# Building Durable Value Beyond Frontier AI Labs

**Podcast:** a16z Podcast
**Published:** 2026-11-10

## Transcript

Chad GPT and Cloud Cowork, they're effectively the new OS.
There's plenty of room to build software outside the path the Frontier AI labs are racing down.
Since then, HubSpot's been busy.
The actual thing that's valuable is the work that's happening.
The interface is a means to an end.
Building an ecosystem is a lot like building a product.
You have to think of it that way.
We had a very broad base of marketing applications.
The reason we chose to do it all...
is the only way for us to solve the actual problem customers had, which is they're intimidated by this fragmentation.
Everything's all right.
We had to do it all in one offering.
The architectural decisions that you made when you originally built HubSpot was for a human to be navigating all of this information.
Now we have these unbelievably powerful models that can go look at things in very different ways.
What is the framework we need for the next 20 years of HubSpot now knowing that we have this AI world?
A couple of things.
One is...
As OpenAI and Anthropic move deeper into applications.
What's left for startups to build?
A16Z partner Joe Schmidt and HubSpot co-founder and CTO Dharmesh Shah explore how founders can avoid competing directly with Frontier Labs and build lasting value through workflows, customer context, and data.
Drawing on HubSpot's evolution and AI experiments, Dharmesh explains why founders should start narrow, learn quickly, and look for markets that cheaper software creation makes possible.
Welcome back to the A16Z podcast.
I'm Joe Schmidt, and today we're joined by Dharmesh Shopp, the co-founder and CTO of HubSpot.
We're picking up on a conversation that started with an exchange on X about my Yellow Brick Road essay, the idea that there's plenty of room to build software outside the path the frontier AI labs are racing down.
Since then, HubSpot's been busy.
They've launched USpot, a CRM for one-person businesses, and they've been rebuilding their own platform around agents.
Today, we're going to talk about what's worth building, what an established software company has to change, and what happens when AI becomes the way customers use your product.
Dharmesh, thanks for joining us.
Thanks for having me.
Hi.
Yeah, so excited.
It's Dharmesh, you know, LeBron, Madonna.
You've got the one word name, so pretty exciting.
This is a fun conversation for me because I wrote that essay a few months ago, really in response to this nihilistic, nothing matters feeling that was going on in Silicon Valley.
And I feel like it's actually still going on.
So it's got to be strange running a...
big public company, successful public company through this time period.
What does it feel like?
I would love to maybe just start just with a market check.
Yeah, on the one hand, it's the old best of times, worst of times.
It's the best of times because we have all this kind of energy and excitement that you have when you have this kind of massive transformation.
I think BackupSpot's 20 years old now.
And when the company started, the kind of genesis of the company was, oh, there's this new thing called the internet that SMB should be benefiting from to drive growth and things like that.
And they're not yet because it's overwhelming and the tools were fragmented and all that.
And that's where HubSpot started.
Now, fast forward 20 years, there's this new thing called AI that we think small, medium-sized businesses should be benefiting from, but it still feels intimidating or whatever.
So it feels like this new kind of revitalized mission, same customer base, just new technology.
On the other hand, it does create a lot of...
the fog of war and uncertainty that we try to, for the most part as a team, stay focused on the customers, whatever the markets will do, what the markets will do.
We have our own thesis in terms of how things are evolving and what bets we're putting down.
But I focus on the positive side.
I've been building commercial software for 30 plus years now, like literally every day.
And this is the most fun I've ever had in terms of building things.
What a time to be a builder.
Yeah, no, I totally agree.
And it's so strange that the perception is negative when literally everything is working.
It's like you fall out of the boat and you hit water right now.
Maybe if we go back to, I'd love to talk a little bit about some of those formation experiences, obviously with Pyramid and then of course HubSpot and how you guys got there.
I'm sure back then people were saying some of the similar things about, hey, it's gotten so much easier to build software and what are you even building now?
I'd love to hear your commentary on the similarities and the differences in terms of how you're actually building companies and what you're seeing today with new startups.
Yeah, I'll give you a slightly geeky response because I'm a geeky guy, is that having been in the software industry since prehistoric ages, 150 years ago, the story of software and software development has always been this kind of increasing levels of abstraction, right?
So when I started, we still had machine language, we were running on mainframes and things like that.
Then we had three GLs, we had C and C++, and we had four GLs.
And so what we've done is to say, okay, can we get to...
whatever manifestation you have in your head of whatever problem you're trying to solve, can we make that easier for you to do, right?
So back then it was really, really hard, and then it got progressively easier.
And we've had some jumps along the way in terms of nonlinear kind of increases in the level of abstraction.
But at its base, this is the thing that kind of excites me about AI is it gives us a new tool set to work at yet higher levels of abstraction.
That's the thing that's sort of changed, right?
And so...
In my mind, like the problems are still the same that humanity is dealing with and businesses are dealing with.
But now we have a better set of tools and I have a kind of software oriented bias.
That's my thing.
But so in some ways, it's sort of the same.
And we'll go off a little bit of a tangent here because one of the things that's happened recently is we had the JEV model.
Oh, yeah.
Released by the TypeSafe folks.
And what that really takes it back to is like, oh.
Well, it is really just software.
And here's another kind of dimension of development that we're having that's not a transformer, but it's actually kind of opening up.
And that's what it does, is we're just putting more tools in the tool chest of builders, and we're expanding the scope of who can be a builder, which is awesome too.
But a lot of it is still the same.
We're still dealing with kind of similar issues, and it's just nice to be able to work at a higher level of abstraction.
And one of the reasons I think this is a great time, it's always a good time to do a startup, but it's a great time to do a startup, is that...
because we're working at such high levels of abstraction, AI lets you iterate so much faster.
So you can learn the lessons that might have taken you six months, a year, two years to do.
It's like, okay, well, just try it.
Build something, get something out there, test it with actual users and customers and see what happens.
And that just wasn't possible before.
Oh my gosh, I totally agree with you.
I wish you could see.
all the things that we've been building here at our venture capital firm, right?
I mean, even being on the front lines is so much more fun.
This actually leads into a question I wanted to talk to you about, which is, I think historically, and if you look, especially at the businesses you've built, you would start in some very narrow product surface and for a very narrow type of customer.
How have you observed this changing with that fast iterative process and the ability to build so much more, create so much more software so much faster?
I'd love to hear you talk a little bit about that.
Yeah, I've been in kind of the startup world directly and indirectly for a long time.
I still think of myself as a startup guy, is that picking the ideas has always been like one of the hardest things, especially for first-time founders that haven't been through it.
