The Exchanges

Q what you said there about those challenges, they might try it. And we, we kind of, uh, chatted because I put a tweet out saying, uh, the biggest companies built in AI will actually be services companies helping integrate AI into large enterprises. Do you agree with that statement that services companies helping integrate AI into large enterprises will be some of the biggest winners of the next few years?

A I think services companies will definitely play a very important role. Um, for how long and how much of the cake they take versus application companies, your guess is as good as mine. Um, but I think especially in these early innings, the services companies are going to be the hand holders, right? They're going to help these enterprises Both with the technical know-how of, you know, for instance, how do you implement a vector database? What's the right embeddings model to use? How do you chunk your content, um, appropriately for the intended use case? How do you do citations? Like, these are all technical implementation details that actually matter a lot, right? To getting a useful solution. And short of having, uh, you know, a, a SI come in and help you, you build it, or having a really, really robust Uh, platform or solution, uh, that comes out of the box with all of these capabilities, which, you know, candidly, I don't think exists yet. I think enterprises are going to need some help, um, you know, figuring this out. Otherwise, you know, I've, I've seen some, uh, you know, go off and, and do this themselves and it's possible, but it's also a lot of, of heavy lift, right? It's a very uphill journey to go and gain the internal technical expertise, um, you know, to, to do this.

AI assessment note: “I think services companies will definitely play a very important role.”

Q How did you get Phantom to write a Series C check? He's incredible, but he writes Series A checks.

A I think we, we were at a very unique inflection point as Airtable And, uh, believed and still believe that there is a massive, uh, market ahead of us, right? And so, you know, I think what really matters in venture is, you know, what is the upside? What's the IRR potential for, for this investment? And, you know, if you're in a market where the biggest you can ever be is, you know, a hundred million dollar revenue, right? And then you're going to plateau. You know, it's hard to come in and get excited from an early stage returns profile standpoint, You know, if you're already investing at, you know, basically a valuation where that's priced in, um, you know, maybe you get a two X, three X on it. When we, uh, when we raised that realm, um, we were very much and still are at this early phase, this point of inflection where things were starting to work. We were starting to monetize. We were seeing a very quick ramp on the revenue growth curve. I think we went from, you know, one to ten million in revenue in a little over a year. Uh, we were well on track to multiple tens of millions. Um, and I think just the, the nature of the adoption, you know, we had everyone from talent farmers to law firms, to nonprofits, to agencies, but also really large enterprises starting to adopt Airtable and paying for us. So it just felt like a very large team, uh, that, you know, could easily, or cou…

AI assessment note: “could potentially have a hundred X even from, from that point”

Q what you said there about those challenges, they might try it. And we, we kind of, uh, chatted because I put a tweet out saying, uh, the biggest companies built in AI will actually be services companies helping integrate AI into large enterprises. Do you agree with that statement that services companies helping integrate AI into large enterprises will be some of the biggest winners of the next few years?

A I think services companies will definitely play a very important role. Um, for how long and how much of the cake they take versus application companies, your guess is as good as mine. Um, but I think especially in these early innings, the services companies are going to be the hand holders, right? They're going to help these enterprises Both with the technical know-how of, you know, for instance, how do you implement a vector database? What's the right embeddings model to use? How do you chunk your content, um, appropriately for the intended use case? How do you do citations? Like, these are all technical implementation details that actually matter a lot, right? To getting a useful solution. And short of having, uh, you know, a, a SI come in and help you, you build it, or having a really, really robust Uh, platform or solution, uh, that comes out of the box with all of these capabilities, which, you know, candidly, I don't think exists yet. I think enterprises are going to need some help, um, you know, figuring this out. Otherwise, you know, I've, I've seen some, uh, you know, go off and, and do this themselves and it's possible, but it's also a lot of, of heavy lift, right? It's a very uphill journey to go and gain the internal technical expertise, um, you know, to, to do this.

AI assessment note: “I think services companies will definitely play a very important role.”

Q my role in this As an investor, and they have these massive logos, your Walmarts, your Nestle's, your Coca-Colas, and you're like, wow, fuck. But truth be told, they're two seats in one department, in one office of, and actually it's 10 K spent for these enterprises, for them to test, see, it means nothing. I guess my question is, to what extent do I start taking those logos seriously?

