How we restructured Airtable's entire org for AI | Howie Liu (co-founder and CEO)

If you were literally founding a new company from scratch with the same mission, how would you execute on that mission using a fully AI native approach? If you can't, then you find a buyer, and then if you really care about this mission, like, go and start the next carnation of it. Or people that work for you, how have you adjusted what you expect of them to help them be successful? If you wanna cancel all your meetings for, like, a day or for an entire week and just go play around with every AI product that you think could be relevant to Airtable, go do it. Of the different functions on our product team, PM, engineering, design, who has had the most success being more productive with these tools? It really does become more about individual attitude. There's a strong advantage to any of those three roles who can kind of cross over into the other two. As a PM, you need to start looking more like a hybrid PM prototyper who has some good design sensibilities. Do you see one of these roles being more in trouble than others? Today, my guest is Howie Liu. Howie is the cofounder and CEO of Airtable. I'm having a bunch of conversations on this podcast with founders who are reinventing their decade plus old business in this AI era to help you navigate this existential transition that every company and product is going through right now. Howie and Airtable's journey is an incredible example of this, and there's so much to learn from what Howie shares in this conversation. We talk about a very interesting trend that I've noticed that Howie is very much an example of, of COs almost becoming individual contributors again, getting into the code, building things, leading initiatives themselves. That's something that we call the I c c o. We also talk about the very specific skills that he believes product managers and product leaders, also engineers and designers, need to build to do well in this new world that we're in. Also, how he restructured his company into two groups, a fast thinking group and a slow thinking group, which allowed their AI investments to significantly accelerate. If you're struggling to figure out how to be successful in this new AI era, this episode is for you. If you enjoy this podcast, don't forget to subscribe and follow it in your favorite podcasting app or YouTube. Also, if you become an annual subscriber of my newsletter, you get a year free of 15 incredible products, including Lovable, Replit, bolt, n eight n, linear, superhuman, descript, whisper flow, gamma, perplexity, warp, granola, magic patterns, raycast, chappier d, and Mobit. Check it out lenny'snewsletter.com and click product pass. With that, I bring you Howie Lew. This episode is brought to you by LucidLink, the storage collaboration platform. You've built a great product, but how you show it through video design and storytelling is what brings it to life. 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To thrive in the AI era, organizations need to adapt quickly. But many organization leaders struggle to answer pressing questions like, which tools are working? How are they being used? What's actually driving value? DX provides the data and insights that leaders need to navigate this shift. With DX, companies like Dropbox, booking.com, Adyen, and Intercom get a deep understanding of how AI is providing value to their developers and what impact AI is having on engineering productivity. To learn more, visit DX's web site at getdx.com/lenny. That's getdx.com/lenny. Howie, thank you so much for being here, and welcome to the podcast. I'm so excited. Thank you, Lenny. I've I've been a listener from afar for a while now. I'm I'm really flattered to hear that. I'm also very excited. You've been on quite a journey over the last, is it thirteen years? Is it is it longer? Like, right yeah. Right about thirteen. Thirteen years. I Imagine there have been a lot of ups and a lot of downs. I wanna talk about all those things. I wanna talk about a lot of the lessons that you've learned along the way. I wanna start with what I imagine was a a very surprising down moment in the history of Airtable. This is something that, unfortunately, is something I think about when I think of Airtable. I feel other people maybe feel this way is there's this tweet that went super viral, maybe a couple years ago at this point where someone just shared all this data and they're like, Airtable is dead. They've raised way more money than they're worth. They're not making enough to get on from an underwater. Yeah. Airtable RIP. What happened there? How much of that was true? How did that Yeah. So very I basically, none of it was true. And, I mean, the surprising thing to me was how viral this tweet went when frankly, like, I I actually looked back at this person's, other tweets. I think they they, they worked at CB Insights, and the irony is, like, that the whole point of that business is to have, like, good data good data quality around private company data. And they just, like, literally had incorrect numbers by, like, a a strong multiple on, like, what our revenue scale was, where our growth rate was, like, you know, and and it. If it gave me some consolation, I look back and, like, this person had also tweeted about other companies, like, Flex Sport was the last, like, kind of takedown tweet. They they have, like, oh, Flex Sport's dead. And, like, you know, their their, you know, their valuation is is, you know, too high and blah blah blah. And so I think that the more surprising thing was just, like, this person has been tweeting a bunch of, like, spicy takes that are not substantiated by real data or correct data, and yet, like, this particular tweet went super viral. And that was the perplexing part to me. And then I think actually, I think what what really gave it legs was on the All In podcast, which is, like, obviously super popular, you know, and I listened to it. Like, you know, they they covered it. They were like, oh, like, you know, latest on on, this week's news, like, you know, this tweet about Airtable. What do we think about this? And it also, I think, became, like, a way to talk about a broader theme of what happens to this last generation of highly valued companies, maybe DecaChorn companies, in this new and at that point, it was, like, kind of the recent moment for both public and private markets. They did also issue a correction, though. All in, did a a follow-up episode a few few, I think weeks later saying, like, hey. Like, you know, we got the numbers wrong. Like, you know, we we're revising our case and and kind of a a view on Airtable. What's that line about how, a lie gets around the world some number of times before truth has even less time to get out of bed? Yeah. Yeah. Well, I I think I learned about, memes and morality very quickly in, in that experience. Not a very good social media person, but, I think I learned a little more. Yeah. It's tough. Twitter is such an the incentives are so misaligned. It's just I I tweet something people want to share, not truth. Well, I mean, especially, like I mean, I I there's a lot to like. I would say, Net Net, I like the post Elon Twitter more than the pre Elon Twitter because it's it's just bolder and, like, I, you know, I guess I I really admire bold product execution where you're not just kinda stuck to, like, the current laurels. And they made so many changes, but, like, I do feel like I get injected into my feed very sensational content all the time. And I mean, it works on me. I'm like, you know, like, I can't help but to, like, click on it and engage with it. And, like, you know, but it it does I think it does result in, like, this kind of content, like, really spreading. Yeah. Now Nikkita writing the show, I don't I don't know if you saw this. There's a new we don't need to keep talking about Twitter, but there's a new feature where you take a screenshot of a tweet and it has, like, a huge x.com logo, watermark in the top right. Yeah. And just to, like, you know, people are sharing these tweets all the time. Yeah. Yeah. Yeah. Never a dull moment over there. For sure. Okay. I wanna go in a completely different direction. It's something that I'm really excited to talk to you about, which is this very, emerging trend that I've noticed that I feel like you're at the forefront of of CEOs becoming ICs again. It's kind of this move of, I see CEOs. CEOs getting their hands dirty again, building again, getting the weeds, coating again. Feel like you're, again, at the forefront of this. Talk about just why you've done this, why you think this is important, and just what that looks like day to day to you versus what your life was like a few years ago. The underlying reason for the shift, at least for me, is that as we started the company, I was very much in this mode. Right? Like, I was literally writing code both on the back end, thinking about the real time data architecture of our platform, also the front end, the UX. And, you know, I would argue that, like, in that founding moment, like, the initial product market fit finding, and especially for a product that is, like, pure software. Right? Like, we weren't building, like, a operationally heavy business, like a dog walking marketplace, where the tech is only an afterthought. Like, the tech was the product. Right? And in a very nice sense, like, Airtable is the platform for other people to build their own apps. Right? So, like, it's all about the attack. Like, the very intimate design decisions, again, both architecturally and and, on the front end and the product UX choices, like, that is the product's value prop. Right? Like, you can't separate those two. You can't say, like, okay, like, I researched the jobs to be done. Here's the workflow. Here's the process. And then like, okay, some engineer can just build it as an afterthought. Like, it's those like little decisions and really be able to, like, be at the bleeding edge of what's possible both in the browser and with, like, you know, kind of the real time data architecture that made the product what it was. Right? I think the same is true for Figma, which, you know, actually, like, had a very parallel timeline to us. Like, we both were founded around the same time, both spent two and a half years building the product, like, hands on, you know, that early team before launching. And, you know, when I think now to, like, both the era in between that founding moment and then now, as well as, like, now the the new kind of Gen AI moment, like, I think there was a maturing era of both SaaS overall and Airtable specifically where, you know, as you scale up and you kinda learn how to build, you know, teams and organizations and, like, you have to kind of, like, scale up stuff that's not actually those intimate details, but process and people and so on. You kinda get, you know, by default, further and further away from those details. Right? And maybe for some businesses, that's fine because, like, no longer is it about finding, like, the the details that make for a magical new product market fit. And it is really just about scaling up an existing thing that works. Right? And using what I would call, like, more blunt instruments, to kinda scale it up. Right? Like a more blunt road map, a more blunt, you know, kinda go to market execution strategy. Regardless, I think that now we're we're entering this moment where, like, every certainly every software product in my opinion has to be refounded because, like, AI is such a paradigm shift. It's not even, like, just like the shift from desktop to mobile or on prem to cloud where that was more like a a very one time and somewhat predictable change in form factor. Like, I think AI is so rapidly evolving that with every evolution, like, every new model release and every new type of, like, capability that's released, it actually implies novel form factors and novel, like, UX patterns to be invented to fully capitalize on those capabilities. And so, like, to be continuous, continuously relevant and how to refine product market fit in this era, I think you have to be in the details. Like, there is no, like, you know, looking at it from 10,000 foot view and saying, oh, we're just gonna throw a bunch of people at this problem. It's actually understanding, like, what is the right product experience and the right business model that backs it up, and the right, you know, everything else to support that engine to take advantage of the capabilities in our product domain. You have this phrase somewhere where you you talk about being the chief tastemaker. Yeah. And to do that, you have to do exactly what you're describing. That's right. I mean, I think that and, like, I would also say, like, it's actually now also hard to taste the soup without participating in, like, at least some part of creating the soup. Right? And, like, meeting with AI, you can kind of look at the final product and say, okay, like, this this feels right or not. Or, like, it feels like we're being bold enough and we're we're properly, you know, productizing these new capabilities. But I think, like, to really understand, you know, the solution space of what's possible, you kind of have to be in the details. Right? I mean, literally, like, you can't just look at, you know, kind of screenshots or, like, a prerecorded video of, like, a a new product feature. Like, AI is something you have to play with. And, ideally, you're playing with both the, like, kind of packaged up, you know, app