---
author: a16z
date: '2026-11-10'
guest: ''
layout: post.njk
source: https://www.youtube.com/watch?v=s4lXP9IuHjk
speaker: a16z
tags:
- ai-application
- software-architecture
- crm
- startup-strategy
- agentic-system
title: 超越大模型实验室的创业突围：HubSpot 联合创始人谈 AI 时代的软件与生态
summary: HubSpot 联合创始人兼 CTO Dharmesh Shah 与 a16z 的 Joe Schmidt 探讨了在 OpenAI 和 Anthropic 等前沿 AI 实验室竞速之外的软件创业空间。Shah 回顾了 HubSpot 从单一营销工具到免费 CRM 平台的演进经验，指出界面只是手段，实际价值在于底层工作与网络。面对基础模型走向基础设施化与可替换化，创业者应避开实验室必经的主干道，专注垂直领域与系统上下文图谱，利用快速迭代与新型单人企业爆发契机构建复利优势。
insight: ''
draft: true
series: ''
category: ai-application
area: tech-engineering
project: []
people:
- Dharmesh Shah
- Joe Schmidt
companies_orgs:
- HubSpot
- Andreessen Horowitz
- OpenAI
- Anthropic
products_models:
- ChatGPT
- Claude
- Uspot
media_books: []
status: evergreen
---
### 开篇对话：前沿实验室路径之外的软件机会
>> ChatGPT 和 Claude Co-work，它们实际上就是新的操作系统。
Original English
Chad GPT and cloud co-work. They're effectively the new OS.
Original English
>> There's plenty of room to build software outside the path the frontier AI labs are racing down. Since then, HubSpot's been busy.
Original English
>> 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.
Original English
>> What is the framework we need for the next 20 years of HubSpot now knowing that we have this AI world? Couple [music] things. One is
Original English
>> welcome back to the A16Z podcast. I'm Joe Schmidt and today we're joined by Dharmmes Sha, 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 oneperson businesses, and they've been rebuilding their own platform around agents. Today, we're going to talk about what what's worth building, what an established software company has to change, and what happens when AI becomes the way customers use your product. Darm, thanks for joining us.
Original English
>> Thanks for having me.
Original English
Hi. Yeah, so excited. Star mesh, you know, LeBron, you know, uh, Madonna, [laughter] you know, the you you've got the one word, you know, the one name one word name. So, pretty pretty exciting. Um, this is a fun conversation for me because I wrote that essay, uh, you know, a few months ago really in response to this like 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.
Original English
>> Yeah, it's uh on the one you it's the old best of times, worst of times. Um it's the best of times because you know we have um all this kind of energy and excitement um that you have when you have this kind of massive transformation. And I think backup spot's 20 years old now. And when the company started and 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 all and that's where HubSpot started. Now, fast forward 20 years, there's this new thing called AI that we think small mediumsiz businesses should be benefiting from, but it still feels intimidating and whatever. So it feels like this new um kind of uh revitalized mission u in same customer base uh just new technology. On the other hand um you know it does create a lot of uh the fog of war and uncertainty um that you know we try to for the most part as a team um custody focus on the customers whatever the markets will do what the markets will do. Uh we have our own thesis in terms of how things are evolving and and what bets we're putting down but uh I I focus on the positive side. I've, you know, I've been building commercial software for 30 plus years now. Like literally like every day. Um, and this is the most fun I've ever had um in terms of building things. It's uh this what a time to be a builder.
Original English
>> Yeah. No, I totally agree. And it's it's it's so strange that the perception is negative when literally everything is working. It's like you fall out of the boat out of the boat and you hit water right now. Um maybe if we go back to I'd love to talk a little bit about some of those form you know formation experiences obviously with Pyramid and and um and then of course HubSpot and and how you guys got there. I I'm sure back then people were saying some of the similar you know things about hey it's gotten so much easier to build software and you know it's not it's not what are you even building now? I'd love to hear your commentary on maybe um you know the the similarities and the differences in terms of like how you're actually building companies and and what you're seeing today with uh you know with new startups.
Original English
Yeah, I'll give you a slightly geeky response because I'm a geeky guy is that um you having been in the software industry since prehistoric ages um 150 years ago. But yeah, the story of software um in software development has always been this kind of increasing levels of abstraction right so when I started we still had you know machine language we were running on mainframes and things like that then we had 3G's we had C and C++ and we had you know 4G's and so it's what we've done is to said 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
Original English
>> uh and we've had some jumps along the way in terms of you know nonlinear uh kind of increases in the in the level of abstraction but like 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 um and so in my mind like the the problems are still the same you know that humanity is dealing with and and businesses are dealing with uh but now we have a better set of tools and I have a you know kind of software oriented bias that that's my thing but um so so in in some ways it's sort of the the same and and um we'll go off a little bit of a tangent here because one of the things that's happened recently is um
Original English
>> you know we had the dev model uh
Original English
>> oh yeah
Original English
>> uh you know released uh by the by the type safe 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 is actually kind of opening up and 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. Um, but like a lot of it is still the same. We're still dealing with uh, you know, kind of similar issues and it's just nice to be able to work at a higher level of abstraction. Um, and one of the reasons I think this is a great time, it's always a good time to do a startup. Uh, but it's a great time to do a startup is that um, because we're working at such high levels of abstraction, AI lets you iterate so much faster. Oh yeah. So you can learn the lessons that might have taken you 6 months, a year or two years to do. It's like, okay, well, just try it, you know, build something, get something out there, test it, you know, with actual users and customers and see what happens. Uh, and that just wasn't possible before. So, it's uh but yeah.