A In my mind, uh, you know, in, in my crash course on, uh, enterprise that I've gained over the past 10 years of, of, uh, you know, of, you know, doing the PLG thing and then shifting into an enterprise, uh, centric model, I think a million dollar logo is really the, the, um, uh, the threshold of being kind of a real enterprise account. Now, you know, you could argue, like, there's a earlier safe milestone before that that's still meaningful. Like, you know, I, I would think Of even like, 250 K, 500 K as a meaningful milestone. Uh, but the truth is, what I've come to appreciate is that anything less than a million is really a spec of stand for a really large enterprise, right? Um, and frankly, if the million is just a starting point, I mean, you've got really large enterprise vendors like, uh, ServiceNow or Salesforce that literally are doing multi-deca million or even hundred million dollar Deals with, with some of their largest enterprises. And that's, that's where you're really powering a really critical part of, of the, um, uh, of how the enterprise runs, right? You know, to me, there's always a bigger fish, but, uh, uh, at least the way my, uh, my thinking is now, I think a million is, is kind of the real threshold at which you're at, you know, you're a, um, uh, a truly battle tested or value, like significant value delivery. Um, enterprise vendor.

AI assessment note: “I think a million dollar logo is really the, the, um, uh, the threshold”

Q Not at all, but I want to kick off today with a little bit on you. So tell me, how did you make your way into the world of startups? And really, how did you come to found the game changer that impacts definitely my life and so many more in the form of Airtable?

A Yeah. So I grew up in a family that had immigrated to the U.S. I'm actually Korean, but both my parents were born in China. And rather than, for some reason, instructing me to become a doctor or an engineer, et cetera, my parents, and especially my mom, really encouraged me to think about entrepreneurship, brought me books about Steve Jobs and Bill Gates. You know, Apple and Microsoft were kind of obviously the big companies when I was growing up in tech. And I just became enamored with this idea of creating technology that would kind of enable people and ultimately become a large business. And so, you know, that was always kind of my obsession growing up. And then throughout college, I learned how to build web apps and Learned more about this new genre of web companies, and ultimately decided to start a company right after college, went through YC for that one called eTax, very briefly kind of experienced that entrepreneurship experience, and then eventually was acquired by Salesforce after about a year. And I think that thereafter, I really kind of was able to go back and do it the second time around and think long and hard about the type of company I wanted to build for Airtable.

AI assessment note: “I really kind of was able to go back and do it the second time”

Q competition levels there from startup to large, large incumbents. Can I ask, with the massive rise in the amount of people building tools oriented maybe towards collaboration, remote work, and work from home, do you think we'll enter this kind of consolidatory period where incumbents buy up a generation of those companies? Do you think we'll see a graveyard of them? How do you think this rise will play out?

A I think there's two tensions. One is that optimistically, I do think this is just an overall area that is seeing a secular trend upwards. Right. I think it's a massive growth opportunity. It's not just everyone zero sum game fighting over a small amount of, you know, kind of users who are either going to use one tool or another, but a lot of these tools are actually quite additive in nature. I think you see not just tools trying to go and replace office three 65 or word documents, but also like tools that are doing completely new things, right? Like guru is this real Knowledge management and kind of in some parts like a wiki, but also like knowledge discovery. And so I think like, especially since in SAS and these productivity or utility oriented areas, like there's no upper bound to how many new services can come out and create additive value. Like with consumer social, for instance, there was a finite amount of time, eyeballs, et cetera, that ultimately all of the companies were competing for between the peaches and the paths and the vines of the world. You only have so much time as a consumer to spread around to these products. And ultimately only somebody advertising dollars will go to the platforms. But I think with this space of like utility oriented products, I think there's no upper bound. And I think we can actually see a lot of these different companies coexist. On th…

AI assessment note: “I think we can actually see a lot of these different companies coexist.”

Q I always love to start with, like, founding stories, but I wanted to do something a bit different today. I wanted to start with, if you could cool yourself up the night before you started Airtable and gave yourself a piece of advice, what would you tell yourself?

A The thing about advice is it's always, uh, twenty-twenty in hindsight. Um, so there, there's a million little things that I would tell myself, but I think, I think the biggest one is, you know, it's really important to think not just about, Product market fit. You know, every first-time founder is concerned about product market fit. And there's this adage that like, you know, a second-time founder thinks about distribution. My take on it is a little bit more nuanced, which is it's still product market fit, but it's about figuring out the right product strategy that marries with an effective go-to-market model that lends well to that product, right? So certain products work well in a bottoms-up, viral, you know, organically adopted way. Certain products are single-user versus team-centric. You know, accordingly, I think you need to design a go to market model, whether it's outbound sales or performance marketing or organic and viral growth, um, that really pairs well with, with that particular product dynamic. In hindsight, we didn't think enough about go to market model, uh, in the early days of the company, we just focused on building a good product and, you know, happily and luckily that was good enough to get us to the next phase where we did start thinking about go to market. But I think it's something that, that, uh, we could have thought about A lot more.

AI assessment note: “the biggest one is, you know, it's really important to think not just about, Product market fit”

Q If you hadn't thought about it a lot more, what would you have done differently? Because to the outside world, it seems like a perfectly executed PLG strategy. What would you have done differently had you hadn't thought about it?

