Google did a code red three years ago on them, and now they're doing a code red back.
How much extra in multiple do you pay for how much extra in growth?
The majority of the private tax companies, I think, are in a TAM trap.
Overpayment only works when the TAM is huge.
In finite TAMs, you got a bit more tightly.
Did SaaS has become like Japan?
It's a great economy, but if everyone only has 0.9 kids, there's only so many seats to go around.
I think, in the fastest growing companies that I've invested in, no one gives a rat's ass about the bottom line.
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You have now arrived at your destination.
Where's Rory?
What?
There's technical difficulties?
I can see you, Harry.
Oh, Rory!
Oh, I sound like the voice of God here.
Amazing!
Yeah!
Oh my God, that's very Big Brother-ish.
This is amazing.
So guys, I've done 20VC for like 10, 11 years.
And I love it.
I love it so much.
But then we started doing these shows with jason and rory, and not only did i realize actually this is like my passion, but i realized that no one actually ever liked me in the first place.
They just freaking love rory and they learned sass from jason.
So this is going to be a live pod, which makes me inherently nervous and excited at the same time.
For those that don't know, this is the show every week where we discuss the biggest news in sass in tech, with no politics, And so we're going to start with Thrive, partnering with OpenAI.
How do we think about this partnership?
Over to you guys.
The quick answer would be, we'll definitely talk about it, but it doesn't matter.
I think the interesting thing, Harry, is that's not the OpenAI story anymore.
That's the open AI story from a day ago.
And the open AI story today is almost the exact opposite.
It's the code red, focus on the core.
It's almost like a statement that says all the other things we've been doing, we ain't doing them now.
We're just going to be fixing our core product.
We're even pushing on ads, but they're even pushing on agents for healthcare, pushing that stuff back and really going all in on no distractions.
So while I think this is an interesting announcement and we'll definitely talk about it in a second the Zoom out comment is 24 hours later.
That's not the zeitgeist at OpenAI anymore.
The zeitgeist is Google did a code red three years ago on them and now they're doing a code red back.
The one thing that is kind of interesting to it is it's a reminder and this can be a little soul crushing as a founder there's like only a couple of deals that matter to VCs.
You'll see a VC stand aboard for 20 years and you'll see them always hanging out with this one CEO.
And Thrive has a lot of winners, right?
But this is a big winner.
And so anything you can do to go deeper with those founders on your one or two winners, it's power law and steroids.
It's power law with what you do with your week.
It's power law with your deal flow.
So I don't totally get who's giving each other how much equity, but I think it's a part about going as deep deep with your winner as humanly possible.
This is open AI investing in Thrive Holdings.
Yeah, but it's the same people.
It's still going deep on your winners.
It's I'm turning my VC fund into a holding company.
I'm putting a billion or two over there.
And then I'm going even deeper with the number one company that I've ever invested in.
If we're going to go on the specifics of it.
First of all, I think it's a great deal for Thrive, because Jason's right.
The whole trick in venture is we try and pretend we matter, but in our hearts we know our best companies matter.
And the best marketing you can do is get as close as possible to your biggest deals.
And Thrive to give them huge credit, put a bunch of money in to open AI.
In that I think it was a 70 billion round.
And we're there for Sam in the great fiasco of two years ago.
So my guess is he's pretty darn loyal.
And this is a chance for them to get a halo effect on this initiative.
And we'll talk about the specifics of the initiative in a second.
But it's a huge halo effect.
Because, as your last speaker said, you go in with the OpenAI moniker and you get some real attention.
So it's awesome for Thrive.
I agree.
The advantage to OpenAI is much less clear.
I'm not sure they're putting in money.
In one of the press releases they said they're going to get a lot of specific data from some of these verticals that Thrive is pushing into.
But-
My guess is I know who was ecstatic when that was announced and who was like, yeah, whatever.
That's pretty clear.
Okay, we said about the importance of our winners and Rory, you humbly said that it's all about our kind of star founders.
Databricks is one of the stars of the last generation or this generation.
They're rumored to be raising $5 billion at $134 billion valuation.
It's 32X 2025 sales, which are 4.1 billion.
They're at 55% year-on-year growth.
Is this actually cheap?
How did we analyze this one?
Well, I wouldn't call it cheap, but possibly reasonably priced.
Because it actually.
It's very convenient right now because the direct competitor Snowflake, is public at exactly roughly the same revenue, around 4 billion, growing at 28, valued at 80 billion, so 20 times the revenues.
It poses very nicely the big picture venture question how much extra in multiple do you pay for?
How much extra in growth?
Right here is the worked example.
It's like you can buy a profitable company doing 4 billion with 28 growth at 20 times, or you can buy a unprofitable but faster accelerating company at 32 33 times.
And is that extra 25% of growth?
Because I think Databricks is growing allegedly at 55%, not 25%.
So you're getting 25% to 30% of extra growth.
And the question is, is that worth it?
First of all, you agree that's fundamentally the question you're asking.
How much extra revenue multiple do you pay for how much extra growth?
Would you agree, Harry?
I agree with that.
And I think very quickly, because you do the math, there's a bunch of ways to do it.
What you say to yourself is, if that extra growth lasts for any length of time, extra growth's worth a shit ton, to use a technical term.
That compounding keeps going.
So if that growth persists for like three or four years, then maybe that extra premium is worth every dollar and then some
Then you start saying, how much extra for how much extra growth?
And you look at the public markets to figure it out.
And then you discover something really funny.
And Jason's talked about this.
There is literally only one public company growing more than 30%.
And that's Palantir.
And for the record, that's growing at 50%, widely profitable, and valued at 80 times sales.
So you just don't have a data set publicly to assess this.
I think the simple answer is it would be the second best public company if it were public today.
It seems about right.
The crazy thing is it continues to modestly accelerate.
It's just something that we just haven't seen before.
And it's something we all have to adjust to that you can continue to accelerate at this scale.
It justifies all the craziness we see in venture, at least for now, because the headroom is still there.
I totally agree, Jason.
And I'd forgotten that.
The reacceleration changes everything.
Because I was going to say, when you develop that model of how much extra is 55 worth versus 25, you kind of make some assumption of gradual deacceleration and gradual conversions.
Because that's the only rational thing to do.
And then you can come up with a number.
It's a high-revenue model, but it's still a number.
When stuff starts reaccelerating at scale, it's almost hard to figure out the model.
By definition, if it continues to reaccelerate, just for the record, it's infinitely valuable.
Because that's just what the math says.
It's probably not going to be infinitely valuable, but it just points out the power of reacceleration at scale.
If you could even stipulate going from 50 to 55 to 60 at scale, oh my God, there's huge value.
Actually, it's the same dynamic that's why it's hard to value the big foundation models.
When Entropic went through that bout of re-acceleration this year at scale, everyone realized the model was wrong.
And they just have to raise their estimates and raise their value.
And that's why you saw that step function increase in valuation.
Because you said re-acceleration is really hard.
We see it maybe one in three companies does it for a single year.
Only one in 10 does it for two years.
I've very rarely seen re-acceleration when you're already at 50%, for God's sake.
No, you're exactly right, Jason.
That's the killer fact here that makes it hard.
So you end up saying to yourself some version of how big is the time?
Because, in the end, the only thing that stops something that's re-acceleration and scale is when you hit the wall of well you sold to everyone.
It's the Zoom thing.
Yeah, it just also reminds you that seed's for suckers.
When you actually look at the certainty that you have that Databricks has a 3 to 5x from here, you're absolutely right.
