The Exchanges

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: “that was four years after launch admittedly”

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 Do you feel pressure about scaling into valuation? Your last valuation was twelve billion. It is high. Um, do you feel pressure to scale into that?

A I feel pressure to drive durable growth in this business. I think valuations are, uh, you know, are always, uh, you know, an outcome metric, right? It's, it's like the, like, it's the output metric that is a function of all of your execution efforts. And to some extent, like, you know, if you focus too much on valuation, you're trying to chase the tail and not the dot. Right. It's hard to directly impact valuation. I mean, maybe you can do a better job of teaching the company out there and that, that, uh, that helps. But I think the, the hard work that goes into building a great business takes a long time, right? You know, Airtable at least was a company that, you know, we spent a lot of time building our initial product before we even raised our first round. We then, you know, spent a lot of time getting product market fit before we went and raised that unicorn round. Right. You know, this was not a let's go and get the valuation first and then justify the business after. You know, we very much focused on trying to build a really great product and a business. Um, and that, that's what we're doing now. Right. I think to some extent, everybody has, has kind of, uh, uh, you know, kind of had a reset in terms of, uh, valuation expectations, revenue multiples, like what's normal in this new era. Certainly, like, if we do well at executing on the durable growth playbook, we figure o…

AI assessment note: “I feel pressure to drive durable growth in this business. I think valuations are”

Q lot of large enterprises. Like, well, you know, I, I have friends who are CEOs of 50 to 500 person companies. They don't know what slack is. Um, let alone air table. And then if gen AI and AI is the next one, my question to you is like, how far away do you actually think we are? And is this tech bros getting a little bit excited too soon?

A One difference between gen AI and, uh, you know, a traditional enterprise tech is that gen AI is not going to be confined to just enterprise deployments, right? In fact, you know, the, the way that we've all become Uh, aware of and, you know, it's become top of mind is through the consumer applications, whether it's ChatGT, Midjourney, you know, these products have gotten real scale, right? I mean, compared to any consumer product like Instagram or Twitter, et cetera, um, the growth curves, as we all know, are pretty profound. And I think to me, one of the interesting things has been how broadly, um, you know, Gen AI has touched a consumer. So it's not just The, you know, Silicon Valley elites who are adopting this product, but, you know, I've, I've come across, you know, just really surprising, um, you know, kind of friends, family, uh, people that you wouldn't otherwise think of as super early adopters, especially of AI, you know, finding interesting applications of, of, uh, of AI, right? I have a friend who, uh, has a dad who's a lawyer, um, and, you know, not, not a tech law, actually, um, just kind of traditional, uh, you know, kind of personal law and not on the West Coast either. And, And yet, uh, you know, this, this dad, uh, has gotten really into using ChatTBP to, to help with, um, uh, you know, kind of triaging legal cases, you know, doing research, et cetera. It's b…

AI assessment note: “gen AI is not going to be confined to just enterprise deployments”

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.”

Q and thinking about kind of systems thinking as a leader. This is quite a binary question, so you can tell me if it's complete shit. Um, Ben Horace has written before about wartime versus peacetime CEOs and leaders, and now is an interesting time for sure. I guess my question is, what would you say you are, and are you making a transition to wartime leadership today in the context?

A Yeah, I think it's not yes, but it's a reduction, right? And I think the unreduced version of it is, it's more like there's maybe two different axes that you care about. One is the urgency of the environment, right? Like, is this a time when you can be a lot more complacent, where you can take your time to do things? Or do you have to be fast? And do you sometimes have to make decisions with imperfect information and risk being wrong to avoid the greater risk or greater downside of not making a decision? That's one axis. I think the other one is how much of a zero sum game is this opportunity? And especially insofar as does competition have to lose for you to win? And is your success really then more about beating your competition and to the point of even like sometimes trying to undercut them directly, as you see with the ride sharing wars between Lyft and Uber and the other international players, or is this one where you should instead be more customer obsessed, right? Or product obsessed and really focused on building a breakthrough new Product or unlocking new value for customers and in doing so really playing on a different entire field than the so-called competition. And so for us, I think that the urgency has certainly heightened over the past year. I think the COVID environment and the recessionary factors around us may be shrinking availability of capital and also reve…

AI assessment note: “it's not yes, but it's a reduction... for us, I think that the urgency has certainly heightened”

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 lot of large enterprises. Like, well, you know, I, I have friends who are CEOs of 50 to 500 person companies. They don't know what slack is. Um, let alone air table. And then if gen AI and AI is the next one, my question to you is like, how far away do you actually think we are? And is this tech bros getting a little bit excited too soon?

