Lenny's Podcast: Product | Career | Growth - How we restructured Airtable’s entire org for AI | Howie Liu (co-founder and CEO)

Starting point is 00:00:00 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 want to cancel all your meetings for like a day or for an entire week and just go play around with every AI product you think could be relevant to air table, go do it.

Starting point is 00:00:26 Of the different functions on a product, TMP, 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?

Starting point is 00:00:54 Today, my guest is Howie Liu. Howie is the co-founder 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 CO's almost becoming individual contributors again, getting into the co-exhares,

Starting point is 00:01:28 building things, leading initiatives themselves. This is something that we call the ICCEO. 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.

Starting point is 00:02:02 Also, if you become an annual subscriber of my newsletter, you get a year free of 15 incredible products, including lovable, replet, bolt, N8N, linear superhuman D-Script, whisperflow, gamma, perplexity, warped, granola, magic patterns, raycast, CHAPERD, and Mobbeth. Check it out Lenny's newsletter.com and click Product Pass. With that, I bring you Howie Lou. 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. If your team works with large media files, videos, design assets, layered project files, you know how painful it can be to stay organized across locations. Files live in different places, you're constantly asking, is this the latest version?

Starting point is 00:02:45 Creative work slows down while people wait for files to transfer. LucidLink fixes this. It gives your team a shared space in the cloud that works like a local drive. Files are instantly accessible from anywhere. No downloading, no syncing, and always up to date. That means producers, editors, designers, and marketers can open massive files in their native apps, work directly from the cloud, and stay aligned wherever they are. Teams at Adobe, Shopify, and top creative agencies use LucidLink to keep their content engine running fast and smooth.

Starting point is 00:03:15 Try it for free at lucidlink.com slash Lenny. That's L-U-C-I-D-L-N-K-com slash Lenny. Today's episode is brought to you by DX, the developer intelligence platform designed by leading researchers. 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.

Starting point is 00:03:46 With DX, companies like Dropbox, booking.com, adion, 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 website at getdX.com slash Lenny. That's getdX.com slash Lenny. Howie, thank you so much for being here. Welcome to the podcast. I'm so excited.

Starting point is 00:04:15 Thank you, Lenny. I've been a listener from afar for a while now. I'm really flattered to hear that. I'm also very excited. You've been on quite a journey over the last, is it 13 years? Is it, is a longer? Like, right, yeah, right about 13. 13 years.

Starting point is 00:04:29 I imagine there have been a lot of ups and a lot of downs. I want to talk about all those things. I want to talk about a lot of the lessons that you've learned along the way. I want to start with what I imagine was a very surprising down moment in the history of Airtable. This is something that, unfortunately, 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 his data and

Starting point is 00:04:55 they're like, air table is dead. They've raised way more money than they're worth. They're not making enough to get from underwater. Air table, RIP. What happened there? How much of that was true? How did that go? Yeah. So very, basically none of it was true. And I mean, the surprising thing to me was how viral this tweet went when, frankly, like, I actually look back at this person's other tweets. I think 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 strong multiple on like what our revenue scale was, what our growth rate was like, you know, and if it gave me some constellation,

Starting point is 00:05:39 I look back and like this person had also tweeted about other companies like Flexport was the last like kind of take down tweet. They have like, oh, flexport's dead. And like, you know, their, you know, their valuation is, you know, too high and 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 really gave it legs was on the All In podcast, which is like obviously super popular. You know, and I listen to it.

Starting point is 00:06:14 Like, you know, they covered it. They were like, oh, like, you know, latest on on this week's news. Like, you know, this tweet about air table. what do we think about this? And it almost I think became like a way to talk about a broader theme of what happens to this last generation of highly valued companies, maybe Deccorne 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 follow up episode a few, I think weeks later saying like, hey, like, you know, we got the numbers wrong.

Starting point is 00:06:47 like, you know, we're revising our case and kind of a view on airtable. What's that line about how a lie gets around the world some number of times before truth has even as time to get out of bed? Yeah. Yeah. Well, I think I learned about memes and morality very quickly 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 as the incentives are so misaligned.

Starting point is 00:07:13 It's just a tweet something people want to share, not truth. Well, I mean, especially like, I mean, I, I, I, there's a lot to like. I would say, Net, Net, Nat, I like the post-Elon Twitter more than the pre-Elon Twitter because it's just bolder. And, like, I, you know, I guess I really admire bold product execution where you're not just kind of 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.

Starting point is 00:07:45 I'm like, you know, but it does, I think it does result in like this kind of content, like really spread. Yeah. Now, Nikita running the show. 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. Yeah. Just to like, you know, people are sharing these tweets all the time.

Starting point is 00:08:05 Yeah. Oh, man. Never a dull moment over there. For sure. Okay. I want to go to 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've noticed that I feel like you're at the forefront of of COs becoming ICs again.

Starting point is 00:08:20 It's kind of this move of I see COs, COs getting their hands dirty again, building again, getting the weeds coding again. I 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 this 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 U.S.

Starting point is 00:08:54 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 net of 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 on the front end and the product UX choices, like that is the product's value prop, right?