A I think one of the differences was, you know, we built the product with the ability to become team-centric. So we built, you know, we spent a lot of time engineering the backend to be real-time collaborative in nature, which was not a small technical feat. We thought about the team-centric use cases Uh, and when we started putting out templates, this was a little after we launched initially, you know, we built, uh, some templates that were more solo user centric, some that were more team centric. In hindsight, you know, I wish we had put even more emphasis on the team scale use cases, and especially those use cases that, that involved larger teams, right? I think we got to those sort of organically, but it was a little bit more, um, diffuse. So early on, we got a very large range of different adoption. And, um, I wish we had guided our adoption more and earlier towards the team-centric use cases with the anticipation that those would be the ones that, um, A, monetize better, uh, B, uh, you know, lend to more, uh, you know, more go-to-market models, right? You know, if you're taking a single user product out to market, um, it's just harder to make performance marketing work. It's harder to make, you know, you can't really make outbound sales work, right? The economics of, You know, pitching a single user who pays a single and relatively small dollar cost to you is just hard. So …

AI assessment note: “I wish we had put even more emphasis on the team scale use cases”

Q founders who say we have a horizontal product, similar in the way that Airtable is, so many different use cases. Should we go for two or three verticals and product market aggressively towards them, or should we let a thousand flowers bloom and And just let the world try our products and be much more horizontal. What advice would you have for those founders? Because I never know the answer.

A Uh, I don't think it's, it's for lack of a good thinking from you. Um, I think it's a genuinely tricky question. Uh, there's nuances, right? You know, some horizontal products, uh, are actually, you know, a vertical of their own, right? When I think about, you know, a Slack or a Dropbox, I think they actually fall into a very well-defined category in my mind. Like, You know what you're going to use Slack for. You know what you're going to use Dropbox for. So even though they're not function or industry specific, they kind of occupy a well-defined category of their own, right? You know, you know, you're going to do chat and, and communication on Slack. You know, you're going to do file sharing on Dropbox. Um, I think for, for other products where the use cases are not as self-evident, um, the importance of verticalization, especially early on is more important. Um, it's kind of the, the crossing the chasm versus inside the tornado metaphor where early on, I think, especially when the market is still trying to figure out what is this thing? Um, you know, it's, it's helpful to really go deeper into a few different use cases and make sure you fully solve those while at the same time, preserving the optionality of the longterm, you know, not over committing the platform or the product roadmap in such a way where you're, you're so brittle, you're so hard coded for those narrow use ca…

AI assessment note: “especially early on... it's helpful to really go deeper into a few different use cases”

Q Speaking of it getting really interesting, we first kind of reconnected and decided to do this next discussion because of a tweet that I did on AI and essentially how it's integrated into enterprise. I want to start with kind of a thread, so to speak, and it's why are advancements in AI as significant as the introduction of cloud computing?

A Yeah. I mean, I, I would even venture to say they're, they're, uh, they're different, but potentially, uh, going to be more profound. And I think the reason for that is, you know, the, the benefits of cloud compute are, are pretty easily grokkable, right? Um, you don't have to manage your own servers. There's infinite scalability, you know, as hardware costs go down, you kind of instantly realize the benefits of that, right? Like we just pay our AWS bill every month and You know, over time, over the long term, you get more compute, more scalability for cheaper, right? And you get more and more resources that are provided that solve a lot of not just, you know, physical headaches with manager hero servers, but even software headaches increasingly, right? They give you architecture out of the box. So by all means, there's a lot of power and value to the cloud compute model. I think AI, while still in its infancy, and especially LLMs, are going to be profound in a very different way, which is You know, when you think about the broad range of knowledge work that's done today, you know, every, every, uh, function, right? Whether it's legal or finance or even the more creative functions, marketing, et cetera, you know, you can just see the glimmers starting to emerge of how a really, really broad set of work can be automated or accelerated with AI, with especially Gen AI. Um, you kno…

AI assessment note: “a really, really broad set of work can be automated or accelerated with AI”

Q What are the hardest things about the transition to enterprise, Howie? You're the PLG kind of glory child. Making the transition to enterprise is no mean feat. What are the hardest parts?

A Going back to the, one of the early questions you asked, um, you know, I think it comes down to product go-to-market model alignment. Um, meaning, you know, you can have a product that's amazing, uh, you know, for, let's say, individual users or small teams. And thankfully, Airtable Was always built to be at least team capable from early on. But, you know, let's just say like hypothetical product, uh, X, you know, product X is purely for individual usage. There's no team collaboration built in, at least from, from day one. And you get all this viral adoption or just all this, this top of funnel adoption for this product X. But, you know, at some point when you try to go into enterprise, you know, it becomes really tough to sell the value on X. To a senior buyer within the enterprise, um, if its value is only experienced by individuals, right? And then you have to do a productivity sale, which is to say like, you go and you say, well, like every person that uses X gets 10% more productivity, right? Or saves two hours a week, or whatever it may be, or they like it. And you should pay more money for this, right? Or buy it for more people. And maybe that works. Although I think in, in, um, uh, increasingly in this environment where Every enterprise is trying to rationalize their tool set, right? They don't want to have, you know, a million different products. I mean, some enterpris…

AI assessment note: “I think it comes down to product go-to-market model alignment.”

