lot of people over the last year >> and I think it's really a continuation of a trend that's been going on for decades right it's it's gotten harder and harder to go public and at the same time more and more attractive and easier here to raise capital as a private company. >> Yeah. >> Yeah.

2:22:56

>> And uh yeah, our efforts in the US to stem the tide are Robin Hood Ventures, >> which is currently on file uh with the SEC.

2:23:05

We filed our N2, which you can think of as kind of a S1 for funds.

2:23:11

>> So, we're in the strict quiet period for that.

2:23:14

Uh so I can't talk about about the fund specifically but in the US we're very focused on on solving this problem and we think we have a path.

2:23:23

>> Um and internationally we're going to push forward on tokenization.

2:23:26

Last year we did our open AI and SpaceX stock token giveaways which showed us that there was just voracious demand for for access to these types of products.

2:23:37

So this year it'll be about >> hopefully getting from the giveaway stage to making that like a real uh making those products real and tradable uh for for customers and and also getting the companies to like uh engage in it willingly, right?

2:23:56

I think I think we experimented a little bit, but uh we realized where we'd like to be is making it clear to companies that this is something they should want and benefit from just as much as as it is to the retail shareholder.

2:24:11

>> If you could rewind, how would you have uh have let retail traders invest in Robin Hood?

2:24:18

Would you have done it at seed round if you could have series A, series B?

2:24:22

Would that have been a headache?

2:24:24

Would it have been worth it?

2:24:26

walk me through if you could replay.

2:24:29

>> We we absolutely would have done it at seed.

2:24:30

Um >> not a lot of people know this about Robin Hood, but Robin Hood was actually we had kind of a hard time raising our seed round. >> Wow.

2:24:40

>> And and so we talked to probably over a hundred investors.

2:24:43

At one point, Robin Hood was live on Angel List, if you remember that platform, >> and you could invest in Robin Hood at seed at a 10 million valuation cap.

2:24:53

So, effectively, think of it as a >> 10 million valuation >> and we would take all comers.

2:25:02

I mean, we would pitch uh, you know, uh, middle-aged exret retirees from Nebraska the same way that we would pitch like Andrea and Horowits or a Sequoia.

2:25:14

And, you know, they would ask us questions and if they wanted to invest, uh, we we typically would just let them invest.

2:25:23

So, we have we have tons of shareholders that were just >> Wow. >> essentially retail. I mean, high net worth. Yeah.

2:25:29

uh maybe uh but but they were just normal people and you know some of them even have messaged us they held through IPO and over the years and and have done quite well.

2:25:39

So I absolutely >> understatement.

2:25:42

[laughter] >> Yeah I absolutely I want to I want to go back >> yeah I want to go back to prediction markets uh uh prediction markets are bringing new people to the Robin Hood platform.

2:25:55

>> Uh that's exciting for the business.

2:25:55

The push back and concern that people have is like people coming on maybe they want to trade the Super Bowl.

2:26:01

Are those people going to make great financial decisions on the Robin Hood platform?

2:26:07

Obviously you guys are an open platform.

2:26:09

people can do whatever they want, but what are you going to be looking for to make sure that uh you know over time uh there's you know I think that the general concern is >> you know I'm not going to use the G word but you know bringing like trading high-risisk trading to the platform um

2:26:29

there's some very real kind of concerns around that so how are you making sure this kind of roll out as prediction markets as a category grow still serve you know the overall user Yeah, I think this is one of the things that we're actively working on. I think

2:26:41

I think we you have some customers that really love prediction markets and for them they want it to be easier to get to and more intuitive and they don't like they they would probably say that our experience right now buries them too much and we make them too hard to get to.

2:27:00

And then you have customers that, you know, don't want anything to do with it.

2:27:04

They don't want to see it.

2:27:04

And so we've been actively working on greater personalization so that we can let customers opt in or out if they'd like and and also we can detect automatically when someone wants to see that content in different places.

2:27:19

So >> this is just I mean prediction markets are kind of a test case.

2:27:23

It's where it's most acute but we see it across the entire spectrum of products as we expand the breadth of our super app offering.

2:27:34

For example, we have we have a credit card. We have banking.

2:27:36

Now, banking is a separate app.

2:27:39

And you have some customers saying, "Well, I'm kind of annoyed having to go through two different apps to get access to to banking.

2:27:45

Can't we put it in the same one?"

2:27:47

Others uh others want it to be separate and prefer it.

2:27:51

And so we're we're continuing to experiment with this stuff, but but where it ends is just uh a really really tightly personalized experience depending on what each customer is looking for and and expecting.

2:28:06

And I I don't think I think we're actually breaking new ground.

2:28:08

I don't think financial services companies have done that.

2:28:12

You see that a lot with with consumer products, but we're investing a lot on the machine learning infrastructure on the AI side into you know delivering that for for customers across our entire product suite.

2:28:23

And I'd [snorts] say more generally, you know, prediction markets um one of the unique things we we have is we're not a monoline prediction markets player.

2:28:32

So we have the suite of products.

2:28:34

We we can offer you a lot of things.

2:28:36

And what we've been seeing increasingly is prediction markets have been great at attracting a new type of customer who previously may have not been as interested in Robin Hood.

2:28:47

You know, they hear about us, they download the app, they onboard for prediction markets, and we're making that process easier and simpler and then we can onboard them to all sorts of other stuff.

2:28:58

So, be it retirement accounts, our credit card, our banking product.

2:29:03

And I think that's just uh something that's generally good for these customers.

2:29:08

I see nothing wrong with someone coming in for prediction markets but then being, you know, discovering our retirement account with >> I I certainly hope that people come in maybe they want to trade something that's happening in the news or or a game or something like that and they realize, hey, I actually just want to save good amount of my paycheck every month, invest in stable assets and, you know, invest in my retirement.

2:29:32

I think that's actually true because >> and I think I think everybody talks about these as two different types of people.

2:29:38

You have your prediction markets users and your people that are interested in stable retirement.