And even now, after 30 years, I think I'm marginally better at it than I used to be.
But one of the things I think the common mistakes...
entrepreneurs make in terms of kind of idea selection is that they think it's a matter of rigorous analysis, that we're going to have this kind of 18-column spreadsheet that's going to give me all the coefficients that out it's going to spit the best possible idea.
Yeah, the number of times I've seen the U.S.
Census file.
Yeah, exactly.
Oh, there's 18,000 lawyer law firms between two and five employees.
This is not relevant.
Yeah.
And what I've experienced, and then not just me, it's not just a data point of one, but even talking to other founders, is that it's almost impossible to know a priori what the quality, quote unquote, of an idea is, or it's kind of probability of success, or what the outcome is going to look like.
And the only real way to test an idea is to actually, or know if an idea is good, is to actually test it.
And what ends up, even if you're successful, the thing that you end up with that succeeds.
will oftentimes, or more often than not, resemble the original idea you started with, right?
So what you get to that people now think of as, oh, that was a successful business, sometimes it doesn't resemble, well, have some similarity, maybe the gene pool of the original concepts are still there, but it's different.
So the kind of byproduct of that thinking is that since you're unlikely to know whether a given idea, a set of ideas maybe you're exploring is going to be good or not.
then the smart move is to say, let's get the idea out there as quickly as possible and learn as quickly as possible as to whether this is or is not a good idea and this should be pursuing something else.
So I think that still holds today.
Let's get back to the kind of AI point we can iterate faster now.
The one thing that's still hard, and I would argue maybe even harder now than it was, is distribution, right?
Because...
It's so much easier to build software now.
Many more people will be doing it.
So there's going to be many more options and it's going to be hard to sort of cut through the noise and kind of get into contact with a customer.
And one of the things I'm a big believer in is kind of starting out with, and I'm not the only person that has said this by far, but it's in order to narrow the aperture in the early days, just kind of focus in, because that's what increases your odds of kind of getting through and learning.
And the mistake number two that entrepreneurs make is that they feel like they need to start with this massive TAM where it's like, oh, this can be a $100 billion business.
That's great.
You have the kind of ambition and vision that this could be $100 billion.
But tell me what you're going to do in the first 30 days.
What's the thing that you're actually going to focus on?
I don't get to $1 revenue first.
Exactly.
And even now, for me, as I explore new ideas within HubSpot, both for HubSpot Next, which is our innovation arm, or even new ideas within the core platform, it's like...
kind of narrowing that field of view so that can we somehow, I think the people that win are the ones that have the shortest iteration time and the cheapest learning time.
So if you can sort of shorten that loop and learn less expensively, whatever the lessons are going to be, over the fullness of time, you end up winning on average.
Yeah.
No, and I still think, though, that this moment is the best possible moment for high agency people.
And the reality is, yes, it's way easier to build software, but there's only so many people who are sitting alone on, 10.45 p.m.
when we exchange an email on Saturday night, hack it on their computer, and just go be that person and go build something cool.
I want to go back to what I believe in the beginning of HubSpot, you started with, and correct me if I'm wrong, a legal product.
Maybe there's a legal product in there somewhere.
And somehow that has now become this CRM for small and mid-sized businesses.
I mean, it's unbelievable what you guys have expanded that wedge into.
I'd love to hear how you guys thought about, you know, the course that evolved into the SMB marketing wedge and so on and so forth, but would love to hear how you expanded from there to platform.
Yeah, so when we first started, you know, we were in business school.
That's where my co-founder and I met here on the East Coast.
And the thing we sort of alighted upon was first the kind of beauty of the SMB as a market.
It's like it was underserved.
And I'll give you the quick story here because it's interesting.
So we had both been in software for a long time, beyond the kind of marketing and sales side, and the kind of product development engineering side.
And we had both done enterprise software before, so we sort of knew that.
And the challenge with enterprise software was it's completely non-fun as a startup entrepreneur.
Sales cycles are long, you get revenue concentration, you've got a small set of customers kind of impacting your product roadmap and your vision and things like that.
So there's that.
On the other end of the spectrum, you have consumer markets, right?
Consumer companies in the software space.
And the issue with consumer markets is that a lot of them have very bimodal outcomes.
That says, okay, if you're successful, it's going to be this massive outcome.
And a lot of times you're doing kind of advertising subsidies or figuring out some other way.
You can't really charge for the product because don't be a chump kind of thing.
And the beauty of SMB was...
Just from a pure market analysis perspective, this is two guys in business school at a time.
It's like, oh, well, SMB has the beauty of enterprise in terms of you can actually charge money for a problem that you're solving.
It's like there's nothing wrong with charging money, but it has a scale of consumer that you're not going to have this revenue concentration.
You can have tens of thousands, hundreds of thousands of millions of customers.
And so you sort of have the kind of best of both, right?
And so that was our kind of original thinking.
It's like, oh, if we were to do a startup, like...
And so then our original idea that we took to the MIT 50K competition was ERP software, like an Oracle for small business.
And the way, and this going back to the kind of narrow the aperture, it's like, okay, well, that seems like an interesting thing because we're going to this kind of transition from client server to the web.
It's like someone should create an Oracle for small business.
That's how everything's integrated, kind of works together.
It's kind of built for SMB.
And when we went to the business plan competition, we said, that's like too big.
Let's narrow the aperture and let's call it LegalSpot.
The HubSpot company name had already existed, but the thing we wrote the business plan around purely as a way to kind of test the market early on is to say, let's focus on ERP for law firms.
Just as an arrow, and back to your original act, I was like, ah, there's all the U.S.
Census Bureau things.
Oh, there's lots of them out there.
We can multiply X by Y.
And it makes for great business school kind of spreadsheets and PowerPoint decks.
And so we did that.
And we have a kind of propensity for kind of testing the waters.
And one thing we learned early on in that, while we're still in business school, kind of noodling on the HubSpot idea, is like, that's not a fun market to sell into.
And as we talked to the law firms and we talked about ERP and what the solution would or could be, the marketing and the website, all that was the part that was most interesting to them.
Yeah, like, wait, hold on.
Can you help me find more customers?
Exactly, yeah.
It's like, we got time tracking and all that.
That doesn't really matter.
Can you help me find more clients that are the ideal fit and things like that?
And so we were sort of like down to those two ideas.
Like, oh, do we kind of stick with the...
kind of ERP for SMB, or do we do this kind of marketing for SMB?
And we chose, we almost could have flipped the coin.
We almost could have.
We didn't.