When you think about opportunity cost of I can put my money here or here, risk adjusted and time adjusted, you could make a very coherent case that it is a better deal to put your money into a Databricks or, like a Kleiner Perkins did with Nantropic at 180 billion, that it is put your money into a much less certain Series B with a 7 to 10 year duration from there.
Yeah, or just, you know, a pre-seed deal at 60 post on a safe.
The Databricks seems like a better deal.
60 post?
It's quite cheap for it.
Quite cheap.
Honestly, it's getting worse.
Snowflakes up year to date 60%.
And we're seeing the re-acceleration of Databricks.
Do they just both grow into absolute monsters?
Can they peacefully coexist?
Do you think one takes majority market share?
I had Ron Gabrisco, their CRO, on our 20 sales podcast and he was like Databricks' technology is five years ahead, which I thought was a really interesting statement.
Do you think they peacefully coexist?
Does one take monopoly?
How does that look?
I mean, Ron was correct.
They came from slightly different places at slightly different times.
Snowflake originally was very much your SQL data warehouse in the cloud.
It was a few years earlier than Databricks, which was originally, I think, the Kafka product, and all about moving data and more AI use cases, even out of the gate.
So he is correct in that.
I mean, no one's going to coexist peacefully.
They probably hate each other.
In fact, we know they hate each other because they time their sales events to overlap with each other.
I would say differently, they're not going to, quote unquote, peacefully coexist.
They're going to struggle and fight against each other for the next 10 years, just like SAP and Oracle fought against each other for the last 20.
They're going to eat each other's lunch, and it's going to be a grind.
I don't think anything folds from here.
It's hard to imagine the core value of relational database isn't going away for transactions.
So the snowflake asset is money good.
And then separately, I think Ron is correct.
Databricks has more of an advantage in brand new AI-centric data manipulation, data movement applications.
So both are in good adjacent overlapping markets.
They want a bit of each other's market.
They're just going to slug it out.
It probably means at some point that some of those margins get dinged a little bit.
But you've seen it before.
You've seen it, as I say, with Oracle, Sybase, and Informix.
You've seen it with Workday, SAP, and Oracle.
This is just what most enterprise software markets tend to be oligopolies, and they tend to punch each other for 10 years.
In our little corner of the world.
That is, scale-ups and startups vis-a-vis Snowflake.
The one thing I do know is we're just starting to learn what we can do with our data, with agents.
And even Snowflake is still learning.
When we had the CEO of Snowflake at Sastra Annual in May just starting to talk about how they were going to use agents right.
And now fast forward to today.
It's a couple months later.
All the Vibe platforms now can directly access Snowflake data.
Yeah.
Like literally, we could fire up our cursor lovable replet and just build an app right now, while we're here and access our Salesforce data.
What will that mean to access that data?
What will that mean for how we think about CRM, how we think about where we host and how we access it?
Like I'm just not smart enough to even predict what that means in a year, because that wasn't even possible a couple of weeks ago.
Now, can you access every bit of data in Snowflake or Databricks in a Fortune 500 company?
I assume the answer is no, but that is an epic change that I can't even predict the slope of the curve next year.
Right.
And so what happens?
I know we overuse this word agentic.
But what happens when I can use easy to use agents where I don't need a lot of engineers to access all of my data any way?
I want to build any report, any analytics, any workflow from that.
I think we're 1 on this journey, but the amount that will empower our data with agents, we were just learning.
If I were to push you honestly and ask the question of will we see our CRMs, your Salesforce, your HubSpots?
Will they become databases which agents sit on top of and feed off?
Or will these platforms move with the agentic world, build their own and not become sheer databases alone?
Which one is the likely outcome?
I think the fact that Mark Benioff has put 2000 people on AgentForce tells you the future right there.
He's already got 2,000 people on it.
It tells you his intentions.
It doesn't tell you his ability.
We are still early in a lot of enterprises.
And I think Salesforce in particular.
They've got two years to unlock all this capability.
I think with the rate of change.
It's just because two years is not a lot of time at Salesforce.
Mm-hmm.
Traditionally, that's a major release.
Snowflake turned out to have time.
We might have thought Snowflake was struggling at the start of the year.
There is more time in the older enterprises.
Where that breaks for those that have massive amounts of data, I am not smart enough to predict.
I would not bet against anyone that is managing a huge amount of structured and unstructured data.
I wouldn't bet against anyone.
What will probably happen is, if you want to build agents that are just using your CRM data and your Salesforce shop, just like a Microsoft was able to bundle Microsoft products, you'll probably take the agent from Salesforce and get a combined thing.
But I think, and to Jason's point, I think enterprises want to build more powerful agents.
We're not just drawing the data from one app by Salesforce, but drawing the data from maybe five or six different sources.
The more likely architecture for that is some version of stuff it all in Snowflake and then run an agent directly against that.
And I think as you were talking Jason, earlier about what you're saying with Snowflake, I remember one of the things we did five or six years ago that turned out in retrospectively very smart is just literally automating to stuff all the data in Snowflake across all the systems.
So over time, you have access to that.
So if I'm a large enterprise and I want to use my internal let's say I'm a bank I want to use my deposit system plus my Salesforce system, plus something else at a certain size.
It won't work easily in just a Salesforce.
So you'll want to go just like every large enterprise since the dawn of time.
Some apps you'll want to build yourself.
And if agents become strategically important enough for super big companies, then they'll throw 5 million and a bunch of snowflake, data breaks and just build it themselves.
So there's no doubt that agent force can get a fair slug of the market.
But I'm also sure that at the high end there'll be a bunch of wonderfully bespoke projects that will make systems integrators rich for the next decade.
Another thing that I just.
Everything we're doing right now in AI is very exciting, but I've been thinking a lot about how Gainsight's been locked out of Salesforce two weeks.
I've been thinking a lot about how OpenAI just kicked Nick's panel this week permanently off OpenAI for security breach.
I really think that, with agents running everywhere with our data, the folks that can securely manage those data and the folks that have secure agents or seemingly secure agents, They may win.
We're willing to bend some rules in the age of AI.
We're willing to bend some rules to move quickly.
I think security is going to benefit the incumbents.
I think we're going to be worried that our agents are depositing our data in 100 different places and are going to be worried.
And it's crazy.
I mean I love Nick and the Gainsight team but essentially their app has been down for two weeks with no known resolution time, but Salesforce has kicked them off the platform.
They kicked Drift off five months ago.
Drift will never come back.
It is dead.
It is completely dead.
And so I think about those and I think about where all these agents are taking our data.
I might want my agents from Salesforce and Snowflake and Databricks.
When things change, we get very excited about new vendors because the incumbents can't do it.
We get very excited.
And inherently, we take a little bit of risk.
And we try and contain that risk in a pilot or in a less critical source of data.
We always try to measure the risk at the beginning.
But I wonder, this is our sensitive data flowing.
And it may not matter for your average startup, but I generally am worried we're underestimating security and data residency in general.
I just worry.
And I feel bad, but I just couldn't imagine going through this at Gainsight.
Do you think the world and big companies are more unforgiving now?
Because over the last 10 or 15 years, a lot of companies have had breaches.
Do you think this was more serious?
It is more serious.
So Drift had the security breach.
700 folks' data were downloaded.
And now a pirate group is asking for millions of dollars for each instance.
And then this happens again.
With Gainsight.
I can't speak for Salesforce or the team.
I mean 45 billion, but I would be more conservative with who I let touch my data.
We could say it's an OAuth issue or whatever, but man, I don't want this ever happening again.
One time we can blame Drift, because it got acquired by another PE firm.