or solution that you've built with it, but you're also playing around directly with the underlying primitives. You're using the models either via API or via, like, a chat interface. Like, you're really pushing them to the boundaries. And, like, because that's the only way that you really understand what these new ingredients it's like as a chef, you just gained access to, like, amazing new ingredients, but you have to, like, actually kinda get comfortable with them to put them into a new dish. And we had, Dan Shipper on the podcast. He runs, this newsletter and podcast product company called Every. And he they work with companies to help them become more AI, successful and adopt AI and all that stuff. And he I asked him, what's the what's the signal that a company will have success adopting AI and seeing huge productivity gains? And he said it's does the CEO use ChatGPT or Claude daily? Yeah. And I feel like you're describing exactly Right? Hourly. Early hourly. Like or, you know, you could even, like, have a measure of, like, inference, like, cost. Right? Like, the equivalent underlying, like, inference compute cycles. Right? How many tokens they use. Yeah. I mean, I I'm proud to say, like, I am, I'm I'm pretty sure I'm still the, I I just checked this recently, but, like, I take pride in being the number one most expensive in inference cost user of Airtable AI, not just within our own company, but I think for a long time I was globally across all our customers as well. Like, I'm just I'm I'm like, well, I mean, like, I'm extremely intentionally wasteful, wasteful in the sense of, like, you know, I'll do something that costs, like, maybe hundreds of dollars of, like, actual inference cost. Right? Like, for instance, you know, doing a lot of LLM calls against like long, you know, kind of transcripts of let's say sales calls to extract different types of insights like here's the product apps identified or here's summaries etcetera. And we we also have now a capability that's basically like an LLM map reduce. So effectively even if you can't fit like you know the entire corpus of content into one LLM call because the the context window, limitations will map through like all of this content and break it up into chunks and then like perform an LLM call in each one and then perform an aggregation LLM call on those chunks. Very expensive. Right? Because you're basically running, like, a highly expensive model against a lot of Dan and then running it again on the aggregates of that. But, like, for me, you know, like, hundreds of dollars spent on this exercise is trivial compared to the potential strategic value of, like, having better insights. It's as if, like, a really, really smart chief of staff has gone through and read every single sales call, like, transcript that we've had in the past year and giving me, like, you know, you know, kind of very, astute product insights, marketing insights, like, you know, kind of positioning insights and segmentation insights. Like, that's invaluable. Right? Like, you could pay a consulting firm, like, literally millions of dollars to get that quality of work. So, like, to me, I still think the, like, the value versus the actual cost of AI when applied greedily but smartly, like, it's just it's it's it's a crazy ratio and, like, more people should be, like, aggressively throwing compute cycles at these very high value problems. Until somebody tweets how you're eating, costing the company so much on on AI compute and you guys are gonna be underwater. I'm pretty dude. Just kidding. It's like how we have personally taken down, the, the cash flow, profile of the business. Like So okay. So CEOs, founders hearing this, they're probably like, okay. I I I should probably start doing this. What does this actually look like? I imagine you still have a lot of other stuff. You got one on ones. You got all these like, how do you actually how do you change your day to day to do this? Yeah. So I actually cut my one on one roster, by default. And the idea is I'm not is not that I don't wanna spend time one on one with people, but rather that I found that the, just like having more standing one on ones actually precludes me from, you know, engaging in more timely topics. Right? Like, I like to think of, you know, the best types of meetings as, like, very, urgency driven. And, like, you know, there's some timely topic. Like, you know, you've you've discovered some insight. Maybe I talked to some new startup. Right? And, you know, I learned something from from their product or their approach, and I wanna bring that into how we're thinking about, like, a new feature at Airtable or even just, like, plant the seed with, like, you know, some different, like, you know, EPD people within Airtable. Like, I wanna make most meetings, very timely and very informed by, like, real alpha. Right? There's gonna be some kind of value and insight, to seed that with. Now in addition to that, I'll supplement with, like, you know, when I'm in person, you know, with someone, like, I wanna carve out time for, like, a, you know, a proper, like, catch up and, like, less structured, less less, like, timely, and just more of, like, you know, building a relationship with a human. But I actually find that, like, you know, having that com it's almost a barbell approach where it's, like, you know, if you're gonna spend time with somebody in a free form way, like, actually doing a high quality, not, like, forced weekly ritual way, like, go for a longer lunch or coffee walk or whatever, in person when you can. Maybe that's, like, a once every month or two kind of thing. And then, like, the the in betweens are either topical. So we do have standing meetings for, you know, like now, we have a weekly basically, sprint check-in on all of our AI execution stuff, which now is like half the company or half the, EPD org is working on AI capabilities. We're trying to ship very quickly. Like, you know, I basically want to always ask the question, like, how would an AI native company like a cursor or windsurf, etcetera, like, how would they execute? Right? And are we executing as fast as them And taking advantage of like all the new stuff as well as them. So like bringing that level of like kind of intensity and urgency to like how I spend my time within, that's been the main the biggest shift for me. What's the change you've made to help the company move faster and and match that sort of pace? Yeah. So I mean, we did do a reorg, of, the EP org. So before we had we've gone through a few different, kind of reorgs over the past, call it, four years. The the, you know, kind of original state as we just kind of proliferated, I think, by default or incrementally was that we had a bunch of groups that were each responsible for, like, a feature or a surface area. So there was a group responsible for search within our table, and there was a group responsible for, like, mobile experience and, you know, so on and so forth. Right? And, you know, that has its benefits. Like, you know, obviously, like, that team can go and, like, you know, get really ramped up on that part of the code base, that part of the product. But it has the disadvantage of, you know, you you tend to think incrementally when everyone's remit is actually, like, a feature that they incrementally improve by definition as opposed to thinking about, like, a mission or, like, a outcome goal. Right? That might need to, you know, coordinate, you know, dramatic changes across a wider set of of, surface areas instead of just, like, each one kind of incrementally, improving. And so we reworked, initially to basically different, business units effectively. Right? So, I know Airbnb has done, like, kind of the the functional to GM, you know, back, etcetera. This was more like saying, look, we have an enterprise business and the MO there is more about, like, scalability. Can we support like the larger scale data sets and use cases? Do you have the core capabilities needed to be able to like push out an app to maybe 10,000 seats or 20,000 seats for product operations? Right? So a lot of architecture, a lot of scale, that kind of work. We would have a, what we call the teams pillar, which is more about self serve, like kind of the product UX, like how easy it is to to adopt the product, onboard, share, do all the kind of like basic functionality, an AI pillar, solutions pillar, and, and then basically infra. And what we found though with that approach is that there was still, you know, there there was more kind of, holistic bets being made. So, like, you know, the teams pillar could think not just about one feature, but, like, the overall onboarding experience. We're, like, really think about NUS, you know, in a way that touched multiple parts of the product. But it still felt like it wasn't especially as as we started to execute more on AI stuff, like, it wasn't, you know, allowing us to aggressively and quickly move as a AI native company would. Right? Like, I mean, when you look at, you know, the cursors of the world, they're shipping, like, major new stuff every week. And, like, you know, it's not like, oh, well, we have, like, this separate, you know, kind of road map for enterprise. We have this road map for for, this group. And, you know, it just feels like one, one cohesive product that's shipping at a breakneck pace. So we did this, recent reorg where now we have the what I call, like, the fast thinking, group, which officially is called AI platform. But it really means, like, we wanna just ship a bunch of new, capabilities on a near weekly basis, and each of them should be, like, truly awesome value. Right? Like, you should drop your jaw at, like, how awesome it is to use this new capability in in Airtable. And then separately, we have the slow thinking group. That's not meant meant to be, like, better or worse. Like, it's it's literally, like, you need fast and slow thinking in the common sense, to operate. Right? Like, as human I have that book behind me. Yeah. I love that book. But, but slow thinking is, like, it's just a different mode of planning and executing. Right? It's, like, more deliberate that's that require more premeditation. Right? Like, we can't just, like, ship a new piece of infrastructure that has a lot of, like, data complexity, like, you know, our our data store HyperDB that, now can handle, like, multi 100,000,000 record datasets. Like, that's not something you ship in a week, right, in a hacky prototype. So we now have these two separate parts of the company. And I actually think what's what's really cool is, like, they they actually complement each other very well. Right? Because, like, the the fast execution, the AI stuff, you know, that creates the top of funnel excitement. And that that also, you know, kind of inspires new use cases and new users coming to Airtable, including in large enterprise. Right? Like, you know, enterprise can use this stuff too. It's not just like a SMB thing. But, like, the slow thinking basically allows those initial seeds of adoption to sprout and grow into much larger deployments. Whereas I think a lot of the challenge for many of the AI native companies I've seen is that they have, like, a very wide top of funnel. Like, get all of this AI tourist traffic, you know, a lot of interest, a lot of, like, kind of, like, you know, early usage. But then, you know, sometimes the the challenge is how do you, like, turn that into more durable, you know, growth and and get each of those adoption seeds to retain and expand over time. That is super cool. I've never heard of this way of structuring teams, the fast thinking thinking fast, thinking slow, the condiment. It's so interesting. For the fast thinking team, do you find there specific archetypes of people that are successful there? Is it a lot of, like, bringing in new people that are not just used to the way of working at our table? What do you find? We we have a mix. So, you know, we've run-in, I mean, we're we're always hiring. Right? Like, there was never a point in, in the company's life where we stopped hiring. And that, you know, candidly, even when we had to do, two rifts, right, that that significantly, you know, kind of reduced our headcount. You know, we just, like, way too quickly grown and over scaled the business at a certain point. But even when we did our rifts, we were still actively recruiting and hiring, you know, in, I mean, every major department, but especially in, in EPD because, you know, it's always been my belief that, like, you you all like, it would be arrogant to say that we have all the people we ever need already in in the, rosters day. Right? Like, we're always gonna need to find new fresh perspectives, new skill sets, etcetera. And so, you know, we we've continued to hire. I think we've learned as we've gone along of, like, you know, what is the ideal type of hire and, you know, we've done some acquihires and learned from that as well. But I think the fast thinking part, it really just requires a a lot of, like, somebody who's able to operate with a lot of autonomy. Right? Like, you know, who's entrepreneurial in nature. It doesn't mean, like, they have to literally be a former founder. I know some companies are, you know, like, Rippling, for instance, does a lot of actual acquisitions and gets actual founders into the company. Like, we found that, you know, that that's great. And we've done some of that as well. But, like, also, there are some really, really capable people who, like, we didn't literally have