Q What's been your biggest lesson from angel investing?

A You know, I think, um, it's, it's that everything looks easier from the outside. You know, when you're a startup founder, it can feel very lonely because you feel like, oh man, everything's so hard and there's so many things we have to figure out. I mean, you look at other companies and if you're only reading what they put out on, you know, press releases and the big announcements and so on, everything looks like it's just so easy. And I think when you come to appreciate when you invest in companies and you're kind of plugged into the community, it's like everybody is, um, you know, got, Got, uh, challenges, right? Like every, it's never this perfectly smooth sailing, um, the whole way at least, right? Maybe there are easier and harder phases, uh, but I think I've just come to, uh, both, uh, empathize with, uh, with every other factor going and figuring things out, especially from the early phases, um, but also normalize that experience for myself.

AI assessment note: “it's that everything looks easier from the outside.”

Q What's the biggest piece of startup advice that you hear that you think is bullshit?

A It's this idea that, you know, if you just find product market fit, all else is, is gravy, right? I think like product market fit is just the beginning. And there are so many more hard parts of, of building a business. Now for sure, like you, you shouldn't have to worry about, you know, like setting up, um, you know, kind of every A bit of like legal infrastructure before you found product market fit. I feel like there's this, uh, you know, mentality or myth that, you know, it, the hardest part is that first phase where you're chasing product market fit. And once you see the takeoff trajectory, you know, that, that's, you know, everything's a downhill battle from there. And in truth, uh, you know, at least in my experience, like that's when the real fun and learnings, but also the challenges really start to emerge, like to build a real business and to steal it.

AI assessment note: “It's this idea that, you know, if you just find product market fit”

Q If you hadn't thought about it a lot more, what would you have done differently? Because to the outside world, it seems like a perfectly executed PLG strategy. What would you have done differently had you hadn't thought about it?

A I think one of the differences was, you know, we built the product with the ability to become team-centric. So we built, you know, we spent a lot of time engineering the backend to be real-time collaborative in nature, which was not a small technical feat. We thought about the team-centric use cases Uh, and when we started putting out templates, this was a little after we launched initially, you know, we built, uh, some templates that were more solo user centric, some that were more team centric. In hindsight, you know, I wish we had put even more emphasis on the team scale use cases, and especially those use cases that, that involved larger teams, right? I think we got to those sort of organically, but it was a little bit more, um, diffuse. So early on, we got a very large range of different adoption. And, um, I wish we had guided our adoption more and earlier towards the team-centric use cases with the anticipation that those would be the ones that, um, A, monetize better, uh, B, uh, you know, lend to more, uh, you know, more go-to-market models, right? You know, if you're taking a single user product out to market, um, it's just harder to make performance marketing work. It's harder to make, you know, you can't really make outbound sales work, right? The economics of, You know, pitching a single user who pays a single and relatively small dollar cost to you is just hard. So …

AI assessment note: “I wish we had guided our adoption more and earlier towards the team-centric use cases”

Q founders who say we have a horizontal product, similar in the way that Airtable is, so many different use cases. Should we go for two or three verticals and product market aggressively towards them, or should we let a thousand flowers bloom and And just let the world try our products and be much more horizontal. What advice would you have for those founders? Because I never know the answer.

A Uh, I don't think it's, it's for lack of a good thinking from you. Um, I think it's a genuinely tricky question. Uh, there's nuances, right? You know, some horizontal products, uh, are actually, you know, a vertical of their own, right? When I think about, you know, a Slack or a Dropbox, I think they actually fall into a very well-defined category in my mind. Like, You know what you're going to use Slack for. You know what you're going to use Dropbox for. So even though they're not function or industry specific, they kind of occupy a well-defined category of their own, right? You know, you know, you're going to do chat and, and communication on Slack. You know, you're going to do file sharing on Dropbox. Um, I think for, for other products where the use cases are not as self-evident, um, the importance of verticalization, especially early on is more important. Um, it's kind of the, the crossing the chasm versus inside the tornado metaphor where early on, I think, especially when the market is still trying to figure out what is this thing? Um, you know, it's, it's helpful to really go deeper into a few different use cases and make sure you fully solve those while at the same time, preserving the optionality of the longterm, you know, not over committing the platform or the product roadmap in such a way where you're, you're so brittle, you're so hard coded for those narrow use ca…

AI assessment note: “importance of verticalization, especially early on is more important”

Q Speaking of it getting really interesting, we first kind of reconnected and decided to do this next discussion because of a tweet that I did on AI and essentially how it's integrated into enterprise. I want to start with kind of a thread, so to speak, and it's why are advancements in AI as significant as the introduction of cloud computing?