That got acquired by another PE firm.
But two times I might start locking down my platform.
The third time I might say, I'm just going to own all the agents.
I'm done with these risks.
I don't know, but it's getting worse.
When people want to steal your data and ransom you for a million dollars across 700 orgs, including Cloudflare?
How big is the SecOps team on most startups you work with?
50?
100?
How big is the latest deal you did?
How big is the security team?
The funny thing is Jason, both the examples you cited are mature first and second generation SaaS companies, not brand new AI first companies.
So what you're saying is new companies might get tagged with the consequence of a more restrictive security policy, even though you could argue it was older companies that I think in both cases were PE managed that actually caused the problem, which is life is unfair.
But there you go.
In AI, probably just before we started doing this, it kind of felt like the enterprise was going to win that ServiceNow and everybody was going to win, and then it doesn't feel like that at all.
Then we saw the numbers take off, and basically very few incumbents grew this year materially.
This could be a piece of the revenge of the enterprise.
Are you cynically suggesting that large enterprise software company could say I'm using security as an excuse to cut you all off, but lo and behold, I have my own agent product right here which you can now safely buy, Mr Customer.
I think it's a good excuse.
I think if you don't want Glean slurping all your data right, which you know, if I'm Glean, I get it.
If I don't want all of it going out of Slack or whatever I mean many incumbents I think it's the best excuse there is.
The existential risk is just too much to the vendor.
It's not worth it.
I don't know how many board meetings you guys have been in where the first half of this presentation was how we're going to be more secure in the age of AI.
But for me, it's been close to zero.
Yeah.
So we spoke about Databricks' growth.
I do just want to take the flip side of that, which is a less positive or optimistic side.
PagerDuty, 2x, a billion valuation at 500 million ARR, 4% growth.
We just saw, literally, it's not on the schedule.
So this is where Rory gets nuts at me, because I just add shit without asking him and then expect him on a whim to come up with something.
And normally we can edit out pauses, but now he's going to be extra pissed with me.
Welcome to my life.
Eventbrite, they've been acquired for like 500 million?
Yeah, that's the premium, right?
Yeah, so that's 1.5 times revenue.
1.5 times revenue.
With a 50% premium.
With a 50% premium.
So new news in today.
And we can take the page Judy, because it's so fresh having that Eventbrite news that it is hard to ask for such immediate thoughts.
But how do we think about this very harsh new reality, given the lack of growth and the subsequent pricing from it?
I'll surprise you, Harry.
I'll cover both despite the complete lack of notice.
I think there's two separate things, and one perhaps is a positive.
One is a fact about being public.
When you're public and your stock is floating around nowhere at a low valuation, you're just very vulnerable to this.
Someone comes into view, and you're not growing quickly.
They offer you a 50% premium, and you get called in, but your board gets called in.
The lawyer gives you the speech about fiduciary duties.
And if you can't come up with a convincing reason why you can build better value than that premium, you're very forced to take it.
It's a tough place to be.
So I can imagine the conversation at Eventbrite.
I can imagine the conversation two weeks ago at SEMrush.
And I'm sure Page of Duty are thinking about the same thing.
Two things to say, though, at a wider level.
The first is, let's start with the positive.
Someone else, very smart money, thinks these things are worth buying.
And I think they're looking at it and saying you, Mr Seller, haven't created value here, haven't found growth, and I think we can.
And if you look at the three companies we're talking about because let's lump in SEMrush because they were acquired two weeks ago by Adobe
And Jason and I disagreed, but we definitely felt someone like Adobe could do something with that asset.
I'm not sure what the direction Eventbrite could take, but I think and you said it in your notes Harry PagerDuty has an obvious set of next products, including AI-agentic products around downtime resolution that feel obvious to me.
And frankly, I wouldn't be surprised if an aggressive PE firm said, oh, my gosh.
I can buy this thing.
I can then buy some small little hot AI startup, put them together and get this thing back to 20 growth value the 10 times and look like a hero.
So the positive would be other people smart, savvy money look at these assets and say two times revenue is stupidly cheap.
I'll have that.
I hope so.
I hope there's more deals.
We see General Catalyst and others doing this, let's add AI to services businesses.
We see a lot of talk of this, but right now we're not seeing a lot of these mashed together legacy company at hundreds of millions and B2B and hot AI startups and magically flipping it into a 20X, 15X era company.
I'm not saying it's not coming, but we haven't seen pagerdutycom and pagerdutyai magically mashed together into a winner yet, have we.
No, it happened.
And you're right, Jason.
But the funny thing is, I like PagerDuty.
We looked at the deal 10 years ago.
My then new partner wrote a term sheet.
We should have let him pay a little more because he was right.
We love that market.
And I remember the investment memo from 10 years ago.
And it said clearly, summary, this is a great market.
It's going to tap out.
And you have to add a whole series of add-on products around managing the process of downtime or security breaches, managing the process of getting something back up.
And we didn't have it at the time, but now, obviously, adding AI-enabled operational resolution.
The direction was clear and is clear.
So you're right, Jason, they haven't done it.
But I think that that's just a disappointing outcome, let's just say, right?
I think that the direction of travel should have been clear.
And if you'd been able to add it, I think you know we talk a lot about how distribution is a huge advantage in software.
I mean, literally every ops team on the planet uses pager duty.
For God's sakes, it's pretty obvious what to add here, people.
Get it done.
Roy, as your views, and Jason too, if your views on market size changed as an investor, given what you just said.
Every ops team on the planet uses PagerDuty and it's a billion valuation 10 holding be 100 million back.
It's just a very sobering reality.
Has your view on market size changed when investing today, given where else you can put your money and the sizes of those markets that we're seeing with your lovables and your replas?
I see more and more folks who I thought would grow out of a small TAM, not grow out enough.
When I started as a B2B founder quite a while ago, everyone seemed to grow out of small TAMs for the most part, some better than others.
But it felt like we had time and it felt like you had four or five years to figure it out at each stage and you could see it coming.
And now that the average public SaaS company is growing like 16, it feels like no one figured this out.
We've never grown more slowly, right?
We literally, just in my presentation before, we looked at this chart.
No one's ever grown this slowly.
So if the public guys can't figure this out, I mean I know the next generation of the kids should do better than the adults, but I'm worried that the majority of the public SaaS companies didn't figure this out.
The majority of the public SaaS companies, I think, are in a TAM trap.
A TAM trap.
It's a good title for the book.
The TAM trap?
The TAM trap.
The TAM trap.
How did the Aaron Levy's and the Drew Houston's and the others not figure out?
And I love them right.
I love Aaron.
How did we not all figure out the TAM trap?
What hope is there for the rest of us?
I can give you a clear answer on that.
First of all, I think it's a great kind of division of the discussion into the TAM trap for the existings.
And then what does it mean for the new AI companies?
And then maybe third, what does it mean for venture?
But let's start on the first one, the SaaS TAM trap.
You keep saying, Jason, how did they not figure it out?
Let me just offer a different perspective.
Maybe there's no answer.
In other words, there's so many SaaS companies.
It's not that everyone was idiots and couldn't find the market.
I don't believe that at all.
I believe that we made so many companies that we saturated the markets.
And by the time you got to the point where you needed to expand beyond your market, in many cases there were other venture-backed SaaS companies in the adjacent market.
So you just kind of ran out of room.
I did a blog post on this in 2019 called Hunger Games and SaaS.
Many of these markets, it's not that some of the CEOs you cite are idiots.
It's that you have high penetration of the markets.
Take the quintessential one you and I talk about all the time, Jason, Zoom.