Original English
>> Oh my gosh. I I totally agree with you and this is I wish you could see, you know, all the things that we're even building here at at our at our venture capital firm, right? I mean, and so it's even being on the front lines is so much more fun. This was 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 um you know you would start in some very narrow product you know surface and for for a very narrow type of customer um 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
Original English
>> yeah I think this this um you know I've been in kind of the startup world directly and indirectly for a long time. I still think of myself um as a startup guy is that uh like picking the ideas has always been like one of the hardest things um especially for like you know first time first- time founders that haven't been through it. Um and even now after 30 years I think I'm marginally better at it than I used to be. Um but one of the things I think the the common mistakes uh entrepreneurs make in terms of kind of idea selection is that they they think it's a matter of like rigorous analysis that we're going to have this kind of 18 column spreadsheet that's going to give me all the coefficients out it's going to spit you know the best possible idea.
Original English
>> Yeah. The number of times I've seen the like US census file. Uh
Original English
>> yeah exactly like 18,000 lawyer law firms.
Original English
>> This is not relevant.
Original English
>> Yeah. Um and and just and what I've experienced and then uh not just me it's not just a data point of one but even you know talking to other founders um is that uh it's almost impossible to know a priority what the quality quote unquote of an idea is or it kind of probability of success um 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 often times or more often than not 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 um you know have some similar similarities maybe you know the gene pool of the original uh you know concepts are still there but um but it's different. So the so the kind of byproduct of that thinking is that um since you're unlikely to know um whether a given idea of a set of ideas maybe you're exploring is going to be good or not um then then the like 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 or um is or is not a good idea and should I be pursuing something something else. Um yeah
Original English
>> so I think that that still holds today. Okay, unless again 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? But that's you 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 uh with a customer. And you know, one of the things I'm a big believer in is kind of starting out with um and I'm not the only person that has uh said this by far, but it's sort of to narrow the aperture in the kind of early days to kind of focus in uh because that sort of increases your odds of of uh you know kind of getting kind of getting through and learning and you know mistake number two that uh entrepreneurs make is that they feel like they need to start with this massive you know TAM where it's like oh this can be a hundred billion dollar business like that's great that you have the kind of ambition and vision that this could 100, but like tell me what you're going to do in the first 30 days. Like what's the thing that you're actually $1 revenue first then let's get to $100.
Original English
>> And and I and like even now for me it's like as I explore new ideas uh you know within within HubSpot both for HubSpot next which is our innovation arm or even um new ideas within the core platform. It's like kind of narrowing that field of views like you know can we somehow like I think the the people that win are the ones that have the shortest uh iteration time and the cheapest learning time. So if you can sort of shorten that loop uh and learn less expensively uh whatever the lessons are going to be uh over over the fullness of time you end up and end up winning on average. Yeah.
Original English
>> Yeah. No, I I still think though I that this moment is the best possible moment for high agency people. And the reality is yes, there's it's way easier to build software, but there's only so many people who are sitting alone on, you know, 10:45 p.m. when we exchange an email on on Saturday night. you don't hack it on their computer and just go be that person and go build something cool. I I want to go to back to like what I I believe in the beginning of HubSpot you started with >> and correct me if I'm wrong a legal product. Um maybe there was a legal a legal product in there somewhere and somehow that has now become this CRM for small and mid-size businesses. I mean it's unbelievable what you guys have like expanded that wedge into. I'd love to hear how you guys thought about you know of 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.