We were a little bit more deliberate about it.
And we did extrapolate from a minor set of data points, but it was like, life is short.
As it turns out, lawyers are the second hardest market to sell into, software developers being the hardest.
So now we're navigating the SMB.
kind of marketing product.
Of course, that then morphs into much more of a platform and a full CRM.
Was that thoughtful from day zero?
And the reason I'm asking is I think there's a lot of folks out here that maybe are using some new AI medium, whether that's, you know, commonly early on it was voice products.
And I actually still think that's a huge opportunity for so many folks.
I'm sure you're exploring that at HubSpot.
Or maybe there's some sort of support kind of chat interface.
And everyone always wants to end up being the HubSpot for whatever use case, right?
So maybe talk a little bit about how you navigated that product journey and created the right loops to get to more of a platform from this initial wedge.
Yeah, so we started off as a suite of marketing applications.
And to answer the first question, this was not a time T equals zero.
We think we're going to be a CRM platform someday.
That was not in any of our PowerPoint decks.
And so, yeah, we didn't have that.
But as the company evolved, we sort of, and this may be a little bit kind of idiosyncratic to HubSpot, but I don't think so.
I think the pattern still exists even outside of a CRM.
You sort of have the need for kind of product number two, right?
Like the second actor, however one tends to phrase it.
And we sort of hit that.
So a couple of things happened simultaneously.
We were in the marketing software business, and one of the things we sort of recognized is that Being in the marketing software business, you know, was very, very close to sales and CRM.
That was kind of the adjacent category.
So that kind of made logical sense.
The other thing that we sort of learned, you know, once we had a bunch of customers, is that we did a survey of our customers.
This is, you know, maybe a couple of years before the IPO.
So maybe five, six years into the company.
And just to see which CRMs they were using.
And we discovered that...
20% were using Salesforce.com.
Another 20% were using some other CRM other than Salesforce.com.
But 60% were not using a CRM at all.
And that was insane to us.
It's like, wait a second.
So you're using HubSpot software, you're paying us money.
So these are not like random companies.
These are people paying us money to generate leads.
What's happening to those leads?
And so that was, so the thing that we sort of...
alighted upon was like, okay, well, like, these companies should be using a CRM.
So, you know, we're, my co-founder and I are very weirdly simple-minded.
It's like, okay, well, why are they not using a CRM?
It's like, the category exists, it's not, and there are great companies with, you know, great products out there.
And we came down to, it's like, oh, well, it's overwhelming.
They're just intimidated by the idea of a CRM.
It's too expensive.
They think it's going to cost too much to kind of get going with a CRM.
And so we made the decision that it was a nice adjacent thing.
We need a second product anyway.
There was a strategic value to saying, okay, well, over the fullness of time, the existing CRM players are likely going to get into the marketing space.
And we're going to have, so even if we want to stay in the marketing software category, it's unlikely that we're going to be able to do that forever, right?
So all those things sort of converged around the same time period.
And so when we launched the CRM, you know.
we sort of address both of those issues.
Like, okay, so we're going to build a CRM and we're going to address the 60%.
It's like, okay, for those people that have not picked a CRM yet, why have they not done it?
Too hard?
Okay, let's make the easiest CRM that's ever been conceived at that point in time.
And we're focused on SMB, so that was a core strength anyway.
And we're going to take the, it's too expensive off the table because we're going to make it free.
Not freemium, free.
It's like, okay, well, this has been sort of the...
kind of philosophy at HubSpot is like create customer value before you try to extract it.
It's like if you can just get out there with something that's useful and we can obviously subsidize it with the kind of the marketing software business that we already had.
But that was the idea.
It's like, okay, well, then we've sort of removed the obstacles and then it's like, let's go out there.
And then as we iterated, we sort of learned that in order to win in the kind of CRM space, it needed to be a platform, right?
It's like it can't just be a...
Because CRM is almost by definition now, and even then, our platform.
So that was the journey.
It's just going from product one to product to expanding out into a strategic adjacent thing.
But then, and this is the other thing I think that carries over to the entrepreneurs listening, is that do what you can to solve the whole customer problem.
How are you to find it?
Whatever circle you draw it around, it's like, what's the actual problem we're trying to solve?
So even when HubSpot started, we had a very broad base of marketing applications, which goes against every piece of advice you get that I've given.
It's like, do one thing really, really well.
We did all the things.
So we had content management, SEO, and landing pages, and forums, whatever.
And they were great companies with great products in each of those categories.
The reason we chose to do it all is the only way for us to solve the actual problem customers had, which is they're intimidated by this fragmentation.
Everything's all right.
We had to do it all in one offering.
And so we sort of carried that idea with us.
for 20 years, we still do the same thing now.
It's like, what's the actual problem we're going to solve?
Well, it's so interesting because I think, you know, with hindsight, everyone always talks about, okay, well, you know, from a go-to-market strategy, there's, you know, the brownfield approach of you go after all these people who are on every core system already and you rip and replace it.
And hopefully you're in the middle of a cycle like this where everyone's willing to revisit that.
Or you go after a greenfield and you try to win all these new businesses who have never adopted software before.
And I think...
the standard thinking on HubSpot is like, oh, well, it was just like a very thoughtful from the beginning.
Like, you know, let's go after the greenfield.
And the reality is it's like, actually, no, like all of our customers just didn't have it and we built it.
And it's still fine if you do it in that order and you can still be a massive company if you nail it.
So interesting.
How did you think about, you know, another part of this is, you know, building the right ecosystem around that initial offering though, right?
And I think that's something that HubSpot has done such an amazing job of.
maybe what are the key learnings from the early days of building the ecosystem?
And then now that you, you know, it's such a different world today where you're able to do a lot of that in different ways.
I'd love to hear you talk about that with, you know, the advent of AI and how that's impacting the ecosystem as well.
Yeah, and I've been a consumer of platforms and ecosystems for most of my professional career.
So I sort of know what it's like on both sides.
And this is no disparagement to any of the existing platforms then or now, but...
What tends to happen with ecosystems and platforms is that the platform providers will start looking to attract the developer ecosystem and get people to build apps or build companies that are kind of adding value to the core platform.
But over time, what ends up happening is that...
either intentionally or unintentionally, they sort of kind of stomp over those developers.
They'll close things up, they'll spread down, and we saw this, we can talk about this, the story's 15 plus years old now.
Like Twitter had this in the early days, right?
The original Twitter was this kind of very open ecosystem, we're a platform, and literally a thousand flowers bloomed back then.
Lots of Twitter clients built, lots of people built products and companies on that original set of APIs.