Everyone who needed a Zoom account has one.
And everyone who has a Zoom account has a team account, the poor bastards.
And they're done.
There's nothing more to sell.
You got to build a new thing.
And the initial quote unquote obvious new thing for Zoom pre-AI was that whole contact center business.
And they couldn't get that acquisition done.
And there was already incumbents in the space.
So I think pre-AI, you ran out of TAM.
So Harry, to your question, as we've said many times, overpayment only works when the TAM is huge.
In finite TAMs, you got a bit more tightly.
It's so funny.
I'm going to anecdote about PagerDuty.
When they went public and we did our internal autopsy because you do I looked at the model we'd underwritten five, six years ago and we were accurate within 3 on the model prediction of revenues.
And all that happened was the market was just willing to pay more for the asset.
And now it's not.
So I think on the existing space, it's the time constraint.
And I think you just have to be careful on price.
Now the question on the new markets, which I think is believable, incredible is does the AI labor expansion save us all and allow us to reach higher on price and still get these huge TAMs?
Or are we going to be in the same place eight years from now?
That's the actually multi-trillion dollar question as a Well, I think there's two.
One is, can AI allow us to tap more into labor budget, right?
I think the second one and I was trying to summarize this earlier today is can AI provide so much value that you can charge an order of magnitude more than you could charge before?
Gamma charging $100 a month instead of, I only pay $8 for Canva, right?
Or Cursor charging $500 a month when I pay $3 for Jira, right?
So you wonder, can we do that?
And, you know, we don't talk about Zoom much.
When I think about Zoom, I can't think of like a better technical founder running a leader than Zoom.
I can't figure out someone I respect more on every level as a human, as an engineer, as a leader than Eric.
There's a mean question and I don't deserve to even ask it, because you talk about why didn't they capture more TAM?
Why didn't they find a way to add 4 billion of note takers when there's a trillion note takers?
Why didn't they?
And I don't know the answer.
It's not because you're not one of the smartest people in the industry thinking about this for a decade, but there was no great second act yet.
I do, going back to here, I worry.
I worry and this is why I tell founders to take their exits and then say no because they can go bigger, but by default, take it.
So many things in that to unpack.
One is the multi-product thing.
I think one of the big takeaways we've had is the need to be thinking about that second product much earlier than you would have thought.
Wait till you hit.
What was the word expression?
I loved it.
It was good, but I'm forgetting what did we call it?
Well, the TAM trap.
The TAM trap.
TAM trap.
Don't wait till you hit the TAM trap.
I mean, we were thinking, actually, we were comparing two of our portfolio companies.
We would say one of them has compounded really well because it's continually added a new product that for the first year or two is a couple of million dollars, but layered it in and now many hundreds of millions.
So I think watching that TAM trap is key.
But the other thing you said and it was in the speaker notes too is on the AI pricing.
If you're pricing versus labor of value created, you're getting enormously great prices because you're saving a lot of labor.
And I think you said on the speaker notes what happens when there's two or three of these companies and the competition goes from hey, I'm saving you 1000 of labor a month to yeah, I'm saving 1000 of labor, but there's three providers of the same software AI software and they're all willing to do it for 100.
So your ability to get $500 gets eroded.
And do you start seeing that happen in AI very quickly?
Is it super clever?
I mean, it hasn't yet, I think.
Speaking of the pricing challenges that we have here, we have Workday coming out saying seat reductions are an existential threat.
We had Jeff Lawson from Twilio on the show with the three of us and he said that we are unwaveringly going to see the movement away from seats and that is going to happen.
Can companies still price by seat in the age of AI?
Our Workday inherently is threatened and right to be concerned by this existential threat.
You know, when Jeff, if folks haven't watched it, it's worth rewatching.
He was so good, right?
And he made that comment that Twilio, especially if he were still CEO, would have maybe somewhat insulated to that because it's based on usage right.
And in fact, Twilio has seen a little bit of a resurgence.
It has seen some reacceleration.
And he said he was very worried about seats.
But he said I hadn't been in the game in a little while and I've been doing AI and working in my shop.
It has resonated in my mind since, which is he is right.
And everyone is shrinking headcount in tech.
At least, even if they're not shrinking headcount, ARR per employee is going to keep going up.
I crunched all the data before this morning.
Everyone is going up.
HubSpot, 2.8 times more efficient than 2021.
Salesforce, two times.
Microsoft has said they're already past peak employee, permanently past peak employee.
We're all going to figure out how to get more AIR per employee.
And if you're a leader, you're just going to run out of seats, right?
Mark was kind of aware of this when he did the pod too.
So I don't have the answers.
I mean, in the early days, it probably doesn't matter, right?
I mean, your model is your model and seats work well in some places, but it is existential.
We are just going to get more and more efficient.
One of my biggest worries for investments is when startups aren't getting more efficient.
I'm not talking about profitability.
That's an investment.
I'm talking about where their teams get more bloated as they scale.
I kind of am out.
When I go to a board meeting and a CMO says, well, I could do that, but I need 50 people.
Or a product guy says the reason we're late is I need another 80 people on the product and engineering team.
I think it's time to part ways.
Give them a nice package and a good recommendation.
Jason's saying, can we get AI to replace you?
I want to see you grow 100% next year with 50% headcount growth.
I think that's healthy today.
The way through early 2023 is I need a 200% head count to grow 100%.
And there's still a lot of that DNA in the ecosystem.
It's still ricocheting around, probably in the majority of executives people will talk to.
It's still ricocheting around.
So I think all these things, just I don't think the seed is dead.
But as time goes by I get more and more worried that it feels like Japan, like our population is organically shrinking.
SaaS has become like Japan.
Yeah.
It's a great economy, but if everyone only has 0.9 kids, there's only so many seats to go around.
So Harry, first of all, my camera is right in front of your smiling face.
So I literally have not seen you.
So I'm going to slide the camera.
Oh, there he is.
Is it still okay on your side?
Because I just miss seeing you, Harry.
You miss seeing me?
Yeah, no.
That's sweet.
How does Rory moving his computer change how he sees things?
Am I missing something in AI video technology?
Doesn't the camera have to move?
Don't be a smartass, Jason.
I'm not being a smartass.
Air is with me.
I don't understand.
I was expecting him to, like, something to change, and then it's like, Rory's moving.
No, no, I'm moving back there.
Gotcha.
I'm assuming it's working and we're continuing.
I want to come back to the last comment first almost, your comment on two to one.
And you're exactly right.
As I think about it, I hadn't thought it until you said it, but in 2021, every discussion was some version of look to get that extra 10 points of growth.
We're going to be twice as inefficient at the margin as we were overall.
And the result of that is overall efficiency has deteriorated.
What you're saying now is at the margin.
We're trying to be twice as efficient, not inefficient at the margin.
So you're exactly right.
Everyone's efficiency is creeping up.
And I think that's obviously independently, that's totally correct.
And super insightful when you said it.
It's why and, by the way, it might explain why, even though the growth rates of the public companies have gone down significantly, the valuations and the revenue multiples have not gone down as much.
And I think it's because, in return for slower growth, fast companies they are at least getting wildly more efficient, fast companies.
And it's not one for one, as we've discussed, but at least it's better than nothing.
But then going back to the existential threat from Workday, I think software prices on value delivered.
And when you couldn't measure value, all you had was perceived pricing.
And therefore, that's what people went with.
Everyone has to access the software.
Everyone pays so much.
Then you had usage pricing, starting with AWS, which was inherently a more rational for buyer and seller way to allocate value, attract value more closely.