2:29:43

But what we increasingly see is that >> actually it's the same people and you know I might be I'm obviously interested in a retirement account.

2:29:52

I might have a small portfolio for my prediction markets or my options trading or my more speculative trades.

2:29:58

But uh having both together in in one roof uh makes it a more valuable service for me.

2:30:07

>> How do you think about uh the news generation from prediction markets?

2:30:10

It's always been an interesting way we we we pull up prediction markets all the time to understand um what what markets think about, you know, how many SpaceX launches there will be this year.

2:30:23

Uh do you want to do more in content driven by prediction markets?

2:30:32

>> Yeah, and and we've been doing that uh quite a bit already.

2:30:34

We have uh a whole slew of prediction markets that >> are non-sports.

2:30:42

And actually, one of the interesting things that we saw was the week after the NFL season ended, we had the government shutdown.

2:30:50

and the the prediction market contract on the government shutdown actually drove a ton of volume because it was on everyone's mind and people wanted to see what the current status was, how likely it is and of course some portion of those customers uh traded.

2:31:04

So we think that'll be a bigger and bigger thing and and again as we make it uh as we make it easier to surface things that are trending and things that we think you might be interested in.

2:31:15

I think that'll strengthen the use case of looking at prediction markets as a source of news.

2:31:22

>> How do you think the wealth management industry broadly will adapt to AI?

2:31:24

I think there's uh a lot of conversation recently around, hey, do I need to pay somebody 1% if I can ask an LLM, hey, what's a good strategy for somebody that makes X amount of money a year and wants to retire at this point and and uh wants to take a little risk but not too much and you can ask them questions about it.

2:31:47

So, feels like that model uh could be threatened or at least uh margins could could compress.

2:31:53

But how are you thinking about it both as an opportunity from from Robin Hood and then you know how the industry will have to evolve?

2:32:01

>> Yeah, I think I think the there's going to be a lot of disruption by AI.

2:32:04

I mean we're starting to see it already.

2:32:06

Um and we have Robin Hood Cortex which really has done well uh sort of like helping customers think through their their trading their sort of self-directed activity.

2:32:18

But we've already begun conversations with regulators about how to bring Cortex to advice, making recommendations and and and doing ongoing portfolio management.

2:32:28

So, uh obviously we'll want to roll that out safely and in a trustworthy way, but it's coming.

2:32:36

And I actually think on the human advisor side, a lot of people prefer a human advisor.

2:32:41

They prefer the relationship.

2:32:44

they, you know, like to have someone that has the full picture and that they can talk to.

2:32:49

So, I don't think that's going away.

2:32:51

And in fact, AI is going to be a really integral part in streamlining the workflow of those people so that rather than serving, you know, 50 clients per advisor, you go to serving 500 or or possibly more.

2:33:06

So I I think you're going to see both models continue but costs and efficiency and capabilities continue to grow for for each of them.

2:33:19

>> What's the status of uh copy trading?

2:33:19

I there's a lot of people that are excited about situational awareness, what Leopold's doing over there.

2:33:25

Uh how many clicks is it to to to copy his strategy and and how closely is it possible to copy these days the the big funds that have generated a lot of excitement? >> Yeah.

2:33:37

Well, we we have a product coming out, Robin Hood social, which should commence rolling out in in uh just like weeks to low singledigit months.

2:33:45

So, we're kind of >> putting the finishing touches on internal testing.

2:33:51

We just integrated prediction markets, which actually makes the the feed much more dynamic. >> Sure.

2:33:57

>> And when we announced it, one of the features that was like particularly popular was um whale tracking.

2:34:01

So, >> following Nancy Pelos's trades.

2:34:05

this one, [snorts] >> you know, other things like that.

2:34:08

So, >> we're going to make it really what others are doing.

2:34:14

>> It is such a funny world we live in.

2:34:16

It's the Nancy Pelosi stock ticker and yeah uh endlessly entertaining category.

2:34:23

Always always new innovation, but congrats on the progress uh that uh Robin Hood social feature uh how much of his vibe coded?

2:34:30

How much of a speed up are you getting internally?

2:34:32

like what is the software engineering org look like these days in an era of coding agents?

2:34:41

>> Yeah, I mean we we've certainly been continuing to hire software engineers. >> Okay.

2:34:46

Perhaps not at the definitely not at the rate we were hiring in 2021, but >> one of the reasons we've been able to deliver this high product velocity and keep costs relatively flat is because of the productivity improvements we've seen with AI. >> Mhm.

2:35:04

>> And there's there's two things that we sort of like talked about at earnings.

2:35:09

when we when we look at internal operations, the two areas that move the needle are software engineering and customer support >> and I think we are at or at at the very least near best-in-class for both of those.

2:35:22

So customer support side 75 plus% of all tickets are handled by AI including licensed cases that would have previously required a licensed brokerage professional.

2:35:35

>> And and we thought I mean frankly we thought that would be further away.

2:35:37

we were able to to get there and deliver a great experience relatively quickly.

2:35:42

And on the software engineering side, it it's been tremendous.

2:35:47

I mean, with every new generation of models, you look at, you know, Opus 4.

2:35:53

6, now you've got codeex.

2:35:55

Uh you can essentially have it running autonomously overnight, checking its own output, debugging itself, and have it do the work that probably would have taken an individual software engineer weeks to do uh while you sleep.

2:36:13

And one year ago, that wasn't possible.

2:36:15

So the acceleration from each new generation of models is uh is tremendous.

2:36:21

And I I think there's going to be lots and lots of disruption.

2:36:23

You can kind of see the market starting to digest that.

2:36:27

But >> I think the firms that adopt AI and are actual technology companies, >> this is the opportunity to dramatically accelerate relative to incumbents and financial services.

2:36:39

You know, >> a lot of our competitors aren't really even on cloud infrastructure anymore.

2:36:46

They're still on mainframes.

2:36:46

So, I think uh I think I think it's going to become it's going to become increasingly tough. >> Yeah.

2:36:53

Uh last last question then then we'll let you go if if you have another second.

2:36:56

Uh how are you thinking about M&A?