And it's not exclusive to Twitter, that's just what jumps to money right now.
But then they sort of closed it down and became, you know, everything from like developer unfriendly to almost developer hostile, right?
And so one of the things that I think this has kind of helped us build the ecosystem is that we've sort of taken those lessons to heart to say, okay, well, let's be the platform that we wished would have existed for us back when we were doing, you know, varying and sundry things.
It's like, let's, you know, be the, sort of carry that HubSpot brand of being kind of friendly, likable.
And That's like we're red-blown capitalists.
We like to think of ourselves as like warm-hearted red-blown capitalists.
Like, okay, everyone's here to make money.
Here's what we're doing.
And we try to be, even with our partners, try to be as open a book as we can be in terms of like, okay, here are things that we can't promise you we're not going to do this, but here's what we're doing.
If we were looking for white space, if we were you, here's the things, the kinds of things we would do that we think there's an opportunity that, you know, we're highly, highly unlikely to kind of traverse into that territory.
And that's work.
So we've built trust across a wide pool of people now.
And then some of it's just the, building an ecosystem is a lot like building a product.
You have to think of it that way, is to say, okay, well, as a developer at heart, it's like, okay, well, in the same way we think about time to value for the core customers, we have to think about time to joy for a developer.
How fast can someone get to, oh, I got something working with the HubSpot APIs to the, oh, I made my first dollar, you know, working within the HubSpot ecosystem.
Whatever that is, can we compress that?
Can we reduce the time to joy, you know, for that class of customer?
Yeah, totally.
And congrats on building such a thriving ecosystem.
Maybe just transitioning a little bit now into, you know, the essay and the conversation we were having around it.
I'd love to hear how you think about the things that you're maybe, concerned about with regard to the workflows that the labs are kind of going after.
And of course, there's many things inside of the HubSpot experience, I think, that those horizontal products are trying to pull in.
And how you think about the area by which you want to defend and where you can kind of build the most durable value.
So we'd love your commentary on that.
Yeah, a few thoughts.
One is I'm going to open this with a very, very biased point of view, given I'm a co-founder and CTO of HubSpot.
I would assume so.
That doesn't necessarily make me wrong.
So a few thoughts.
One is around, and we'll just talk more broadly, and then we can kind of zero in on some of the specific things, is that for those on the outside looking in, it's like it feels like, and this is your kind of yellow brick road, which I love the essay, the idea and the analogy was very apt, which is like there's this...
well-traved, shiny, bright road that's kind of pointed to the Emerald City or whatever, how could you not walk down?
And it feels empty at the time, right?
But you don't know that there's like a fleet of tanks coming down that road.
And they're getting faster.
It's not that they're even slow because they've invented this new thing that makes them go fast.
And so, and this was kind of the premise of your essay, which I wholeheartedly agree with, is that...
Yes, they're going to barrel down that road.
And it is a shiny, nice road, and hence the trillion-dollar valuations and soon-to-be market caps.
But there's so much opportunity outside of that.
And so here's like a framework kind of guy.
Like, here's a mistake I think entrepreneurs make on both sides of it.
When they dismiss it, they say, oh, well, chat GPT doesn't do this or cloud coworker doesn't do that.
Well, we're going to do this.
We're going to fill this gap.
And those are the ideas that make me nervous, right?
Because there's two things sort of, I think, misguided about that thinking.
One is, if you can just append the word yet to it, and it still holds water, that's a problem.
It's like, oh, ChatGPT can't do that yet.
Does that ring true?
If it sort of does, it's like, okay, well, that's a problem.
That's thing number one.
Thing number two is what I think of as measuring the product versus the company.
It's like, oh, ChatGPT can't do that.
It's like, okay.
But can OpenAI, the company, do that?
Like maybe, you know, it's a new product, a new product line or whatever.
It's like, so you have to sort of think through how wide is that road?
You know, like, okay, maybe the road itself is getting wider, fine.
So maybe stay off the road, but maybe also stay, you know, a little bit outside.
It's like, okay, if there's all things being equal, if you can just be a little bit further away.
So even if as they expand, and it's somewhat predictable.
So that's kind of thing number one is to make sure that...
And either, you know, pick things that the frontier model companies either have a structural constraint that they just can't do, regulatory-wise, whatever it is, or have what I think of as like an incentive constraint.
Like, yes, they could do that, but the odds of them doing that are really, really low because I'll just, I'll use HubSpot as an example.
So let's say any of the frontier model companies, I'll pick on Sam Altman since I'm an investor in OpenAI and I know Sam.
It's like, he could wake up tomorrow and say, you know, that CRM industry, that looks awfully tempting.
And that, you know, three plus billion dollars of revenue that HubSpot has, we're going to make it our mission or somebody within the company's mission to go take that revenue.
Are they smart enough?
Yes.
Do they have ambition?
Yes.
But it's that very ambition that makes it highly unlikely that the team at OpenAI or SAM or anyone, or same thing with Anthropic or any of the frontier model companies, they're unlikely to do that.
But that's what it would...
take to be able to.
It's like, okay, so my thesis, and this kind of winds back to where do you find the pockets of opportunity that are off the yellow brick road, which is one thing we know for sure is the frontier model companies have invested hundreds of billions of dollars kind of building, doing the pre-trading, as you all know.
And so their whole business effectively now is taking the capex that they've spent and the money they're continuing to spend and say, how do we sell inference?
How do we sell tokens?
How do we kind of monetize the thing that we've built?
Yep.
Awesome.
A tale as old as time.
And they have two choices.
One is they can say, oh, we're just going to go directly to everybody on the planet and sell them tokens.
And they'll do that by virtue of the consumer product, and they'll do that.
And even on the high end, they'll say, okay, well, we're going to go directly to Fortune 500, JP Morgan's, and we're going to sell them tokens because we're going to sell them.
There doesn't need to be an intermediary, and we'll have an army of FDEs that can help us do that.
And that's certainly a path, and they're kind of walking down that path.
Another possible path is, it's like, okay, well, there are, SaaS companies and products and companies and startups or whatever that know their particular domain, know their market, have some distribution or have something that allows them to sell tokens and be a reseller of inference, for lack of a better term.
It's like, okay, well, and they don't actually, this is not a binary choice.
They can do both.
They can say, oh, for these kinds of things, for a consumer, we want to own that.
We don't want other things, people doing like a chat GPT equivalent.
We're going to own that.
But there's going to be lots of opportunity to say, okay, well, think of AI, as infrastructure in the same way we thought of AWS and cloud computers infrastructure 15 years ago.