And I think the trend in everything is just to get more efficient.
I think that's how capitalism works.
To the point of if you're using AI to deliver value and if the AI is doing the work, it's going to be super hard to have a per seat model, because it's irrelevant.
Now, I don't think for a lot of Workday, it will be as irrelevant as for some.
There are other areas like, for example, some areas of Salesforce.
You can imagine to the extent you entirely automate an SDR team.
It's going to be hard to have a perceived SDR model.
My guess is Workday will still be able to have some kind of X dollars per month for end employees served and then Y dollars per month for HR staff actually using the software, but there probably will be less HR staff using the software.
To your point Jason, because if half the make work that HR was doing is now done by AI, you're not going to get the same price.
So therefore, maybe you have to charge on the value delivered versus simply the seats.
And that's a more complex calculation.
And I think that is true, is that all our companies are wrestling with this.
You deliver a ton of value in AI, and maybe now you get the innovation budget, no one cares.
But a year, two years from now, you're going to have to link, as a startup, your pricing to the value delivered and you're going to have to measure.
And it's a lot harder to measure value than seats.
You can count butts and seats pretty easily.
Every login is a butt.
When you're trying to measure value delivered, that's tricky.
Can we just go back to the growth and efficiency element?
Because I always think when you're creating content, you have to think of your customer.
And the customer that I always have in my head is the founder on their way to work or the operator on their way to work, listening to our podcast or watching it.
And they're hearing, I want growth, growth, growth.
And now they're hearing, I also want efficiency, efficiency, efficiency.
And 2 million per employee for gamma and lovable at whatever it is.
Do we just need both now?
And it is a higher expectation to meet the bar for VCs.
Or when you are looking at those two.
I want growth above everything, and I'm fine to see less efficiency in the early days.
I think, in the fastest growing companies that I've invested in, no one gives a rat's ass about the bottom line.
That's a different metric than how you scale today, right?
And Rory made this point, there's actually fewer and fewer companies are true outperformers.
So as soon as your top portfolio company that performs, everyone wants to give it 100 million today at every board meeting.
And no one really cares about efficiency per se, as long as they can get their money into the deal.
So I don't think that's the issue.
I think we're confusing the fact that everybody is just generating more revenue per employee.
But you're going to this we've talked about before going to like this, the iconic data early in the year the fastest growing AI companies, even with high inference costs, even with high AI costs, have the lowest burn multiples because their revenue is growing so much faster than the inference costs.
I think that's what we're hoping for is that companies have never gotten to a hundred million ARR more quickly.
If you do, I don't think we care how you get there anymore.
I don't think that we care.
But we know deep down that hiring a thousand people isn't the way to get to a hundred million in a year.
You can't hire them that quickly.
As Maggie said, they're not all gonna be great.
So you literally can't brute force 100 million in 10 months with humans.
It's just maybe Larry Ellison or Mark Benioff could, but I don't think anyone else.
There's just not enough calls.
You can't go from one to 110 months without massive inbound demand and a lot of AI.
Yeah.
I think you should break it up in a couple of areas.
And, in fact, as we think about it Jason, it's given me an insight on your eternal question on employment.
Because big picture, divide it up into AI startups and mature companies.
The comment on ARR, efficiency per ARR, is very much a mature company comment.
If you're a public company and you're only growing 10 or 15, you better be kicking off cash or you'll be in trouble real quickly.
Even if you are kicking off cash, you'll still get grief.
But those are the companies that are optimizing their ARR per employee and are just focused on FCF free cash flow.
And that's a very different set of people with a very different set of dynamics than the AI startup.
So we'll come to them in a second.
So public companies grinding on efficiency, which means, as you say, lower employment and all that stuff.
Now come to the private AI companies.
I think there's two categories.
A small number of companies which are taking huge amounts of capital because they need it for model development.
And primarily, it's not humans.
They've got to spend it with Nvidia.
So look, no one's telling open AI be efficient, or if they are, he's clearly not listening.
To a rounding error.
Those companies, as Jason said, able to get all the money they want, spend it on compute, have relatively small headcount relative to their size.
And no one's saying be efficient.
They're just saying grow quickly.
Then separately, at the apps layer, you're seeing something slightly different.
And Gamma is a good example of that.
The interesting thing is, because of this amazing new capability for lack of a better word called the foundation models, there are people in apps land, building a product, shipping it, and they're getting such traction that the traction is ahead of their ability to hire.
I mean, there's no way to spend the money, right?
So we're seeing some of these apps companies be astonishingly capital efficient, especially at the early stages.
Gamma is a great example of that.
It's like you ship the product, it's freaking amazing, people buy it, they give you credit cards.
By the time you get around to hiring a sales force, you're doing so much money already that you're kicking off cash.
At the apps level.
Not all the time.
I think some companies at scale are spending, but we're seeing the combination of hyper growth, even reasonable margins, not as good as Fastland, but still 60.
If you have that, then you have quite attractive profile.
Not all of them are that case.
Obviously, the coding companies have margin issues.
But a lot of the companies are getting a long way and not a lot of capital and definitely not a lot of employees.
So I think those are the three categories.
And the interesting thing Jason, this goes back to something you've been talking about and I've been trying to figure out the answer to.
What's going on on employment?
What's the consequence?
And I've been more, it'll all be fine in the end.
And I still stand by that.
But the interesting thing, when I lifted those three categories, The one thing they all have in common is they all don't need people.
The big companies can't have people because they've got to be efficient.
The model companies don't need people because they just need geniuses and GPU.
And the small AI app startups are growing so damn quickly they can't hire people.
That's not great if you're people.
And overall, I'm an AI optimist.
I think all this unemployment thing is bullshit.
But in the near in what you recognize.
It's why it's a toughish market for employees in the tech marketplace.
Because labor versus capital discussion is, you need more capital relative to labor at the moment.
The topic we have to discuss.
We talk about rapid the whole time.
But then Google have come out with a competitor.
I think we've always been waiting for Google and ChatGPT to come out with one.
And it's been very good.
It's tied to Gemini, which is obviously blown past a lot of people's expectations.
When we look at this, how did we analyze this?
And is this a case of incumbent waiting for enough traction in a market and then going?
Thank you very much, Mr Startup.
I'm going to come in now with great models and distribution. and it's game over?
Or actually have they left it too late and Lovable Replit have built enough user base, enough brand, enough brand trust that actually there is still a real dominant threat then to Google's new product with it.
Well, look, for what it's worth, you know, I did try it.
They launched this week.
They launched a Replit Lovable clone with no database, no OAuth.
They said it's coming soon.
And sometimes that's okay for big companies.
So we'll see.
We'll see if One thing that hasn't changed in the age of AI is big companies only have so many priorities.
They can introduce a lot of little tests.
But at the end of the day it takes a lot of energy in a big company to keep a big initiative going because there's so much else to support.
So we'll see.
It wasn't impressive on itself.
But on the other hand, Google launched their competitor in less than 10 months.
So you don't get five years anymore.
I mean, Datadog just launched their PagerDuty competitor like in the last 24 months.
Windows PagerDuty founded 2008.
You don't get that much.
Now you don't even get a year.
The incessant pace of cloning and competition does worry me.
Man, if you only get months before the big guys come into your space, if you blow up, I mean it should make sense, right?
If you go from zero to 200 million in a year, you should attract some competition.
It's not a free lunch, right?
But is there something that we take from this?
Like Rory just did, you did a GCAI, I think it is.
Like where we're like okay, they're not going to go into GCAI, but they are going to go into lovable.