2:36:58

You guys clearly have built the muscle to take new products from zero to one.

2:37:03

I'm sure you have a lot of confidence around that.

2:37:04

But what what's interesting from an acquisition standpoint?

2:37:08

What's your M&A team, you know, spending time on generally?

2:37:13

>> I mean we're certainly uh always always looking.

2:37:15

Last year we were quite active with a number of acquisitions and I think we've really built the muscle to integrate them well.

2:37:21

integrate them well. uh in particular you have Bitstamp which since we closed that acquisition has basically doubled in in revenue and typically when you go through an integration like this it's tougher right because things tend to slow down but we've been able to actually accelerate as we've integrated >> so that's good to see um and and we're on the lookout you know a lot of people

2:37:44

are bearish on the crypto industry right now we remain bullish on on crypto and we think that you know now is the time for builders to build and uh just just like in the past the cycle goes up and down but long run we think crypto is going to become the financial system and they're going to converge and so um [clears throat] you know I think we're we're still investing heavily there. >> That's awesome. >> That's awesome. >> Very cool. >> Yeah. Yeah.

2:38:09

Thank you so much for taking the time to come chat with us. Very very interesting. Uh >> thanks Sean. Thanks. >> Yeah.

2:38:15

Hope you have a good rest of your day. It's funny.

2:38:16

So, so many other other CEOs come on and they're dealing, you know, with the crazy volatility in the market and you're just like you're like first time. >> Yeah. >> Uh it's great.

2:38:25

So, good good to see you. >> Grizzled. >> Congrats.

2:38:29

>> We'll talk to you later. Have a good one. >> Cheers. >> Goodbye.

2:38:31

Let me tell you about Cisco.

2:38:33

Unlock infrastructure for the AI era.

2:38:36

Unlock seamless realtime experiences and new value with Cisco.

2:38:38

And without further ado, we have Jeff Lawson.

2:38:42

>> And we are starting the lightning round.

2:38:44

We are starting the the lambda lightning round.

2:38:48

>> Let's let's activate the gong. Thank you, Ben.

2:38:52

>> We have Jeff Lawson in the reream waiting room.

2:38:54

Or actually, are we delayed here?

2:38:56

Let's uh let's figure it out.

2:38:59

>> I will tell you about Lambda because it's actually the next uh one in the stack.

2:39:03

Lambda is the super intelligence cloud building building AI supercomputers for training and inference that scale from one GPU to hundreds of thousands.

2:39:11

Uh we have Sam Blonde coming on the show in just a few minutes and >> uh this kind of gets at what I was asking Vlad about.

2:39:18

Buco says unless you have 5 million AI is already good enough to be your financial adviser.

2:39:22

Even then it's probably good enough. Try it.

2:39:23

Share net worth where how you've allocated assets what your goals are.

2:39:28

Ask it to analyze and identify opportunities for improvement.

2:39:32

>> Stress test different scenarios.

2:39:35

>> It gets basically everything right.

2:39:35

So, uh, bullish on just out of the box LLMs for helping with this stuff. >> Very good.

2:39:42

So, >> well, let's bring Jeff Lawson in to the TBP and Ultra Dome. >> How are you doing? >> What's happening? >> Very good. Thanks, guys.

2:39:50

>> Thank you so much for taking the time to come chat with us.

2:39:52

Uh, first time on the show.

2:39:54

I mean, I feel like most people will be familiar with your career, but but please give us a brief introduction. >> All right. So, I'm Jeff.

2:39:58

Uh, you know, I've been a an entrepreneur my whole career.

2:40:02

I've been a software developer and started a bunch of companies uh on the internet.

2:40:06

So um very first company during the dotcom era was the first CTO of StubHub was one of the first product managers at AWS.

2:40:12

Uh but then founded the company that most people know me for which is Twilio back in 2008.

2:40:16

So enabling software developers to build um communications and all the apps that we use all day and grew that over 16 years to about four billion in revenue and took it public in 2016 and uh and now I'm here in the fusion energy world with inertia. >> Amazing.

2:40:33

I have to I have to say thank you because uh Twilio sponsored a lot of hackathons when I was in college and it was like the go-to like fun tool to pull off the shelf and build something that was a little bit more interactive than just a normal website.

2:40:48

I built something that would text me every day with little updates and stuff.

2:40:52

It was like so much fun to be tinkering in that era.

2:40:54

So, thank you for everything you did at Twilio.

2:40:56

But >> it was a crowd-pleaser. >> Yeah. Yeah.

2:40:58

No, it just like delightful product experience.

2:41:00

uh so many interesting unlocks and then obviously like huge partnerships you see it part powering Uber and all the big companies that need to send a lot of text messages.

2:41:09

So obviously fantastic business but uh get us up to speed on Inertia Enterprises. >> Absolutely.

2:41:14

Well, so Inertia is the commercial fusion energy company.

2:41:16

And I know that sounds like, you know, saying we're selling unicorns or something, but um that's because fusion energy has been the thing of of myth for nearly 100 years since it was first uh hypothesized because fusion energy is the perfect form of energy for humanity.

2:41:32

It is clean, it is safe, it is low cost, it is abundant.

2:41:36

The only question has ever been, will it work?

2:41:38

Well, that changed in 2022 when the scientists at Lawrence Livermore National Lab actually created the first experiment to create energy with fusion.

2:41:47

And this was a huge uh breakthrough.

2:41:50

And so, Inertia is commercializing that experiment, taking it out of the lab and bringing it to the grid.

2:41:56

And the way we do that is with few things.

2:41:58

Well, the way that experiment works is they hit this tiny little peppercorns sized uh bit of fusion fuel uh with the world's largest laser.

2:42:03

you know, you get it just right, you compress it, and you create uh this reaction that releases a bunch of energy.

2:42:11

>> Uh and so for us, commercialization means number one, we're starting with proven science.

2:42:15

This is pretty important, right?

2:42:16

You want to have science, basic science that works before you start commercializing. So that's step one.

2:42:21

Step two, we're going to go build the world's most powerful laser.