A Yeah. I mean, I, I would even venture to say they're, they're, uh, they're different, but potentially, uh, going to be more profound. And I think the reason for that is, you know, the, the benefits of cloud compute are, are pretty easily grokkable, right? Um, you don't have to manage your own servers. There's infinite scalability, you know, as hardware costs go down, you kind of instantly realize the benefits of that, right? Like we just pay our AWS bill every month and You know, over time, over the long term, you get more compute, more scalability for cheaper, right? And you get more and more resources that are provided that solve a lot of not just, you know, physical headaches with manager hero servers, but even software headaches increasingly, right? They give you architecture out of the box. So by all means, there's a lot of power and value to the cloud compute model. I think AI, while still in its infancy, and especially LLMs, are going to be profound in a very different way, which is You know, when you think about the broad range of knowledge work that's done today, you know, every, every, uh, function, right? Whether it's legal or finance or even the more creative functions, marketing, et cetera, you know, you can just see the glimmers starting to emerge of how a really, really broad set of work can be automated or accelerated with AI, with especially Gen AI. Um, you kno…

AI assessment note: “they're different, but potentially, uh, going to be more profound.”

Q What are the hardest things about the transition to enterprise, Howie? You're the PLG kind of glory child. Making the transition to enterprise is no mean feat. What are the hardest parts?

A Going back to the, one of the early questions you asked, um, you know, I think it comes down to product go-to-market model alignment. Um, meaning, you know, you can have a product that's amazing, uh, you know, for, let's say, individual users or small teams. And thankfully, Airtable Was always built to be at least team capable from early on. But, you know, let's just say like hypothetical product, uh, X, you know, product X is purely for individual usage. There's no team collaboration built in, at least from, from day one. And you get all this viral adoption or just all this, this top of funnel adoption for this product X. But, you know, at some point when you try to go into enterprise, you know, it becomes really tough to sell the value on X. To a senior buyer within the enterprise, um, if its value is only experienced by individuals, right? And then you have to do a productivity sale, which is to say like, you go and you say, well, like every person that uses X gets 10% more productivity, right? Or saves two hours a week, or whatever it may be, or they like it. And you should pay more money for this, right? Or buy it for more people. And maybe that works. Although I think in, in, um, uh, increasingly in this environment where Every enterprise is trying to rationalize their tool set, right? They don't want to have, you know, a million different products. I mean, some enterpris…

AI assessment note: “I think it comes down to product go-to-market model alignment.”

Q How long did it take you to get in a million ARR contracts?

A I think it happened fairly early for us. Um, I would, I think probably 2019 roughly. So maybe a year after we got our unicorn valuation, um, you know, that was four years after launch admittedly, and we had gotten a lot of PLD adoption. Uh, we were well at the, the, you know, mid to high tens of millions in revenue. I, um, I believe certainly it wasn't like we, we got A million dollar contract right away. And especially given the nature of how our product was adopted, like we got there because we had this groundswell of organic momentum within these larger enterprises. And by then, you know, there were many fortune 500 that already were using air cable to the tune of thousands of active users who were easy to monetize.

AI assessment note: “I think probably 2019 roughly. So maybe a year after we got our unicorn valuation”

Q Yeah, and now not only are they not adding more seats because the teams aren't growing, but they're also wanting data to prove ROI, to prove usage, to prove value, and it's actually changing how he structures his teams because they have to be much more CS heavy Uh, in particular. Do you agree with that? And are you seeing the same?

A You know, we touched on the, the tool rationalization before, and I think it makes sense. I mean, in a way it's, it's interesting now, you know, uh, when you operate a company at scale, you start to realize how much macro plays into enterprise behavior and therefore your, your own execution behavior, right? When interest rates were low and every company was, um, you know, going on a little bit of a binge. Uh, spending across the board, uh, but including, you know, software where, you know, maybe there was a rational argument for it during COVID. Every company had to digitize their workforce really quickly, shift into remote work, figure out how to enable company, you know, enable their workforce to be effective, even when they weren't in office and they had to disrupt how, how they worked. Um, so that, you know, there was kind of this massive groundswell of adoption and just, you know, dollars being thrown at a lot of different products, right? I think now there is a very understandable rationalization of, wait a second, we kind of had to go during the mad rush over the past few years of adopting tech, spending on tech, um, and also, you know, less budget sensitivity. We adopted all these products and now we're feeling, you know, a little fool. We've gorged ourselves and we have to go in and understand what product is added, what value, which ones are duplicitous, Or duplicativ…

AI assessment note: “we touched on the, the tool rationalization before, and I think it makes sense.”