They are going to go into Decagon.
They are going to go here.
There's themes where they're like, they are going to go.
And there's themes where we're like, hey, model providers.
The core question being hey, where will model providers go in the application layer and threaten our businesses?
This is, I mean, competing with coding tools is not that big of a jump right with, whatever happens.
Rory did a deal, I think, in the last week, or scaled it.
I really liked personally, even though I didn't examine it.
You did sort of an AI for like wealth management or asset management, right?
I love this for a lot of reasons.
I have some questions, but Google isn't gonna copy that.
They're not gonna copy automating trusts, estate planning, investment advice, tax efficiency, your investment, legacy planning, or maybe it doesn't do all of that, the investment.
Those are spaces where you have incumbents, but maybe you have some space to run, right?
Agreed.
The model provider is not the constraint there.
And I, for the record, would say I don't think the model provider will be the competition in many apps.
And going back to where I started, I think the OpenAI Code Red this morning was frankly tantamount to an admission that we need to do our core mission for the next year, and probably less foots and around in other things.
I mean, that sound you might hear is the consumer hardware product slipping out a little.
So I do believe that more of these apps are defensible.
I think the model providers will be there.
I think coding is obvious.
But even when you get much beyond that, I think if I was on the board of OpenAI it would be like when the chat GPT wars and you are worth 2 trillion.
Let's not fuss around with little vertical markets that can be worth a couple of hundred million bucks.
Why are you even talking about this, especially when everybody poked Paul at Google and Microsoft said we'll make them dance.
OpenAI kind of laughed at them and now they're poking back and you put all your effort behind that.
I think we may have seen peak, the models are going to do everything.
I mean they're going to do coding, but I don't know if they're going to expand into all these verticals at that level.
And then, yeah, thank you, Jason.
On the range wealth management.
I think the interesting comment and again, we're always low to just push our investments.
But I think the big picture story there is can you use AI not just sell software to wealth managers, but automate the business of wealth management?
And this is the key sentence that I like, because I hate the word wealth management.
The idea is you can go much further down the wealth continuum and give the same kind of product that the super rich get in terms of managing your stuff, managing your taxes, which is how he knows in the UK, are now north of 50 and getting higher.
So you want to be able to manage your affairs, file your taxes.
And there's a whole ton of that work that's done expensively with humans.
That can be done really cheaply with AI, because it really is just follow the law, fill in the forms, do the work.
And hopefully the idea there is you automate a lot of that and then you can deliver a high quality product to a much broader marketplace.
And one of the big picture things I think that's always true in investing is whenever you see a product that only really rich people have, if you can find a way to get that in the hands of the rest of us, we all want it too.
Just on, what do we call it?
The terrible TAM?
The TAM track.
On the wealth management, what's the vendor called?
Sorry, I should know.
Range.
Range.
I love it.
I get the problem.
Anyone's lived it that has gone through any of this stuff.
We could talk about it.
But I think you do have to be smart about the TAM, right?
Because they're going to charge eight to 10 grand for something that you pay a bunch of numbnuts now, 30, 40, 50 grand a year if you're wealthy, right?
Maybe more.
But it's not 10 times the price of the existing product.
You just got to be smart because...
You can pretend everyone in the world will pay you 10 grand, but you also have to be rational to not have a TAM trap right.
Because Wealthfront's trying to go public, right?
In theory, maybe it's a comp.
In theory, Wealthfront should be a $10 trillion company.
I mean, everyone could use this product, right?
But in reality, there is some TAM limitation for Wealthfront.
I totally agree.
And it's all about segmentation.
I love Wealthfront, as a comment here.
The Wealthfront and Betterment, I really love those companies.
Because again, it's back to the same thing.
I get uncomfortable in the wealth discussion because who gives a damn what the ultra wealthy have to deal with?
What I love about Wealthfront, what I like about these is Wealthfront was saying even paying 50, 70 bps to someone to manage your money is crazy because we can just put it in this automatic thing and do it automatically, and for 10 bits.
And the thing about those business year TAM comment is they actually take a long time to build because the whole value properties is we're charging you less and you just get to compound more.
But in the end, they're lovely businesses.
And we looked at actually not Wealthfront but Betterment 10 years ago and we figured it would take about this long 10 years to just build.
Because remember, if you're charging 1% of assets A billion is a lot of money.
If you're only charging one-tenth of that, you need 10 billion to get to the same place.
If you're targeting people with less money, by definition, it takes longer.
These businesses take a long time to build, but I think when they do they're way more powerful than some quote-unquote wealth manager.
That's really good, because he takes you golfing and gives you a PowerPoint once a quarter about how badly your money is doing, and they're really sorry.
Or even better, they ask me if I want exposure to private equity and venture.
That's the main value I get from Morgan Stanley.
Hey, Jason, it's your advisor this quarter.
I can get you into a hot venture fund you've never heard of.
Stebbings Lemkin 4.
The returns are negative at the moment, but it's a lengthy J curve and it's a hot.
It's a three and 30.
Triple layered SPV.
Have you ever looked at my account?
Do you know anything about me?
Okay.
I didn't actually, sorry.
I didn't mean to be divisive.
I didn't like this deal.
I saw this and I thought, Ooh, gosh, sorry.
I didn't see it.
Why don't you like it?
What big business and what good business like really big has been built in the wealth management space.
Wealthfront?
Merlin.
Just pause, pause, pause, pause, pause, pause, pause, pause, pause.
Okay, one, very old, but we're looking at Wealthfront.
What, 17 years?
Index and every good investor in there.
How big is that? in the opportunity cost world that we live in.
But you have to really... The real question is, why does... Okay, listen, there's a gap.
There's the wealth front and Vanguard at the bottom.
I want to hear Rory's thoughts.
And then there's the world's crappiest product, which are Goldman Sachs and Morgan Stanley, which take 1 of your assets and do nothing.
I can see other than give you loans, which are very valuable.
For folks that don't know.
Literally.
If you're sitting on 50 million of Nvidia stock right now, you can sell it and pay 25 million in tax or a bank will give you a loan.
Now, it's not cheap today.
It's 6%, but that's a lot better than 50% if you can deploy.
That's the only product I know.
They'll tell you they'll help you with your trusts.
They don't.
They refer you to someone that doesn't call you back.
They'll tell you to help with your taxes and they'll tell you we're not allowed to talk about taxes.
So they can't really do anything except give you a loan.
There is such a gap in the middle if AI can do estate planning, taxes, all this.
So Murray challenged me if I'm wrong.
The question is, if AI enables it, then something that was shitty, Darius Point, might become great, if AI lets you do it right.
It might become great.
This episode was brought to you by Goldman Sachs Wealth Management.
That's exactly right.
First of all, you just nailed it.
That's exactly the value proposition.
Yeah, I like it.
You deliver trust, you deliver estate, you deliver taxes.
Because when you file your taxes, the fact that you do your estate with one person, you do your taxes with another person, you wealth management with a third one is absurd.
It should all be under one roof.
But I want to go back to your comment, Harry, on Wealthfront.
Because again, I'm always uneasy just pushing our company.
So let's talk about, I think, an excellent company that's not ours.
Yes, it's taken a long time to compound to here.
But not everything is a tech first where the adoption cycles are five years.
I think when you launch an investment in a company like Wealthfront, the adoption cycle of something like that is going to be 10 or 15 years.
So in my view, it's just on track.
And the financials are lovely because at scale, Asset management is a wonderful business.
They are providing a cheaper product than anyone else at 10 bps.