to, like, acquire in. And yet they're just able to, like, think full stack about the problem and, like, the user experience. Problem not just meaning, like, you know, the the technical layers of the problem, but, like, also, like, what is the wow factor we're trying to create. Right? So tangibly, like, you know, we're we're doing this new thing that's about to ship where, you know, not only can you describe the app you wanna build and then iterate on it with, know, kind of our conversational agent Omni, but, and it builds it with, like, the existing Airtable platform capabilities. But, we're also giving it the ability to actually do CodeGen to extend those apps with, like, really final mile, very bespoke functionality or, like, visuals. Right? So you could say, like, hey, generate me a very, very specific type of map view with, like, this kind of, like, heat mapping and this kind of, like, you know, icons. And when you click it, do this. And, like, that's a capability that, like, there's so much ambiguity in some of the design decisions around it. Like, you know, and and you have to blend that design thinking with some of the technical constraints of, like, what can the AI models actually one shot effectively? And if not, like, how do you add in, like, the right human workflow for approval and review and then reprompting and so on? So just so many different, like, design decisions, and you need somebody who can, like, really think full stack about that kind of product and is not overwhelmed by that, you know, kind of openness, but, like, relishes in it. I was actually playing with it, before we started chatting. I made a really cute startup CRM. Oh, that's awesome. Yeah. Started talking Omni over here. It's like the colors are beautiful. That was that's what's standing out to me right now. We did. There is, I will say, like, just as a as a note, you know, I consider myself, like, at my core, like, a product UX person. Right? Like, that that's my, like, passion. And, you know, everything else I've had to learn to to kind of run this company, is almost like what was a necessary, you know, part of the the journey. Like, you know, but but, like, my real passion is thinking about product UX. Right? And I, you know, I I think of UX in a deeper sense than just, like, the cosmetic, like, design, like, you know, what you could put into a framer, you know, kind of prototype. Like, I think of it as, like, literally, like, what should this product do and how should it represent that and behave for the user? That is the product in my opinion. Right? And of course, then you have to figure out, like, technically what's possible and how to implement it. But, like, I think to me, what's under, executed today in the world of AI products is, like, there's so many awesome capabilities of AI, and most of them are really under merchandise. And there's, like, very poor actually visual or otherwise metaphors or affordances given to users to help represent or understand, like, what those are underlying capabilities are. Right? Like, I mean, Chachipity, obviously, like, you know, extremely successful products, so not knocking it at all. But, like, you come in and you just get this, like, completely blank chat box, right, by default. Now they have suggestions underneath it and then so on. But, like, you know, the product UX part of me is just, like, craving more visual metaphors or colors or some kind of, like, use the canvas of a web interface to and and all the richness, you know, interaction you create there to better represent or or show all the different things that you can do with, you know, with with the underlying model. Right? And so that's something we've tried to do with Airtable. It's, like, show, like, all of the different states and, like, use colors even to play those up. It's interesting how much of this connects with I just had Nick Turley on the podcast. He's head of ChatGPT at OpenAI. And he had these two really interesting insights that resonate, directly with what you're describing. One is he has this concept of whenever something is being worked on, he's always asking, is this maximally accelerated? How do we move faster? Is the if this is important, what would allow us to move faster? Yeah. And I love that that's one of the themes that's coming up as you talk is just this creating this very clear sense of speed, and you even call it the fast thinking team. Like, you're gonna move fast. Yeah. And then the other one is just this insight that with AI, you often don't know what peep what what it can do and what people want to do with it until it's out. So there's this need to get it out, and that'll tell you what it should be. I I couldn't agree more with with both of those. And particularly on the second point, you know, I think it's interesting, like, clearly, there have been companies, that have both been successful in PLG and, like, kind of more sales led, you know, kind of distribution for AI products. Like, you know, the the most notable ones I could think of are, like, Palantir with their AIP deployments. Like, that's obviously very sales led. You're not PLG into a, Palantir deployment. But even, you know, like, companies like Harvey and and, and so on, like, you know, they're doing very well. And, like, it's primarily, from what I understand, like, sales led. Right? You're not self serving into a Harvey instance at a law firm. And yet, like, to me, the the best way to get AI value out there is experientially. Right? And so, like, you can kinda get that in a sales motion. You can, like, you know, show a demo. Maybe you can get to a POC. But, like, it's so much more powerful when you just open up the doors and say, anyone who wants to come and sign up and trial this product, like, can. Right? And, I think, you know, it's to me, it's, like, you know, kind of a a real proof point that, like, Chargebee is arguably, like, the most successful, you know, kind of PLG product of all time. Right? Just in terms of, like, sheer scale of users. Like, they announced 700,000,000, like, m a is it MAUs or we, I think Weekly active users. 10% of humans on earth use that weekly. That's insane. In, like, how many years? Right? Like, a few years. Three years. Under three years. Yeah. And and so, like, I mean, literally, that that is just, like, the most insane ramp curve. And I don't think they would have gotten there if, like, you couldn't just come in and literally tried the product out. Like and and, you know, kind of as a little bit of a rebuttal of the point I made earlier where, like, I think Chativity doesn't do a ton right now. And and even earlier, like, they they did even less to, like, expose all the different ways you could use it, but they just made it so frictionless to just try it for yourself that you as a user could come in and just literally ask it anything and see how it did. And, of course, like, you know, people in the early days tried to stump it and showed, like, oh, look. See, it's not that smart. Like, it doesn't answer this this hard question really well. But, like, clearly, the magical, like, you know, kind of nature of it still appealed to you enough. You're like, you you everybody used it. And so I think, you know, I I do have a view. Like, we've gone through that whole, you know, kind of arc of we started PLG. I'd like to think Airtable was one of the the kind of PLG darlings of of our era. And, anyway, kinda started moving up market and, like, doing more, sales execution, although that was still always on top of, like, usually PLG within an enterprise. But we started doing more and more sales, execution. We still have that. That's still really, important for our business. But I also think, like, me personally, like, one of my goals is to shift my attention back into that kind of, like, you know, builder led adoption and, like, literally showing in the product, experientially not telling in, like, a deck the value that you can get from from AI and Airtable. Right? Like, I think that's so key. And it's it's, you know, it's Nux, but it's also more than that. It's not just, like, literally how do you onboard somebody into the product. It's, like, literally thinking about the entire product experience itself. Right? And in our case, like, we just, like, made the entire product experience AI centric. Right? Like, it used to be that, like, you know, we had kind of this, like, secondary thing that you could ask questions to, the assistant sidebar. We now made our agent the default way of doing everything in Airtable. And, like, you know, it's like now the the Airtable app as you know it is almost like an artifact that's manipulated by, you know, and and kind of, like, can be tool used by the agent. Let me follow that thread. So if you go to airtable.com today, it looks it looks like basically all the other AI app building sites. Now it's just tell me which you wanna build. Thoughts on that as just like a thing everyone's starting to do. Is there what do you think comes next? Is this does is it working well? There's clearly a an incredible magic to, vibe coding and and app building with AI. Right? And, this is actually, you know, like a prime illustration, in my view of of, that that cost we talked about a second ago, which is, you know, as capabilities of these underlying models evolve, the form factor and the product UX also needs to evolve with it. Right? And so, like, the earliest models, like the kind of original ChachiPT, like GPT 3.5, you know, kind of era models were were not nearly as smart as the current models. Right? And so, like, you couldn't really ask it to one shot a more complicated chunk of code or or certainly not like a full stack app and expect it to work. And so the right form factor for leveraging those models in a software creation context was GitHub Copilot. Right? It's like auto complete a few lines of code at a time. Right? But, you know, you you couldn't chat to it and tell it, like, build me this entire app from scratch. Right? And I think that, like, as the models got better and better, you saw that the new form factors emerge. Like, I think Cursor did a great job of, like, being an early pioneer of this more agentic way of leveraging the models to to do more complex things and generate more, you know, kinda larger chunks of code. And now with composer, you can literally just go into cursor and build an app from scratch. Like, build me a three d shooter game from scratch and just watch it go and, like, create all the files and, you know, fill out each file and then, like, you know, like, the thing actually runs some of the time. And so to me, this is, you know, where the world is going. The models are clearly getting smarter. And, you know, if you think about the original vision of Airtable, it was always about democratizing self creation. Like, we just strongly believed that, you know, the number of people who use apps far outweighs the number of people who can actually like build their own or manipulate apps and like harness like custom software to their advantage. That sounds very familiar. Very familiar these days. Yeah. Exactly. And and so, like, I think this is like it's a different means to the same end. And so, like, it's almost like we have to lean into this because if we started Airtable today, like, this is what we would be all in on. Now I think that the advantage that we have, and, like, I do think you have to be realistic to yourself, especially as as a, as a company that predates GenAI and now has to kinda find your new footing in the AI landscape. Like, you can't fool yourself and just say, like, okay. I'm gonna throw in some AI stuff on the landing on the marketing site, you know, put in a couple AI features and call it a day. Like, I think you actually have to take a clean slate, approach to saying, like, how would our mission best be expressed? Like, if you were literally founding a new company from scratch with the same mission, how would you execute on that mission using a fully AI native approach? Right? And, like I and and and then by the way, like, do you have useful building blocks, you know, that you can leverage from your existing product, and your existing business? Or are you literally worse off having this legacy asset versus starting something from scratch? And, like, I don't think the answer is always yes or no. I think it just depends on the product. And if you can't really introspect and say, like, look, I think I'm better off doing this with the pieces that I have for my existing business and product, then I think you should sell. Right? Like, you should find a buyer for that company and then go and and, like, you know, if you really care about this mission, like, go and start the next carnation of it. Right? In my case, like, I I I really, you know, thought about this and, like, really feel strongly that the building blocks that we have, like, these no code components, actually do allow us to execute better on this vision than if I had to start from scratch. Right? Meaning, like, the problem with Vibe Coding, especially for building business apps. So I should clarify that, like, you know, we wanna democratize software creation, but specifically, we are focused on business apps. Right? We're not trying to be the platform where you create, like, a cool viral consumer game. This is for, like, your CRM. Right? Or if you wanna build an inventory management system as a small restaurant or a lawyer trying to build, like, a case management system. Like, that's what we've always been been, focused on. And I think in