Q What's been your biggest lesson from angel investing?

A You know, I think, um, it's, it's that everything looks easier from the outside. You know, when you're a startup founder, it can feel very lonely because you feel like, oh man, everything's so hard and there's so many things we have to figure out. I mean, you look at other companies and if you're only reading what they put out on, you know, press releases and the big announcements and so on, everything looks like it's just so easy. And I think when you come to appreciate when you invest in companies and you're kind of plugged into the community, it's like everybody is, um, you know, got, Got, uh, challenges, right? Like every, it's never this perfectly smooth sailing, um, the whole way at least, right? Maybe there are easier and harder phases, uh, but I think I've just come to, uh, both, uh, empathize with, uh, with every other factor going and figuring things out, especially from the early phases, um, but also normalize that experience for myself.

AI assessment note: “it's that everything looks easier from the outside.”

Q How did you get Phantom to write a Series C check? He's incredible, but he writes Series A checks.

A I think we, we were at a very unique inflection point as Airtable And, uh, believed and still believe that there is a massive, uh, market ahead of us, right? And so, you know, I think what really matters in venture is, you know, what is the upside? What's the IRR potential for, for this investment? And, you know, if you're in a market where the biggest you can ever be is, you know, a hundred million dollar revenue, right? And then you're going to plateau. You know, it's hard to come in and get excited from an early stage returns profile standpoint, You know, if you're already investing at, you know, basically a valuation where that's priced in, um, you know, maybe you get a two X, three X on it. When we, uh, when we raised that realm, um, we were very much and still are at this early phase, this point of inflection where things were starting to work. We were starting to monetize. We were seeing a very quick ramp on the revenue growth curve. I think we went from, you know, one to ten million in revenue in a little over a year. Uh, we were well on track to multiple tens of millions. Um, and I think just the, the nature of the adoption, you know, we had everyone from talent farmers to law firms, to nonprofits, to agencies, but also really large enterprises starting to adopt Airtable and paying for us. So it just felt like a very large team, uh, that, you know, could easily, or cou…

AI assessment note: “could potentially have a hundred X even from, from that point.”

Q What's the biggest piece of startup advice that you hear that you think is bullshit?

A It's this idea that, you know, if you just find product market fit, all else is, is gravy, right? I think like product market fit is just the beginning. And there are so many more hard parts of, of building a business. Now for sure, like you, you shouldn't have to worry about, you know, like setting up, um, you know, kind of every A bit of like legal infrastructure before you found product market fit. I feel like there's this, uh, you know, mentality or myth that, you know, it, the hardest part is that first phase where you're chasing product market fit. And once you see the takeoff trajectory, you know, that, that's, you know, everything's a downhill battle from there. And in truth, uh, you know, at least in my experience, like that's when the real fun and learnings, but also the challenges really start to emerge, like to build a real business and to steal it.

AI assessment note: “this idea that, you know, if you just find product market fit, all else is, is gravy”

Q What do you know now that you wish you'd known when you started?

A I think it's really about, um, you know, thinking out on, uh, on, on longer timescales. Uh, you know, we were always a very patient company. AirTable took two and a half years to build the product before we even launched. But what I wish I had done more of was not only have that patience, be willing to think on, you know, ten-year-long time horizons, but actually be more measured. About holding ourselves to certain goals along each of the, you know, add milestones along that way. So, um, I remember, I don't know if it's true, completely true or not, but I remember, uh, you know, LinkedIn supposedly had put out a business plan before they started. Um, I think Reid Hoffman had wrote, wrote, uh, written this, this, uh, this plan and, you know, it had like MAU counts and revenue goals and, and, uh, and just in full detail, Um, and in exactly the right chronological order, um, you know, they spelled out. Here's what we're gonna be five years in. Here's what we're gonna be seven years in. Like the MBA's dream of a business plan, right? So it's like the next, you know, 10 years of growth expectation and, you know, product execution expectation in. And usually that never works, right? Like when you try to predict the past of a company, it's like everything is volatile. You're not, you know, there's so many things out of your control. But apparently, in their case, it actually worked su…

AI assessment note: “what I wish I had done more of was not only have that patience”

Q And then the final one, and the most exciting for me, definitely, what do the next five years hold for you and for Airtable? Can you paint that vision for us?