It's the exact same thing.
And as entrepreneurs, once again, I'm biased but not wrong, I think it's less scary now to build in and around kind of the AI arena than it was in 2023.
And the reason I say that is back in 2023, and I have very few...
rules for business.
One is never own a restaurant.
Number two is don't ever be a landlord and charge rent.
And number three is never compete with Sam Altman, which I've accidentally done a couple of times.
But the reality, though, is that at the time in 2023, if we take ourselves back, if I were a betting person, I would have said they are just so far ahead.
It was like they had figured out this kind of magic elixir or something like that.
It's like I have no idea of anyone.
ever is going to be able to really solve it and be able to pull all the things, including the capex spend, that was going to be necessary.
I was thankfully wrong about that.
Thankfully, in terms of from entrepreneurs and from an ecosystem perspective, because where things stand now is that models, I'm not going to say they're a commodity, but part of the virtue of them being as common as they are is they are infrastructure, and they're going to trend toward both from a pricing perspective and from a fungibility perspective.
Right now, you know, Things like Open Router exists because it's easy to sort of swap out models back.
And even within HubSpot and most SaaS companies are doing some form of use case decomposition and model routing to figure out what's the right model for this task.
The byproduct of that is that you can sort of swap out what you need or whatever, so there's less reason to be scared because you don't have this kind of supply chain.
power where like this one company controls the one crucial ingredient for you to build a product and solve the problems that you're solving.
We don't have that right now.
We have open source.
We have lots of great commercial products.
So as long as you stay off the yellow brick road, it is completely possible now that you're not going to get margined out or whatever because you have options.
There's not just one company providing the one key ingredient to building an AI native company.
No, totally.
And I think that the other piece of this, which you kind of touch on, it's like, okay, of course, with enough focus, but it's also just that the advances or the advantages you're going to build as a startup or as a hub thought or whoever it is, if you're not building a foundation model, you're actually building still high quality software.
I think that is the layer that you're going after to provide value to your customer.
And so, of course, there's all these other great pieces of infrastructure that you can now package up and then give to those customers.
And the way that at least I think about it, and of course I argue in this essay, it's like, you know, there's loops, there's tests, there's things that you can kind of do to try to identify these pockets.
But then, hopefully you're building some sort of, you know, increasing return to scale or compounding advantage in this layer.
And so I'd love to hear how you think about this, you know, HubSpot or any of the things you're working on as it relates to the loops you try to build in these products or the advantages you're trying to build in.
Yeah, it's compounding loops all the way down, Joe.
Of course.
That's the entire name of the game before AI, after AI.
But a couple of things I'll say.
So I'm going to rewind.
I pushed one idea on the stack.
I'm going to pop it off and talk through it.
So, you know, one of the questions we get, you know, back on the, if you were an entrepreneur kind of evaluating the ideas, it's like, okay, well, so today was OpenAI's Dev Day, by the way, so September 30th.
So right before this call, I was watching that.
What's that?
I said we're dating the recording for the audience.
So you now know time stamped.
Exactly.
You know exactly when this is being recorded.
And HubSpot launched our, we were the first CRM company to do so, our connector to ChatGPT over a year ago.
And we have a similar one for Anthropic.
And one of the questions we get sometimes is like, oh, well, doesn't that sort of diminish the long-term value of HubSpot?
It's like, okay, if everyone's coming in through ChatGPT or through Cloud Cowork or something like that, isn't that like just saying, eroding the kind of long-term value?
And I understand the reasoning.
My sort of counter to that is that, Like the interface matters, but it matters to varying degrees.
There's a spectrum.
So let's say one of the spectrum, I'm making this up as I go.
Let's say you look at something like an Uber Eats or a DoorDash, right?
It's like, okay, they have very compelling apps, but it's like, okay, well, the app is trivial.
What's actually valuable is the network that they have, the partnerships with the restaurants and things like that.
So a driver can show up, pick up food and deliver it to the logistics and all of that.
That's what the actual value is.
And that's the part that's sort of hard to displace.
There are other things where the interface is the entirety of the product, right?
That's all there is.
If it weren't for the interface, there would be no value.
And I think most business applications actually sit more towards the Uber Eats kind of thing, right?
Not in the sense that they have network effects like Uber Eats and DoorDash do, but in the sense that the actual thing that's valuable is the work that's happening.
The interface is a means to an end.
The only reason the interface is important to HubSpot is because...
marketers and salespeople are trying to get something done or deliver on certain outcomes, and the interface is the way, in order for them to communicate with a computer, and before AI happened, it's like HubSpot's claim to fame was like, oh, we understand the problem you're trying to do, whatever, and we've actually built the interface that's super simple to help you kind of get there, but that was not the entirety of the value.
Now, one can argue where on the spectrum HubSpot falls, but I can guarantee you it does not fall on the interface has 99% of the value.
And so my argument is that In the same way, everything kind of comes back around again, is that when we saw the original kind of SaaS development just moving to the kind of web-based application world, we had the same kind of thing.
It's like, okay, well, we had client-server apps running on our desktops back in the day.
And then we had this browser thing come along, the Internet Explorer and later Mozilla, as you folks know well.
And it's like, okay, well, now my software is running inside of a browser.
As it turns out, Google did not...
owned the entire application stack, right?
There was an entire, lots and lots of software companies that got built, and it's like, oh, the interface became the browser because that was a convenient way to get to the actual kind of product that you needed to get to.
Browser was a better way than installing something on, you know, 18 million computers.
We have a similar thing now.
And it's different, right?
Because the AI is doing cognition work, it's doing actual smart things, it can do more things.
But if you just look at the kind of ChatGPT and Cloud Cowork thing or whatever, they're effectively the new OS.
They are the new browsers.
Like, this is the way people are consuming value.
And there will be companies like HubSpot that sort of plug in.
And this is the thing we saw from DevDay.
And we saw it last year.
And we continue to see.
It's like, oh, they're going to increase the richness of what's available within ChatGPT.
They launched a, you know, this kind of go-through at a marketplace.
for people to plug in, you know, in plug-in architecture and all those things, which makes complete sense to me.
Yeah.
So my fundamental philosophy, which I think holds true for most people looking to, at least in the B2B world, is that, like, don't overthink the interface.
Figure out what's the best possible way to achieve the outcomes your customers are looking for.
And then the other value that you can bring is around, like, what's the economic...
best way?
What's the lowest latency way?
What's the lowest friction way to kind of accomplish those outcomes?
And often, like an LLM is very, very good at lots and lots of things.