A One difference between gen AI and, uh, you know, a traditional enterprise tech is that gen AI is not going to be confined to just enterprise deployments, right? In fact, you know, the, the way that we've all become Uh, aware of and, you know, it's become top of mind is through the consumer applications, whether it's ChatGT, Midjourney, you know, these products have gotten real scale, right? I mean, compared to any consumer product like Instagram or Twitter, et cetera, um, the growth curves, as we all know, are pretty profound. And I think to me, one of the interesting things has been how broadly, um, you know, Gen AI has touched a consumer. So it's not just The, you know, Silicon Valley elites who are adopting this product, but, you know, I've, I've come across, you know, just really surprising, um, you know, kind of friends, family, uh, people that you wouldn't otherwise think of as super early adopters, especially of AI, you know, finding interesting applications of, of, uh, of AI, right? I have a friend who, uh, has a dad who's a lawyer, um, and, you know, not, not a tech law, actually, um, just kind of traditional, uh, you know, kind of personal law and not on the West Coast either. And, And yet, uh, you know, this, this dad, uh, has gotten really into using ChatTBP to, to help with, um, uh, you know, kind of triaging legal cases, you know, doing research, et cetera. It's b…

AI assessment note: “it's not just The, you know, Silicon Valley elites who are adopting this product”

Q Favorite book and why? I promised myself I'd read more, especially in a pandemic, but even in a pandemic, I'm failing. So help me out.

A What should I read? Well, because it is a Stay at home environment. I'm going to cheat here and give two because I'm reading 10 times more than I would ordinarily. The first is hard drive, which is basically a account of the early founding history of Microsoft. I just think it's so fascinating to kind of go back in time and see all the strategic decisions that the team there made that ultimately led into the almost unexpected rise of such a large and successful platform company. And the other one on a more lighthearted note is spying on whales. I just think it's almost like this complete antithesis to all the What is your superpower and then your weakness in company building, 30 seconds on each? Mathematically about the answers to really absorb as much as I can from it. On the weakness side, I would just say bluntly, I haven't done this before, right? And Airtable is the kind of first company or is the largest company that I've ever operated in this way, and it will be as we continue to grow. So I think that the huge weakness is I'm coming in with completely fresh eyes and without any prior experience of having done it before.

AI assessment note: “The first is hard drive, which is basically a account of the early founding history”

Q Brit, so I feel very uncomfortable asking quite direct questions. Everyone talks about like the bundling of a CFO purchasing decisions. How do you think about that? Would Airtable be a bundling or an unbundling? Like, would you be vulnerable to a Google suite or would it be in favor of you? I don't really know the answer there. And, and is it true that there is a bundling happening?

A So I think bundling is going to become, uh, really, uh, it, you know, it already is very important, um, for products that fit into that core productivity suite. So if you, you know, if you're a product, um, that generally provides very horizontal, uh, but in my mind, shallow value or commoditized value, meaning like there's a lot of different products that do the same thing, right? Um, so certainly if you're doing video conferencing, There's, you know, Zoom is great. Um, but there's also other products that offer the same thing, whether it's Teams or Meet, you know, there, there, there were many other products like BlueJeans, et cetera, that, that predated, um, you know, the, the current era of products. And I think, um, for those products, or if you're doing whiteboarding, or if you're doing any kind of like free form or, or a very generalizable document editing, um, I think those products are screaming to be bundled, right? Because they, they're, they're very broadly applicable. Every company wants some form of it. Maybe not for every employee. Like does everybody need video conferencing? Yes. Does everybody need whiteboarding? Maybe, maybe not. Uh, unclear to me at least, but either way you think of it as an aggregate decision that you make across the entire company, right? So the CIO can say, look, I'm going to go with teams and not use Slack. Uh, I'm going to go with, you …

AI assessment note: “So I think bundling is going to become, uh, really, uh, it, you know, it already is very important”

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: “I think the thinnest or the shallowest analysis that enterprises are doing is that active to paid”

Q Brit, so I feel very uncomfortable asking quite direct questions. Everyone talks about like the bundling of a CFO purchasing decisions. How do you think about that? Would Airtable be a bundling or an unbundling? Like, would you be vulnerable to a Google suite or would it be in favor of you? I don't really know the answer there. And, and is it true that there is a bundling happening?