A Airtable is really trying to be a software creation platform. And when we first launched, I think a lot of people looked at it and said, hey, this thing looks like a spreadsheet, or maybe even like a Database, you know, Microsoft Access or FileMaker that's been modernized and now is web and collaborative based. But really, we've always been driving towards being this true application building platform. And the way that people use Airtable today even is more app-like. I mean, they're building really complex, robust use cases on top of Airtable with like sometimes thousands of fields, many dozens of tables, and lots of like sophisticated collaboration on it. And I think the next five years are really about us Taking that starting point and really further bolstering and extending what you can build on top of Airtable. And namely, I think to offer more layers of customization into the platform itself so that when it's all said and done in five years, you're able to build apps that no longer just look like a spreadsheet and no longer just behave like a spreadsheet. There's going to be a lot more integrations built in or ways to build integrations into Airtable and customize even the interface and Make it a lot more dynamic. And then on the personal side, I think for me, like, you know, so much of my passion in mindshare is totally, you know, kind of imbued in Airtable, and it's hard…

AI assessment note: “I think the next five years are really about us Taking that starting point”

Q Not at all, but I want to kick off today with a little bit on you. So tell me, how did you make your way into the world of startups? And really, how did you come to found the game changer that impacts definitely my life and so many more in the form of Airtable?

A Yeah. So I grew up in a family that had immigrated to the U.S. I'm actually Korean, but both my parents were born in China. And rather than, for some reason, instructing me to become a doctor or an engineer, et cetera, my parents, and especially my mom, really encouraged me to think about entrepreneurship, brought me books about Steve Jobs and Bill Gates. You know, Apple and Microsoft were kind of obviously the big companies when I was growing up in tech. And I just became enamored with this idea of creating technology that would kind of enable people and ultimately become a large business. And so, you know, that was always kind of my obsession growing up. And then throughout college, I learned how to build web apps and Learned more about this new genre of web companies, and ultimately decided to start a company right after college, went through YC for that one called eTax, very briefly kind of experienced that entrepreneurship experience, and then eventually was acquired by Salesforce after about a year. And I think that thereafter, I really kind of was able to go back and do it the second time around and think long and hard about the type of company I wanted to build for Airtable.

AI assessment note: “decided to start a company right after college, went through YC for that one”

Q incumbent versus startups, and then the other is in terms of, like, actually normal company world. Big toy company, startup toy company. If we start in the traditional tech world, who wins, like, who does AI favor more? Does it favor more? Adobe or does it favor the next generation creative cloud company? Does it favor Airtable or the, you know, AI first Airtable from two months ago in YC?

A One thought I have is it grows the entire pie. Um, when you think about like Microsoft's co-pilot offering, it's going to add significant ARPU to every single seat of office, which is a massive install base, right? So It's actually growing the pie of dollars, um, because it's creating new economic value in the world, right? So we're actually expanding GDP by enabling people to be more productive, um, and, and creating a new market. You know, first, um, I don't think it has to be purely a, you know, winner takes all, you know, Adobe wins and Canva loses type of equation, right? I think AI could actually enable both Adobe and Canva to grow and to actually create disruptive experiences that, Both deepen the, the value crop. I mean, generous still, for instance, in Adobe is amazing, right? It's amazing for existing Photoshop users in a way that I think, uh, you know, I personally would be willing to pay a lot more money for. Um, so probably, you know, lots of monetization upside there. You know, some of the AI capabilities are also going to be amazing from the standpoint of creating disruptive, uh, capabilities that, that, uh, that open these products up to new user basis, right? And even new use cases. And that's where Uh, you know, potentially the startups, um, or the, uh, the newer companies that have more ability to, uh, to lean into the tech and kind of build products, um, wit…

AI assessment note: “I don't think it has to be purely a, you know, winner takes all”

Q my role in this As an investor, and they have these massive logos, your Walmarts, your Nestle's, your Coca-Colas, and you're like, wow, fuck. But truth be told, they're two seats in one department, in one office of, and actually it's 10 K spent for these enterprises, for them to test, see, it means nothing. I guess my question is, to what extent do I start taking those logos seriously?

A In my mind, uh, you know, in, in my crash course on, uh, enterprise that I've gained over the past 10 years of, of, uh, you know, of, you know, doing the PLG thing and then shifting into an enterprise, uh, centric model, I think a million dollar logo is really the, the, um, uh, the threshold of being kind of a real enterprise account. Now, you know, you could argue, like, there's a earlier safe milestone before that that's still meaningful. Like, you know, I, I would think Of even like, 250 K, 500 K as a meaningful milestone. Uh, but the truth is, what I've come to appreciate is that anything less than a million is really a spec of stand for a really large enterprise, right? Um, and frankly, if the million is just a starting point, I mean, you've got really large enterprise vendors like, uh, ServiceNow or Salesforce that literally are doing multi-deca million or even hundred million dollar Deals with, with some of their largest enterprises. And that's, that's where you're really powering a really critical part of, of the, um, uh, of how the enterprise runs, right? You know, to me, there's always a bigger fish, but, uh, uh, at least the way my, uh, my thinking is now, I think a million is, is kind of the real threshold at which you're at, you know, you're a, um, uh, a truly battle tested or value, like significant value delivery. Um, enterprise vendor.

