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

If you were literally founding a new company from scratch with the same mission, how would you execute on that mission using a fully AI-native approach? If you can't, then you should find a buyer. And then if you really care about this mission, like go and start the next incarnation of it.

For 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 that you think could be relevant to Airtable, go do it.

Of the different functions on a product team— PM, engineering, design— who has had the most success being more productive with these tools?

It really does become more about individual attitude. There's a strong advantage to any of those 3 roles who can kind of cross over into the other 2. As a PM, you need to start looking more like a hybrid PM prototyper who has some good design sensibilities.

Do you see one of these roles being more in trouble than others? Today, my guest is Howie Liu. Howie is the 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 CEOs almost becoming individual contributors again, getting into the code, building things, leading initiatives themselves. The something that we call the IC CEO. We also talk about the very specific skills that he believes product managers and product leaders, also engineers and designers, need to build to do well in this new world that we're in. Also, how he restructured his company into two groups: a fast-thinking group and a slow-thinking group, which allowed their AI investments to significantly accelerate. If you're struggling to figure out how to be successful in this new AI era, this episode is for you. If you enjoy this podcast, don't forget to subscribe and follow it in your favorite podcasting app or YouTube. Also, if you become an annual subscriber of my newsletter, you get a year free of 15 incredible products, including Lovable, Replit, Bolt, N8N, Linear, Superhuman, Descript, Whisperflow, Gamma, Perplexity, Warp, Granola, Magic Patterns, Raycast, ChatGPT, and Mobbit. Check it out at lennysnewsletter.com and click Product Pass. With that, I bring you Howie Liu. 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? 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. Try it for free at lucidlink.com/lenny. That's L-U-C-I-D-L-I-N-K.com/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. With DX, companies like Dropbox, Booking.com, Adyen, and Intercom get a deep understanding of how AI is providing value to their developers and what impact AI is having on engineering productivity. To learn more, visit DX's website at getdx.com/lenny. That's getdx.com/lenny. Howie, thank you so much for being here and welcome to the podcast.

I'm so excited. Thank you, Lenny. I've, I've been a listener from afar for a while now.

I'm, I'm really flattered to hear that. I'm also very excited. You've been on quite a journey over the last, uh, is it 13 years? Is it, is it longer?

Like right, yeah, right about 13.

13 years. I imagine there have been a lot of ups and a lot of downs. Uh, 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 is something I think about when I think of Airtable. Uh, I feel other people maybe feel this way is there's this tweet that went super viral, uh, maybe a couple years ago at this point where someone just shared all this data and they're like, Airtable is dead. They've raised way more money than they're worth. They're not making enough to get from underwater. Yeah. Airtable RIP. Uh, what happened there? How much of that was true? How did that go?

Yeah, so very, I mean, basically none of it was true. Uh, and, um, I mean, the surprising thing to me was how viral this tweet went when Frankly, like, I actually looked back at this person's other tweets. I think 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 consolation, I looked back and like this person had also tweeted about other companies. Like Flexport was the last like kind of takedown tweet they had. Like, oh, Flexport's dead. I'm like, their valuation is too high and blah, blah, blah. And so I think that the more surprising thing was just like, this person has been tweeting a bunch of spicy takes that are not substantiated by real data or correct data. And yet 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 obviously super popular. And I listened to it, they covered it. They were like, oh, latest on this week's news, this tweet about Airtable. 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 decacorn companies in this new— and at that point it was like kind of the reset 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. 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 even has time to get out of bed? Yeah.

Well, I think I learned about memes and virality 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's such an— the incentives are so misaligned. It's just, I need to tweet something people want to share, not truth.

Well, I mean, especially like, I mean, I, there's a lot to like, I would say net-net, I like the post-Elon Twitter more than the pre-Elon Twitter because it's 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've made so many changes, but Like, I do feel like I get injected into my feed very sensational content all the time. And I mean, it works on me. I'm like, you know, like I can't help but to like click on it and engage with it. And like, you know, but it does, I think it does result in like this kind of content, like really spreading.

Yeah. Now Nikita running the show. I don't, I don't know if you saw this. There's a new, we don't need to keep talking about Twitter, but there's a new feature where you take a screenshot of a tweet and it has like a huge x.com logo. Watermark in the top right. Yeah. Just to like, you know, people are sharing these tweets all the time. Yeah.

Yeah.