And they've lined up a bunch of millennial and whatever the generation a little bit older, 30-year-old and 40-year-olds.
And over the next 10 or 15 years, that generation is going to get rich.
They're going to get rich with Wealthfront.
They're going to keep their money there.
And it's going to be a compounding machine, just like Charlie Schwab was a compounding machine when they started in the 70s with cheap brokerage.
It took a long time.
They went through a lot of it.
They actually were owned by BFA and then spun out in the 90s.
I was there.
But in the end it just compounds, because you just over time.
The only good thing is it does compound.
And early on.
Wealth management in any form is a tough business because it takes a long time to build.
But when it does build and Wealthfront is over that gap now it's going to be there for the next 30 years in frankly, a way that a lot of your tech companies want.
I get you on the compounding machine and I share your view in the beauty of those businesses.
But actually you're competing for dollars against the same people like your Kleiner Perkins or like your Andreessen Horowitz, where LPs can put money in their funds or your funds at a B and C stage.
And they are in Glean and they are in Replit and they are in the races to 100 million in Fasten.
We've ever seen, and those LPs will be going wow, Those funds, they're more exciting.
And you're going, oh, but it's compounding.
It's Charles Schwab 2 is coming.
I promise you.
Watch the pod.
I don't know that that's 100% true though, Harry.
I think it's 80% true, right?
I think if you're going in to raise capital for your fund and you're being compared to Glean and everything else, I think as long as you have the numbers, actually LPs are kind of excited if you have a slightly different way to get there.
Slightly.
But you've got to have top 10% numbers.
Do you think so?
If you've got companies that are kind of and actually to your point and to our point on, like hey bluntly, growth rates are so much higher, growth expectations are so much higher.
If it is a slower compounder, the next round is less certain than ever.
It's less guaranteed.
Yeah, but LPs are looking backwards.
If you're sitting on multiple high-performing funds, you're going to get a fair amount of flexibility today, right?
I think the point is that it's hard to not be seduced by the hottest deals today.
And by the way, LPs love to see great fall on investors.
Well, Sequoia came into this and Andreessen.
I want to push back a little.
I do take on board your point.
And there's no doubt that the velocity of validation is super strong for AI companies right now.
If you want to do a deal with the highest probability of a step up in the next six to nine months.
You should do an AI company that's raised at a billion pre, because 40 of the unicorns in Q1 I said 23, last week one of my colleagues corrected me 40
40 of the unicorns that raised in Q1 as a unicorn for the first time have already had a follow-on round.
So I think, Harry, you're exactly right.
If you want to buy short-term momentum, that's a great place to play.
And it's not just short-term momentum.
It's also driven by great performance.
So yes, that's absolutely a good plug of what you're doing.
But in the end, the biggest uncertainty is not, can you get a markup?
That's nice.
The biggest uncertainty is, can you build a big company here or not?
And there's so few times when you can say I believe you can build a big company here that you shouldn't then screen out and say oh, I can build a big company, but it might take a little too long.
Because there's a rule in engineering that you're only as accurate as your least accurate variable.
In other words, if you have six or seven variables, that goes into something your accuracy is determined by the thing you know has the widest variance.
And if you have high certainty that something can be a company, that's the hard thing to do.
If you've got that and everything else, you can adjust for valuation, you can adjust for time, et cetera.
I would love to be in Wealthfront, for example.
I think it's just an awesome company.
And even if, again, I think that will compound and you'll hold it.
And 15, 20 years from now, and it's going to sound pejorative to AI.
It's not.
I love that space.
It's where I play most of the time.
Okay, let's do it this way, Harry.
I think Schwab went public in either 82 or 83.
It's public today.
It's worth $60, $80 billion.
Name me five tech companies that went public in 1983.
Dude, are you fucking kidding me?
I was born in 96.
But my point is this, tech companies, they come quick and most of them go quick.
Now, by the way, if I'd said 1986, you could have come back to me and said Microsoft, Oracle and Sun.
If I'd said, I think 82, you could have said Apple.
That's why I think I picked 83.
The point is, is that these singular different companies are a little like, you know, mid-annuals.
These companies that are off the beaten track and are just a different thing.
They often take longer to compound, but they end up with more empty space.
And as I say, Schwab has compounded for three or four decades and got you where you're in it.
But sorry, I didn't mean it.
I just think we're playing a relevance game.
And I think this is the honest truth about New Age Venture.
We're playing a relevance game where Ram praises four rounds in a year where media matters more than ever before.
Duh, all of us here and where you're like oh it's slow, compounding coming soon.
Play slow, buddy.
It's just a tougher game.
And I think LPs are seduced by incredible follow-on investors, quick up rounds, and numbers still.
I'd rather be playing that game than the, it's coming.
And you're right, Harry.
You shouldn't be playing that, provided you're also right about the underlying investments.
So if you play that game and you're wrong about the investments, then you'll just be the guy who did a lot of high-priced rounds in a deal that didn't work.
So I agree with you, but again, I go back to my comment.
When you have high certainty that a big company can be built here, you weight that more highly than everything else.
I think actually Peter Thiel as all intelligent venture commons.
When you go back long enough, you discover Peter Thiel made them already.
I think he said somewhere in his book something to the effect of all that matters is can you build a big company here?
And literally he said because it's so hard to find them, They have no other rules, because their perspective is once I filter for that, I can't have any bullshit rules on stage.
On sector
I just want big.
And it's what gave them the courage to do biotech, defense, and software.
We're not as brilliant as that obviously, but I think it's some version of that rule, which is, when you see a company that can be big and you see its tracking to be big, prioritize that over hype and FOMO.
Rory, can I be absolutely savage?
Do you have to be in that slow compounding?
Because there's two worlds in venture.
There's obvious and really, really competitive.
Insane growth, really, really obvious.
And then there's, I'm going to be smarter pick the compounder, see beauty where others don't.
Do you have to be here respectfully because you're sitting in the valley at Series B and you're against Andreessen, Founders Fund, Sequoia, and you can't beat them? to do both and you can do both.
I think again I'm going back to my comment is I'm not sitting here going?
I want to filter for X, Y or Z.
I want to filter for great companies.
Then I have to win them.
And you're right.
If you're identifying a great AI company in X Y, Z space, then you're going to find way more competition, which means either you'll lose or you'll win, and you'll pay the market price to win, which won't be cheap.
And that's one way to make money.
That's most of what we do.
But you can also go and look at space where you go.
Oh, I think this is interesting and differentiated.
And as long as I have the same conviction on the ultimate outcome, you can do both.
Again, it's back to the.
You're trying to apply a momentum and hotness rule and I'm trying to apply a will there be a big company in the end?
Rule.
And I get the interim consequences.
To be very clear, someone said it to me 20 years ago as an LP.
He said, there's no such thing as blue collar venture.
It was a brutal comment, but I think it's your point, Harry, right?
You see what I'm saying?
It's like there's no such thing as off-value, randomly non-cool stuff.
At the end of the day, we're building high-growth companies and you're not going to make it on value.
You're not trying to choose on value.
You're trying to choose on certainty of a big outcome.
For what it's worth.
It might be a fool's errand to invest in things that you're just very interested in, but I think there is an advantage to it.
And I'll tell you what I'm interested in for 26, 27.
This is why I like Rory's investment.
I know this sounds obvious, but AI for coding is great, but we didn't even figure that out.
Claude figured that out.
Cursa didn't figure this out.
Replit and Lovable and Bolt didn't figure it out.
I can tell you the story.
Claude figured it out.
Anthropic, the guys you know.