Starting point is 00:09:31 Like you can't separate those two. You can't say like, okay, like I research the jobs 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 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

Starting point is 00:09:53 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 new kind of general, Gen AI moment, like I think there was a maturing era of both SaaS overall and error table specifically where, you know, as you scale up and you kind of 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 kind of get, you know, by default,

Starting point is 00:10:34 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 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 kind of scale it up, right? Like a more blunt roadmap, a more blunt, you know, kind of go-to-market execution strategy. Regardless, I think that now 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 very one-time and somewhat predictable change in form factor.

Starting point is 00:11:18 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 kind of refine product market it fit in this era, I think you have to be of the details. Like there is no like, you know, looking at it from 10,000 foot view and saying, oh, we're just going to 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

Starting point is 00:12:01 to take advantage of the capabilities in our product domain. You have this phrase somewhere where you talk about being the chief taste maker. 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,

Starting point is 00:12:30 this feels right or not. Or like it feels like we're being bold enough and 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 pre-recorded video of like 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

Starting point is 00:13:00 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. So 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 kind of get comfortable with them to put them into a new dish. And we had Dan Shipper on the podcast.

Starting point is 00:13:25 He runs this newsletter and podcast to provide a company called Every. And he, they work with companies to help them become more AI successful and adopt AI and all that stuff. And I asked them, 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 chat GPT or Claude daily? Yeah. And I feel like you're describing exactly. Right.

Starting point is 00:13:50 Hourly. Early hourly. Like, or you know, you could even like have a measure of like inference, like costs, right? Like the equivalent underlying like inference compute cycles. Right. How many tokens they use? Yeah. I mean, I'm proud to say like I am, I'm pretty sure I'm still.

Starting point is 00:14:07 the, 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 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, identify or here's summaries, et cetera.

Starting point is 00:14:49 And we also have now a capability that's basically like an LLM map reduced. So effectively, even if you can't fit like, you know, the entire corpus of content into one LLM call because the context window limitations will map through like all of this content and break it up in the chunks and then like perform an LLM call in each one and then perform. form an aggregation LLM call on those chunks, very expensive, right? Because you're basically running like a highly expensive model against a lot of 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

Starting point is 00:15:24 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 to 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 a crazy ratio and like more people should be like

Starting point is 00:16:06 aggressively throwing compute cycles at these very high value problems. Until somebody tweets how you're eating, costing the company so much on AI compute and you guys are going to be underwater. Just kidding. It's like how we have personally taken down the cash flow of the business. So, okay, so CEOs, founders hearing this, they're probably like, okay, 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.

Starting point is 00:16:37 You got all these. Like, how do you actually, how have you changed your day-to-day to do this? Yeah. So I actually cut my one-on-one roster by default. And the idea is not that I don't want to 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,

Starting point is 00:16:59 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 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 want to bring that into how we're thinking about like a new feature at

Starting point is 00:17:23 air table or even just like plant the seed with like, you know, some different like, you know, EPD people within our table. Like I want to make most meetings, uh, very timely and very informed by like real alpha, right? there's got 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 want to carve out time for like a, you know, a proper like ketchup and like less structured, less like, less like timely and just more of like, you know, building a relationship with a human.

Starting point is 00:17:52 But I actually find that like, you know, having that common, it's almost a barbell approach where it's like, you know, if you're going to spend time with somebody in a freeform way, like actually do it in 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 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

Starting point is 00:18:25 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, etc? 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.

Starting point is 00:18:55 What's a change you've made to help the company move faster and match that sort of pace? Yeah. So I mean, we did do a reorder. 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, you know, kind of original state

Starting point is 00:19:13 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, someone in support, right?

Starting point is 00:19:27 And, you know, that has this 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 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 surface areas instead of just like each one kind of incrementally

Starting point is 00:20:00 improving. And so we reorged. initially to basically different business units effectively, right? So I know Airbnb has done like kind of the functional to GM, you know, back, etc. 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?

Starting point is 00:20:30 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 adopt the product, onboard, share, do all the kind of like basic functionality, an AI pillar, solutions pillar, and basically impra. And what we found, though, with that approach is that there was still, you know, there was more kind of holistic bets being made. So like, you know, the team's pillar could think not just about one feature, but like the overall onboarding experience. We're like really think about NUCS, you know, in a way that touched multiple parts of the product. But it still felt like it wasn't, especially 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.

Starting point is 00:21:25 And like, you know, it's not like, oh, well, we have like this separate, you know, kind of roadmap for enterprise. We have this roadmap 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 want to 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 like how awesome it is to use this new capability in inner table. And then separately, we have the slow thinking group.

Starting point is 00:22:05 That's not meant to be like better or worse. Like it's literally like you need fast and slow thinking in the connemons sense to operate, right? Like I have that book behind me. Yeah. I love that book. But slow thinking is like it's just a different mode of planning and executing, right? It's like more deliberate bets 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 data store hyperDB that now can handle like multi hundred million record data sets.

Starting point is 00:22:35 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 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 also, you know, kind of inspires new use cases and new users to come into Airtable, including in large enterprise, right? Like, you know, enterprises can use the stuff too. It's not just like an S&B thing.

Starting point is 00:23:02 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 use. But then, you know, sometimes the challenge is how do you like turn that into more durable, you know, growth and get each of those adoption seeds to retain and expand over time? That is super cool.