Oh man. Never a dull moment over there for sure. Okay. I want to go in a completely different direction and something that I'm really excited to talk to you about, which is this very emerging trend that I've noticed that I feel like you're at the forefront of, of CEOs becoming ICs again. It's kind of this move of IC CEOs, CEOs getting their hands dirty again, building again, getting in 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 backend, thinking about the real-time data architecture of our platform, also the frontend, the UX. And I would argue that 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 an 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 meta sense, like Airtable is the platform for other people to build their own apps, right? So like it's all about the tech. 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? Like you can't separate those two. You can't say like, okay, like I researched the jobs to be done. Here's the workflow, here's the process. And then like, okay, some engineer can just build it as an afterthought. Like it's those like little decisions and really be able to like be at the bleeding edge of what's possible both in the browser and with like, you know, kind of the real-time data architecture. That made the product what it was, right? I think the same is true for Figma, which actually had a very parallel timeline to us. We both were founded around the same time, both spent 2 and a half years building the product hands-on, that early team before launching. And when I think now to both the era in between that founding moment and then now, as well as now the new kind of GenAI moment, Like, I think there was a maturing era of both SaaS overall and Airtable specifically where, you know, as you scale up and you 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 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 more blunt instruments to kind of scale it up, right? Like a more blunt roadmap, a more blunt kind of go-to-market execution strategy. Regardless, I think that now we're entering this moment where every, certainly every software product, in my opinion, has to be refounded because 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. 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 to be continuously relevant and to kind of refine product market fit in this era, I think you have to be in the details. There is no looking at it from a 10,000-foot view and saying, oh, we're just going to throw a bunch of people at this problem. It's actually understanding what is the right product experience and the right business model that backs it up and the right everything else to support that engine. To take advantage of the capabilities in our product domain.

You have this phrase somewhere where you, you talk about being the chief tastemaker.

Yeah.

And to do that, you have to do exactly what you're describing.

That's right. I mean, I think that, and like, I would also say like, it's actually now also hard to taste the soup without participating in like at least some part of creating the soup. Right. And like meeting with AI. You can kind of look at the final product and say, okay, like this feels right or not, or like it feels like we're being bold enough and we're properly productizing these new capabilities. But I think like to really understand 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 kind of screenshots or like a prerecorded 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 that you've built with it, but you're also playing around directly with the underlying primitives. You're using the models either via API or via like a chat interface. Like you're really pushing them to the boundaries. And like, because that's the only way that you really understand what these new ingredients— it's like as a chef, you just gained access to like amazing new ingredients, but you have to like Actually kind of get comfortable with them to put them into a new dish.

And we had, um, Dan Schipper on the podcast. He runs, uh, this newsletter and podcast, a product company called Every, and he, they work with companies to help them become more AI, uh, successful and adopt AI and all that stuff. And I asked him, what's the, what's the signal that a company will have success adopting AI and seeing huge productivity gains? And he said, it's, does the CEO use ChatGPT or Claude daily. And I feel like you're describing exactly hourly.

Literally hourly. You could even have a measure of inference costs, right? The equivalent underlying inference compute cycles, right?

How many tokens they use.

Yeah. I'm proud to say, I'm pretty sure I'm still the— I just checked this recently, but 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. I'm extremely intentionally wasteful, wasteful in the sense of I'll do something that costs maybe hundreds of dollars of actual inference cost. Right. Like, for instance, Doing a lot of LLM calls against long transcripts of, let's say, sales calls to extract different types of insights. Like, here's the product gaps identified, or here's summaries, et cetera. And we also have now a capability that's basically like an LLM MapReduce. So effectively, even if you can't fit the entire corpus of content into one LLM call because of the context window limitations, we'll map through all of this content and break it up into chunks and then Perform an LLM call on each one, and then perform an aggregation LLM call on those chunks. Very expensive, right? Because you're basically running like a highly expensive model against a lot of data and then running it again on the aggregates of that. But like, for me, you know, like hundreds of dollars spent on this exercise is trivial compared to the potential strategic value of like having better insights. It's as if like a really, really smart chief of staff, has gone through and read every single sales call transcript that we've had in the past year and giving me kind of very astute product insights, marketing insights, kind of positioning insights and segmentation insights. That's invaluable, right? You could pay a consulting firm literally millions of dollars to get that quality of work. So to me, I still think the value versus the actual cost of AI when applied greedily, but smartly. It's a crazy ratio and more people should be aggressively throwing compute cycles at these very high value problems.