this, AI native world, clearly, you should be able to generate those apps agentically. And yet if you have an agent that has to generate every single bit of that app from scratch, from code, it's gonna be very unreliable. There's gonna be bugs. There's gonna be data and security issues. And then you're also gonna have a context collapse as it just cannot manage all of the code that it's written basically as the app gets more and more complex. Right? And what we actually have are basically these primitives that the agent can manipulate and use without having to, like, literally write the code from scratch to represent, like, here's a beautiful CRUD interface on top of the data layer. Right? Like, ours is real time collaborative and really rich and has collaboration on it. And by the way, here's all these other view types and a layout engine for a custom interface, you know, a layout. Right? Or automations and business logic. And so it's almost like, in programming terms, like, the Airtable pieces in our Lego kit today can be used by this agent as almost like a more expressive DSL, like a domain specific language, to build business apps instead of literally having to write everything down to, like, the SQL and HTML and JavaScript to build every part of that app from scratch. And so, like, if we can combine the best of both worlds, like, we have these very reliable high quality Lego pieces. Now an agent can go and, like, assemble them for you instead of you just using the GUI to do that. And by the way, if you do wanna fall back to the GUI, there's a really great, you know, kind of way for the nontechnical user to still understand and participate in what's going on. Whereas if you're not technical, you can't inspect the code underneath a v zero or Lovable or Revlon app. Right? Like, it's just kind of opaque to you. And if you can't reprompt it to get what you want, you're kinda stuck. You know, this is much more akin to, like, a developer using cursor can generate lots of code, but then can still drop back to the IDE to edit and and manipulate it to the final, you know, kind of production ready state. So, like, that's that's kind of the the play that we're making. And if I didn't fully and truly believe, like, you know, we have a better shot at doing it with our existing product, like, I wouldn't be running this company in its forum today. I'm talking to a lot of founders that are going through the journey you're going on, which is we've had a business for a decade, AI emerged, and, wow, we gotta figure out something that works that could work even better. And so I'm trying to pull out the threads that are consistently working across these journeys because I think a lot of companies are trying to figure this out. So one that you just touched on is just if you were to start today, what will you do? Like, what would that business be? Plus, how can how can do we have an unfair advantage with the thing we've done in the past? That feels like an important ingredient. And then the other circling back to stuff you've shared already, there's just, just like creating a sense of urgency and pace and getting people, to understand this is how things move in AI, and we need to create this fast thinking team. I love that metaphor and framing. And then there's the point you made about just talking to AI regularly as the founder. Feels like an important element just, like, to truly be this I c CEO talking to AI, working with AI regularly. Just on that note a little bit more, what just to give people a sense of what this looks like day to day. So you're talking to Omni all day, trying to under flex the power of what you can do and iterate on it. Is there anything else you're doing day to day that helps you figure out what to do for the business? One, I try to use as many different AI products, including not Airtable. Right? Like, as I can. And both literally for the novelty factor and just, like, you know, some new cool demo comes out, like, runway released their, like, immersive world, you know, kind of engine. Right? And, and so, like, I'm gonna go try try it out. Right? Like, when, Sesame AI put out their, like, cool, like, kind of interactive voice voice chat, you know, you know, demo, like, I tried that out because, like, even though we don't have a direct and near term, like, you know, kind of, need for, like, really, realistic and and interruptible, like, kind of voice mode, where it's not as core to our capabilities. Like, I just wanna understand and and, like, get a feel for everything that's out there. Right? And I try to invent little, like, kind of almost like side projects of my own to have a a real kind of reason to use these products. Like, you know, oh, cool. What if I were to take, like, a what what if I were to, like, try to create, like, a funny little, like, you know, like, a short a funny video short. Right? Using a combination of, like, Hey, Jen avatars with, like, a script like, a a comical script generated by AI. Right? And maybe it'll be on, like, an interesting topic. So I'll do, like, deep research on the topic with Chachapati and pull together the results, have it compose, like, you know, kind of a a little bit of a do this? Is there something that I need to do? That's literally an example of something like just, you know, a fun weekend project. And, like, to be honest, like, these things only take you, like, an hour. Right? If you're if you become kind of pre pretty proficient with using the products, like, they're all so easy to use. Like, you can literally do the deep research thing, you know, kick off a query, make a coffee, come back in twenty minutes. Okay. Like, let me let me prompt it to, like, generate me some dialogue. It's a little bit like what notebook l m does for you out of the box, but sometimes I like to just, like, do it myself. Right? And then, okay, let me take the script and, like, cut it up and, like, you know, turn it into an HeyGen avatar and then download the video and and, like, play it. Right? Like and just for fun. Right? I'm not, like, trying to make make that into an actual, like, you know, kind of YouTube, like, video business. But but I think, like, coming up with, like, these different, like, fun weekend projects is a really useful construct to, like, force myself to actually try these products in a more than just like a twitch click way. And you know what what it gives me is like a like it's not just understanding the models which is also very very important. Right? Like GD five came out yesterday and like playing around with it a bunch, just on like a variety of different like personal use cases. You know, but like there's a difference between just understanding the model, but then also understanding like the product form factors in which they can be placed. Right? Meaning like, you know, when you apply the model in a more structured way. Right? You know, when you apply the model with different tool calling than maybe what Chachpi has in its kind of, like, out of the box form, you know, when you apply it with, like, you know, kind of a more agentic workflow, again, that might be different from, like, what Chachap Tea gives you out of the box. Like, that's when you kinda learn, like, you know, you you really get to inspire yourself on, like, what are the products form factors that these new models can take. So, like and and plus, by the way, like, I find it to be really fun. Like, there is a to me, like, a delight and entertainment value to just using AI period because, like, a, it's it's it's not it's not, like, perfectly predictable. So I think the element of, like, you're not quite sure what you're gonna get. You know? It's like a box of chocolates, you know? And and, b, like, it always blows my mind just to think about, like, wow. Like, you know, five years ago, we didn't have any of this stuff. Right? Like, you know, AI was like, okay. Like, it's like, we can do predictive analytics. It's like, you know, there there's some, like, basically very advanced, you know, kind of regressions that we could run with with AI. But, like, it looked nothing like this, right, in its in its current form. And it's just, like, actually super fun, in my opinion, to get to play around with all the different types of products that that, that come out. So I think that is a big part of it. You know, because on the point about, like, the pace of the world moving so much faster in AI than any other landscape, it's like, you know, in SaaS, you know, in the mature SaaS era, like it was important to study your competition. Right? Like if you were building a SaaS company, you'd be crazy not to follow Salesforce. Right? Every, like, year and see what the, you know, the major releases they're putting out are or ServiceNow or, you know, so on. Like, this is the equivalent of that, but, like, there's major new releases and products and and so on, like, every week. Right? Not, like, every year. And so I just think you have to stay abreast of all, of it all. And combining this with our point earlier of, like, a lot of this has to be experienced, not just, like, read. Like, you can't just read, like, the write up on TechCrunch or or, you know, even a tweet about, like, a new capability. Like, you kinda have to try it to really get a sense of, like, what it is. Today's episode is brought to you by Anthropic, the team behind Claude. I use Claude at least 10 times a day. 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There's a difference when, like, you come in with a curiosity and, like, you know, you're kind of, like, exploring. Right? And it's both more fun and energizing, but also I think, like, you learn more through that. Right? And so, like, I've really tried to stress the value of play with these AI products. And I kind of, you know, try to lead by example by, like, literally going and, like, sharing out links or or, screenshots, like, you know, of the things that I'm doing in these various products. So, like, you know, as an example, you know, like, I, will go into, you know, like, what one of the, prototyping tools and show, like, hey. Like, you know, I built a marketing landing page for, you know, this new, capability we're launching. I kinda created, like, a landing page for it in Replit, let's say. And now I'm sharing that link instead of, you know, what typically, like, we would have done in the past is, like, okay. We're gonna write a doc about it and then share the doc. I'm just gonna show you, like, an actual landing page with, like, visuals and everything in there. Right? Or, like, I'll share, like, you know, the actual link to my deep research reports or, like, instead of me writing a perfect memo on a topic, like, I'll actually just, like, prompt my way into getting, like, a chat thread, or chat output that basically covers all the content that I care about and maybe even, like, ask it to, like, okay, summarize this all into, like, a final, you know, kind of, like, memo output and then intentionally share that rather than expose the fact that, like, I'm using AI in this way and here's literally how I'm prompting it so you could follow along as well. You know? But really trying to encourage everyone to, like, go and just play with these products. And I've even said, look. If anyone wants to just literally block out a day or frankly even a week and, like like, have the ultimate, excuse, like, you can use, like, you know, you you could say that I told you to do it. Right? Like, if you wanna cancel all your meetings for, like, a day or for an entire week and just go play around with every product AI product that you can find that you think could be relevant to Airtable, go do it. Like, period. So I think that's the most important thing is, like, this this play, this experimentation. I think there's also a lot of other, you know, kinda shifts in how we execute, prototypes over decks. You know, like, I I wanna see, like, actual interactive demos because, like, again, like, it's hard to to, you know, in a deck or in a PRD, you could say, like, okay. Well, we're gonna make Omni really good at handling this kind of app building. Okay. Those are just words. The real proof is in the pudding of, like, okay. Let me try it out on a few, like, realistic prompts that I can imagine. And in a demo, in a real prototype, you can, like, instantly, you know, try it out on unrealistic rather than golden pathy scenarios, and see how it feels too. Like, is it does it feel too slow? Like, do we need to expose more of the the reasoning or steps, you know, kind of, you know, that that are happening behind the scenes, create a progress bar or something like that. But, like, it's really hard to get that feel of the product with anything but, like, a functional prototype that really does in an open end way, you know, like, use the the AI to to do whatever, you know, you put in. So, you know, I think it's it's more like a, like, experimentation playground, it feels like, how we need to execute versus I think in the past, it sometimes felt like a more, like, deterministic resourcing and and, like, kinda timelines view of execution. Right? Like, we're gonna put this many people on this problem, and this is the eight week timeline to this milestone, and we're gonna ship in a quarter from now. And, like, I think now the whole thing is just, like, a lot more experimentation and iteration driven. Of the different functions on a product team, PM engineering design, who has had the most success being more productive with these tools? And how do you think this will impact each of