Starting point is 00:23:33 I've never heard of this way of structuring teams. The fast thinking, thinking fast, thinking slow, the connemon. It's so interesting. For the fast thinking team, do you find their 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 have a mix. So, you know, we've run in, I mean, 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,

Starting point is 00:24:00 candidly, even when we had to do two riffs, right, that significantly, you know, kind of reduced our headcount. You know, we had just like way too quickly grown and overscaled 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 an EPD because, you know, 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 roster's day, right? Like, we're always going to need to find new fresh perspectives, new skill sets, et cetera. And so, you know, we've continued higher. I think we've learned as we've gone along of like, you know, what is the ideal type of hire? And, you know,

Starting point is 00:24:42 we've done some aquil hires and learned from that as well. But I think the fast thinking part, it really just requires a lot of like somebody who's able to operate with a lot of autonomy, right? Like, you know, who's entrepreneurial in nature. Now it doesn't mean like they have to literally be a former founder. I know some companies are, you know, like Riplink, 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 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 doing this new thing that's about to ship where you know not only can you describe the app you want to build and then iterate on it with you know kind of our conversational agent omni but and it builds it with like the existing air table.

Starting point is 00:25:44 platform capabilities, but we're also giving it the ability to actually do code gen 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 not being 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 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

Starting point is 00:26:22 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 open evidence, 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's what's standing out to be right now. 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's my like passion. And you know, everything else I've had to learn to kind of run this company is almost like

Starting point is 00:27:05 what was a necessary, you know, part of the journey. Like, you know, but like my real passion is thinking about product UX, right? And 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.

Starting point is 00:27:35 But like I think to me, what's under XS. 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 underlying capabilities are right like I mean chat chavit obviously like you know extremely successful products of 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 have suggestions underneath and so on. But like, you know, the product UX part of me is just like

Starting point is 00:28:16 craving more visual metaphors or colors or some kind of like use the canvas of a web interface 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 the underlying model, right? And so that's something we've tried to do with AirTable is like show like all of the different states. and use colors even to play those off. It's interesting how much of this connects with, I just had Nick Turley on the podcast. He's head of ChatGBT at OpenAI.

Starting point is 00:28:50 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? If this is important, what would allow us to move faster? And I love that that's one of the themes that's coming up as you talk is just creating this very clear sense of speech.

Starting point is 00:29:11 and you even call it the fast thinking team. Like, you're going to move fast. Yeah. And then the other one is just this insight that with AI, you often don't know 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.

Starting point is 00:29:28 I couldn't agree more with both of those, and particularly on the second point, I think it's interesting. Like, clearly there have been companies that have both been successful in PLG and like more sales-led, you know, kind of distribution for AI products, like, you know, the most notable ones I can think of

Starting point is 00:29:45 are like Palantir with their AI deployments. Like that's obviously very sales led. You're not PLGing into a Palantir deployment. But even, you know, like companies like Harvey 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 best way to get AI value out there is experientially. Right. And so like, You can kind of get that in a sales motion. You can, like, you know, show a demo. Maybe you can do a POC.

Starting point is 00:30:16 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 real proof point that, like, chat Chb-T 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 million like M-A, is it M-U's or we? weekly active users, 10% of humans on Earth use it weekly. That's insane.

Starting point is 00:30:45 In like how many years, right? Like a few years. Three years under three years. Yeah. And so like, I mean, literally, 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, you know, kind of has a little bit of a rebuttal of the point I made earlier where like

Starting point is 00:31:04 I think Chatsbytee doesn't do a ton right now. And even earlier like 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, let's 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 appeal to you enough. Like, everybody used it. And so I think, you know, I do have a view.

Starting point is 00:31:36 Like we've gone through that whole, you know, kind of arc of we start appeal. I'd like to think AirTable was one of the kind of PLG darlings of our era. And anyway, I kind of 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

Starting point is 00:32:07 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 AI and RT table, right? Like, I think that's so key. And it's, you know, it's nucks, but it's also more than that. It's not just like literally how you onboard somebody into the product. It's like literally thinking about the entire product experience itself, right?

Starting point is 00:32:30 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 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 like basically all the other AI app building sites. Now, just tell me which you want to build. Thoughts on that as just like a thing everyone's starting to do, is there, what do you think comes next? Is this, is it working

Starting point is 00:33:14 well? There's clearly an incredible magic to vibe coding and app building with AI, right? And this is actually, you know, like a prime illustration in my view of that, that constantly talked about a second ago, which is, you know, as capabilities of these underlying models evolve, the form factor in the product UX also needs to evolve with it. Right. And so like the earliest models, like the kind of original chat chip T like JPD 3.5, you know, kind of era models were, we're 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

Starting point is 00:33:53 certainly not like a full stack app and expected to work. And so the right form factor for leveraging those models in a software creation context was GitHub co-pilot, right? It's like auto complete a few lines of code out of time, right? But you know, you couldn't chat to it until 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 do more complex things and generate more, you know, kind of 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 3D shooter game from scratch and just watch.

Starting point is 00:34:33 you go and like create all the files and 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 air table it was always about democratizing soft creation like we just strongly believe 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 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.