Until somebody tweets how you're costing the company so much on AI compute and you guys are going to be underwater. I'm just kidding.

It's like Howie has personally taken down the cash flow profile 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, 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 engaging in more timely topics, right? Like, I like to think of the best types of meetings as very urgency-driven. And there's some timely topic, like you've discovered some insight. Maybe I talked to some new startup, right? And I learned something from their product or their approach. And I want to bring that into how we're thinking about a new feature at Airtable or even just plant the seed with some different EPD people within Airtable. I want to make most meetings very timely and very informed by real alpha, right? There's got to be some kind of value and insight to seed that with. Now, in addition to that, I'll supplement with when I'm in person with someone, I want to carve out time for a proper catch-up and less structured, less timely, and just more of like building a relationship with a human. But I actually find that having that combo, it's almost a barbell approach where it's like, 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 2 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 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, et cetera, like how would they execute, right? And are we executing as fast as them? And taking advantage of like all the new stuff as well as them. So like bringing that level of like kind of intensity and urgency to like how I spend my time within, that's been the main, the biggest shift for me.

What's 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 reorg of the EPD org. So before we had, we've gone through a few different kind of reorgs over the past, call it 4 years. The kind of original state as we just kind of proliferated, I think by default or incrementally, was that we had a bunch of groups that were each responsible for like a feature or a surface area. So there was a group responsible for search within Airtable and there was a group responsible for like mobile experience and so on and so forth. And that has its benefits. Obviously that team can go and get really ramped up on that part of the codebase, that part of the product. But it has the disadvantage of, 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 an outcome goal, right, that might need to coordinate dramatic changes across a wider set of surface areas instead of just like each one kind of incrementally 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 datasets and use cases? Do you have the core capabilities needed to be able to like push out an app to maybe 10,000 seats or 20,000 seats for product operations, right? So a lot of architecture, a lot of scale, that kind of work. We would have 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 infra. 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 teams pillar could think not just about one feature, but like the overall onboarding experience. We're like really thinking about NUX, you know, in a way that touched multiple parts of the product. But it still felt like it wasn't, especially as as we started to execute more on AI stuff, like it wasn't you know allowing us to aggressively and quickly move as an AI native company would, right? Like I mean when you look at the cursors of the world, they're shipping major new stuff every week. And it's not like, oh, well, we have this separate roadmap for enterprise. We have this roadmap for this group. And it just feels like one cohesive product that's shipping at a breakneck pace. So we did this recent reorg where now we have what I call the fast thinking group, which officially is called AI platform. But it really means We want to just ship a bunch of new capabilities on a near weekly basis. And each of them should be truly awesome value, right? You should drop your jaw at how awesome it is to use this new capability in Airtable. And then separately, we have the slow thinking group. That's not meant to be better or worse. It's literally like you need fast and slow thinking in the Kahneman sense to operate, right?

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 our data store HyperDB that now can handle like multi-hundred million record datasets. Like that's not something you ship in a week, right? In a hacky prototype. So we now have these 2 separate parts of the company. And I actually think what's really cool is like they actually complement each other very well, right? Because like the fast execution, the AI stuff, you know, that creates the top of funnel excitement 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 this stuff too. It's not just like an SMB thing, but like the slow thinking basically allows those initial seeds of adoption to sprout and grow into much larger deployments. Whereas I think a lot of the challenge for many of the AI-native companies I've seen is that they can have a very wide top of funnel, like get all of this AI tourist traffic, a lot of interest, a lot of early usage. But then sometimes the challenge is how do you turn that into more durable growth and get each of those adoption seeds to retain and expand over time?

That is super cool. I've never heard of this way of structuring teams, the fast thinking, thinking fast, thinking slow, the Kahneman. It's so interesting. For the fast thinking team, do you find there's 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 Airtable? What do you find?