these three functions over time? What I found is that it really does become more about individual attitude and maybe some, like, you know, polymathism. Like, you you know, there's a strong, advantage to any of those three roles who can kind of cross over into the other two. Right? Like, kind of the the hybrid unicorn types. Right? So if you're a designer who can be just technical enough to kind of be dangerous and and understand a little bit of, like, how these models work and, you know, like, how does tool calling work and, and all of this stuff. Like, then you can actually design a concept or even prototype a concept in including in these prototyping tools, that that's much more interesting and maybe realistic than if you're just stuck in kind of the flat, like, let me put something in a static design. Right? Concept. Right? Because, I think, you know, designs have to be more interactive. Like, the the whole the the the value of the product, and the product functionality is in the interaction of it. Right? Like, you know, think about the design of ChatChappiti. Again, it's like, you know, it's the most basic design you could possibly imagine. The real design actually is happening underneath the hood in how it responds to different queries. Right? And what happens after you fire off a prompt. Right? So, you know, I think, like, I found that there are people within each of these functions, like, there are engineers who are very good at thinking about product and experience and, like, you know, kinda can can go and prototype out, like, the whole thing. There are designers who can kinda do do the same. Even if they can't literally code, they can prototype something out, like, literally using a prototyping tool. And I think that's where, like, AI tooling is also giving more advantage to people who can think in this way by equipping them with an alternative to actually having to go through the long hoops of learning CS. Right? And then PMs as well. I think, like, there are some PMs who are, like, really getting into the technical details and studying up on, like, you know, how does this stuff work and actually getting hands on rather than seeing the role as, you know, kind of writing documents, writing PRDs. Do you see one of these roles, I don't know, being more in trouble than others? Just like you need fewer of these these people in the future potentially? I think overall you can get more done with fewer people and that's not to say like you know we wanna go and like like make the team smaller but rather like like the really cool thing for for, Austin I think a lot of other companies is it's not like you have a finite set of things you need to do and execute on from a product standpoint. And, okay, like, now I can do that with a tenth of people. I mean, you could do that in a lot of cases. But, like, for us, maybe it's also because we're a very meta product. Right? Like, we are the app platform with which you can build now any AI app with AI. Right? The apps themselves leverage AI capabilities at runtime whether it's to generate imagery for a creative production workflow or, you know, kind of leveraging deep research, or AI based, like, you know, kind of crawling of the web to search for companies that match a certain criteria for your deal flow app. Right? Or something like that. Like, we can effectively leverage all of these of our AI capabilities in this this kind of, like, app platform because by definition, we're enabling our customers to build apps that have this wide range of AI capabilities. But because of that, it's like we have a, you know, kind of almost infinite, like, set of possible AI capabilities that we could execute on. Right? And I'm always telling the team, like, look. Like, the great news is, like, we have it's like we have all these fruit trees and, like, there's so many crazy low hanging fruit. Right? Like and you got literally, like, massive watermelons, like, literally sitting on the ground. Right? And all you have to do is, like, kinda walk over 20 feet and pick it up instead of having to climb the really tall coconut tree to grab, like, a hard coconut from, like, 50 feet up. And so, like, there's so many watermelons on the ground. Just go out and, like, start finding the biggest ones and attacking those. Right? And, like, and what that means is that, like, if we can build this culture and I do think, like, it's a learnable way of operating. Like, I I I really like to believe in, like, the, like, the growth potential of, like, any human. Right? Like, and and, any individual. Like, I think if you really have a growth mindset, that's why one of our like most important core values is is growth mindset. Right? Like if you really have that growth mindset, I think like especially if you're willing to put in the nights and weekends hours or in my case like I'm literally telling people like like, take a full day off, take a full week off and learn this stuff. Like, you can, you know, become more fluent, in this way. And I think then what we get is, like, a team that can just go and work on more things in a much more leveraged and fast way. Right? So I like to think like, you know, people who are willing to jump on the train are just gonna become more and more effective and it's not like, oh, like, as a PM, my role is becoming entirely irrelevant. Right? Like, no. It means that as a PM, you need to start looking more like a hybrid PM prototyper who has some good design sensibilities. And by the way, like, I think some of the best eng PM and design cultures respectively over the past even few decades have always been multidisciplinary in nature. Right? Like, the original PM spec at Google required the PMs to actually be somewhat technical so they could they could understand the engineering, you know, kind of, limitations of of, like, the product, you know, designs they wanted to make. And they had to be kinda design y. Right? Like, I remember my my cofounder, Andrew, when he was in the APM program was, like, always reading books about, like, design. Like, even down to, like, visual design and color theory and that kind of thing. Right? And so I think it's just a reminder that, you know, like, designers as well, like, the you know, some of the best designers, if you're designer at Apple, like, you know, including hardware designer, like, you have to understand some of the technical capabilities of how this stuff works. Right? And if you're an engineer, like, I think some of the best engineers and maybe Stripe always had a very good engineering culture of engineers who could think about the product and business requirements. In fact, like, you know, on any given product group, at Stripe, my understanding is that, like, you know, the DRI isn't always the PM. Right? Like, as is traditionally the case in in kind of that that triangle. It's like, you know, sometimes it's actually the engineer who's taking the product lead and saying, like, this is what we need to build. So what I'm hearing is essentially, if you want like, the trend across product engineering design is each of those functions needs to get good at one of the other functions at least. Yeah. Ideally, you can do them all. But if if you can just do one additional so PM becomes better design and engineer becomes better at product management. Well, I would actually go further and say, like, I think you mean get, like, decently good at all three. Like, there's just a minimum baseline of, like, if you're any one of those roles, you need to be, like, minimally good at the other two, and then you can go deeper into your own kind of specialty. Right? Like, you know, you could be a designer who's really good at thinking about UX and interaction design And then just, like, good enough to be dangerous on thinking about, like, what's technically possible and, like, what is the product, you know, kind of, you know, kind of story around this this, feature. I love that. And to do that, one piece of advice that comes up again again in what you're what you've been describing is using use the tools constantly to see what's possible, and that will teach you a lot of these things. I think use well, use the tools gives you exposure to what's possible. Right? It's kind of like if you want it to be a great industrial designer and let's say, like, I mean, the chair is kind of the ultimate, like, hello world of, like, industrial design. Right? It's like the the, like, canonical design object. Like, you wouldn't just sit there in a vacuum and with no familiarity with, like, the materials that you can use, plywood, steel, whatever, or, like, existing form factors of chairs trying to invent the world's best chair in a vacuum. Right? Like, you should go and first do a study of, like, all of the best chairs out there today. Like, go look at an Eames chair, sit in it, like, try to examine it to kind of reverse engineer how it was made. Right? And, like, you know, and and, just look at the prior art for that type of product. Like, that's how I see the go out and play with these products. And also, I think, like, actually going and designing or implementing or executing is the best practice. So, like, you can't just only go and look at other people's shares. Like, eventually, you have to go and, like, actually try building your own and then try building another one and another one and another one. And so I think that's where, like, you know, when I think about how I honed my own product UX sensibilities, like, I never, like I mean, you know, and at that time, like, that I was in in a school and then kinda learning about this stuff, like, there wasn't really any good curriculum for UX. Right? It's not like there were, like, great, you know, college classes to learn product UX. I mean, even CS was, like, very academic in nature at that time. It wasn't applied software engineering, like, build an app or whatever. Maybe now at, like, some of the schools, like Stanford, MIT, they have, like, actually UX y type courses, but it's it's still a rarity for most people to have access to that. And so, like, the way I learned, like, all of my product sensibilities was just, like, trial and error and, like, also using and studying other products. Right? And then going and trying to build, like, my own weekend project ideas. Right? Oh, I wanna build, like, a Yelp style app with a map view and then also a list view, and I want it so that when you when you pan around in the map for it to automatically update the list view, and maybe there's some UX improvements I can make on top of that, but I can also, like, test my technical skills to to figure out, like, which parts of this are hard to implement and, like, how do you make it work and what are some of the design changes or affordances that you can use to kind of, like, map to, like, the technical possibilities. To do that, I loved your piece of advice, which I forgot to double down on, which I also find really powerful. The best tip there is find something to actually build that is useful to you and fun. Like, pick a project that's like, oh, yeah. This would be fun to do. Have, like, a problem you're solving that forces you to actually do this thing. For sure. And, look, I think that can be, like, night and weekend projects. It can also be, like, the daytime job projects. Right? I mean, like, I am basically telling our teams on the AI platform, group, especially, like, look. Like, you know, in that that low hanging fruit metaphor, it's like, I'm not being prescriptive with you on, like, which watermelons you should pick. But, like, you should go and, like and and we do have different, like, pods within that group. But one of them, for instance, is, what we call the field agents team, and they are responsible for the agents that work within your app. So this is not the agent that builds your app, but these agents that run on a customer's behalf to do, like, web research on your customers or they can, you know, go and analyze a document. And, like, in the future maybe do things like actually generate a, like, prototype, like, of of a, of a feature, you know, from a PRD or from, like, a future idea. And, you know, I'm telling them, like, look. Like, there's a almost infinite number of things you could like, superpowers you can give these field agents. I'm not gonna tell you which specifically to do. Now you can ask me to weigh in for sure, but, like, you should go and, like, you know, just experiment and prototype, like, a few different versions of like, a a few different directions we could go. Like, what if you prototype what it would look like to have a deep research implementation in field agents so that, like, for any given row of data, let's say in your case, it's podcast guest, you can just click a button or click a button en masse across the entire, like, every speaker you have lined up to do deep research, like, powered by chap GBT's own deep research on each of the speakers and have them all laid out side by side in this table. Right? Like, go prototype that and see how, like, you know, see how it feels and looks like. And so I think some of the stuff can also be, like, in your daytime job, especially if that daytime job is literally to go and build AI functionality. I actually tried to do exactly that. The The problem I ran into, I wonder if it's changed as there's no API for, for chat gbt deep research yet. There is now. There is now. There is. I see. There we go. Ends up being, and I think they only recently exposed it. It ends up being, like, something on the order of, like, a dollar plus