Starting point is 00:35:17 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 a as a as a company that predates Gen. AI and now has to kind of find your new footing in the AI landscape, like, you can't fool yourself or just say like, okay, I'm going to throw in some AI stuff on the landing on the marketing site, you know, put in a couple AI features and call out a day. Like, I think you actually have to take a clean slate approach to saying like, how would our mission best be expressed?

Starting point is 00:35:51 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

Starting point is 00:36:23 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 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 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 app. So I should clarify that like, you know, we want to democratize software creation,

Starting point is 00:36:57 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 want to 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 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

Starting point is 00:37:27 from scratch from code, it's going to be very unreliable. There's going to be bugs. There's going to be data and security issues. And then you're also going to 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 and 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,

Starting point is 00:38:06 you know, a layout, right? Or automations and business logic. And so it's almost like in programming terms, like the air table 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. really 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

Starting point is 00:38:39 assemble them for you instead of you just using the GUI to do that. And by the way, if you do want to fall back to the GUI, there's a really great, you know, kind of way for the non-technical 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 V0 or lovable or Revlin 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 kind of 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 manipulate it to the final, you know,

Starting point is 00:39:13 kind of production ready safe. So like that's that's kind of 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've got to figure out something that could work even better.

Starting point is 00:39:36 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 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 like creating a sense of urgency and pace

Starting point is 00:40:02 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 in framing. And then there's the point you made about just talking to AI regularly as the founder. It feels like an important element just like to truly be this ICEO talking to AI working with AI regularly. Just on that note a little bit more, just to give people a sense of what this looks like day to day.

Starting point is 00:40:26 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 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, as I can. And both literally for the novelty factor and just like, you know,

Starting point is 00:40:48 some new cool demo comes out like runway release their like immersive world uh you know kind of engine right and um and so like i'm gonna go try try it out right like when uh sesame i put out their like cool like kind of interactive voice voice chat um you know uh uh you know demo like i tried that out because like even though we don't have a direct and near term like um you know kind of need for like really um realistic and and interruptible like kind of voice mode uh where it's not as core to our kid abilities like I just want to understand 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 real kind of

Starting point is 00:41:30 reason to use these products. Like you know, oh cool. What if I were to take like a 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 Altars with like a script like 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 chat with tea and pulled together the results, have it composed like, you know, kind of a little thought. Did you actually do this? Is there something you made? That's literally an example of

Starting point is 00:42:01 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 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 20 minutes. Okay, like, let me, let me prompt it to like generate need 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 a Hey Jen Avatar and then download the video and like play it, right? Like, and just for fun, right? I'm not like trying to make,

Starting point is 00:42:33 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 it gives me is like, A, like, it's not just understanding the models, which is also very, very important, right? Like, GPD 5 came out yesterday. They're 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,

Starting point is 00:43:09 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 Chachapit 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 Chachat T gives you out of the box. Like that's when you kind of learn like, you know, you really get to inspire yourself on like one of the product's form factors that these new models can take.

Starting point is 00:43:42 So like, 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 not, it's not like perfectly predictable. So I think the element of like, like, you're not quite sure what you're going to get. It's like a box of chocolates, uh, you know, uh, 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's some like basically very advanced, you know, kind of regressions that we can run with with AI,

Starting point is 00:44:21 but like it looked nothing like this, right, 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 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, But 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 service now or, you know, so on. Like, this is the equivalent of that, but like there's major new releases and products and so on, like every week, right? Not like every year.

Starting point is 00:45:11 And so I just think you have to say 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 tech crunch or or you know, even a tweet about like a new capability. Like you kind of 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. I use it for researching my podcast guests, for brainstorming title ideas for both my podcast and

Starting point is 00:45:45 my newsletter, for getting feedback on my writing, and all kinds of stuff. Just last week, I was preparing for an interview with a very fancy guest, and I had Claude tell me, what are all the questions that other podcast hosts have asked this guest so that I don't ask them these questions? How much time do you spend every week, trying to synthesize all of your user research insights, support tickets, sales calls, experiment results, and competitive intel? Claude can handle incredibly complex multi-step work. You can throw a hundred-paid strategy document at it and ask it for insights,

Starting point is 00:46:16 or you can dump all your user research and ask it to find patterns. With Cloud 4 and the new integrations, including Cloud 4 Opus, the world's best coding model, you get voice conversations, advanced research capabilities, direct Google workspace integration, and now MCP connections to your custom tools and data sources. Cloud just becomes part of your workflow. If you want to try it out, get started at Cloud. Clod.a.a.luney and using this link, you get an incredible 50% off your first three months of the pro plan. That's clod.a.i slash Lenny.

Starting point is 00:46:50 For people that work for you across their table, say the product team, PMs, maybe engineers, designers, how have you adjusted what you expect of them to help them be successful in this new world? One is, you know, really, really, really stressing this idea of like go play with this. stuff. And I mean, when I say play, I really mean play like in the psychological sense of like, you know, it's there's a difference when like you go in and you're kind of just trying to check the box and like get a job done. Right. There's a difference when like you come in with a curiosity and like 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

Starting point is 00:47:34 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 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 kind of 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 going to write a doc about it and then share the doc. I'm just going to 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 a 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.

Starting point is 00:48:38 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 can 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 have the ultimate excuse, like you can use like, you know, you can say that I told you to do it. Right. Like if you want to 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 air table, 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, kind of shifts in how we execute prototypes over decks. You know, like I want to see like actual interactive demos because like, again, like it's hard to, you know, in a deck.