2:42:26

It is uh a million times more powerful than the laser they currently use over at Silvermore National Lab. >> That's crazy.

2:42:32

It is uh 20 times more efficient. It is onetenth the size.

2:42:35

So, it's a really modern but the coolest laser uh the humanity will have ever built.

2:42:40

The third thing we're going to go do is build the world's first fusion fuel uh factory where we are making these fuel targets in a automated scaled way.

2:42:49

And then lastly, we bring all that together and we build a grid scale gig gigawatt scale power plant that is enough energy to be able to power a medium to large size city.

2:42:58

A million homes you can power with this facility. So that's our plan.

2:43:03

>> That's actually that's so crazy.

2:43:03

Uh talk to me about the capital intensivity of this. This is hard tech. This is energy. This is a big deal. How much did you raise?

2:43:11

And >> I love that you're doing the meme too.

2:43:14

The like, you know, make you build software, you know, hardware and do and then do the hardest possible, right? >> That's great.

2:43:22

>> Well, you know, I feel like that's one of the things that uh that is exciting to do.

2:43:26

like having done the software thing for most of my career, uh, taking what I've learned in terms of building a company and scaling a company and now bringing it to this new domain is is really exciting.

2:43:36

So, in terms of the capital intensity, you're right, fusion is not a cheap endeavor.

2:43:40

Uh, so today we announced uh our first capital raise, $450 million.

2:43:44

It's a milestone based approach.

2:43:50

>> Nothing like 450 to to kick things off.

2:43:53

>> That's a fantastic round.

2:43:53

It's a good way to get started. >> Thanks. Thanks.

2:43:57

So, we've got uh a milestone based approach.

2:43:59

So, we basically we take this and we've got a great group of investors who have come around and said, "Hey, look, you know, fusion is something that we want to invest in, but we want to invest in a commercialization effort, not in basic science."

2:44:10

And so, that's what our investors have come to the table to do.

2:44:13

And so, we're really excited to be embarking on this.

2:44:15

Now, we will raise more capital later, especially as we get to that last stage, which is to go build the first fusion power plant.

2:44:20

That'll be capital intensive.

2:44:22

Uh but this funding is uh allowing us to take a lot of the design work that we're doing today and then start building these uh prototypes.

2:44:30

So scaled down version of that laser, a scaled down version of that uh target assembly plant in order to prove that uh these technologies are ready for the scallop. >> Yeah.

2:44:39

>> Uh with a business like this, it feels like you know uh obviously the TAM is massive.

2:44:45

It's no doubt that the world needs tons and tons of energy.

2:44:47

We want as much of it as possible.

2:44:51

uh how do you how do you look at the risk to the business?

2:44:53

You've got technical risk, execution risk, regulatory risk.

2:44:56

What's your what's your kind of personal framework and and how are you trying to like, you know, chase each one of those down and to uh you know, eliminate that risk? >> Yeah, absolutely.

2:45:06

You know, it's interesting.

2:45:07

Uh it's the exact opposite of the world of software.

2:45:09

In the world of software, it was always, you know, you can build just about anything.

2:45:12

The only question is does the world want it?

2:45:15

>> Is anyone going to pay you for it?

2:45:15

This is the opposite, right?

2:45:17

know the world needs energy especially if it is cheap, clean, abundant uh and uh safe.

2:45:20

Uh the only question has always been will it work?

2:45:26

>> And so here we are with the you know physics of it now proven it's the scale up and so what is that scale up consist of?

2:45:31

Well it is essentially building supply chains building vendor bases and scaling up uh a number of fields to meet the demands that a first uh power plant would put on some new technologies.

2:45:41

So for example, we're working with a lot of uh companies in the uh laser diode field to scale up production of the particular kinds of laser diodes that we need to go build our um our plant.

2:45:54

And in order to do that, we have to scale up production of these particular semiconductor diodes by about a,000x what the global production is today.

2:46:03

And so you look at something like that and you're like, okay, that is doable. It's a lot of hard work.

2:46:08

Uh and so the milestones that we look at is like, okay, we're bringing the vendors along for the ride.

2:46:12

We have to do some invention, some automation.

2:46:15

But, you know, this looks a lot like bringing um a consumer product uh to the market.

2:46:19

You know, I think about here's what Apple does every year.

2:46:21

They dream up a new iPhone and then they figure out how are we going to make a billion of them and then they introduce it to the world.

2:46:26

And every time they do that, well, there's a bunch of hard things they have to go figure out about how they're going to uh take a design and manufacture them at scale and with a certain yield and with a certain precision.

2:46:36

And so those are the kinds of uh undertakings that we are uh going under for both the laser scale up as well as our target development scale up.

2:46:45

>> How important is it to find a dance partner with one of the hyperscalers?

2:46:49

Now I I've seen a number of news articles about not just fusion but also fision projects and just big energy projects.

2:46:58

You know these things are measured in years if not decades.

2:47:00

uh and it feels like uh there's a lot of advantages to having uh at least an LOI that says hey if we can deliver this you know AWS wants it or something like that.

2:47:12

How are you thinking about pull uh you know spinning up the bisdev muscle of the business maybe before you break ground?

2:47:20

>> Well you know I think that if anybody is able to deliver on cheap uh abundant clean safe energy is there any question that you will have buyers for it?

2:47:27

You know I don't think that's really the problem.

2:47:31

I think really the problem is actually bringing those things to reality.

2:47:34

But we are >> So would you say would you say the people that are like you know still have all this risk technical risk to their business? Can they scale it up?

2:47:43

Regulatory risk all that and they're focused on like finding their dance partner.

2:47:45

It's like is that just for hype and and and do you think maybe that's like the wrong focus or is creating some amount of hype necessary to attract capital?

2:47:54

I mean, you you have the luxury of a track record that allows you to raise half a billion dollars out the gate, >> whereas someone else might need to find that dance partner to get any type of excitement around what they're doing.

2:48:06

>> Well, I think really it's about focusing on the core progress that needs to be made because um no matter what your approach is, there's a lot of things that have to get proven.