We, we have a mix. So, you know, we've brought in, uh, I mean, we're, we're always hiring, right? Like there was never a point in, um, in the company's life where we stopped hiring. And that, you know, candidly, even when we had to do 2 RIFs, 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 RIFs, we were still actively recruiting and hiring, you know, in, I mean, every major department, but especially in EPD, because, you know, it's always been my belief that like, you all, like, it would be arrogant to say that we have all the people we ever need. already in the roster today, right? Like, we're always going to need to find new fresh perspectives, new skill sets, et cetera. And so we've continued to hire. I think we've learned as we've gone along of what is the ideal type of hire, and we've done some acquihires and learned from that as well. But I think the fast thinking part, it really just requires somebody who's able to operate with a lot of autonomy, right? Like, who's entrepreneurial in nature. Now, it doesn't mean they have to literally be a former founder. I know some companies are, like Rippling, for instance, does a lot of actual acquisitions and gets actual founders into the company. We found that that's great, and we've done some of that as well. But also, there are some really capable people who we didn't literally have to acquire in, and yet they're just able to think full stack about the problem and the user experience problem, not just meaning the technical layers of the problem, but also what is the wow factor we're trying to create, right? So tangibly, we're doing this new thing that's about to ship where not only can you describe the app you want to build and then iterate on it with kind of our conversational agent Omni, and it builds it with the existing Airtable platform capabilities. But we're also giving it the ability to actually do codegen to extend those apps with like really final mile, very bespoke functionality or like visuals, right? So you could say like, hey, generate me a very, very specific type of map view with like this kind of like heat mapping and this kind of like, you know, icons. And when you click it, do this. And like, that's a capability that like there's so much ambiguity in some of the design decisions around it. Like, And you have to blend that design thinking with some of the technical constraints of what can the AI models actually one-shot effectively? And if not, how do you add in the right human workflow for approval and review and then reprompting and so on? So just so many different design decisions, and you need somebody who can really think full stack about that kind of product and is not overwhelmed by that kind of open-endedness, but relishes in it.

I was actually playing with it, uh, before we started chatting. I made a really cute startup CRM.

Oh, that's awesome.

Yeah. Started talking Omni over here. It's like the colors are beautiful. That was, that's what's standing out to me right now.

Um, I will say like, just as a, as a note, um, you know, I consider myself like at my core, like a product UX person, right? Like that, that's my like passion. And, you know, everything else I've had to learn to, to kind of run this company. It's almost like what was a necessary part of the journey. But my real passion is thinking about product UX, right? And I think of UX in a deeper sense than just the cosmetic design, what you could put into a Framer kind of prototype. I think of it as literally what should this product do and how should it represent that and behave for the user? That is the product, in my opinion, right? And of course, then you have to figure out like technically what's possible and how to implement it. But like, I think to me, what's under-executed today in the world of AI products is like, there's so many awesome capabilities of AI and most of them are really under-merchandised. 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, ChatGPT, obviously, like, you know, extremely successful product. So not knocking it at all, but like you come in and you just get this like completely blank chat box, right? By default. And now they have suggestions underneath it and so on. But like, you know, the product UX part of me is just like craving more visual metaphors or colors or some kind of like use the canvas of a web interface. to, and all the richness, um, you know, of interaction you create there to better represent or show all the different things that you can do with, uh, you know, with the underlying model, right? Um, and so that's something we've tried to do with Airtable is like show like all of the different states and like use colors even to play those up.

It's interesting how much of this connects with, I just had Nick Turley on the podcast. He's head of ChatGPT at OpenAI. And he had these 2 really interesting insights that resonate directly with what you're describing. One is he has this concept of whenever something is being worked on, he's always asking, is this maximally accelerated? How do we move faster? Is that 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 this creating this very clear sense of speed. And you even call it the fast thinking team. Like you are 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.

I couldn't agree more with both of those. And particularly on the second point, I think it's interesting. Clearly, there have been companies that have both been successful in PLG and more sales-led distribution for AI products. The most notable ones I can think of are Palantir with their AIP deployments. That's obviously very sales-led. You're not PLGing into a Palantir deployment, but even companies like Harvey and so on, they're doing very well. And it's primarily, from what I understand, sales-led, right? You're not self-serving into a Harvey instance at a law firm. And yet, 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 get to do a POC, but, like, it's so much more powerful when you just open up the doors and say anyone who wants to come and sign up and trial this product, like, can, right? And I think, you know, it's, to me, it's like, you know, kind of a real proof point that, like, ChatGPT 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, MA— is it MAUs or weekly active users?

10% of humans on Earth use it weekly.

That's insane. In like how many years, right? Like a few years?