Original English
>> Yeah. Um so when we first started you know we were in business school that's where my co-founder and I met um here on the east coast and the the thing we sort of ellighted upon was first the the kind of beauty of the SMB as a market. Um it's like it was underserved like and I'll give you the quick story here because it's it's interesting. So we had both been in software for a long time. you on the kind of uh marketing and sales side, my on the kind of product development engineering side. Uh and and we had both done enterprise software before. Uh so we sort of knew that. Um and the challenge with enterprise software was it's uh completely nonfun. Um as a startup entrepreneur, sales cycles are long. You get revenue concentration. You got a small set of customers kind of impacting your product roadmap and your vision and things like that. Um and and so that
Original English
>> so there's that. On the other end of the 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 biodal outcomes that says okay if you're successful it's going to be this massive outcome um 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 uh because you don't be a chunk kind of thing and the the beauty of SMB was um just from a pure market analysis perspective this is you know two guys in business school at the time it's like oh well SMB has like the beauty of enterprise in terms of you can actually charge money for 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 um so that was our kind of original thinking like, oh, if we were to do a startup like uh and so then our original idea that we took to the MIT 50K uh competition was um like ERP software like an oracle for small business. Y
Original English
>> um and the way this going back to the kind of narrow the aperture it's like okay well that seems like an interesting thing because you know we're going to this kind of transition from client server to to the web it's like like someone should create like an oracle for for small business that's everything's integrated kind of works together it's kind of built for SMB um and when we went to the business plan competition uh we said that's like too big let's narrow the aperture and let's call it legal spot uh the HubSpot company name had already existed but the thing we wrote the business plan around um 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 a narrow and you know back to the your original act like ah there's you know all the US census bureau things oh there's lots of them out there we can multiply x by y and it makes for great uh business school kind of spreadsheets um and poweroint decks
Original English
>> and so and so we did that and and uh you know we have a kind of propensity for kind of testing the waters and one thing we learned early on uh in that uh while we're still in business kind of noodling on the HubSpot idea is like that's not a fun market to sell into. Uh and as we talked to the law firms and we talked about, you know, ERP and what the solution, you know, would or could be, uh the the marketing and the website, all that was the part that was the most interesting to them.
Original English
>> Yeah. They're like, "Wait, hold on. Can you help me find more customers?"
Original English
>> Exactly. Yeah. I was like, "We got the 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 um for SMB or do we do this kind of marketing for for SMB and we chose we almost could have flipped the coin. We almost could have uh we we didn't we were you know a little bit more deliberate about it and we did extrapolate from a a minor set of data points but it was like life is short. Uh as it turns out lawyers uh are the second hardest market to sell into. Software developers being the hardest. Uh it's like
Original English
>> so now we're in uh you know navigating the SMB kind of marketing uh product. Of course that then morphs into you know more of a much more of a platform and a full CRM. Was that thoughtful from day zero? And I 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 voice products and I actually still think that's a huge opportunity for so many folks. Um I'm sure you're exploring that at HubSpot. uh or maybe there's there's some sort of support kind of chat, you know, interface >> and everyone of everyone always wants to end up being the hubspot for whatever use case, right? So maybe talk a little bit about how you you navigated that product journey and created the right the right loops to get to more of a platform from this initial wedge.
Original English
>> Yeah. So we started off as a um a suite of marketing applications and uh to answer your kind of um the first question, this was not at time t equals zero, we think we're going to be a CRM platform someday. that was not um it was not in any of our PowerPoint decks. It was um and and so yeah, we 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 um kind of product number two, right? Like the second actor or however one tends to phrase it. And we sort of hit that. So a couple things happened simultaneously. uh we were in the marketing software business and one of the things we sort of recognized is that being in the marketing software business um you know was very very close to you know sales and CRM that was the kind of the adjacent category so that kind of made logical sense. Uh the other thing that we sort of learned um you know once you know we had a bunch of customers is that we did a survey of our customers um this is you know maybe a couple years before the IPO um so maybe five six years into the company uh and just to see which CRM they were using and we discovered um that 20% um were using Salesforce.com uh another 20% were using some other CRM other than Salesforce.com.
Original English
>> Yeah.
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>> Uh but 60% were not using a CRM at all.
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>> Yeah.
Original English
>> 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, you know, companies. These are people paying us money um to generate leads. What's happening to those leads? Like if they're not where you put like what?
Original English
>> And so that was so the the thing that we sort of ellighted upon was like, okay, well >> like these companies should be using a CRM. So, you know, we're u my co-founder and I are very um weirdly s simple-minded. It's like, okay, well, why are they not using a CRM? It's like it's the categories exist. 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 uh overwhelming. They're just intimidated by the idea of a CRM. Uh it's too expensive. They think it's going to cost too much to kind of get going with a CRM. Uh 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 um the existing CRM players are likely going to get into the marketing space uh and we're going to have so even if we wanted to stay in in the marketing software category it's unlikely that we're going to be able to do that forever right so that all those things sort of converged around the same time period and so when we launched the CRM um you know we sort of addressed 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.
Original English
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. We were 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 premium, free. It's like, okay, well, and this this has been sort of the um 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 could obviously subsidize it with the kind of the marketing software business that we already had. Um but that that was the idea. It's like okay well then we've sort of removed the obstacles uh and then it's like let's get out there and then uh and then as we iterated we sort of learned um you know that in 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 like because CRM is almost by definition now um and even then um are platforms. So that that was a journey just going from product one to product two expanding out into a strategic adjacent thing.
Original English
But then and this is the other thing I think that carries over to um the entrepreneurs listening is that do what you can to solve like the whole customer problem uh like how however you define 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 um we had a very broad base of marketing applications and which goes against every piece of advice you get and that I've given it's like do one thing really really well. We did all the things. So we had content management and SEO and landing pages and forms or 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 and we still do the same thing now. It's like what's the actual problem we're trying to solve?