2:48:14

There's a lot of things that have to be done.

2:48:15

And so I don't think that necessarily the validation of a buyer is the most important thing for the stage at which you know most fusion companies are at.

2:48:25

Um that said we were happy to have Google ventures become a part of our uh our round.

2:48:30

So they are an investor in inertia and obviously we you know we think that if we are able to deliver on the promise of clean safe cheap abundant energy that they and many others will be interested buyers but really our focus is heads down let's make it work.

2:48:43

let's do the engineering and the scale up and the supply chain work that is needed in order to uh go build that first plant. >> Why inertia?

2:48:53

>> How'd you pick the name?

2:48:54

>> Well, uh the there are two major uh types of fusion like u methods.

2:48:58

One of them which I think you may have heard about before is magnetic confinement fusion.

2:49:03

The other one is called inertial confinement fusion.

2:49:06

And we are doing the inertial confinement fusion using lasers.

2:49:09

Uh, and so given that, I thought the word inertia was a super interesting word.

2:49:15

>> Um, because it both uh can refer to the um the lack of change of direction, right?

2:49:21

The if you have inertia, you're like, well, you're not going to move.

2:49:24

And I thought that actually spoke to humanity's dependence on carbon-based energy, interestingly enough.

2:49:32

>> But inertia, the flip side of inertia is once you have uh momentum, once you are moving, it's hard to stop you.

2:49:37

And of course that's our goal with building the company.

2:49:40

And so I thought there was a number of interesting things about the name.

2:49:43

But it all stems from the the basic technology that we're pursuing which is inertial confinement fusion. >> That makes sense.

2:49:48

>> Uh prior to this you've kind of lived and built through a number of cycles.

2:49:53

How have you been processing kind of everything else happening in nature outside of outside of energy? >> Yeah.

2:50:00

You know it's interesting. We started um StubHub.

2:50:01

It was during the the dot meltdown in 2000.

2:50:03

Started uh Twilio during 2008.

2:50:06

the financial crisis and so >> you were born in the darkness. >> Yeah.

2:50:12

[laughter] >> You know, I think the thing is you got to start companies irrespective of the macro environment uh that you're operating in because the macro environment is going to change and so the business itself has to be built on the fundamentals of whatever is going to make that business successful.

2:50:24

So for the case of say StubHub or Twilio, the fundamental was focus on customers.

2:50:28

If customers need what we're doing, great.

2:50:31

We'll eventually, you know, show the world and win and do all the things we need to do.

2:50:34

If we're not serving customers, then we won't. It's as simple as that.

2:50:37

For inertia, it's a little bit different because we're not going to have customers in the short term.

2:50:40

But I like to say our biggest customer is the laws of science, right?

2:50:44

So, we always have to be serving the laws of physics.

2:50:48

Uh, and if we focus on that, taking >> got to talk to the you got to talk to your you got to focus your time talking to your customers.

2:50:53

The law physics laws of science.

2:50:55

[laughter] >> Our customer is uh the universe. >> Yeah.

2:51:00

And but if we focus on that of doing all the engineering, all the scale up work we have to go do to go take the proven result and now build it bigger and um uh into a power plant, that's the thing.

2:51:08

By the time we're done with that and proving that out, whatever the current economic story of the day is or or even the story of the year is will be long gone and we talking about something else.

2:51:19

And that's how I've always looked at my uh at my startups.

2:51:22

>> What's the what's the hardest role to hire for right now? Hm.

2:51:26

Well, you know what's interesting?

2:51:29

[clears throat] We are, one of the things I like and I'm really uh excited about with Inertia is [clears throat] that we are not fighting the talent war for AI engineers.

2:51:37

Now, we have software engineers on staff and we are hiring people versed in AI, but it's not the same kind of people that, you know, uh that Meta and Google and every startup down the street and I'm here in San Francisco at the moment, uh is fighting for.

2:51:53

And you see some pretty bonkers things going on in the talent market right now for those, you know, foundational AI engineers.

2:51:59

And I'm quite frankly just happy that we're not in the market for that talent.

2:52:03

We're we're hiring for a lot of engineers, but, you know, not necessarily those.

2:52:07

We're hiring for mechanical engineers and materials engineers and industrial engineers.

2:52:12

We're hiring people from the likes of, you know, Apple, people who figured out how to take these products every year and take them from a designer's desktop into, you know, a factory where they're making billions of them.

2:52:23

We are hiring people from the likes of Whimo, where they had to figure out over the last decade, hey, how are we going to build this first of a kind autonomous car and scale up things like LAR and make them better and cheaper and faster and all these things in order to enable those amazing cars we see driving around autonomously in here in San Francisco and elsewhere.

2:52:39

And it's like those are the types of people who've done those scaleups uh are the most um you know a lot of the interesting talent that we're going after right now.

2:52:48

And I think that's just a little bit different than the [snorts] you know than the AI uh um uh let's just call it a hot mess [laughter] right now in the industry.

2:52:59

>> Well, thank you so much for taking the time to come by and explain it all to us.

2:53:03

This is >> great to excited. Come back on anytime.

2:53:07

>> Everyone's rooting for you in the chat.

2:53:08

>> Big updates, small updates.

2:53:08

You're going to be legendary.

2:53:10

Uh thank you for all the hard work.

2:53:12

It's going to be probably decades, but hopefully we'll have you back a bunch along the journey because this is a lot of fun. >> Hopefully a a decade.

2:53:18

Uh and then and then the next >> optimism. There we go.

2:53:22

>> Thank you very much, guys. Appreciate it.

2:53:24

>> Have a great rest of your day. We'll talk to you soon.

2:53:26

>> And uh without further ado, we have Sam Blonde coming in to the TVP Ultra Dome. Sam, good to see you. How you doing? >> I'm awesome.

2:53:35

Thank you for having me, guys.

2:53:37

Here, let's start off with a little bit of fun.

2:53:38

And I think the squad is ready for a big show and we're going to dong it right back at you. >> Let's go.