3 years. Under 3 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 try the product out. Like, and, you know, kind of as a little bit of a rebuttal of the point I made earlier where I think ChatGPT doesn't do a ton right now, and even earlier they did even less to 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, people in the early days tried to stump it and showed like, oh, look, see, it's not that smart. It doesn't answer this hard question really well. But clearly the magical nature of it still appeal to you enough, everybody used it. And so I think I do have a view, like we've gone through that whole kind of arc of we started PLG. I'd like to think Airtable was one of the kind of PLG darlings of our era. And anyway, kind of started moving upmarket and doing more sales execution, although that was still always on top of usually PLG within an enterprise. But we started doing more and more sales. execution. We still have that. That's still really important for our business. But I also think like me personally, like one of my goals is to shift my attention back into that kind of like, you know, builder-led adoption and like literally showing in the product experientially, not telling in like a deck, the value that you can get from AI in Airtable, right? Like I think that's so key and it's, you know, it's NUX, but it's also more than that. It's not just like literally how do you onboard somebody into the product? It's like literally thinking about the entire product experience itself, right? And in our case, like we just like made the entire product experience AI-centric, right? Like it used to be that like, you know, we had kind of this like secondary thing that you could ask questions to the assistant sidebar. We now made our agent the default way of doing everything in Airtable. And like, you know, it's like now the, the Airtable app as you know it is almost like an artifact. that's manipulated by, um, 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, it looks like basically all the other AI app building sites now. It's just, tell me what 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 well?

There's clearly a, an incredible magic to uh, vibe coding and, and app building with AI, right? And, um, this is actually, you know, like a prime illustration, uh, in my view of, of, uh, that, that concept we talked about a second ago, which is, you know, as capabilities of these underlying models evolve, the form factor and the product UX also needs to evolve with it, right? And so, like, the earliest models, like the kind of original ChatGPT, like GPT-3.5, uh, you know, kind of era models, were not nearly as smart as the current models, right? And so you couldn't really ask it to one-shot a more complicated chunk of code or certainly not like a full-stack app and expect it to work. And so the right form factor for leveraging those models in a software creation context was GitHub Copilot, right? It's like autocomplete a few lines of code at a time, right? But you couldn't chat to it and tell it, build me this entire app from scratch, right? And I think that as the models got better and better, you saw that the new form factors emerge. I think Cursor did a great job of being an early pioneer of this more agentic way of leveraging the models to do more complex things and generate more 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 it go and create all the files and fill out each file. And then the thing actually runs some of the time. And so to me, this is where the world is going. The models are clearly getting smarter. And if you think about the original vision of Airtable, it was always about democratizing software creation. We just strongly believed that the number of people who use apps far outweighs the number of people who can actually 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 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 company that predates GenAI and now has to kind of find your new footing in the AI landscape, you can't fool yourself and just say, okay, I'm going to throw in some AI stuff on the marketing site, put in a couple of AI features and call it a day. I think you actually have to take a clean slate approach to saying, how would our mission best be expressed? 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 then, by the way, do you have useful building blocks 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 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, look, I think I'm better off doing this with the pieces that I have for my existing business and product, then I think you should sell, right? Like you should find a buyer for that company and then go and 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 apps. So I should clarify that, like, you know, we want to democratize software creation, but specifically we are focused on business apps, right? We're not trying to be the platform where you create like a cool viral consumer game. This is for like your CRM, right? Or if you 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 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 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 layout, right? Or automations and business logic. And so it's almost like, um, in programming terms, like the Airtable pieces in our Lego kit today can be used by this agent as almost like a more expressive DSL, like a domain-specific language to build business apps instead of literally having to write everything down to like the SQL and HTML and JavaScript to build every part of that app from scratch. And so like, if we can combine the best of both worlds, like we have these very reliable, high-quality Lego pieces. Now an agent can go and 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 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 Replit 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. This is much more akin to 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, kind of production-ready state. So like, 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 form today.

I'm talking to a lot of founders that are going through the journey you're going on, which is we've had a business for a decade, AI emerged and wow, we gotta figure out something that works, that could work even better. And so I'm trying to pull out the threads that are consistently working across these journeys, 'cause 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 would you do? Like, what would that business be? Plus, how can, how can, do we have an unfair advantage with the thing we've done in the past? That feels like an important ingredient. And then the other, circling back to stuff you've shared already, there's just, uh, just like creating a sense of urgency and pace and getting people, uh, to understand this is how things move in AI and we need to create this fast thinking team. I love that metaphor and framing. And then there's the point you made about just talking to AI regularly as the founder feels like an important element, just like to truly be this IC CEO talking to AI, working with AI regularly.