A So I think bundling is going to become, uh, really, uh, it, you know, it already is very important, um, for products that fit into that core productivity suite. So if you, you know, if you're a product, um, that generally provides very horizontal, uh, but in my mind, shallow value or commoditized value, meaning like there's a lot of different products that do the same thing, right? Um, so certainly if you're doing video conferencing, There's, you know, Zoom is great. Um, but there's also other products that offer the same thing, whether it's Teams or Meet, you know, there, there, there were many other products like BlueJeans, et cetera, that, that predated, um, you know, the, the current era of products. And I think, um, for those products, or if you're doing whiteboarding, or if you're doing any kind of like free form or, or a very generalizable document editing, um, I think those products are screaming to be bundled, right? Because they, they're, they're very broadly applicable. Every company wants some form of it. Maybe not for every employee. Like does everybody need video conferencing? Yes. Does everybody need whiteboarding? Maybe, maybe not. Uh, unclear to me at least, but either way you think of it as an aggregate decision that you make across the entire company, right? So the CIO can say, look, I'm going to go with teams and not use Slack. Uh, I'm going to go with, you …

AI assessment note: “bundling is going to become, uh, really, uh, it, you know, it already is very important”

Q Listen, dude, I want to do one final one. Uh, and it's a very simple one. What would you like to be remembered for as a leader?

A You know, I think I care less about being remembered, um, and instead about doing a good job. Meaning, you know, I care about, uh, our, our team, um, as a constituency, I care about, you know, doing right on behalf of the company's shareholders, you know, having a fiduciary and also like a moral duty to, uh, to build a really good, uh, business and company. I think ultimately, you know, what I've learned is there's much more to this than just building a, a product, right? You know, it's, it's fun and easy in some ways to, to build a good product. I think to build a great company, um, and, uh, you know, and the one that, you know, is not only a great business, but also is, uh, you know, a place where great things are built, are, are done. Um, I think that's, that's a very different challenge. And so I am learning to become A company builder. And while it's, it's less about having a legacy attached to my name around that, I think it's something that, that I, uh, want, you know, I, I hold a lot of, uh, you know, both pride and accountability around getting good at.

AI assessment note: “I think I care less about being remembered, um, and instead about doing a good job.”

Q So if we think about piece by piece in enterprise, you know, you speak to some of the biggest enterprise leaders in the world. What are the commonalities, I guess, in what enterprises want to achieve through the implementation of AI and gen AI, do you think? What are those commonalities?

A For sure. So I think it's super early. I mean, I've, I've spent a lot of time talking to the, the C-suite, uh, fortune by hundreds about AI and, and, uh, you know, air people has some AI capabilities that we're excited to, um, Uh, you know, to get into the hands of both enterprise and self-serve customers. Admittedly, I think, um, one thing I've learned is, is just that it's super early. I think, um, a lot of customers are still trying to, to figure out what you can do with AI. So to some extent, I think we're still limited by the broader, um, understanding of what Gen AI is capable of, what its affordances are. So, you know, what are its limitations? Obviously there's, you know, hallucinations and accuracy issues that are a major problem. Challenge, right? When you're trying to, you know, implement a, you know, a use case that requires a high degree of accuracy. Uh, for instance, you want to use a retrieval use case where you're able to ask, uh, you know, a smart AI bot, uh, questions about whether it's HR benefits or, you know, wealth management information. These are things where you want to have it be right. You want to have it cite the sources, um, and you want it to, to give you a good answer to, you know, there, there's all these limitations for sure. And there's also just a, um, you know, we're still in the education phase, uh, where I think every enterprise is, is gett…

AI assessment note: “a lot of customers are still trying to, to figure out what you can do”

Q For those that are educated in enterprise, And those that are aware, what are the biggest reasons for them not to adopt? What are the biggest implementation challenges that they face? Why are they not adopting it if they're post-education phase?