2:53:45

>> Wow, look at that team. Here we go. >> Amazing. Amazing. Hey team. >> Wow.

2:53:54

So coming out of stealth today, it seems like you hired half of half half of San Francisco already. How big is the team?

2:54:02

How long have you actually been working on this?

2:54:03

cuz we worked together what 2 years ago and then uh you called me and you were ready to launch. >> That's right.

2:54:09

Uh so we we really started working on this September of 24. Okay.

2:54:14

>> Uh Kugan, awesome to see you again.

2:54:16

Jordy, great to great to see you.

2:54:18

Hopefully the first of many.

2:54:18

Uh and started September of 24.

2:54:20

Squad's about uh going on 40. Wow. So >> yeah, going on 40.

2:54:26

Um a lot of EPD and we're starting to build out go to market too. So having a lot of fun.

2:54:30

too. So having a lot of fun. re uh introduce the full the full product the company since no one's heard about it yet but >> people have heard of Monaco they've heard of Monaco >> but now they've heard of the real Monaco >> real Monaco >> [snorts] >> uh uh there's a maybe fun story with

2:54:45

Monaco we've already been in a a bit of a lawsuit so we can uh if entertaining for the viewers absolutely [clears throat] okay so uh more importantly uh we're an AI sales uh platform uh and I I think like you know two-minute version or one minute version is on the tool tools side or a replacement for legacy CRM. Most

2:55:03

Most commonly, this is going to be like your HubSpot, your AIO, your Salesforce.

2:55:07

We also replace all of the point solutions that integrate to those uh tools.

2:55:12

So, this is going to be data provider like an Apollo or a Zoom info.

2:55:16

We provide all of your signals like a Clay.

2:55:18

We do your call recording like a Otter or Fireflies.

2:55:23

We do all your sequences like a number of different companies that do outbound in a deeply integrated platform.

2:55:30

And for us, that's really a means to an end, which is we're replacing full sales workflows with agents. Yeah.

2:55:37

>> And so we have agents who identify the right company to target, the right person to target, the right message to send.

2:55:43

We leverage s signals to incorporate into that message.

2:55:45

When you get a response, we schedule a meeting. We record that meeting. We update your pipeline.

2:55:51

And we're really architected in a way that is um not to be reactive to user input.

2:55:56

If you've ever worked in a a sales tool, you sort of get a a database that's largely empty that you need to tell it what to do.

2:56:03

Day one, when you log into Monaco, everything is already done for you.

2:56:07

You're just sort of a beneficiary and recipient of things like meetings, feedback on things you can be doing better and more. >> Yeah.

2:56:16

Is is is launching with a platform like this only possible because of AI and and the advancements in coding agents and coding tools?

2:56:23

Because it seems like you're b you're sort of rebundling.

2:56:26

Yeah, >> you listed off maybe like 10 different point solutions that are now coming together.

2:56:32

>> Uh, and it's it's notable that that you guys didn't come out of stealth like maybe 6 months ago when you maybe had five of those things operational, but you you you clearly decided to launch with a with a full suite.

2:56:45

>> I I think a few things come to mind.

2:56:45

One is uh we are able to build software faster because of uh the coding co-pilots that you just alluded to.

2:56:52

Um and so I don't know that we would have been able to build a Monaco like PLA like platform in the amount of time that we've been able to pre AI.

2:56:59

Um we're also building for a segment of the market were purposebuilt for earlier stage startups.

2:57:08

So this is series A seedstage companies.

2:57:11

The needs of these businesses are relatively unsophisticated compared to much larger companies.

2:57:16

And so because we're purpose-built for a type of company that doesn't need super deep functionality unlike the database side, in fact when you have super deep functionality, it makes it more difficult to interact with.

2:57:29

Uh and so you bundle all these tools together if you're a series A startup it actually works against you because the tools are so complicated to integrate, customize, work with.

2:57:40

Uh and again, we're purpose-built for that company.

2:57:42

And then um the last thing that comes to mind is wouldn't be possible to build Monaco without AI because we're AI native.

2:57:48

So like everything that we do is sort of oriented in the decisions that we make are around how can we program the platform to have an agent doing this rather than a user and and so very different user experience than if you're used to logging into these sort of reactive databases. I listed a few of them. HubSpot Adio Salesforce.

2:58:08

Um totally different user experience. Yeah. Talk about the domain. You got monaco. com. Talk about the lawsuit.

2:58:15

Talk about how you picked Monaco to begin with.

2:58:21

Uh I want the full story. >> Okay. So, uh naming was hard.

2:58:24

It took us uh a couple months and like tried a bunch of different names.

2:58:29

And you can't just like pick a name that you like.

2:58:31

We couldn't have just called ourselves like sales. com.

2:58:34

uh because the like one we wanted the to be available and two you like can't name it if something already has that name.

2:58:41

So I was trying to associate the brand with um like luxury premium was thinking through like what are some names that uh are typically associated with that and I came up with Monaco.

2:58:55

>> My older brother who is a co-founder when I told him I really like the name Monaco his response was that's the stupidest name ever.

2:59:02

what are we going to just call it like New York?

2:59:03

Uh [laughter] and so uh he wasn't a fan but I think like o over time um started socializing it with some other people and started picking up some traction.

2:59:14

There are a few things that we really like about it.

2:59:15

Um it's a cool sounding word like Monaco is just like a nice word itself.

2:59:19

Uh the place is associated with I don't know um wealth and success.

2:59:26

>> Yachts >> yachts um a big one is Formula 1.

2:59:28

A lot of really cool things that we can do there with the brand.

2:59:32

Our our logo is actually like a checkered flag that's going up and to the right. >> Uh and um let's see.

2:59:38

So the domain dispute, we we ended up calling it Monaco.

2:59:44

Really liked the the domain.

2:59:44

Uh >> was the domain just available or did you have to go to a broker and get pay?

2:59:51

>> A domain like that doesn't just sit for $12 on GoDaddy. >> Go. >> We we had monaco.

2:59:56

co and that was a couple thousand dollars.