Original English
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 if 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 green field and you you try to win all these new businesses who have never adopted software before and I think uh the standard thinking on HubSpot is like oh well it was just like a very thoughtful from the beginning let you know let's go after the green field and the reality is it's like actually no like all of our customers just didn't have it and we built it and um it's totally fine if you do it in that order and you can still be a massive company if you if you nail it. Um, so interesting. How 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 role today where that eos you're 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.
Original English
>> Yeah. Uh and I've been a consumer of platforms and ecosystems for you know most of my professional career. So I sort of know what it's like on both sides. Um and this is no disparagement to any of the existing platforms then or now. But uh what tends to happen with um ecosystems and platforms is that um the platform providers will start um you looking to attract the developer ecosystem and and get people to build apps or build uh you know companies that are kind of adding value to the core platform. Uh but over time what ends up happening is that um either intentionally or or unintentionally they sort of kind of stomp over uh those developers. They'll close things up. They'll shut down and we saw this I can we can talk about this as story is 15 plus years old now like Twitter had this in the early days right they had the original Twitter was this kind of very open ecosystem. were a platform and we and and literally a thousand flowers bloomed back then. Lots of Twitter clients built lots of people um you know built uh products and and uh and companies uh on that original set of APIs. And it's not exclusive to Twitter. That's just what jumps to mind right now. But um but then they sort of closed it down and became you know everything from like developer unfriendly to almost developer hostile, right?
Original English
Um and so one of the things that I think this has kind of helped us build the ecosystem is that we've sort of take the taken those lessons to heart that says okay well let's be the platform that we wished would have existed for us back when we were doing you know very incendurary things like let's you know be the sort of carry that HubSpot brand of being kind of friendly likable um and that's like we're we're a we're red blooded capitalists uh we like to think of ourselves as like warm-hearted red-blooded capitalists like okay everyone's here to make money here's what we're doing and we try to be uh even with our uh with our partners uh try to be as open a book as we can be in terms of like okay here are things that we're 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 uh and that's worked so we've built trust um you know across a a wide pool of people now then some of it's just the uh you know building an ecosystem is a lot like building a product you have think of it that way is to say okay well in um 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 on with the HubSpot APIs to the oh I made my first dollar you know working with the HubSpot within the HubSpot ecosystem whatever that is can we compress that can we reduce the time to joy um you know for for that that class of customer yeah so
Original English
>> no to totally and uh no congrats on building such a thriving ecosystem. Maybe just transitioning a little bit now into, you know, the 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 uh with regard to the workflows that the the labs are kind of going after. And of course, there's many things inside of the HubSpot experience. I think that that those horizontal products are trying to pull in. Um and how you think about like the the area that by which you want to defend and and where you can kind of build the most durable value. would love your commentary on that.
Original English
>> Yeah, a few thoughts. Uh, one is I'm going to open this with a have a very very biased point of view. Uh, given that I'm co-founder CTO of HubSpot, >> that doesn't necessarily make me wrong. Um, >> so the a few thoughts. one is around um and we'll just talk more broadly and then we can kind of zero in on uh some of the specific things is that you know for those on the outside looking in um it's like it feels like and this is your kind of yellow brick uh road which I you know I love the essay the the idea and the analogy was you know very apt which is like there's this you know well praved shiny bright road that's kind of pointed to the emerald city or whatever how could you not like walk down it's like and it feels empty at the time right but you don't know that there's like a like a fleet of tanks coming down that road. Um and and they're getting faster. It's not that that they're even slow because they've invented this new thing that makes them even go fast. >> Um
Original English
>> and so and and this was kind of the premise of your essay, which I wholeheartedly agree with, is that uh yes, they're going to um they're going to barrel down that road. Um and it's it is a shiny nice road and and hence the trillion dollar um you know, valuations um and soon to be market caps. But uh but there's so much opportunity outside of that. And so here's like a I'm a framework kind of guy like here's a mistake I think entrepreneurs make on both sides of it. Uh one when they dismiss it they say oh well chat GPT doesn't do this or cloud co-work doesn't do that well we're going to do this we're going to fill this gap. Um and those are the ideas that uh make me nervous right because there's and there's two things sort of I think misguided about that thinking. One is if you can just append uh the word yet to it uh and it still holds water that's a problem. It's like, oh, Chad GPD can't do that yet. Does that ring true? If it sort of does, it's like, okay, well, that that's a problem. That's thing number one. >> Thing number two is what I think of as u measuring the product versus the company. It's like, oh, >> chat GPT 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? Um, you know, like, okay, maybe the road itself is getting wider. Fine. So maybe stay off the road, but maybe also stay out, 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 when you can and it's somewhat predictable. Um, so that's kind of thing number one is to make sure um that and and either, you know, pick things that the frontier model companies um either have a structural constraint uh that they just can't do regulatory wise, whatever it is, um or have a what I think of as like an incentive constraint.