Once they quit OpenAI, they figured it out and everyone grafted on this, including Gamma.
What I like is the next generation.
Can AI take large markets like wealth management that don't work today?
Can AI really for real with cloud seven and everything utterly disrupt it?
And I think that can be huge.
And I'll give you an example.
Like I set up three trusts, okay?
The wealth management didn't help at all.
And then I went to the lawyers, okay?
And it took me 11 months to set up three trusts.
And I said, I'm really frustrated this took too long.
So this guy that's like a celebrated trust lawyer in Silicon Valley is like well, good news, most of my clients never even finished them.
I'm not saying momentum investment isn't the right thing today.
If you can come in with AI and magically take every single frustrating part.
How many Americans like I think the Wall Street Journal just said today, the average American retiring is like 18 million in cash and equity.
Okay,
If you can take all the friction out of that, All the friction out of retirement, wealth management, investing trust, redeploying QSBS and everything.
Because of AI, I think you could build a $20, $40, $50 billion company.
I would at least want to take the meeting because this is something that...
Okay listen, I'm just interested intellectually.
Can AI solve some of the biggest headaches that we see?
That maybe you don't see every day?
Maybe they're in environmental compliance.
Maybe they're in other things.
But it's at least worth the meeting to see if it can utterly disrupt how it's done.
I totally agree.
Jason, I totally agree.
And I really like the pitch here, which is it's not the ultra.
Well, they got a million people who'll flatter them and do their work for them and charge them a gazillion dollars.
It's the entrepreneur, it's the doctor, it's the dentist who's earning good coin because, we discussed earlier, dentists and doctors are well paid.
But their affairs are modestly complex, but they don't want to screw up the Roth IRA withdrawal.
They want to leave their house to the kids.
They don't want to have a big estate tax problem.
Those are the kind of things more complex than nothing, but not where you can spend 20 grand on a lawyer to fix it.
That I think that's a huge market.
I'm sure people in the UK know this, but in the US, unlike the UK, everyone has to file their own taxes, which is just one.
I mean, I paid taxes in Ireland, England and the States, so I know the different systems.
Everyone has to file this God awful tax return every year.
And the minute your affairs get even mildly complex.
You do a rental property, you have a distribution, you have a capital gain because an investment you made in a restaurant, Suddenly your tax affairs are complex.
And if you screw it up, you end up paying more money.
And those are the people who need that kind of mass market wealth advice on how to handle their affairs better.
And right now, it's a disparate group of attorneys, accountants, and it's quite messy.
And I do think AI, like a lot of other markets, is a little like healthcare.
There's a whole bunch of this knowable but nonetheless complex information that has to be assembled and marshaled.
And at the right time, the person who has the question has to get the right answer.
That question can be, what form of cancer is this based on the CT scan?
Or how much do I owe to the US government based on these facts?
But you want the right answer at the right time.
And it turns out machines do that a lot better than humans.
My takeaway is you need a new wealth manager, dude.
Seriously, a Goldman... Okay, we need to... I'm not just doing the Goldman.
I can introduce you to... Harry, not everyone has a wealth management problem, Harry.
How about we focus back on the problems of the people, the founders, that are trying to build wealth, rather than you, as a rich guy, trying to spend it okay?
Come on.
I'm a humble podcaster, Rory.
I believe that AI will disrupt some of these categories and build huge businesses.
Okay.
I believe it.
Maybe be capital efficient until you prove it.
If Rory's deal does 100 million growing 150% or 200%, everyone will flood into this.
Okay. and say it made no sense back in the day.
I mean, not every founder can directly compete with Cursor as founders.
Like we have to play to our strengths.
And if you find someone, like I might've invested just because I'm passionate.
Maybe it was a bad idea.
I mean, I'm into it, but you might've convinced me, maybe just don't spend all of it.
Maybe be a little more conservative.
Did he not bring you into the deal?
Not bring me into the deal.
Oh, he brought me into the deal.
Yeah, he did not bring me into the deal.
Shut up Harry, because Jason's made a really important point that I think is relevant to our wider founders.
Your discipline as a founder on capital is exactly proportional to, in part, to how hot the market is perceived to be.
And if you're playing a game that's in a market where you need to make progress before you can raise, then you don't have the ramp for raises before Friday strategy.
You have the capital discipline to prove your point.
In the end, if you prove it, you'll get the capital.
But I think, Jason, that was, frankly, a spot on comment we could send you as a board member.
Literally.
It's like, here guys, build value.
If you prove it, the world will be beating the path to your door.
But if you half prove it, you'll be screwed.
I think that's a great note to close on.
Guys, thank you so much for being part of a live show.
There's no Kalshi quickfire?
You want a Kalshi quickfire?
One quickfire is Superbase is now at $5 billion.
Lovable is at $6 billion.
Now, obviously, Lovable uses Superbase for every instance.
Would you rather be in Superbase or would you rather be in Lovable?
I'll say Lovable.
And I'll tell you why.
I think Superbase is benefiting by the trend of vibe coding.
And Lovable is a bet fundamentally.
It's in the front end monetizing on vibe coding.
One of two things happens.
Either vibe coding is a category or it's not.
If it's not a category, both of them are screwed.
And if it is a category Lovable gets more of the money than Superbase, just because it's the front end and it gets I don't know 20 bucks and they pay two of it to Superbase some version like that.
If you're in a highly risky category, the dumb bet is to be well, if I win, I get a little, but if I lose, I lose 100.
You may as well be in for a penny versus in for a pound, as we would say in the UK.
And the thing about the Lovable bet is, if you win, you're going to win big which, of course, is why a smart young man like you are in Lovable Harry.
See, I thought I'd put in one pitch for you there, dude.
Thank you so much.
I would take Superbase.
No, I'll tell you why.
For what it's worth, this is how I'm feeling today because of stability.
I think Superbase is a harder problem to solve.
Yep.
And so right now today, this is where I'm conservative.
There's just so much change.
I don't know what Google is going to do.
I would just prefer a harder problem today.
And even if my returns were the same or lower, I mean, I'm sleeping fine.
But I'm just anxious about clonable stuff.
And I want hard problems are reassuring.
Like only so many people.
I mean, at the end of the day, Supabase is just, I think, a fork of Postgres.
It's open source that they've redone.
It can be done again.
Neon did it.
That Repl.it lose and Databricks bought in for a billion.
But databases are a hard problem.
Like you can only lose so much data.
You can only have so many issues.
You have to figure this out.
And five years of investing in a database that everybody uses.
It ain't so easy to churn and leave your database right.
And so I just, this is what I'm thinking going into next year if we want to close.
This was a year where we didn't, we tolerated a lot of churn.
We only cared about, this was the year of growth, but nothing.
And so is next year.
But I love a little defensibility.
I just love a little hard friggin' problems.
And you know we're past the thin wrapper layer, but I'm going.
What are you picking between Loveable and Supabase?
Oh, dude, I'm...
A lovable all the way.
Lovable all the way.
We'd love to lead the team in both.
Loyal to his paycheck.
The loveliest thing about this is we knew each other well before, but the friendship that we have as a three now having done this show, it's just fricking awesome.
Like honestly, it's one of the highlights of my week, doing this show every week.
And I've never said this to both of you guys.
I so appreciate the friendship that we have.
And thank you for doing the show with me because it's always so much fun.
I learn so much.
I get so many messages from founders who learn so much.
So thank you for putting up with me, both of you.
I know it's not always easy, but you're awesome.
And thanks for everyone that stuck it out to the end.
We appreciate it.
Take care, guys.
Thanks here in London.
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