3:00:00

Okay, >> I think all is said and done, both the domain cost and the broker's fees, we spent like I don't know another$8 or $900,000 to add the M. So, we got monaco. co evolved to monaco. com. Uh, we did use a broker. Shout out to Lumis.

3:00:16

Uh, if they're watching >> I love Lumis.

3:00:17

I've used I've worked with them on a bunch of domains. >> Awesome. Shout out Lumis. Cool.

3:00:22

>> Um, how what what the dispute? >> Yeah. Yeah, the dispute. What actually happened?

3:00:26

So, um, shortly after we acquired the domain, I think it had sort of been parked for a little while, uh, and we get this like hate mail from the escrow company that was holding the domain >> that the government of Monaco had filed what's called a UDRP dispute against us.

3:00:42

We had never heard that this was a thing.

3:00:44

I didn't know there was like a regulatory body for domains.

3:00:45

Anyway, they made like, you know, all sorts of uh what turned out to be unsubstantiated like trademark claims.

3:00:53

We we I tried to get legal representation.

3:00:56

This was like a couple monthsl long process that required all sorts of evidence and more and we ended up uh winning the case.

3:01:02

So uh all the ends well we are Monaco. It's official monaco.

3:01:07

com >> just coming went to war with a country before you even launched.

3:01:11

Not not many >> wartime CEO. There we go.

3:01:15

>> Uh what uh what are you learn we we've been covering the SAS apocalypse.

3:01:18

You guys have the benefit of kind of understanding the world in its current form and building from the ground up.

3:01:24

Uh but but a lot of questions around seatbased pricing.

3:01:28

Do companies need to evolve to more valuebased pricing?

3:01:30

What are you learning about kind of the broader concerns around uh enterprise software?

3:01:38

And how are you kind of applying it?

3:01:42

>> Well, I can tell you what we're doing right now.

3:01:43

Um we're we're um in public beta.

3:01:46

So, uh, yesterday we were in private beta.

3:01:49

Today we're in public beta.

3:01:50

We'll eventually get to general availability.

3:01:53

Right now, we're pricing around simplicity.

3:01:55

So, we charge a platform fee that includes all of the compute that you need.

3:02:01

Relative to these other companies that I've referenced, we have very high compute costs because of all of the agents that are doing the work.

3:02:08

We also have really high servicing costs.

3:02:09

We pair what we call forward deployed AES with every customer that signs up.

3:02:14

Um, so we charge a platform fee.

3:02:16

those things are included.

3:02:16

Uh right now we're charging annual platform fee of $25,000.

3:02:20

That's discounted to what it will be as we go into GA.

3:02:24

Uh and we will I I suspect when somebody who is at the company that is much smarter than me on the finance side, I think we will be in the sort of like you pay a minimum minimum amount for the initial compute and then it's pay as you go.

3:02:40

It just makes far more sense with the value that we're adding to do this usage based sort of compute predicated pricing.

3:02:46

But right now we're solving for simplicity and eliminating friction from onboarding customers and this has been a price point that has been met with very little resistance.

3:02:57

resistance. How do you think sales is evolving >> if you compare you know code uh any any software engineer says oh I don't write any code I just review code now what what's the equivalent experience uh in sales how where do you think it goes

3:03:12

>> yeah it's it's a thoughtful question um you know look my answer may change 6 to 12 months ago from now so let me give you the like today answer um >> I it doesn't seem that uh the sort of customerf facing relationship building aspect of sales is going anywhere. In

3:03:29

In fact, that that seems today to be the highest ROI activity that sales people in in some of our customers cases, founders are doing trying to replace the founder for many of the startups that are selling our product with, you know, some sort of like agent that is pretending to be a salesperson or or whatever it might be.

3:03:50

People want to talk to someone in sales oftentimes.

3:03:51

And so what we're doing is we're actually optimizing around that.

3:03:55

It's the sort of non-c customerf facing activities that we believe agents are far better at.

3:04:00

So I'll give some examples building and scoring your addressable market.

3:04:05

So what we're effectively doing is we are telling you um without being customerf facing who are the best companies for you to target and why.

3:04:14

Here's your prioritized list.

3:04:16

We've added buyers to that prioritized list.

3:04:19

We've added sequences based off of signals to that prioritize list.

3:04:24

We are going to automate those sequences with no human involvement.

3:04:28

And you as the beneficiary, whether you're a sales rep or a founder, you will spend your time customerf facing the way that I'm speaking with you guys right now.

3:04:37

And we're going to optimize everything in the platform around that experience, including the postf follow-up.

3:04:43

So you get off the call, we have the call transcript, we've written an email for you to follow up with that person.

3:04:49

and it's very opinionated and trained on the way that we think about sales and go to market.

3:04:54

You can review that email and click send.

3:04:56

It's time for the next call.

3:04:56

And so that's the sort of optimization that we believe AI is uh influencing the function of sales right now around.

3:05:04

It's getting more qualified demos, helping you close more of those customers and actually emphasizing the relationship building that happens uh that is sort of customerf facing.

3:05:17

What's the best way to get a job as a salesperson in 2026?

3:05:23

Advice for young people, maybe mid-career people, somebody who wants to sort of be on I mean, you you worked in sales, had a great career.

3:05:30

What does it take to be the next Sam Blonde?

3:05:35

>> Oh, well, that's um that my my answer might come off as too arrogant.

3:05:37

Why don't I just come why don't I come up with like uh what what what would I do if I wanted a uh job in Monaco?

3:05:42

I I think um uh I I think there are um a couple things that stand out right now.

3:05:51

We we've come out of this like and I think we're long out of the the sort of like COVID time period.

3:05:54

We are five days a week at least in San Francisco.

3:05:57

Uh and so anybody that is sort of looking for this like I I I expect to be able to you know potentially work from home one or two days that that like sort of co hangover that's a a thing of the past.

3:06:11

So I I think um from a a quality standpoint, people that are just looking to win um understand that it it's like hard work to to work and win at a company like Monaco.

3:06:22

Um I do think that like track record of performance is an important thing.