Yeah.

Just on that note, a little bit more, what, just to give people a sense of what this looks like day to day. So you're talking to Omni all day, trying to underflex the power of what you can do and iterate on it. Is there anything else you're doing day to day that helps you figure out what to do for the business?

One, I try to use as many different AI products, including not Airtable, right? Like as I can. Um, and both literally for the novelty factor and just like You know, some new cool demo comes out, like Runway released their like immersive world, you know, kind of engine, right? And and so like I'm gonna go try try it out, right? Like when Sesame AI put out their like cool like kind of interactive voice voice chat, you know, you know demo, like I tried that out because like even though we don't have a direct and near-term like you know kind of need for like really. realistic and interruptible, like, kind of voice mode, where it's not as core to our capabilities. 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 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 HeyGen avatars 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 ChatGPT and pull together the results, have it compose like, you know, kind of a little—

Did you actually do this? Is there something you made?

Yeah, that's literally an example of something like just, you know, a fun weekend project. And like, to be honest, like these things only take you like an hour, right? If you become kind of pre— pretty proficient with using the products. Like, they're all so easy to use. Like, you can literally do the deep research thing, you know, kick off a query, make a coffee, come back in 20 minutes. Okay, like, let me prompt it to, like, generate me some dialogue. It's a little bit like what NotebookLM 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 HeyGen avatar and then download the video and then, like, play it, right? Like, and just for fun, right? I'm not, like, trying to make make that into an actual, like, you know, kind of YouTube, like, video business. But, but I think, like, coming up with, like, these different, like, fun weekend projects is a really useful construct to, like, force myself to actually try these products in a more than just, like, a Twitch click way. And, you know, what, what it gives me is, like, A, like, it's not just understanding the models, which is also very, very important, right? Like, GPT-5 came out yesterday. I've been playing around with it a bunch, just on a variety of different personal use cases. But there's a difference between just understanding the model, but then also understanding the product form factors in which they can be placed, right? Meaning when you apply the model in a more structured way, right? When you apply the model with different tool calling than maybe what ChatGPT 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 ChatGPT 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, what are the product form factors that these new models can take? 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 A, it's not perfectly predictable. So I think the element of you're not quite sure what you're going to get. It's like a box of chocolates. And B, it always blows my mind just to think about, wow, 5 years ago we didn't have any of this stuff, right? AI was like, okay, we can do predictive analytics. basically very advanced regressions that we could run with AI, but it looked nothing like this in its current form. And it's just 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. Because on the point about the pace of the world moving so much faster in AI than any other landscape, In SaaS, in the mature SaaS era, it was important to study your competition, right? If you were building a SaaS company, you'd be crazy not to follow Salesforce every year and see what the major releases they're putting out are, or ServiceNow, or so on. This is the equivalent of that, but there's major new releases and products and so on. every week, right? Not like every year. And so I just think you have to stay abreast of all, uh, of it all. And combining this with our point earlier of like, a lot of this has to be experienced, not just like read, like you can't just read like the write-up on TechCrunch or, or, you know, even a tweet about like a new capability. Like you kind of have to try it to really get a sense of like what it is.

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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 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 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 one of the prototyping tools and show like, hey, I built a marketing landing page for 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 what typically we would have done in the past is like, okay, we're gonna write a doc about it and then share the doc. I'm just gonna show you like an actual landing page with visuals and everything in there, right? Or I'll share the actual link to my deep research reports, or instead of me writing a perfect memo on a topic, I'll actually just prompt my way into getting a chat thread or a chat output that basically covers all the content that I care about and maybe even ask it to summarize this all into a final 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, like, um, have the ultimate, uh, excuse, like you can use, like, you know, you could 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 AI product that you can find that you think could be relevant to Airtable, go do it, like period. So I think that's the most important thing is like this play, this experimentation. I think there's also a lot of other kind of shifts in how we execute prototypes over decks. I want to see like actual interactive demos because again, it's hard to In a deck or in a PRD, you could say, 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, okay, let me try it out on a few realistic prompts that I can imagine. And in a demo, in a real prototype, you can instantly try it out on realistic rather than golden pathy scenarios and see how it feels too. Does it feel too slow? Do we need to expose more of the reasoning or steps that are happening behind the scenes, create a progress bar or something like that? But it's really hard to get that feel of the product with anything but a functional prototype that really does in an open-ended way use the AI to do whatever you put in. So I think 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 deterministic resourcing and timelines view of execution, right? Like, we're going to put this many people on this problem and this is the 8-week timeline to this milestone and then we're going to ship in a quarter from now. And I think now the whole thing is just a lot more experimentation and iteration driven.