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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 um any of the frontier model companies um I'll pick on Sam Alman since uh I'm an investor in OpenAI and and know Sam. It's like he could wake up tomorrow and say, you know, that CRM industry that looks awfully tempting and that uh you know three plus billion dollars of revenue that that HubSpot has, we're going to make it our mission or somebody within the company's mission to go 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 Enthropic or any of the frontier model companies, they're unlikely to do that. Uh and but that's what it would take to be able 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-training as as as you well know and so their whole business effectively now is um taking the capex that they've spent and the money they're continuing to spend and say how do we sell Infer how do we sell tokens how do we kind of monetize the thing that we've built? Yep.
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>> Awesome. uh it's a tale as old as time and they have two choices. Uh like 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 uh and even on the high end they'll say okay well we're going to go directly to Fortune 500 JP Morgans 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 FTEEs that can help us do that. Uh 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 uh you know SAS 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 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 consumer we want to own that we don't want other things you know people doing like a chat GPT equivalent uh we're going to own that >> but there's going to be lots of opportunity to say okay well think of um AI as infrastructure in the same way we thought of AWS and and cloud comput as infrastructure 15 years ago
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>> it's the exact same thing it's like and um and as entrepreneurs once again I'm biased but not wrong. I think it's less scary now to build um in and around uh kind of the AI arena than it was in 2023. And the reason I say that is back in 2023 um and I have, you know, very few uh uh rules for business. One is uh never own a restaurant. Number two is don't ever be a landlord and charge rent. And number three is never compete with Sam Alman. Um which I've accidentally done a couple times. Um but the the reality though is that at the time in 2023 if we take ourselves back um if I were a betting person I would have said they are just so far it was like they had figured out this kind of magic elixir or something like that. It's like I have no idea if anyone ever is going to be able to really solve it in the and and be able to pull all the things including the capex spend that was going to be necessary. Uh I was thankfully wrong about that.
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Like you know thankfully in terms of from entrepreneurs and from an ecosystem perspective because where things stand now is that um 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 even a fungibility perspective. Right now, you know, things like open router exist because it's easy to sort of swap out models back and even within HubSpot and most SAS companies are doing some form of uh use case decomposition and model routing to figure out what's the right model for the for this task. The byproduct of that is that like 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 uh supply chain power where like this one company controls the one crucial ingredient for you to build the 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. Um, 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 an AI native company.
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>> 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 it's also just that uh the advances or the advantages you're going to build is uh as a as a startup or as a HubSpot or whoever it is if you're not building a foundation model. It's you're actually you're 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 those uh you know those customers. And and the way that at least I think about it and of course I argue in this essay is like you know there's like 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 at 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 the advantages you're trying to to build in.
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>> Yeah, it it's compounding loops all the way down, Joe. Um, of course that's that's the the entire name of the game. Before AI, after AI, but um, a couple of things I'll say. So I'm going to rewind. Uh, I pushed one idea on on the stack. I'm going to pop it off and and talk through it. Is that so the you know, one of the questions we get, you know, back on the um, if you were an entrepreneur kind of evaluating the ideas. Um, it's like, okay, well, so today was uh, OpenAI's uh, dev day by the way. So, September 30th. So, you right before this call is uh our recording.
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>> What's that?
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>> I said we're dating the recording for for the the audience.
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>> So, you now know timestamped.
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>> Exactly. You know exactly when this is being recorded. Um so, and HubSpot launched our um we were the first, you know, CRM company to do so our connector to chat GPT over a year ago and we have some more one for Anthropic. And one of the questions, you know, 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 chatbt or through cloud co-work or something like that isn't that like just saying eroding the kind of long-term value and um I and I understand the reasoning my sort of counter that is that um like the interface matters uh 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 um let's say you look at something like an Uber Eats or a Door Dash 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 of 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 where the actual value is and that's the part that's sort of hard to displace. Um, there are other things where the 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.
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So, and and and I think most business applications actually sit more towards the Uber Eats kind of thing, right? Not in the sense that they have uh network effects like Uber Eats and Door Dash 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. Mhm. >> The only reason the interface is important to HubSpot is because uh marketers and sales people are trying to get something done or deliver on certain outcomes and the interface is the way but 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 you know you know HubSpot falls but I can guarantee you it does not fall in the the interface has you know 99% of the value and so my argument is that in the same way you know you know everything kind of comes back around again is that uh when when we saw the original kind of SAS development just moving to the kind of web- based application world we had the same kind of thing it's like okay well we have client server apps you know running on our desktops you know back in the day uh and then we had you know this browser thing come along the internet explorer and you know later Mozilla uh you folks uh know well um and it's like okay well now my software is running inside of a browser but as it turns out like Google did not own the entire application stack right there was an entire lots and lots of 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 19 uh million uh computers
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we have a similar thing now like and it's different right because uh the AI doing work. It's doing actual smart things. They can do more things. >> But if you just look at the kind of chat GPT and cloud cos >> 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 dev day and we saw it you know last year and we continue to see it's like oh they're going to increase the richness of what's available within chat GPT. they launched a you know this kind of go at it a marketplace for people to plug in a um you know in plug-in architecture and all those things which makes complete sense to me um so 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 um and then the other you know value that you can bring uh is around like what's the economic um you know best way, what's the lowest latency way, what's the lowest friction way to kind of accomplish those outcomes.