Starting point is 00:49:36 or in a PRD, you could say like, okay, well, we're going to 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 and 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 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

Starting point is 00:50:15 prototype that really does in an open end way, you know, like use the, the AI 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 like kind of timelines view of execution, right? Like, we're going to put this many people on this problem and this is the eight-week timeline to this milestone and we're going to ship in a quarter from now. And like, I think now the whole thing is just like a lot more experimentation and iteration driven.

Starting point is 00:50:55 Of the different functions on a product, 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 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 hybrid unicorn types, right? So if you're a designer who can be just technical enough to kind of be dangerous and understand a little bit of like how these models work and, you know, like how does tool

Starting point is 00:51:36 calling work and, uh, and all of this stuff. Like then you can actually design a concept or even prototype a concept, including in these prototyping tools, um, 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, um, concept, right? Cause I think, you know, designs have to be more interactive. Like the whole, the, the, the value of the product, um, and the product functionality is in the interaction of it, right?

Starting point is 00:52:06 Like, you know, think about the design of Chachapiti. Again, it's like, you know, it's the most basic design you can 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, they're engineers who are very good at thinking about product and experience and like, you know, kind of can go and prototype out like the whole thing. They're designers who can kind of do the same, even if they can't literally code,

Starting point is 00:52:39 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 their role as, you know, kind of writing documents, writing PRDs.

Starting point is 00:53:08 Do you see one of these roles, I don't know, being more in trouble than others, just like you need fewer of 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 want to go and like make the team smaller, but rather like, like the really cool thing for us and 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, now I can do that with a 10th of people. I mean, you could do that in a lot of cases.

Starting point is 00:53:42 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, 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 over 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.

Starting point is 00:54:22 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've got literally, like, massive watermelons, like, literally sitting on the ground, right? And all you have to do is, like, kind of 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 wines and attacking those. right? And like, and what that means is that like if we can build this culture, and I do think like

Starting point is 00:55:06 it's a learnable way of operating. Like I, I really like to believe in like the like the growth potential of like any human, right, like and any individual. Like I think if you really have a growth mindset, and 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 week and hours or in my case, like, I'm literally telling people 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

Starting point is 00:55:51 jump on the train are just going to 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 EngPM 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 understand the engineering, you know, kind of limitations of like the product, you know, designs they wanted to make. And they had to be kind of designy, right? Like,

Starting point is 00:56:32 I remember my co-founder 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 and 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,

Starting point is 00:57:10 at Stripe, my understanding is that like, you know, the DRI isn't always the PM, right? Like, as is traditionally the case in kind of 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 to like the trend across product engineering and design is each of those functions needs to get good at one of the other functions at least. Ideally, you can do them all. But if you can just do one additional, so a PM becomes better design and engineer

Starting point is 00:57:41 becomes better at product management. Well, I would actually go further and say, like, I think you need to get like decently good at all three. Like, there's just a minimum base line 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 special. right? Like, you know, you could be a designer who's really good at thinking about U-X and interaction design and then just like good enough to be dangerous on thinking about like

Starting point is 00:58:09 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, you. 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 like canonical design object. Like you would have 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 e-share, sit in it, like, try to examine it to kind of reverse engineer how it was made, right? And like, you know, 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,

Starting point is 00:59:16 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. 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 school and then kind of 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

Starting point is 00:59:54 app or whatever. Maybe now at like some of the schools like Stanford and MIT, they have like actually UxC type courses, but 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 want to build like a Yelp style app with a map view and then also a list view. And I want it so that when you pan around in the map for it to automatically update the list view.

Starting point is 01:00:25 And maybe there's some UX improvements I can make on top of that. But I can also like. test my technical skills 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

Starting point is 01:00:58 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 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 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 with 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 a, of a feature, you know, from a PRD or from like a feature 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 going to tell you which specifically to do.

Starting point is 01:02:01 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 few different directions we could go. Like, what if you prototyped what it would look like to have a deep research implementation and field agents so that like for any given row of data, let's say in your case, it's podcast guests, you can just click a button or click a button on mass across the entire, like every speaker you have lined up to do deep research like powered by. chat ChpT's own deep research on each of the speakers and have them all laid out side by side

Starting point is 01:02:33 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 problem I ran into, I wonder if it's changed is there's no API for for chat GPT deep research yet. There is now. There is. There is. There is. There is. It ends up being, I 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.

Starting point is 01:03:05 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'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 actually have a researcher that I pay to give me background on guests that was like four or 500 bucks. And the dollar sounds great.

Starting point is 01:03:26 And I've been doing this. I've been doing this manually. He'll be using deep research and they just collecting the R1. 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 e-vals.