3:06:29

And so if you are uh you know a little bit later in your career or have several years of experience leveraging the relationships and the network that you've developed through that process, I think for us it's going to be hard to hire someone that sort of comes to the website and fills out a like I want to be a senior AE at this company uh like job application w without a close connection in >> send you a bottle of champagne, right? That's the secret.

3:06:57

Look, [snorts] um I won't say I can't be bought [laughter] a case of champagne.

3:07:06

Yeah, if you're looking for a job, send a case of champagne.

3:07:10

You'll get the interview, maybe. Who knows?

3:07:12

You got to have the resume, too, and the skills to back it up. Jordan, anything else? >> No, this is great.

3:07:16

The whole team on all the progress.

3:07:18

Uh I'm Yeah, I'm excited to uh watch more companies pick this up and >> and uh start to grow their revenue faster hopefully. So, >> this is awesome. Thanks so much. Come back on soon. We'll talk to you soon.

3:07:31

>> Congrats on bump to success. We'll talk soon. Take care. Have a good one.

3:07:34

>> Let me tell you about Railway.

3:07:34

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3:07:38

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3:07:42

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3:07:46

And without further ado, we have someone in person. Who is it? It's John. How you doing, John? What's happening? Welcome. Thank you. >> Grab a seat. >> Better in person.

3:08:01

>> Yes, even better in person. What brings you to LA?

3:08:04

>> Well, a couple of other meetings, but I figured I had to stop by. >> Yeah.

3:08:07

>> And you know, little known fact, I was actually in journalism school. >> Okay.

3:08:11

>> Before along with data science, I was also majoring in journalism in Northwestern. >> Mhm.

3:08:16

>> And if this had been an option when I was still in school, I might have not dropped out and just tried to get a job here. >> Who are your heroes?

3:08:19

Who Who's the Who's the GOAT journalist in your opinion? >> Oh, man.

3:08:23

Well, I dropped out for a reason.

3:08:26

>> [laughter] >> didn't learn anyone's name. >> Uh, that's funny.

3:08:29

Uh, well, uh, reintroduce yourself.

3:08:31

Tell everyone what you're working on, what you're building. >> For sure.

3:08:34

So, I'm the founder and CEO of JXA, which is a GPS alternative that can track anywhere on Earth, outdoors, indoors, underground without relying on hardware like satellites, beacons, or cameras.

3:08:44

So, >> that's a bunch of buzzwords to say without external >> without external hardware, right?

3:08:48

>> You still need your hardware.

3:08:48

We use uh IMUs that are already installed on devices like phones, robots, embedded devices, medical devices.

3:08:56

>> So, no magnetic fields involved.

3:08:58

>> No, that's kind of a um >> different tech, right?

3:09:00

>> It's a it's different tech.

3:09:00

And and the key differentiator in what we've built is something called synthetic fingerprinting, which is this idea of being able to simulate IMU measurements at scale for different people and objects.

3:09:12

And the value behind that is essentially from this desk here, we could map out and simulate uh an environment anywhere in the world, a Amazon warehouse in Boston, and then have that up and running like in an hour. >> Okay.

3:09:24

>> If you wanted to typically use like a magnetic um approach, you actually because it's hard to simulate magnetic movement because it's usually dependent on objects that are hard to predict being in the environment. >> Sure.

3:09:34

>> You actually have to go to that warehouse, collect that data manually, and then train models on that. Mhm.

3:09:39

>> Um and so our idea is that the ultimate scalability with any positioning system is one that can be deployed fully remotely cuz I can't possibly go to, you know, every corner of the earth and install beacons, cameras, or you know, collect fingerprint data.

3:09:52

>> So what's the what's the textbook device? Android phone, iPhone. >> Yeah.

3:09:55

So I mean every every mobile phone today has an IMU inside of it.

3:09:58

So like the same thing that's powering your Compass app, right?

3:10:00

Accelerometers, gyroscopes are what we rely on.

3:10:03

>> Are they getting better?

3:10:03

because I feel like the compass app came out I don't know a decade ago and it works as well as I can tell.

3:10:10

>> I mean they've gotten better like so the traditional problem you'll see in the like inertial measurement unit space if that's one space that you find yourself in is that drift is pretty >> prominent.

3:10:19

>> prominent. So um you know in theory if we can do something that's faster, better, cheaper and more accurate you know everyone's like why haven't this been been done before right so the idea is typically because IMUs drift a lot >> so if you want to actually you know track someone over or an object over a long period of time typically they veer

3:10:36

off course and then you end up losing >> the example is the phone's here you know the phone's here to start then you raise it one foot the IMU knows you went up a foot you put it down a foot the IMU knows you went down so you know where you are probably accelerometer like a altitude sensor but we're talking about um usually speed and orientation vectors. So the simplest way to think

3:10:54

So the simplest way to think about it is right if you know your starting position and you're stacking vectors related to speed and direction >> um that's called dead reckoning.

3:11:01

That's the approach where you're not actually that's just like very drift right and so what our what we do with our simulation and then our kind of um the models that we've built >> is what mitigates drift by like 90 plus%. >> Yeah.

3:11:14

>> And is able to track people and things over long periods of time.

3:11:15

So the value ads are places like in defense and military, right?

3:11:19

Cuz GPS gets jammed like instantly in any war zone.

3:11:21

Um in indoor environments like warehouses, hospitals, uh any sort of like logistic center.

3:11:29

So those are kind of where we target first.

3:11:30

Obviously our long-term goals sort of be like a like I said a pretty widescale GPS replacement.

3:11:34

Um you can imagine like that way down the road eventually someone like FEMA being able to use this to find survivors of natural disasters under piles of rubble where a GPS signal might not be able to penetrate through.

3:11:45

Um but in the near term those commercial opportunities are pretty >> Do you have any customers yet or do you have pilots running and how big are these firms that you're working with? >> Yeah.

3:11:54

So we work with like I said kind of those three industries mostly right now.

3:11:57

Logistics, healthcare and defense.

3:11:59