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Um and often like an LLM is very very good at lots and lots of things. It's the most you brilliant technology we've had in the history of humankind. But uh one of the things I've kind of gone record of saying is like anything that can be solved with a structured query deterministically, solve 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 uh from Ireland, >> you shouldn't have to troll through 8 million Slack messages and emails or whatever infer the answer. Yes, the data is probably there somewhere. >> Yeah. >> But that should be a database query that should not be uh you know, solved through inference and and throw a 300 IQ model at it.
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>> No, totally. And I I I think I think there's many companies that are navigating through this as they try to understand their own pricing and and consumption uh ideas here which could be its own dang podcast I think um for that matter. May 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 uh you know when we would benefit hindsight I don't know how you would revisit those. I'm 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 to be navigating all of this this information and you're storing that in a way that's intuitive to a human and so now we have these you know unbelievable 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 as as a as an executive at HubSpot.
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>> Yeah. Um couple things. one is you know so I'm a classically trained computer science software development nerd um forever and one of the things I'm a big believer in in terms of uh you know large scale software applications is around this notion of like frameworks and and starting with a set of primitives that you sort of evolve over time because that's the thing that gives you that's coming back to kind of uh compounding and leverage one of the things I've learned you know across um every company I've I've I've done and worked in is that you know software if you can kind of get those core primitives right um and then what you end up doing is sort um remixing and recomposing those uh 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 uh kind of operating system or operating framework that we had on which we built the marketing automation things like that. So when we went to product you know 2 3 4 or whatever like most of the value that we needed to bring to market already existed in the form of primitives like 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 marketing 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? Like and and so that part of it I think still holds true.
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Um 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 uh 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. It's like you just couldn't do anything with it. uh that was meaningful uh at any sort of uh well at any price actually back 10 years ago but now you can right so so now we revisit the primitives and say okay well we still need a structured data store um and I will uh you know happily debate this with whoever wants to debate it like there is still room whether it's relational some other there needs to be some persistent mechanism for storing kind of known facts uh and data some sort of system or record if you will uh alongside uh this kind of system we think of as a system of context which is this unstructured data and that's the thing that um we're sort of building out and the way I think this is going to evolve is um this notion of um and I use this term others use it too like a second brain or like an open like a >> can we put all the things that are happening um and and the the kind of the structure that likely makes sense um is some sort of graph structure can we store this in some sort of uh context graph another term that's um has been used and 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 and and get work done.
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So uh one thing that's interesting uh in terms of AI you didn't asked this question but uh it occurred to me as as we were chatting is that one of the things that's really beautiful about uh agentic coding now um is and this is particularly true for actually even more true for incumbents is 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 um deeper and do larger projects that you might not have otherwise considered. So what's possible now um 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 you know a fable 5.1 or like um six Astra um that's out now or 6.1 that's out now. Um 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 um to now say I want to 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 you know infinite possible universes thing or let's let's jump to that branch of the universe where we had made a different choice and then see what happens where we wind up and one of the advantages um you know companies like HubSpot have is that we have uh what people used to call unit tests uh and now show up as eval can we actually measure the viability of the thing that we just did 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 do we run this test now when new models come out. It's like okay well we can run our battery of evals across uh new models and say okay well here's a trade-off. Here's the economic value like we lose about 3% of quality points uh but we gain this much in terms of latency or or economic. We could do the same thing with testing these kind of theories like okay if we did rewrite this the whole thing in Rust I'm making that >> what what would it look like? what what what's the actual and you can you know test it uh now with small bodies of work. So >> anyway that's it's it's exciting. Uh
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>> I think this is such a fascinating topic. I I wrote a different essay um I think right around the same time I wrote the yellowbook road maybe a little bit before and I actually used workday as an example uh on this front but of just like hey you have to kind of start over to think about being AI native and here's all the here's all the advantages you have but here's all the disadvantages and so you know it's it's almost you know the 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 and driving these changes and so that I I love that example of like trying to think about these like alternative universes that you can Are there other processes that you're trying to create inside of HubSpot or teams you're trying to create in HubSpot or or or destroying bureaucracy? I'm just curious to hear what you're doing as a as a founder right now.