Starting point is 01:03:42 The power of getting good at e-vals. I know there'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 listen to your episodes with No. And Mike, who talked about this, I think it's like interesting that, like, you know, both heads of opening eye and anthropic, you know, have converged on this point. I mean, look, I think I would add like 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

Starting point is 01:04:15 with e-vals and you should start with vibes, right? Meaning like, you know, 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 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 agentic workflow used to generate these outputs and you have to define like, you know,

Starting point is 01:04:49 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 props 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 kind of 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 your product market fit finding either for an entirely

Starting point is 01:05:19 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 and like throwing stuff at it, seeing what works to understand, okay, like, let's use an example. You know, 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, similar to deep research, but what it actually does is instead of outputting like a, you know, kind of a report,

Starting point is 01:06:02 it's actually going and compiling a list of things. The things could be companies or people or anything else, right? Like find me every Marvel movie, right, ever made. Find me every like, you know, kind of DC comics like a spin-off, right? Like a series, right? Literally anything. And, you know, you have to go and 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 and companies with this kind of parameter. And I think to me, like, evils 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 output for that, right? But like by that point, you've probably already scoped the product and maybe the way

Starting point is 01:07:05 we would merchandise it in the, in air table is not like a completely open-ended capability. But like, hey, like here's 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 to find to give it the prompting to search for that thing, right? But I kind of 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?

Starting point is 01:07:34 You can maybe test, especially if you have the scale of a really large product like anthropic or open AI. You can like just test everything and see like, oh, this model like should perform certain this one. This prop performs order into this one. Um, 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.

Starting point is 01:07:52 Evils could constrain you too early. I think about just the double diamond and no IDEO kind of framework of like be divergent first and then conversion and maybe that's really right. Exactly. I hadn't heard that before, but 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.

Starting point is 01:08:14 And let me see if I'm missing anything that you think is really important. So one is there's a sense of just like reset the experience. 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. 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. to play as you talked about it and then sharing things they've learned,

Starting point is 01:08:52 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

Starting point is 01:09:07 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. is going up? Is there anything else that I missed there that you're like, you need to do this too, to be really, to have a chance? I think just to really try to break down role silos. Like, and I think that's true certainly for EPD in the typical like, you know, EPD triangle. But I also think

Starting point is 01:09:35 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 a marketing team is like, you know, really leading into actually is, is like, you know, if you can just do all of the thing yourself, like traditionally, you know,

Starting point is 01:09:56 how a marketing team might operate is like, okay, you have one person who's kind of 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,

Starting point is 01:10:10 budget and like, you know, kind of conversion, uh, tracking, et cetera. And, and then somebody else is actually responsible for like,

Starting point is 01:10:17 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 yet 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 very specially, you know, specialize in deep in one dimension like engineering, but they're well-rounded enough to kind of like be dangerous on the other

Starting point is 01:10:51 two. Like I think that's kind of 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 eye product now without actually being fluent in the product and be able to demo the product, right? So like, you know, 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

Starting point is 01:11:33 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. on having assets created by marketing and like, you know, an SE 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 a great addition.

Starting point is 01:12:06 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. Hey, there's the head of engineering, we're just doing stuff. Totally. It needs 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

Starting point is 01:12:21 really strong at and then you just have to, as you describe the minimum of being good at engineering design or an SC, by the way, sales engineering, imagine is what that sense were. They 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 kind of converging. Exactly. Amazing.

Starting point is 01:12:42 Okay, let me take a step back and kind of 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 the most counterintuitive lesson you've learned about building, airtable, building, and company building teams that maybe goes against common startup wisdom? You know, I heard your interview with Brian Chesky and then later you talk about founder mode in that kind of YSlee retreat. and the points there really, really resonated with me, you know, and I feel like maybe less eloquently I had kind of like deduced, you know, some of the same principles 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 kind of 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 going to be like and like, you know, how are we going to market this product? What does the website look like? Like they're all very intertwined, right? You can't like

Starting point is 01:13:47 compartmentalize and then like, you know, almost like factory produce, you know, kind of each of these things separately. Like they're all intertwined, right? And you have a very small tight knit name 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. 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, you know, kind of like larger scale, you know, kind of company investors is like, okay, you got to kind of industrialize the process of all of

Starting point is 01:14:27 this stuff, right? It's kind of like going from like a bespoke artisanal, like one person made an entire, you know, item of clothing to like, like, we got to like factory produce this thing, right? And, you know, what that means in a organizational context is like, you then create these different fief dumps. 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 you got sales kind of 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 kind of 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?

Starting point is 01:15:14 Like each one can kind of operate, you know, like in a, in a more autonomous and like, you know, purely like scale up, you know, focus kind of wait, 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 going to, you know, go and ship, ship, ship more stuff to improve search. And, you know, so it's not completely crazy, like, you know, why people give this advice. But I think what you lose is the magical integrative value of holistic thinking, right? 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 a company that is really serious about product, first of all, like, you know, I really like to his point about like the CEO has to play a CPO role, right? you have to care about the product.