per research call, which What a deal. I mean, again, exactly. I mean, some people would say, oh my god. That's so expensive. And you rack up 50 of those. You you've cost $50 a month. I think it's like, well, it just saved you, like, hours of research by human. Not only that. I I actually have a researcher that I pay to give me background on guests that was, like, 4 or $500. And the dollar sounds great. And I I've been doing this manually. You're smart. You'll be using deep research, And then just collecting the They might just be. Oh, man. Okay. There's one more, skill I wanted to talk about real quick. This comes up a lot in these conversations is evals. Okay. The power of getting good at evals. I know that's something you value highly. Talk about just why you think this is something people need to get good at. Yeah. I mean, and I listened to your your, your episodes with, with Kevin and Mike, who talk about this. I think it's, like Yep. Interesting that, like, you know, like, both heads of OpenAI and Anthropic, you know, have converged on on this point. I mean, look, I think, I I would add, like, a a slightly different or additive take, though, which is, like, I think, for a completely novel product experience or form factor, you should actually not start with evals and you start with vibes. Right? Meaning, like, you know, you you need to go and just kind of test in a much more open ended way. Like like, does this even work, like, you know, in in kind of, like, a broad sense? So, like, as an example, for our custom code generation capability, like, instead of defining evals that get repeatedly tested, you know, as you vary, like, the prompt or the model or, like, the the agentic workflow used to generate the these outputs, and you have to define, like, you know, what does good look like, right, by definition for the eval. Like, I would first start with a much more open ended and, like, ad hoc style of, like, just throw stuff against the wall, like, try different prompts and see how well it does. And to me, evals are more useful, a, once you've converged on the kind of, like, basic scaffold of the form factor and you kinda know what are the use cases you want it to work well for and what you want to test against it. Whereas in the early days, especially if if your product market fit finding either for an entirely new company or for, like, a new a pretty dramatically new or bold new capability that doesn't really have, like it's not an incremental improvement of something that exists in our table today. Like, I think you have to just be a little bit more creative initially in, like, throwing stuff at it, seeing what works to understand, okay, like let's use an example. You know, we we're implementing this new capability that can use, basically a long running AI crawler agent that goes and researches the web, you know, for a specific type of object or entity. Right? So it's a little bit different from deep research. It's similar to deep research, but what it actually does is instead of outputting, like, a, you know, kind of a report, it's actually going and compiling a list of things. The things could be companies or people, or or anything else. Right? Like, find me every Marvel movie. Right? Ever made. Find me every, like, you know, kind of DC comics, like, spin off. Right? Like, series. Right? Literally anything. And, you know, you have to go in at first, like, just try out a bunch of random, like, you know, use your own brain to think of, like, what are all the, like what's the range of use cases I can test this against. Right? And then you get back some results and you're like, okay. Well, like, it's clear that, like, where it does really well are these types of searches. Right? Like, people on companies with this kind of parameter. And I think to me, like, evals are useful once you have, like, a sense of, like, what is that cluster of useful use cases? You can start then more, like, programmatically, like, measuring the changes that you're making to improve, like, the the, the the the output for that. Right? But, like, by that point, you've probably already scoped the product and maybe the way we would merchandise it in the the, in Airtable is not like a completely open ended capability, but, like, hey. Like, here is a specific capability that can research one of these x number of, entity types including people and companies, and here's even, like, the filter conditions or criteria that are more explicit that you can define to give it the prompting to to search for that thing. Right? But I kinda think it's it's more useful as a way to iterate your way to improvement. And you can start, you know, really testing stuff, like, empirically. Right? You can AB test, especially if you have the scale of a really large product like Infropic or OpenAI. You can, like, just test everything and and see, like, oh, this model actually performs certain than this one. This prop performs certain than this one. But I think early on, like, you don't have that luxury, and you're in a much more open ended discovery process. That is very wise. Evals could constrain you too early. I think about just the double diamond, I don't know, IDO kind of framework of, like, be divergent first and then converge and then maybe Yeah. Yeah. I I exactly. I hadn't heard that before, but, that that, completely resonates. Okay. Let me try to reflect back some of the advice I've been hearing about how to shift a company to be successful in this new world. And let me see if I'm missing anything that you think is really important. So one is there's this sense of just, like, reset expectations on pace and urgency and help people understand in AI, things move incredibly fast. This is how we need to operate. And then there's also a piece of get stuff out so that you can learn how people use it and what it's capable of versus polishing it endlessly. Mhmm. Forcing people almost I don't know. Forcing is the right word, but encouraging people to play with the latest stuff and, like, giving them chance to take days off to or block out calendars, cancel meetings, just, like, stay on top of the stuff Yeah. To play as you talked about it and then sharing things they've learned, get the vibes of what's possible. There's also this idea of just rethink, okay, if we were to start today in this world, what would we do to achieve the same mission we have achieved we are trying to achieve? And ideally, it leverages this unfair advantage we have with things we've been working on for a long time. And then there's just, like, Talk to AI constantly every hour as you describe. Yeah. Multiple times an hour. Multiple times an hour. Just going up. Is there anything else that I missed there that you're like, this is you need to do this to to be really to have a chance? I think just to really, really try to break down role silos. Like and I think that's true certainly for EPND, in the typical, like, you know, EPD triangle. But I also think it's it's probably true even for, like, non product roles. Right? Like, I think, it's true in marketing. Right? Like, I'm seeing, you know, something, you know, something I'm really pushing for in marketing. I think our marketing team is, like, you know, really leaning into actually is, is, like, you know, if you can just do all of the thing yourself, like, traditionally, you know, how a marketing team might operate is, like, okay, you have one person who's kinda responsible for executing the performance marketing, you know, kind of, part of a campaign. Right? Like, they literally go into the Google AdWords interface and they're, like, tweaking the parameters of targeting and, you know, budget and, like, you know, kind of, conversion, tracking, etcetera. And and then somebody else is actually responsible for, like, coming up with the specific ad copy. Right? And somebody else yet was responsible for coming up with, like, the seed content or positioning, you know, guide, like, written by a PMM that feeds into the ad creative and, you know, so on and so forth. Right? Like, maybe they're promoting some, like, new demo asset, right, that somebody else, yeah, created. And I just think that, like, you know, in the same way that you can collapse the roles in EPD and, like, the ideal person, maybe they're they're very specially, you know, specialized in deep in one dimension like engineering, but they're well rounded enough to kind of, like, be dangerous on the other two. Like, I think that's kinda true in almost every other function. Right? Like, you know, like, sales as well. Like, I think you should, you know, start to be able to play more of an SE role. Like, traditionally, salespeople, didn't necessarily know the product that well and, like, you know, kind of relied on the SE to come in and be the product experts. Like, I think it's really hard to sell any kind of the AI product now without actually being fluent in the product and be able to demo the product. Right? So, like, you know, in, AEs need to be, like, SE fluent as well. So I just think that that concept of, like, collapsing roles, you know, everybody needs to, like, become more full stack to do the thing like, being more outcome oriented. Right? Like, your outcome as an AE is to, like, show customers, you know, convince customers of the value of your product and close deals. Right? Okay. Well, in order to do that, like, you used to have dependencies on having assets created by marketing and, like, you know, an SC to help you demo. Like, can you collapse more of those dependencies so that if you had to, you could do it all yourself. Right? And I just think that's a new way like, it's a new operating mentality overall for every AI native company or company that wants to compete in this new arena. That is that is a great addition. It almost feels like you go back to startup times when everyone's doing a bunch of stuff. There's no, like, here's the head of product. Here's the head of engineers. We're just doing stuff. Totally. To be done. Totally. Yeah. I'm kind of seeing it as this is, like, upside down t where there's, like, the thing you're really strong at, and then you just have to the as you describe, the minimum of being good at engineering design or and SC, by the way, sales engineering, imagine, is what that stands for. That you just like, they're adjacent roles. You need to start having a baseline. The baseline is increasing of how much you need to understand that. Everyone's Venn diagrams are kinda converging. Exactly. Amazing. Okay. Let me take a step back and kinda zoom out and think about the broader journey you've been on over the past decade plus. Let me just ask you this. What's what's the most counterintuitive lesson you've learned about building Airtable building company building teams that maybe goes against common startup wisdom? You know, I I heard, you know, your interview with with Brian Chesty. I mean, later he talked about founder mode, in in that kind of YC retreat. And the points there really, really resonated with me. You know, and I I feel like, maybe less eloquently, I kind of, like, deduced, you know, some of the same principles just just in my own experience, which is, like, I think, when you're scaling up, and this relates also to what we talked about before around, like, the early days of building a company. You're, like, in the details. You're finding product market fit. You kinda have to be, like, you know, pretty versatile. Right? Like, you know, all these decisions from a technical standpoint to design to even commercial and, like, what's the freemium model gonna be like and, like, you know, how are we gonna market this product? What does the website look like? Like, they're all very intertwined. Right? You can't, like, compartmentalize and then, like, you know, almost, like, factory produce, you know, kinda each of these things separately. Like, you they're all intertwined. Right? And you have a very small tight knit meme that's, like, a tight knit team that's thinking full stack about all of this combined. And, you know, obviously, like, that's the only way, in my opinion, to create, like, that that magical product market fit in the first place. And then I think as you scale up, you know, the default guidance that you often get from, you know, like, operational experts and and, you know, kind of, like, larger scale, you know, kind of, company investors is like, okay. You gotta kind of industrialize the process of all of this stuff. Right? It's kind of kind of like going from, like, a bespoke artisanal, like, one person made an entire, you know, item of clothing to, like, we gotta, like, factory produce this thing. Right? And, you know, what that means in a organizational context is, like, you then create these different fiefdoms, you hire all these execs, and, like, you know, each exec kind of, like, just manages their own swim lane. And there's relatively looser coupling between all of those different groups. Right? So we got sales kinda kinda executing on its own thing. Marketing is executing on its own thing. Product's executing on its own thing. Rather and even within product, there's different product groups and surface areas that are each kinda executing on their own thing. And, you know, using the factory metaphor, like, there's there's an argument that that's actually kind of an efficient way to scale up production for each of these different swim lanes. Right? Like, each one can kinda operate, you know, like, in a in a more autonomous and, like, you know, purely, like, scale up, you know, focus on a