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>> Yeah. Um so we have a group within HubSpot um called HubSpot Next and the idea is it's it's a um effectively an innovation lab. So it's a it's a startup within a startup. Um 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 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 had cordoned off the team. Uh 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. Um and we've sort of carried that idea through now. And so um and the and uh and I've championed uh and led several of these projects over um over the years. And the one I'm working on right now literally every every single night um is a project called Uspot. Um and it's a oneperson CRM. It's a CRM for solopreneurs. That's the market. And this going back to the uh kind of narrow your um aperture of focus. But the HubSpot next projects have um 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. It's like I have this idea for a second brain, right? Like, oh, maybe a graph, you know, graph model works better. Maybe you plug in all the social media, everything that's coming in or whatever, and it's like, okay, well, let's test this in in Uspot because that's a much easier kind of faster paced way to test it. Um and so the product uh now is exactly 30 days old. Uh so
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congratulations on
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yeah and and it's and it's been fascinating um kind of learning and so the answer to the the original question is you know can something like that work? The answer is yes. um it it does work and I think um other entrepreneurs should kind of take away from um you know this is that so that that notion of having a second brain um that holds um and it 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 chat GPT and cloud corework are really bad at memory or whatever and this like
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>> yeah it's like it's going to get better
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>> don't solve that problem don't solve the horizontal use case or whatever but say hey within this class of customer here's is a class of problems that they have that would be benefited by thinking about this notion of having a second brain. What would the injection points be? How do you pull it together? What's the actual agents that you would produce or the work that you would kind sort of accomplish? But I think that underlying primitive um is actually a powerful one. I think it it it applies. Um so >> yeah. And then now that you I mean I think you spot so fascinating and I think it's very valuable for that particularly for this type of user. I mean it's it's what they they want of course. Yeah. um how do you then take those learnings and like productize them at the mothership if if at all and and what processes do you need to put in place to to make that happen?
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>> Yeah. Um the way we've done it which we you know we've kind of stumbled over the years and tried various mechanisms um is to kind of pull on that original thread of um this is a startup within a startup. So we do a couple of things. Um one is if the thing gets to scale uh and we've had this happen you know multiple times before. So, there was a product I launched a couple years ago called agent.ai. >> Uh, and agent.AI was a marketplace for AI agents, you know, back back in the day. This was one of my accidentally competed with Sam Alman uh stories. Although it was focused on go to market, it was uh two horizontal uh 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 uh kind of mix of deterministic nondeterministic um agents?" And what we discovered is that uh half of the idea was right uh but actually belonged and needed uh the full HubSpot team behind it. So we did a effectively an acquisition, right? So he's like 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 lives at right now. So in the US case, right? Like uh 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 uh HubSpot becomes a product of HubSpot. Um maybe we say, "Oh, well, the product itself still probably needs to be standalone or maybe the market doesn't work. Uh but the idea of a second brain maybe works and like here are the things in the ejection points that we think work for SMB uh and 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 it's a little bit like they're looking like at an aqua hire and it's literally like that. It's like, "Oh, here's what we can buy." Um, at the low low price of it's included.
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>> It's included. Yeah. [laughter]
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>> It's not It's not free. It's free. >> Exactly. It's free. Um, so yeah, that's and >> 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 you know the core core of 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 you know long said you know being a startup guy is that um the the issue that incumbents sort of hard to use uh incumbent when I refer to HubSpot now I still think of it in some way >> it's still a startup don't worry >> y um is that not the absence of something it's not like startups you know have something that um that the larger companies don't the issue is that >> is the kind of I'll call it baggage um 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 eval, you have, you know, 20 years of a code base that you can use as data to kind of inform the next product that you build. All this stuff is is actually an asset. So, if you can sort of shed the liabilities um and you know, 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 with a startup, we can just go off and do our thing, which we've been doing. Um, 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. So,
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>> it's so easy right now, especially with some of the the the national discourse to 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. Um, and I actually think you spot is a really good example of of this potential growth, right? It's like when in the 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 Uspot or or what you're seeing from from growth. It's just it's it's it is really amazing time to be alive.