AI assessment note: “I think a million dollar logo is really the threshold of being kind of a real enterprise account.”

Q Howie, I had email at stability on the show a while ago, and he said that enterprise will adopt AI next year, and when they do, it will be a freaking train. If we break that up into two separate parts, um, do you agree that enterprises will adopt AI en masse next year? And how do you think about that timing?

A Personally, I don't know if there's anything particularly special about next year. I mean, I think, um, every month, That goes by enterprises are getting more savvy about, uh, about AI. You know, I'm seeing it in my conversations, uh, with enterprises, you know, today versus three or six months ago. Um, there is this, this constant and kind of rapid, uh, progression of, of savviness, right? Understanding, you know, what are the types of use cases that we as an enterprise should deploy AI into first? Lower stakes, higher upside, Easier to, to get, you know, some product into our, our, uh, our workforces and, um, and start experimenting with, I see this as more of a, um, uh, you know, kind of a agile or an iterative approach to, to, uh, productization, right? Uh, whether that productization is done by the enterprise themselves or with the help of an SI or, um, you know, by startups, uh, or existing software vendors that are going to provide AI powered solutions into the hands of the enterprise. To me, it's, it's a, um, it's a feedback loop. And, you know, as we go and see what works in the enterprise, and Airtable is definitely, you know, leaning very much into this mentality, you know, we don't think we can predict exactly what the killer use cases are going to be. I mean, there are some known use cases that are going to be valuable, but we think it's too early to really know ev…

AI assessment note: “Personally, I don't know if there's anything particularly special about next year.”

Q incumbent versus startups, and then the other is in terms of, like, actually normal company world. Big toy company, startup toy company. If we start in the traditional tech world, who wins, like, who does AI favor more? Does it favor more? Adobe or does it favor the next generation creative cloud company? Does it favor Airtable or the, you know, AI first Airtable from two months ago in YC?

A One thought I have is it grows the entire pie. Um, when you think about like Microsoft's co-pilot offering, it's going to add significant ARPU to every single seat of office, which is a massive install base, right? So It's actually growing the pie of dollars, um, because it's creating new economic value in the world, right? So we're actually expanding GDP by enabling people to be more productive, um, and, and creating a new market. You know, first, um, I don't think it has to be purely a, you know, winner takes all, you know, Adobe wins and Canva loses type of equation, right? I think AI could actually enable both Adobe and Canva to grow and to actually create disruptive experiences that, Both deepen the, the value crop. I mean, generous still, for instance, in Adobe is amazing, right? It's amazing for existing Photoshop users in a way that I think, uh, you know, I personally would be willing to pay a lot more money for. Um, so probably, you know, lots of monetization upside there. You know, some of the AI capabilities are also going to be amazing from the standpoint of creating disruptive, uh, capabilities that, that, uh, that open these products up to new user basis, right? And even new use cases. And that's where Uh, you know, potentially the startups, um, or the, uh, the newer companies that have more ability to, uh, to lean into the tech and kind of build products, um, wit…

AI assessment note: “I don't think it has to be purely a, you know, winner takes all”

Q be considered the incumbent if we're being blunt. Are you able to move as fast as startups are? Everyone always says with incumbents, well, they can't move as fast. They have the distribution, but they don't have the speed. When we look at Adobe speed of execution, Google in many ways speed of execution, for you as Airtable State, do you think you can move as fast as startups can?

A Yeah. So the short answer is yes. And I think it's, it's sometimes a rational choice that every company, and you know, I think it's really a gradient. It's a spectrum of how much of an incumbent versus an upstart you are. And you know, like in, in all spirit of, uh, humility, I would put us very much still on the upstart. Uh, side of the equation, you know, I think, um, any company sub one billion in revenue is, is, uh, is an upstart compared to the enterprise type, you know, whether you're Salesforce or service now, or obviously, um, you know, the, uh, the big thing companies, we're just still operating at a much smaller, leaner scale than those companies. So I like to think, first of all, that, that, that we do have a higher pace of execution velocity than a very, very large company. But I also think, um, you know, within our table, There is this conscious choice that we always have to make of, you know, we, we still have a finite number of resources, right? We may have raised over a billion in capital. We may have, you know, many more employees than we did when we started the company at two and the three and the, you know, five people, but there's always resource scarcity. And, and so I think it's, it's always this question of, okay, we could go and put, you know, 10 people, um, let's say, uh, on a completely new Suncorks project that's building literally a separate product …

AI assessment note: “Yeah. So the short answer is yes.”