way. How do we produce more of this thing? If the thing happens to be within one product group improving search, that's our main focus. We're just gonna, you know, go and ship ship ship more stuff to improve search. And, you know, so there there it's not completely crazy, like, you know, why why people give this advice. But I think what you lose is the magical integrative value of holistic thinking. Right? And and making the bigger picture bets. Right? And I think Brian talked a lot about this on his, episode with you, which is, like, look, like, in in a company that is really serious about product, first of all, like, you know, I really liked his point about, like, the CEO has to play a CPO role. Right? You have to care about product. Like, ultimately, like, the product is the thing. Right? And you can't just coast on scaling up go to market around the product forever. Like, you gotta keep innovating in the product. And by the way, the best way to innovate on the product is not incrementally split over all these different, you know, different little service areas, but actually to have, like, a bigger, you know, kinda more step function vision of how this product needs to make a leap. Right? Or what's the next big, like, you know, kind of, either act of the product or new capability of the product, or reinvention of the product. Right? And so, like, I think if you really care about doing that from a product execution standpoint and almost like refinding new product market fit on a regular basis, like, I think it necessitates a completely different operating and leadership model throughout the organization. And all of the stuff we just talked about in terms of how to operate in the AI native era, I think it's actually exactly the same as how you need to operate in this, like, constant product market refinding a fit, state. So, like, could not agree more with with that concept of, you know, kinda you gotta, you know, think ambitiously and move the organization holistically towards these bigger outcomes, but also like ship and learn and experiment a lot more in this era. And then, you know, maybe the meta learning I had from all of the above is that like, you know, the specific advice obviously was like, okay. Go scale up in this way or go hire these types of people, experience operators to obviously, there's some truth to that. Right? Like, you know, the people giving this advice are not incompetent. You know, they they had some reason for getting it, and in certain context, it that is the right thing to do. But I think, like, my meta learning is, you know, it's it's not, enough to just, like, trust the recommendation. Like, here's the action you should take from a lot of people because everyone has different priors. And it's almost like we're all our own l labs. Right? And, like, we all have different training from a different corpus of data informed by our own experiences. And maybe you're trained on, like, the, like, you know, kind of ServiceNow or the, you know, kind of a Oracle, you know, kind of, you know, training corpus. Right? And, you know, this person's trained on the Facebook corpus, and I'm trained on, like, you know, the Airtable one. Right? And I think what I've tried to do more and more is, like, not just, like, ignore advice from smart people. Like, obviously, that's not the right answer. But, like, to kinda take their it's almost like, in an LLM, you can now, like, with a reasoning model, like, actually inspect the chain of thought. Right? Like and and, see how it's thinking. Why did it come up with this answer? Right? And to me, that, like, chain of thought, like, why did you recommend this is actually more informative than the actual, like, just do this recommendation. Right? So the answer might be like, hey. Like, you know, at so and so company, this is how we eliminated the PM role entirely. Right? For for Brian, like, at Airbnb, like, made sense. Like, we're no longer having PMs in their traditional form. Now we have program managers and product marketers. And but, like, more than the actual decision, because I don't think it's a one size fits all. Like, everybody should do the same. Why did you do that? Right? And the why actually was very informative, and then be able to take that and say, like, okay. Like, how would I apply that? And maybe it yields a different outcome, but the reasoning actually is very, informative. It's interesting how this idea of founder mode is not so different from this ICCEO trend that you're following, and it's it's yeah. Yeah. It's like being in the weeds, being in the details, trying things yourself, not delegating to execs. Yeah. You know, and and, like, I think anything taken to an extreme can be problematic. Right? So, like, there is a world where, like, you know, you are so in the details and in every detail that you're basically just micromanaging and you're you're you're kinda creating, like, you know, kind of euphemism for that. And that's not really what founder mode is about. Right? Like, that's not, like, the the Bryan of founder mode is to, like, micromanage everything and, like, not trust anyone. But I think it's more about, like, finding that right balance of being unabashed about caring about the details that do matter and where the tying together of details across different groups or departments actually is the only way to yield a non incremental outcome because otherwise each person is just optimizing within their own domain. Right. But you'll never get to the global maxima or the global breakthrough. And, you know, I think, like, the really cool thing about, you know, CEOs as ICs and frankly any leader playing more of an IC like role and being in the details is I think for the right type of person, it's it's actually more fun that way. Right? Like, I mean, to be honest, like, for me, like, the the times where I felt most, disintermediated from, like, what I felt was, like, the substance of this company was when I thought that I I was almost, like, you know, forcing myself to step away from the details because I I thought that's, like, what, you know, a at scale CEO was supposed to do. Right? Like, I mean, there there's, you know, some, like, you know, famous CEOs who have talked about, like, the the less decisions I could make, the better. Right? Like, the less details I'm exposed to, the better. Right? Like, I just wanna inspect at the top most layer how this business is running. And if the everything underneath it is going smoothly, then, like, I'm able to do that. Right? And everything looks good. And I just think that's a maybe, again, it works in a certain type of very mature type of business. Like, you know, even then though, like, I can't imagine that, like, at a CPG company, like, in Procter and Gamble, you wouldn't want to have a CEO who still actually goes and tastes the soup and, like, tries the products and sees, like, literally the details of, like, what the new product innovation pipeline looks like, as well as, like, how it's being experienced on the shelves and so on. Like, so I don't know I I guess, like I guess I'm just more and more skeptical that that like hands off, you know, pure delegation, you know, and process management role ever works as a CEO. So maybe maybe you just like you go through a long enough period of like where the business is coasting that like nobody notices. But I gotta say like for me like it's just much more invigorating to get to play that role. And I think for for the types of operators and leaders that I most admire, like, it's it's like, that's what makes the job interesting. Like, they don't wanna have, like, a automated away, you know, kind of role as a leader. If you could go back in time and whisper something in, decade ago, Howie's ear that would have saved you a lot of pain and suffering over the last decade, what would that be? Don't step away from the details that both you love. Like, I mean, first of all, like, if your passion is, like, building product and product design, even if it feels like at times the company needs to do all this other stuff, like, scale up, you know, go to market and operations and, like, just have, like, a large people organization that itself creates a lot of, you know, kind of, you know, need to to do things and manage and, like, there there becomes a new job invented just to, like, manage a larger group of people. Right? And, like, you know, obviously, you're gonna have to do some of that. You can't just completely ask you all your responsibility as, like, a upscale CEO. But, like, don't lose the, like, the the essence of, like, the thing that you love doing and that, you know, had, like, really made this product happen, and gives, you know, this company as many companies that, like, were were founded on, like, a, you know, kind of a magical product market fit finding insight. Don't, like, step too far away from that. Right? And always make sure that is still your, like, number one even if, like, other stuff has to also add to your plate. I think people don't talk enough about this, how if someone starts a company, that's an idea they have they're excited about. It takes off, and then you're stuck on that for a long time. And then even if things are pushed in a direction you're not as excited about. And so this point about just remembering what you actually love about it and coming back to that is so important because that's the only way to keep doing this for for a long time. I I I think that's so true. And to me, that's why there's always been a difference between entrepreneurs who love the the act of building a product or, you know, the business too versus those who saw a, you know, just purely business or financial opportunity that they felt like they couldn't pass up exploiting or or going after. And, look, no knock on people who are more the latter and, like, there's entire industries where, like, it's all just about alpha generation. Right? Like, you know, you could go into private equity business and and so on. And it's just purely it's it's rationally about, like, how do I find the alpha. And I think that like, you know, the some of the best companies, product central companies at least in my opinion are like, you know, run by those people who like actually just love the product. Right? I think you get a feel for that from some of the AI companies like Sam, like, I think genuinely just loves, like, working on AI. Right? Like, if he could spend a 100% of his time on, like, just being close to the AI and the research, I mean, he won, and he's even said as much. Right? Like, you know, but but ranging to, like, the Brian's with Airbnb, like like, it's pretty clear, you know, that, you know, people like this are not motivated. Like, Airbnb was not founded because, like, oh my god. We we wanna make a lot of money off this, like, arbitrage opportunity against hotels. They just needed to pay their rent. Yeah. Well, that that and, like, I think they loved the the product, and I think all they also love the way in which they built the product. Right? Like, you know, the design centric nature of that product and company and culture, like, you know, and and that's what gives you, like, the continued joy of of, working on, you know, what could be the same company for a very long time. Howie, is there anything else that you wanted to touch on or leave listeners with before we get to our very exciting lightning round? I I just wanna reiterate, you know, especially for for listeners here who who are in, you know, an EP or D role and especially in the p role, like, you know, I really do believe that this is not a like, you either have or you don't, like, in terms of the skill set needed to be relevant and AI needed. But I do think, like, it's a call to action to go and and bolster your skill sets where where, you know, where where they may be, you know, less refined right now. Right? Like, I think everyone like, even programming, I really believe, like, everyone could learn how to be a software engineer if they wanted to. Now, like, obviously, like, some people just as with, like, great writers are never gonna be, like, you know, a published author. Right? Or, like, you know, the the Hemingway. Right? But, like, everyone can gain a good enough proficiency of software engineering if they really wanted to. You could take that boot camp. You could do, like, some, like, you know, coding, you know, kind of exercises on on the side, etcetera. And the point there is that, like, you know, sometimes I think we treat these disciplines like, you know, hard, hard skills that, like, if you're not already if you're already halfway into your career and you're not already an engineer, if you're not already a designer, like, okay, well, you can never be one. And I just think, like, you know, our brains are malleable. I mean, there's a lot of great curriculum out there to learn and and, you know, a lot of it, like I said, just comes down to also, like, trial and error and, like, building projects, maybe nights and weekends projects, even, to learn, this stuff. But, like, everyone can learn how to be a versatile, you know, kind of unicorn, like, product engineer designer hybrid in the AI native era. And and, like, the only thing stopping you is, like, just going out and doing it. That is a really empowering way to end it. And I just to double down on that, it's never been easier to learn these things. Like Yeah. There are super intelligences that you can talk to that do a lot, like, as they're building can help you learn. I mean, like, I literally I