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>> Yeah. Um so it's what's interesting like the I knew this to be the case but I wasn't sure to what degree. So as I mentioned the one thing I did differently with Uspot um versus prior kind of HubSpot next projects that I've done is I uh I monetized really early. Um, and part of it is not to kind of cover COGS or something like that. It's like 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 you know value people ascribe to this. That was part of it. So the thing I've been really surprised by is uh willingness of for people to put a credit card down on a consumptionbased model. Um like it's like nothing. I've I've launched lots of projects um you know over the years at HubSpot. This has been in that regard the most successful. So there's like this signal um out there um and part of it I think is just driven by you know the sheer numbers you know we'll bring the the US census data into this right now is that so in 2025 we had the most number of new company formation the United States has ever seen I think it was like 5.6 million closely on 6 million uh which is great uh this year we were already at four like by August um we were already over four million so it's going to be another record year so it's not like oh we had this onetime spike and now it's selling back in. So that's kind of fact number one that's super interesting. Uh fact number two that's even more interesting is the percentage of those new company formations that are expected to remain oneperson companies is the highest it's ever been and it's increasing and so the US censure actually tracks this data they say they put every new company into two buckets and they 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. Uh that percentage is now it's yeah over 70%. Um so so it's exciting. So there's this new market. Um and so for the entrepreneurs that are out there's a entirely and just like SMB was back when you know and everybody sort of uh pushed back on HubSpot back in the day. It's like oh you can't make money in SMB. It's so hard or no software company has ever other than into it has ever made a multi-billion dollar business in SMB. Um but you can it's like it's big enough. Yeah, there's going to be painful parts to uh you know those kinds of markets. But anyway, I'm I'm excited for that. I'm excited for excited for the economy. I'm excited for all the entrepreneurs that are going to be starting these millions of businesses or whatever. Um yeah, and and then excited for the entrepreneurs that build things for the for that market just like it's exciting all the way around. I'm uh yeah
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>> no I totally agree with this and and we we talk a bunch about uh you know aspects of this all the time and I think one of the one of the areas we've 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 uh you know interchange revenue and and I just don't know if people are fully appreciating the increase in in opportunity size as there's just so much more you can and and so many other ways you can you can offer value and and create value for your your small customer.
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>> This is yeah and this is my uh kind of counter to the >> sort of the the the SAS apocalypse um kind of idea is that the reality is that you know 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 it's not some new energy source it's it's software really smart software but software uh and what what has really happened now is like if you look at the class of problems um that software uh was designed okay I'm gonna I'm gonna take one minute because this is actually a good story only a handful of good stories so when we were first starting uh in the first year of HubSpot and we were out raising venture capital we said hey we're building this marketing software company um here's what we're going to do u and and the 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 um like that that's so we got two strikes like the SMB strike and the fact that we're doing marketing software and our argument at the time was the reason okay so if you look down the P&L of any uh any size business every line item on the on the P&L has a 100 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 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 and that's why a software company needs to didn't need to exist 5 years prior to HubSpot starting but now someone will build a massive uh you know marketing uh marketing software business.
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I'm going to make the same argument now that before there was a class of problems that software wasn't really equipped to solve. >> Yes. Now there is a massive set of these new problems uh 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 SAS in cloud-based things or whatever like that's the circle of life kind of thing but >> in aggregate the opportunity is bigger than we've ever like if you're anywhere near like software have the agency and and are entrepreneurial there's never been a better time to build a software company >> go right now do it
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yeah I totally agree with you this has been uh unbelievably fun I'm I'm I'm so grateful for your time. I'm going to end with a quick lightning round for you >> and we can go on on our merry ways.
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>> I'm not very fast on my feet, so there's only a few of these are softballs.
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Um, I'll start with a very easy one. I I I would assume Duncan or Starbucks.
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>> Uh, Duncan. Okay.
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>> But I don't drink coffee, by the way.
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>> Oh, wow. Okay. Well, then what what do you drink instead? Just only water. Are you a cyborg?
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>> Uh, just just what? Yeah. Wow. I gave up caffeine like years ago.
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So, anyway, even more impressive, Darm. Okay. Um, uh, Instinct or Muse? >> I'm sorry, what? >> Instinct or muse? You know, on the new, uh, the new agentic shopping experiences,
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>> I'm g have to say instinct.
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>> Okay, interesting. It, um, if you had to be an animal, which type would you be?
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>> I would still be a mammal. >> Maybe an elephant.
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>> An elephant. I like that. Okay, good. What's the most Boston thing about HubSpot?
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>> Um, almost everything. It's
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>> good good answer.
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>> Yeah. Um we're very pragmatic solve for the customer. Uh I I say that um we're sort of like a hybrid between like a some of the best of the kind of west coast uh kind of valley thinking in terms of uh ambition aggression but some of the pragmatism of the the east coast heads down just work at it grind.
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>> I love it. And then uh finally what's the best day you've ever had at HubSpot?
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about a week ago. Um it's like the things are starting to fall into place like both in my head and like it's just like okay I I can sort of see how this is unraveling. It's um yeah it's hard hard to explain. This is not something I'm going to be able to say but uh yeah it's
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>> oh that's so cool. I mean after however many years the be you know the best day was a week. I mean
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>> yeah but and I also say this more broadly um and I mean this like all things but um >> so the best time I've had even being a startup guy in the history um of HubSpot which is 20 years old now is the time I'm having right now. U and and the reason is and people like oh that can't possibly be true if you're it's like um 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 a um an IC, but um and the reason is that I have all the benefits of scale. You get a seat at the grown-ups table. You can make long-term bets. You can put, you know, you can like you can do things, but I have like another downside. I can do HubSpot, you know, next projects like Uspot or whatever. So, I have sort of the best of both worlds. Uh and it's so much fun right now. Yeah. So,
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>> it's awesome. Well, uh Darm, 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 enjoy.
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>> I look forward to the next time.
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>> Thank you.
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>> See you, buddy.