A We're candidly still very much in the education phase. And I would say, you know, the first half of that, uh, uh, of that journey, you know, keep in mind that this technology is so new in the, the awareness of, uh, you know, the mainstream or, or, uh, you know, if you don't think we're the mainstream, but even in the, You know, the minds of, let's say, enterprise decision makers, right? You know, I think everybody kind of had this wake up call, uh, roughly a year ago, um, and, and, you know, the, the, uh, just the buzz around Gen AI's capabilities. And I'd like to think it's not just because of an accidental excitement that built up because of, of the, uh, consumer-facing products, but also because the, the capabilities of the newest models just got really good. I mean, if you look at GPT-IV's performance versus GPT-III, for instance, you know, in, um, in pretty profound ways, it's actually able to do things like, you know, pass the bar, pass job interviews, solve problems that, uh, you know, previous generations of models just did not do well enough, right, to be useful. You know, the technology has actually reached this breakthrough point, and we've only really had less than a year, um, as, uh, as a world, and especially within enterprises, Uh, to, to keep up and figure out what is this thing that even now, uh, public market investors are pricing into our stock, you know, bas…

AI assessment note: “We're candidly still very much in the education phase.”

Q For those that are educated in enterprise, And those that are aware, what are the biggest reasons for them not to adopt? What are the biggest implementation challenges that they face? Why are they not adopting it if they're post-education phase?

A We're candidly still very much in the education phase. And I would say, you know, the first half of that, uh, uh, of that journey, you know, keep in mind that this technology is so new in the, the awareness of, uh, you know, the mainstream or, or, uh, you know, if you don't think we're the mainstream, but even in the, You know, the minds of, let's say, enterprise decision makers, right? You know, I think everybody kind of had this wake up call, uh, roughly a year ago, um, and, and, you know, the, the, uh, just the buzz around Gen AI's capabilities. And I'd like to think it's not just because of an accidental excitement that built up because of, of the, uh, consumer-facing products, but also because the, the capabilities of the newest models just got really good. I mean, if you look at GPT-IV's performance versus GPT-III, for instance, you know, in, um, in pretty profound ways, it's actually able to do things like, you know, pass the bar, pass job interviews, solve problems that, uh, you know, previous generations of models just did not do well enough, right, to be useful. You know, the technology has actually reached this breakthrough point, and we've only really had less than a year, um, as, uh, as a world, and especially within enterprises, Uh, to, to keep up and figure out what is this thing that even now, uh, public market investors are pricing into our stock, you know, bas…

AI assessment note: “We're candidly still very much in the education phase.”

Q So if we think about piece by piece in enterprise, you know, you speak to some of the biggest enterprise leaders in the world. What are the commonalities, I guess, in what enterprises want to achieve through the implementation of AI and gen AI, do you think? What are those commonalities?

A For sure. So I think it's super early. I mean, I've, I've spent a lot of time talking to the, the C-suite, uh, fortune by hundreds about AI and, and, uh, you know, air people has some AI capabilities that we're excited to, um, Uh, you know, to get into the hands of both enterprise and self-serve customers. Admittedly, I think, um, one thing I've learned is, is just that it's super early. I think, um, a lot of customers are still trying to, to figure out what you can do with AI. So to some extent, I think we're still limited by the broader, um, understanding of what Gen AI is capable of, what its affordances are. So, you know, what are its limitations? Obviously there's, you know, hallucinations and accuracy issues that are a major problem. Challenge, right? When you're trying to, you know, implement a, you know, a use case that requires a high degree of accuracy. Uh, for instance, you want to use a retrieval use case where you're able to ask, uh, you know, a smart AI bot, uh, questions about whether it's HR benefits or, you know, wealth management information. These are things where you want to have it be right. You want to have it cite the sources, um, and you want it to, to give you a good answer to, you know, there, there's all these limitations for sure. And there's also just a, um, you know, we're still in the education phase, uh, where I think every enterprise is, is gett…

AI assessment note: “a lot of customers are still trying to, to figure out what you can do”