It's the most brilliant technology we've had in the history of humankind.
But one of the things I've kind of gone on record as saying is like anything that can be solved with a structured query deterministically, solved with a structured query deterministically.
Don't use inference to solve something that a query can solve.
It doesn't make any sense.
So even if the data were there, it's like, oh.
If your question is, how many customers or how much revenue are we getting from Ireland?
You shouldn't have to troll through 8 million Slack messages and emails or whatever and for the answer, yes, the data is probably there somewhere.
But that should be a database query.
That should not be solved through inference and throw a 300 IQ model at it.
No, totally.
And I think there's many companies that are navigating through this as they try to understand their own pricing and consumption ideas here, which could be its own dang podcast, I think, for that matter.
Maybe last question on this, because I think it's really interesting you talk through this.
The architectural decisions that you made when you originally built HubSpot are probably, you know, with the benefit of hindsight, I don't know how you would revisit those.
I'm so curious to hear how you think about that, because, of course, now the way that...
you know, that you designed it originally was for a human to be navigating all of this information.
And you're storing that in a way that's intuitive to a human.
And so now we have these, you know, unbelievably powerful models that can go look at things in very different ways.
And so I don't know how you think about the way you may have wanted to start differently or maybe what you're doing to address that now as an executive hotspot.
Yeah, a couple of things.
One is, you know, so I'm a classically trained computer science, software development nerd.
And one of the things I'm a big believer in in terms of large-scale software applications is around this notion of frameworks and starting with a set of primitives that you sort of evolve over time.
That's the thing that gives you this coming back to kind of compounding and leverage.
So one of the things I've learned across every company I've done and worked in is that software, if you can kind of get those core primitives right, And then what you end up doing is sort of remixing and recomposing those primitives in kind of novel ways based on how the market evolves and how the product evolves.
And so that part has been true at HubSpot since the beginning, right?
So the thing we built out was we had this kind of core kind of operating system or operating framework that we had on which we built the marketing automation and things like that.
So when we went to product, you know, two, three, four, whatever, like most of the value that we needed to bring to market already existed in the form of primitives.
For instance, we started with marketing automation, which is, oh, here's this deterministic workflow to do marketing, like send an email out, wait three days, wait for them to click.
It's like, oh, well, then when we got into sales and CRM, it's like, well, our market of automation primitive is actually a primitive.
We can just reuse all of that technology and we will have more on day one of our sales automation app or product than anyone likely has that's been added for a few years, right?
And so that part of it, I think, still holds true.
And so what we're doing now is to say, okay.
what is the framework we need for the next 20 years of HubSpot now knowing that we have this AI world?
And so you touched on one of the things is, oh, well, the data is no longer just this kind of structured data in a relational data store or whatever, which made sense for the kinds of queries, determinist queries you're doing.
Now it's both structured and unstructured data.
And it's not like this data didn't exist within the organization, even within our customers' organizations.
Like you just couldn't do anything with it that was meaningful at any sort of, well, at any price actually back there.
10 years ago, but now you can, right?
So now we revisit the primitives and say, okay, well, we still need a structured data store, and I will, you know, happily debate this with whoever wants to debate it.
There is still room, whether it's relational, some other, there needs to be some persistent mechanism for storing kind of known facts and data, some sort of system or record, if you will, alongside this kind of system we think of as a system of context, which is this unstructured data.
And that's the thing that, We're sort of building out.
And the way I think this is going to evolve is this notion of, and I use this term, others use it too, like a second brain.
Can we put all the things that are happening?
And the kind of the structure that likely makes sense is some sort of graph structure.
Can we store this in some sort of context graph, another term that has been used?
And that's the idea.
It's like, okay, well, can we take this and then use that in combination with the structured data store and then draw inference and drive agents and drive outcomes and get work done?
So one thing that's interesting in terms of AI, you didn't ask this question, but it occurred to me as we were chatting, is that one of the things that's really...
beautiful about agentic coding now is, and this is particularly true for, even more true for incumbents, it's like, yes, it allows us to produce software faster.
We can test ideas faster, which we've talked about before, build products faster, which is all awesome.
We benefit from that.
But the other thing you can do is you can actually go deeper and do larger projects that you might not have otherwise considered.
So what's possible now is that, you know, so...
We have a system of record for code, which most people, which is GitHub.
So imagine you said, okay, well, I have something like a Fable 5.1 or like 6 Astra that's out now, or 6.1 that's out now.
But so imagine you say, okay, well, I wish like younger me had made these choices when it came to, if I just could go back in time.
here's how I would have done those primitives, or I would have introduced this as a primitive that's a reusable service versus because we didn't know that then, but we sort of know that now.
In theory, it's actually possible to now say, I want to play that back.
I want to take this body of code that we used this data structure for, this language for, this framework for, this architecture for, and what would happen if we said, we're going to spend $200,000 on tokens to go just redo that and basically just...
Play that.
It's like the infinite possible universes thing.
Let's jump to that branch of the universe where we have made a different choice and then see what happens.
Where do you wind up?
And one of the advantages companies like HubSpot have is that we have what people used to call unit tests and now show up as evals.
This is, can we actually measure the viability of the thing that we just did?
Does it still pass the test?
Does it still produce the outcomes?
Does it still do all the things that it needs to do?
Like, we have that now.
So we run this test now when new models come out.
It's like, okay, we can run our battery of evals across new models and say, okay, well, here's a tradeoff.
Here's the economic value.
Like, we lose about 3% of quality points, but we gain this much in terms of latency or economic.
We can do the same thing with testing these kind of theories.
Like, okay, if we did rewrite this whole thing into rust, I'm making that up.
Yeah, whatever, whatever.
What would it look like?
What's the actual, and you can test it now with small bodies of work.
Anyway, it's exciting.
I think this is such a fascinating topic.
I wrote a different essay, I think right around the same time I wrote The Yellow Book Road, maybe a little bit before, and I actually used Workday as an example on this front.
Just like, hey, you have to kind of start over to think about being AI native, and here's all the advantages you have, but here's all the disadvantages.
And so, you know, it's almost, you know, the benefit I think that HubSpot has is it has...
an amazing, you know, founder who's still very, very involved in the company, of course, running the business and driving these changes.
And so I love that example of like trying to think about these like alternative universes that you can build.
Are there other processes that you're trying to create inside of HubSpot or teams you're trying to create in HubSpot or destroying bureaucracy?
I'm just curious to see what you're doing as a founder right now.
Yeah.
So we have a group within HubSpot called HubSpot Next.
And the idea is it's effectively an innovation lab.