Starting point is 01:16:03 Ultimately, the product is the thing, right? And you can't just coast on scaling up, go to market around the product forever. Like, you've got to 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 little surface areas, but actually to have like a bigger, you know, kind of 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 capabilities

Starting point is 01:16:31 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 refining 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 refining a fit state. So I could not agree more with with that concept of, you know, kind of you got to, you know, think ambitiously and move the organization holistically towards

Starting point is 01:17:13 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, experienced operators, because obviously, there's some truth to that, right? Like, you know,

Starting point is 01:17:32 the people giving this advice are not incompetent. You know, they had some reason for getting it. And in certain contexts, it is the right thing to do. But I think, like,

Starting point is 01:17:41 my meta learning is, you know, it's not enough to just, like, trust the recommendation. Like, here's the action you should take from a lot of people

Starting point is 01:17:50 because everybody has different priors. And it's almost like we're all our own LMs, right? And like, we all have different training from a different course, of data informed by our own experiences and maybe you're trained on like the like you know kind of service now or the you know kind of an oracle you know kind of um 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 air

Starting point is 01:18:14 table one right and i think what i've tried to do more and more is like not to just like ignore advice from smart people like obviously that's not the right answer but like to kind of take their it's almost like in an lm uh you can now like with a reason model, like actually inspect the chain of thought, right? Like, and, uh, 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,

Starting point is 01:18:53 made sense. Like, we're no longer having PMs in their traditional form. Now we have programs. 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.

Starting point is 01:19:15 But the reasoning actually is very informative. It's interesting how this idea found her mode is not so different from this ICCO trend that you're following. And it's, yeah, yeah. It's like being in the way. being the details, trying things yourself, not delegating to execs. Yeah. You know, and like, I think anything taken to an extreme can be problematic, right?

Starting point is 01:19:38 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 kind of creating, like, you know, kind of the euphemism for that. And that's not really what founder mode is about, right? Like, that's not like the, the Brian conceptual 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,

Starting point is 01:20:28 you know, CEOs as ICs and frankly any leader playing more of an icy like role 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 times where I felt most disintermediated from like what I felt was like the substance of this company was when I thought that I was almost like, you know, forcing myself to step away from the details because I thought that's like what, you know, a at-scale CEO was supposed to do, right? Like, I mean, there's, you know, some, like, you know, famous CEOs who have talked about, like, the less decisions I can make, the better, right?

Starting point is 01:21:06 Like, the less details I'm exposed to, the better, right? Like, I just want to inspect at the topmost 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 CPD, company like in Procter & Gamble, you wouldn't want to have a CEO who still actually goes and

Starting point is 01:21:33 taste 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 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. Maybe maybe you're just like, you go through a long enough period of like where the business is coasting that like nobody notices. But I got to 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 like that's what makes the job interesting. Like they don't

Starting point is 01:22:16 want to have like a automated away, you know, kind of role as a leader. If you could go back in time and whisper something in a 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,

Starting point is 01:22:42 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 do things and manage. And like there becomes a new job invented just to like manage a larger group of people. Right. And like, you know, obviously you're going to have to do some of that. You can't just completely askew all your responsibility as like an outscale CEO. But like don't lose the like the essence of like the thing that you love doing and that, you know, has like really made this product happen and gives, you know,

Starting point is 01:23:28 this company as many companies that like were founded on like a, you know, kind of a magical product market finding insight. Don't like step too far away from that, right? And always make sure that is still you're 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 the 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 think that's so true and to me that's

Starting point is 01:24:08 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 going after. And look, no knock on people who are more of the latter. And like, there's entire industries where like it's all just about alpha generation, right? Like, you know, you can go into the private equity business 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, 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?

Starting point is 01:24:56 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 you could spend 100% of the 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 ranging to like the Bryan's with Airbnb 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 want to make a lot of money off this like arbitrage opportunity against hotels.

Starting point is 01:25:24 They just needed to pay their rent. Yeah. Well, that, that and like I think they loved the product. And I think they also loved 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 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?

Starting point is 01:25:50 I just want to reiterate, especially for listeners here who are in, you know, an E, P 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 the I needed. But I do think, like, it's a call to action to go and bolster your skill sets 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 going to be like, you know, a published author, right?

Starting point is 01:26:31 Or, like, you know, the Hemingway, right? But, like, everyone can gain a good enough proficiency of software engineering. If they really wanted to, you could take that bootcap, you can do, like, some, like, you know, coding, you know, kind of exercises on, on the software. side, et cetera. 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.

Starting point is 01:27:04 And there's a lot of great curriculum out there to learn. 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, there are super intelligences that you can talk to that do a lot, like as their building can help you learn. I mean, like, I literally, I mean, I go into chat to Cotis sometimes and I ask it like,

Starting point is 01:27:47 you know, just like, hey, like, how would you build this app? Like, or, you know, like, I'm just curious. I'm like, like, how would you build Maness, right? Like the agent, uh, 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 24-7, 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.

Starting point is 01:28:27 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++, 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 08, 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,

Starting point is 01:29:04 you literally took Photoshop, opened it up, created like a rounded corner and picked. and then pixel up 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? It's like to create like to line stuff. You just kind of have this invisible one pixel thing

Starting point is 01:29:55 that you just stick in places. Yeah, no. I do. 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. Here we go. What are two or three books you find yourself argumenting most to other people? You know, 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 a mind expanding book. Like I like sci-fi and fiction that like kind of opens your brain.

Starting point is 01:30:24 So maybe this is my cheat card, but, you know, it's a three book series. 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.

Starting point is 01:30:38 I liked even the first one. 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 intercepted into like another layer. Right. Awesome. Okay. What's a favorite recent movie or TV show you've really enjoyed? TV show.

Starting point is 01:30:57 I just started watching the studio. It's like the Seth Rogen, Rogan. Yeah. So stressful. Yeah. It is very stressful. And, you know, I just kind of. I mean, Silicon Valley was like too close to home when it came out.