mean, I go into chat to get you sometimes and I ask it, like, you know, just like, hey, like, how would you build this app? Like, we're you know, like, I'm just curious. I'm like like, how would you build Manus? Right? Like, the the agent, open ended agent. Like, literally, how would you build it? You can ask you questions, and it's like having, like, an amazing, brilliant software architect, software engineer, product manager, designer, expert, tutor, that you can literally like, there's no dumb question. They have infinite patience. They're literally on and awake, like, twenty four seven. Like, it is the most incredible time to, like, learn this stuff to your point. And then, of course, like, the interactive tools to go and actually build stuff, like anyone can download cursor and just start, like, asking composer to generate some code for you and then looking at the code and trying to figure out what it does. And, you know, to your point, like, it you know, when I think back to the earliest era that I experienced of building apps, like, you know, first I learned c plus plus, then I learned PHP and JavaScript and, like, even, like, building, you know, kind of JavaScript, like, single page apps in the early days, like, o eight, you know, through 2010. Like, it was a dark, dark art. I mean, there were some, like, you just have to, like, go and, like, learn some of these things. There wasn't great, like, you know, tutorials for it. You know, you had to reverse engineer certain things. Like, there were just, like, weird things. Like, if you wanted rounded corners in your UI, you literally took Photoshop, opened it up, created, like, a rounded corner and pixels, and then I remember that. Pixel off into an image that you dropped onto the page at exactly the right position to be at the edge of, like, a box. Like, crazy stuff. Right? I mean, everything was, like, so much more arcane at the time, and now it's just it feels so much more fluid and accessible. And, like, the gap between the arcane tech that you have to wade through to build something has just been minimized so much. It's like the the effort and, like, abstraction between you and, like, the magical, delightful, actual building of the thing that you want has been so minimized. So it's never been a more exciting time to be a builder. You remember spacer.gif? I was yeah. Yeah. It's like to create, like, the line stuff you just I remember. Yeah. Invisible one pixel thing that you just stick in places. Yeah. Yeah. No. I Oh, my God. What a time to be alive. Howie, with that, we've reached our very exciting lightning round. I've got five questions for you. Are you ready? Yes. There we go. What are two or three books you find yourself recommending most to other people? You know, I I've, I've been trying to read fiction more, partly because I think it's just a really nice mental reset. I will say, like, Three Body Problem, like, for anyone who hasn't read it, like, it's it's a mind expanding book. Like, I like sci fi and fiction that, like, kind of opens your brain. So this is my cheat card, but, you know, it's a three book series. Those are those are three great books. I love that series. And my tip there is it gets good. One and a half books in is my tip. So just keep reading. That's where it's, like, whole Yeah. How I'm in. I like even the first one. Okay. But I do like, it I felt like it was, like, inception where every book every subsequent book was, like, you dropped into another like, you you incepted into, like, another layer. Right? Awesome. Okay. What's a favorite recent movie or TV show you've really enjoyed? TV show. I just started watching the studio. The it's, like, the Seth Rogen, Rogan. Yeah. So stressful. Yeah. It is pretty stressful. And, you know, I I just kinda like I mean, Silicon Valley was, like, too close to home, when it came out. So, like, I watched it, but it was, like, just cringey. The studio is kinda fun to watch because, like, it's it's it's a little bit about, like, inside baseball of, of Hollywood, and yet, like, I'm not in Hollywood, so it's, like, entertaining to watch. And, it's just, you know, it's it's a I thought smart and, funny show. And, you know, because I split time between LA and SF, like, I also feel like it's, it's very real to me. I see a lot of the, like, literal characters out there in the world that that, it's characterizing. Do you have a favorite product you recently discovered that you really love? Could be an app. Could be gadget. Could be a clothing. So okay. So I'll I'll give, two, because I feel like I have to I have to say some kind of software product. Right? I mean, I, I'm a really big fan of Runway, the product and the company. I just think, like, you know, every, like, new model, they come out with, they just came out with with a new one just, I think, like, two days ago, that gives even more, like, controls and refinement on, like, creating exactly the video scene that you want. And so, like, I think just the photo realism, in in what you can generate now. And, like, they also built this, like, cool demo thing that's, like, an immersive world generator I mentioned before. I think, it's just cool to see I also like the underdog story. I'm, like, clearly, like, Google's gunning gunning in space, has v o three and so on and, like, you know, as is opening the eye, but, like, I love the underdog story of this, like, sub 100 person company still punching above their weight and building, like, really awesome, you know, video experiences. Right? So that's the software one. And then a very, very, kinda nerdy, real world, answer on product is I kinda just recently got into, like, this whole, cottage industry of artisanally produced, you know, basically clothing, you know, by, like, small scale, like, Japanese manufacturers that use, like, like, literally, like, 100 year old looms to to make clothes, like, the old fashioned way, like, you know, or or the old fashioned industrial way. Right? Like, they have these, like, loop wheeler machines and they spin the the cloth in, like, a very slow pace. So it's completely impractical from, like, a production scale standpoint. But, you know, it's like, I've gotten, like, some of these t shirts and they, like, I just love the, no. I guess, Ed, you know, in a world where it feels like everything is becoming so much, faster moving and, like, you know, even tech from five years ago is obsolete, like, I love a little bit of the throwback to, like, you know, old things sometimes can be even more cherishable in this new era. Right? So, like, maybe that makes me a hipster, but, like, I I love the, you know, the, the vintage, the retro, increasingly these days. I feel like anything that starts with artisanal small batch Japanese is gonna be really good stuff. Is there is there a brand you wanna share that is that? Or is this, like, you wanna keep it Yeah. In the radar. Actually, so Self Edge, which actually is a a storefront like, the main storefront is, on Valencia Street in SF. They carry a lot of these items of kind of like, that's kind of their whole MO, and they have, like, jeans and, like, T shirts. So So I've gotten a lot I mean, they they basically curate a really good selection of different actual makers. Like, one of them is called Studio D'Arizon. Another one's called, actually, it's cool. There's this company, called, I think that the umbrella company is actually just Toyo, t o y o, manufacturing, which sounds like it's a big, like, you know, kind of, like, large scale conglomerate, but it's anything but it's like a really small scale, Japanese, you know, kind of, like, vintage manufacturer of clothing. And but they have a few sub brands. They actually bought the rights to this, like, American coast war brand that was kinda like Hanes. Like, one of the, like, big, like, four or five, like, you know, kind of, men's wear, like, know, kind of undershirts and athletic wear, brands called Whitesville. I don't know where the name came from, but, you know, it it, it basically it's a bunch of, like, basic clothing, like T shirts, etcetera. And, and they the this Japanese indie company, Mitsleep, bought the, like, defunct, you know, basically name, you know, and and now, like, is reproducing clothes almost made to the exact shape and stack. And even with, like, the exact recreation of, like, the graphic packaging on these, tees, but, like, you know, today. Right? So I just think there's something really funny and ironic about, like, you know, they've taken, like, an American post war aesthetic and literal brand, but, like, it's actually, like, a indie, you know, small scale Japanese manufacturing, approach to to, to make those clothes. I feel like we just tapped into what could be a whole other podcast conversation about clothing and craftsmanship, but let's I'm gonna pull us out of that. The the next podcast, franchise. Or just Howie and Lenny talking about clothing. That's true. Okay. Two more questions. Yeah. Do you have a life motto that you often find useful in work or life, share with friends or family? I I stumbled on this, this this guy, Paul Conte, who I think, he's an MD, but also, like, a psychologist. And, he has a book, you know but also like he did this long form podcast with with Andrew Huberman and you know he actually ends up talking a lot about like just how to think about like, your life outlook and, like, kind of your framework for thinking about life, but grounded in a kind of, like, scientific and, like, you know, kind of neurological, and and cognitive science, basis. And, you know, I found one particular point really, really powerful. It stuck with me, which is, like, you know, if you live your life in a way that's, you know, foundationally built around humility and gratitude. Right? And and look, like, you know, everybody has different circumstances. Like, you know, I think, like, I I fully own that, like, you know, even though, you know, I didn't come for money, like, my family was was very very financially modest, like, growing up. Like, I still had an incredible resources and opportunities, you know, afforded to me, even just by virtue of growing up in The US, right, being more in and growing up in The US, like, you know, but also, like, having access to a computer and the Internet and, like, even all the free resources I could then access and and learn about from there. But, you know, like, I I still feel like, you know, whatever you have or don't have to start with, like, if you kind of approach the world and and, you know, kind of the future with a spirit of humility and gratitude rather than, I guess, the the opposite of that. You know, it just I think I felt like it it makes like, it kind of like becomes a self fulfilling prophecy. Right? Like, you know, you're you're you're you're open minded, you're kind of grateful, and then, like, more opportunities actually come your way. Right? And maybe it's because of the energy you're putting out into the world and, you know, and other people and, like, you're kind of attracting, like, you know, good opportunities and and good people and good things. But I, you know, I I think, like, you know, there's a lot of other parts of, like, his framework, but, like, the one that, you know, is easiest to remember is just, like, how do I approach each day even if, like, I'm going through a tough moment and, you know, I mean, we have to, like, you know, I had to fire somebody today or maybe, like, you know, I got disappointed because we lost a customer deal or something broke or whatever. You know? You know, but, like, to still try to look at the entire situation from an overall, you know, feeling of of humility and gratitude, I think just really does shift your your, like you know, it it spills over into everything else, for that day and maybe even for, like, you know, the the whole, lifetime. That, super resonates. That is really powerful advice. That's hard to internalize, but important. Yeah. Easily said hard to, practice. Yeah. Where can folks find you? What should they know about Airtable? And how can listeners be useful to you? Okay. So, I am on Twitter, Howie TL. I don't post that much, but I am a I'm a lurker, so I listen, and and watch, and you can always DM me there. You can also email me directly howie at air table dot com anytime you can have ideas, feedback, etcetera. You know, on Airtable, like, just go try it. Like, the whole point is we wanna make this an experiential product. Right? Like, you know, that's why we're we're really leaning into the PLG roots. We talked about, like, the home page literally says, like, just start building right now. What do you wanna build? Go. Like, it starts building. And so use the product. Give me feedback. And, you know, if you have ideas of your own and and you wanna rip on them, like, I I love because my passion is thinking of a product and, like, product UX especially in the AI era, if you're working on or, you know, thinking about something interesting in that space, Like and even if it's just purely to, like, riff on a concept, like, that's that's something I enjoy doing and maybe I get to learn and then sharpen my own skill set from. So feel free to reach out. And, and yeah. I mean, you know, tell your friends and family to to try Airtable as well. Like, that's that's the, main thing. Sounds like you're looking for people to nerd snipe you and Yes. Yeah. Howie, thank you so much for being here. Awesome. Thank you, Lenny. Hi, everyone. Thank you so much for listening. 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