So it's a startup within a startup.
And so we'll have any number of these kind of going on at any particular point in time.
And the motivation, and we really truly do treat it like a startup.
And we did...
a variation of this when we built the CRM.
It's like, okay, we're going to build this CRM thing.
It's like, wait, what's that?
We're in the marketing software business.
And it's like, and we sort of cordoned off the team.
They had none of the rules.
You didn't have to build it on our stack.
You didn't have to use the brand.
You didn't have to do anything.
Just go solve the problem.
And we sort of carried that idea through now.
And I've championed and led several of these projects over the years.
And the one I'm working on right now, literally every single night.
is a project called YouSpot.
And it's a one-person CRM.
It's a CRM for solopreneurs.
That's the market.
And it's going back to the kind of narrow your aperture of focus.
But the HubSpot next projects have, they're pursuing either a new product category, a new product idea, pursuing a new market, or testing a new technology.
And going back to the, can you learn your lesson cheaply?
It's much easier for me.
I have this idea for a second brain, right?
Like, oh.
Maybe a graph model works better.
Maybe you plug in all the social media and everything that's coming in or whatever.
And it's like, okay, well, let's test this in USpot because that's a much easier, kind of faster-paced way to test it.
And so the product now is exactly 30 days old.
Congratulations.
Yeah, and it's been fascinating kind of learning.
So the answer to the original question is, can something like that work?
The answer is yes, it does work.
And I think...
Other entrepreneurs should kind of take away from, you know, this is that.
So that notion of having a second brain, that holds.
And the thing to, going back to the kind of yellow brick road conversation, kind of avoiding being run over, the thing you shouldn't do is to say, oh, well, ChatGPT and CloudCore are really bad at memory or whatever.
Yeah, it's like, it's going to get better.
Don't solve that problem.
Don't solve the horizontal use case or whatever, but say, hey.
within this class of customer, here's a class of problems that they have that would be benefited by thinking about this notion of having a second brain.
What would the ingestion points be?
How do you pull it together?
What's the actual agents that you would produce or the work that you would sort of accomplish?
But I think that underlying primitive is actually a powerful one.
I think it applies.
Yeah.
And then now that you, I mean, I think Uspot's so fascinating.
I think it's very valuable for that, particularly for this type of user.
I mean, it's what they want, of course.
Yeah.
How do you then take those learnings and like productize them at the mothership, if at all?
And what processes do you need to put in place to make that happen?
Yeah, the way we've done it, which we've kind of stumbled over the years and tried various mechanisms, is to kind of pull on that original thread of this is a startup within a startup.
So we do a couple of things.
One is, if the thing gets to scale, and we've had this happen multiple times before.
So there was a product I launched a couple of years ago called Agent.ai.
And Agent.ai was a marketplace for AI agents back in the day.
This was one of my accidentally-competed-with-Sam Altman stories.
Although it was focused on go-to-market, it was too horizontal.
But there were two parts to it.
There was this kind of Agent.ai marketplace, and there was an agent builder that says, oh, can we let mere mortals actually build these kind of mix of determinants?
non-deterministic agents.
And what we discovered is that half of the idea was right, but actually belonged and needed the full HubSpot team behind it.
So we did effectively an acquisition, right?
So we're going to take that, and now we're going to make agent builder a product within HubSpot or whatever, and that's what it lives at right now.
So in the USpot case, right, like one possible outcome is...
oh, like we're building the CRM for one-person companies.
We got these things right, those things wrong, whatever.
Maybe we just absorb it into HubSpot, becomes a product of HubSpot.
Maybe we say, oh, well, the product itself still probably needs to be standalone or maybe the market doesn't work.
But the idea of a second brain maybe works.
And like, here are the things in the suggestion points that we think work for SMB and multiplayer kind of team-based mode or whatever.
We just sort of...
let the core team decide what they want to pick and choose.
It's a little bit like they're looking at an acqui-hire.
And it's literally like that.
It's like, oh, here's what we can buy.
There's a low, low price of it's included.
It's included, yeah.
It's not free, it's free.
Exactly, it's free.
So yeah, and we sort of try to have an open mind about it.
But the nice thing about doing it the way we do it is that, so you think it's like, why can't you just do it within the core business is that, Those degrees of freedom are super important to be able to run the experiments at the rate that you want to run them.
So you have to, like one of the things I've long said, being a startup guy, is that the issue that incumbents are hard to use, incumbent when I refer to HubSpot, I still think of it.
It's still a startup, don't worry.
It's not the absence of something.
It's not like startups have something that the larger companies don't.
The issue is that is the kind of, I'll call it baggage, and the weight that the organization has.
And if they can find a way to kind of shed that, then you get all the advantages of being larger.
You have distribution, you have customer relationships, you have evals, you have 20 years of a code base that you can use as data to kind of inform the next product that you built.
All this stuff is actually an asset.
So if you can sort of shed the liabilities, and HubSpot Next is a way to say, okay, well, we're just going to pretend.
that we have none of those liabilities, which we don't.
As a startup, as a startup, we can just go off and do our thing, which we've been doing.
But then when it comes time to lean into the asset, it's like, oh, it would be helpful to have the HubSpot brand here, or can we get some advice on distribution over there?
It's like, we can do that.
It's so easy right now, especially with some of the national discourse to think negatively about AI and like the impacts.
But the reality is all the data I've seen are so it's so exciting.
Like growth is unbelievable.
And I actually think YouSpot is a really good example of this potential growth, right?
It's like when in the history of mankind would it have been like a good idea to go build like this like super individualized?
CRM for one person.
Like it would have been almost impossible to do that historically, right?
But now we're able to do that.
And what is that then going to let those one people companies do?
Like that is, we're going to see growth unlike I think anything we've ever seen before.
And it's just so cool to dream.
So maybe I'd love to just hear you talk a little bit about what you're seeing, like these initial use cases, maybe from UseBot or what you're seeing from growth.
It's just, it is really amazing time to be alive.
Yeah.
So what's interesting, like the, I knew this to be the case, but I wasn't sure to what degree.
So as I mentioned, one thing that I did differently with USpot versus prior HubSpot next projects that I've done is I monetized really early.
And part of it is not to kind of cover cogs or something like that.
That's one of the lessons I wanted to learn is I want to learn like the pricing lessons and some of the things that we want to learn more about kind of monetization pricing and what value do people ascribe to this.
That was part of it.
So the thing I've been really surprised by is willingness for people to put a credit card down on a consumption-based model.
It's like nothing, I've launched lots of projects over the years at HubSpot.