Starting point is 01:31:13 So like I watched it, but it was like just cringy. The studio is kind of fun to watch because like it's it's a little bit of that like inside baseball 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 because I split time between LAA and stuff 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 it's characterizing. Do you have a favorite product you recently discover they really love?

Starting point is 01:31:45 Could be an app, could be gadget, could be a clothing. So, okay, so I'll give two because I feel like I have to say some kind of software product, right? I mean, 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

Starting point is 01:32:28 underdog story. I'm like clearly like Google's gunning, gunning a in the space has V-O-3 and so on and like you know as is opening eye but like I love the underdog story of this like sub hundred 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 kind of nerdy real world answer on product is I kind of just recently got into like this whole cottage industry of artisanally produced uh 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,

Starting point is 01:33:11 or the old fashioned industrial way, right? Like, they have these like loop wheeler machines and they spin up the cloth in like a very slow pace. So it's completely impractical from like a production scale standpoint. But, you know, I just like I've gotten like some of these t-shirts and they like I just love the, you know, I guess, 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.

Starting point is 01:33:47 Right. So like maybe that makes me a hipster, but like I love the, you know, the vintage, the retro increasingly these days. I feel like anything that starts with artisanal small batch Japanese is going to be really good. stuff. Is there a brand you want to share that is that? Or is it like, you want to keep it Yeah. Actually, so self-edge, which actually has a storefront, like the main storefront is on Valencia Street in SF. They carry a lot of these items. And like that's kind of their whole M-O and they have like jeans and like T-shirts. So I've gotten a lot of, I mean, they basically curate a really good selection of different actual makers. Like one of them is called Studio Dard

Starting point is 01:34:25 is on. Another one's called. Actually, it's cool. There's this company called, um, I think that the umbrella company is actually just Toyo, T-O-Y-O-O-Mufacturing, 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 post-war brand that was kind of like Haynes, like one of the like big like four or five like, you know, kind of. menswear like, you know, kind of undershirts and athletic wear brands called Whitesville. I don't know where the name came from, but, you know, it, it basically, it's a bunch of, like, basic clothing, like t-shirts, et cetera.

Starting point is 01:35:13 And they, this Japanese indie company, basically 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, tease, 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 in the small-scale Japanese manufacturing approach to making those clothes. I feel like we just tapped into what could be a whole other podcast conversation about

Starting point is 01:35:54 clothing and craftsmanship, but let's, I'm going to pull us out of that. The next podcast franchise. Or just Howie and Lenny talking about clothing. Okay, two more questions. Do you have a life motto that you often find useful in working and life share with friends or family? I stumbled on this guy, Paul Conti, who I think is an MD, but also like a psychologist. And he has a book, but also like he did this long form podcast with Andrew Huberman. And, you know, he actually ends up talking a lot about, like, just how to think about, like,

Starting point is 01:36:35 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 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 fully own that like, you know, even though, you know, I didn't come from 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

Starting point is 01:37:21 of growing up in the U.S. where I'd be born in and growing up in the U.S., 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 learn about from there. But, you know, like 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, you know, kind of the future with a spirit of humility and gratitude rather than, I guess, the opposite of that, you know, it just, I think I've felt like it makes like it kind of like becomes a self-fulfilling prophecy, right? Like, you know, you're, you're open-minded, you're kind of grateful. And then, like, more opportunities actually come your way, right?

Starting point is 01:38:03 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 good people and good things. But I, you know, 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 had 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, but like to still try to look at the entire situation from overall, you know, feeling of humility and gratitude. I think just really does shift your, you're like, you know, it spills over into everything else for that day and maybe even for like, you know, the whole lifetime.

Starting point is 01:38:51 That super resonates. That is really powerful advice. That's hard to internalize, but important. Yeah. It easily said hard to practice. 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, HowieTL. I don't post that much, but I'm a lurker. So I listen and watch and you can always DM me there. You can also email me directly Howie at Airtable.com anytime you can have ideas, feedback, etc. Um, you know, on air table, like, just go try it. Like the whole point is we want to make this an experiential product, right? Like, you know, that's why we're, we're really leaning into the PLG routes.

Starting point is 01:39:30 We talked about like the homepage literally says like, just start building right now. What do you want to 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 want to rip on them, like I love, because my passion is thinking of a product and like product UX, especially in the AI era,

Starting point is 01:39:47 if you're working on or, you know, thinking about something interesting in that space, like and even if just purely to like riff on a concept like that's that's something I enjoy doing and maybe I get to learn and 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 try air people as well. Like that's that's the main thing. Sounds like you're looking for people to nerd snipe you and. Yes. Howie, thank you so much for being here.

Starting point is 01:40:13 Awesome. Thank you, Lenny. Bye, everyone. Thank you so much for listening. If you found this valuable, you can subscribe to the show on Apple podcast, Spotify, or your favorite podcast app. Also, please consider giving us a rating or leaving a review, as that really helps other listeners find the podcast. You can find all past episodes or learn more about the show at lenniespodcast.com. See you in the next episode.

Lenny's Podcast: Product | Career | Growth - How we restructured Airtable’s entire org for AI | Howie Liu (co-founder and CEO)

There aren't comments yet for this episode. Click on any sentence in the transcript to leave a comment.