This has been, in that regard, the most successful.
So there's like this signal out there.
And part of it, I think, is just driven by sheer numbers.
We'll bring the U.S.
Census data into this right now.
So in 2025, we had the most number of new company formation that the United States has ever seen.
I think it was like 5.6 million, closing on 6 million, which is great.
This year, we're already at, like by August, we were already over 4 million.
So it's going to be another record year.
So it's not like, well, we had this one-time spike and now it's selling back in.
So that's kind of fact number one that's super interesting.
Fact number two that's even more interesting.
is the percentage of those new company formations that are expected to remain one-person companies is the highest it's ever been.
And it's increasing.
And so the U.S.
Census Bureau actually tracks this data.
They say they put every new company into two buckets.
And one is that this company is predicted to hire an employee within, at least an employee within the next two years.
And they bucket them in those two ways.
And the bucket of they are unlikely to actually hire an employee in the next two years, that percentage is now.
It's over 70%.
So it's exciting.
So there's this new market.
And so for the entrepreneurs that are out there, there's entirely, just like SMB was back when, you know, everybody sort of pushed back on HubSpot back in the day.
It's like, oh, you can't make money in SMB.
It's so hard.
No software company has ever, other than Intuit, has ever made a multi-billion dollar business in SMB.
But you can.
It's like, it's big enough.
Yeah, there's going to be painful parts to...
you know, those kinds of markets.
But anyway, I'm excited for that.
I'm excited for the economy.
I'm excited for all the entrepreneurs that are going to be starting these millions of businesses or whatever.
Yeah.
And then excited for the entrepreneurs that build things for that market.
Just like it's exciting all the way around.
So I'm, yeah.
No, I totally agree with this.
And we talk a bunch about, you know, aspects of this all the time.
And I think one of the...
one of the areas we talked about has been like, oh, well, vertical software in the past, well, how did you make that work?
Well, you made vertical software work with a low, you know, ACV or annual or monthly cost, but then you made it up because you had payments, you know, interchange revenue.
And I just don't know if people are fully appreciating the increase in opportunity size as there's just so much more you can do and so many other ways you can offer value and create value for your small customers.
Yeah, and this is my kind of counter to the SaaS-pocalypse idea, is that the reality is that, and AI, by the way, for the record, I know you know this, it is software, just so you know.
It's not like it's not software, right?
Yeah, it's not an alien.
That's a new energy source, it's software.
Really smart software, but software.
And what has really happened now is if you look at the class of problems, That software was designed, okay, I'm going to take one minute because it's actually a good story.
A handful of good stories.
So when we were first starting, in the first year of HubSpot, when we were out raising venture capital, we said, hey, we're building this marketing software company.
Here's what we're going to do.
And almost universally, across all the VCs that we talked to, came back and said, well, there's not been a marketing software company in the billions or whatever.
So we had two strikes, the SMB strike and the fact that we're doing marketing software.
And our argument at the time was, okay, so if you look down the P&L of any size business, every line item on the P&L has a hundred plus billion dollar software company name attached to that line item, except for marketing.
It's not like people don't spend, and the reason is, is that marketing historically has been an arts craftsy kind of thing or whatever.
It's like, you have this amount of spend, you spend a little bit on creating the creative, but then you just spend it on ads and billboards and all those kinds of things.
Fine.
And our thesis was that as a result of the internet, marketing the industry is going to look a lot like a problem that software was designed to solve.
That's why a software company didn't need to exist five years prior to HubSpot starting, but now someone will build a massive marketing software business.
And they make the same argument now that before, there was a class of problems that software wasn't really equipped to solve.
Now there is a massive set of these new problems, problems existed, new things that we can do with AI that didn't exist before.
So the opportunity set is way larger than, yes, some software companies will die, no doubt, just like some software companies did not make the transition into SaaS and cloud-based things or whatever.
Like, that's the circle of life kind of thing.
In aggregate, the opportunity is bigger than we've ever.
If you're anywhere near software, have the agency and are entrepreneurial, there's never been a better time to build a software company.
Go right now.
Yeah, I totally agree with you.
This has been unbelievably fun.
I'm so grateful for your time.
I'm going to end with a quick lightning round for you.
Sure.
And we can go on our merry ways.
I'm not very tasked on my feet.
There's only a few.
These are softballs.
I'll start with a very easy one, I would assume.
Dunkin' or Starbucks?
Duncan.
Okay.
But I don't drink coffee, by the way.
Oh, wow.
Okay, well then, what do you drink instead?
Just only water?
Are you a cyborg?
Just, yeah.
Wow, wow.
I gave up caffeine like years ago, so anyway.
Even more impressive, Dharmesh.
Okay.
Instinct or muse?
I'm sorry, what?
Instinct or muse, you know, on the new agentic shopping experiences?
I'm going to have to say instinct.
Okay, interesting.
If you had to be an animal, which type would you be?
I would still be a mammal.
Maybe an elephant.
An elephant.
I like that.
Okay, good.
What's the most Boston thing about HubSpot?
Almost everything.
Good answer.
Yeah.
We're very pragmatic, solve for the customer.
I say that.
We're sort of like a hybrid between like a...
Some of the best of the kind of West Coast kind of Valley thinking in terms of ambition and aggression, but some of the pragmatism of the East Coast.
I love it.
Heads down, just work at it, ride.
I love it.
And then finally, what's the best day you've ever had at HubSpot?
About a week ago, it's like things are starting to fall into place, like both in my head and like it's just like, okay, I can sort of see how this is unraveling.
Yeah, it's hard to explain.
It's not something I'm going to be able to say, but yeah.
Oh, that's so cool.
I mean, after however many years, the best day was a week.
I mean.
Yeah, and I'll say this more broadly, and I mean this like all things, but so the best time I've had, even being a startup guy in the history of HubSpot, which is 20 years old now, is a time I'm having right now.
And the reason is, and people are like, oh, that can't possibly be true.
It's like I have all the...
So by the way, I have no direct reports at HubSpot.
I've never had direct reports.
So like I'm an IC.
And the reason is that I have all the benefits of scale.
You get a seat at the grownups table.
You can make long-term bets.
You can do things.
But I have like another downside.
I can do HubSpot next projects like USpot or whatever.
So I have sort of the best of both worlds.
And it's so much fun right now.
It's awesome.
Well, Dharmesh, you are a generational entrepreneur, a wonderfully kind human and a generational thinker as well.
And I'm so grateful for your time today and for your engagement on all these topics.
So I look forward to the next time.
Thank you.
See you, buddy.
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