Of the different functions on a product team, PM, engineering, design, who has had the most success being more productive with these tools? And how do you think this will impact each of these 3 functions over time?

What I found is that it really does become more about individual attitude and maybe some like, um, you know, polymathism. Like, you know, there's a strong, uh, advantage to any of those 3 roles who can cross over into the other 2, like the hybrid unicorn types. If you're a designer who can be just technical enough to be dangerous and understand a little bit of how these models work and how does tool calling work and all of this stuff, then you can actually design a concept or even prototype a concept, including in these prototyping tools, 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 concept, right? Because I think designs have to be more interactive. Like the whole, the value of the product and the product functionality is in the interaction of it, right? Like, think about the design of ChatGPT again. It's like, it's the most basic design. could possibly imagine. The real design actually is happening underneath the hood in how it responds to different queries, right? And what happens after you fire off a prompt, right? So, you know, I think like I found that there are people within each of these functions, like there are engineers who are very good at thinking about product and experience and like, you know, kind of can go and prototype out like the whole thing. There are designers who can kind of do the same, even if they can't literally code. They can prototype something out, like literally using a prototyping tool. And I think that's where like AI tooling is also giving more advantage to people who can think in this way by equipping them with an alternative to actually having to go through the long hoops of learning CS, right? And then PMs as well. I think like there are some PMs who are like really getting into the technical details and studying up on like, you know, how does this stuff work and actually getting hands-on rather than seeing their role as writing documents, writing PRDs.

Do you see one of these roles 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 we want to go and make the team smaller, but rather 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, like now I can do that with a 10th of the people. I mean, you could do that in a lot of cases, but like for us, maybe it's also because we're a very meta product, right? Like we are the app platform with which you can build now any AI app with AI, right? The apps themselves leverage AI capabilities at runtime, whether it's to generate imagery for a creative production workflow, or kind of leveraging deep research or AI-based 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. We can effectively leverage all of these different AI capabilities in this kind of app platform because by definition, we're enabling our customers to build apps that have this wide range of AI capabilities. But because of that, it's like we have a you know, kind of almost infinite, like, set of possible AI capabilities that we could execute on, right? And I'm always telling the team, like, look, like, the great news is, like, we have— it's like we have all these fruit trees, and, like, there's so many crazy low-hanging fruit, right? Like, and you'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 there's so many watermelons on the ground, just go out and start finding the biggest ones and attacking those, right? And what that means is that if we can build this culture, and I do think it's a learnable way of operating, I really like to believe in the growth potential of any human, right? And any individual. I think if you really have a growth mindset, And that's why one of our most important core values is growth mindset, right? If you really have that growth mindset, I think especially if you're willing to put in the nights and weekends hours, or in my case, I'm literally telling people, take a full day off, take a full week off and learn this stuff. You can become more fluent in this way. And I think then what we get is a team that can just go and work on more things in a much more leveraged and fast Way, right? So I like to think like you know people who are willing to jump on the train are just 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 eng PM and design cultures respectively. Over the past even few decades have always been multidisciplinary in nature, right? Like the original PM stack 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 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 a designer at Apple, like, you know, including hardware designer, like you have to understand some of the technical capabilities of how this stuff works, right? And if you're an engineer, like I think some of the best engineers and maybe Stripe always had a very good engineering culture of engineers who could think about the product and business requirements. In fact, like, you know, on any given product group at Stripe, my understanding is that like, you know, the DRI isn't always the PM, right? Like, as is traditionally the case in 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, if you can just do one additional, so a PM becomes better at design and engineer 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 3. Like there's just a minimum baseline of like, if you're any one of those roles, you need to be like minimally good at the other 2. And then you can go deeper into your own kind of specialty, right? Like, You know, you could be a designer who's really good at thinking about UX and interaction design, and then just like good enough to be dangerous on thinking about like what's technically possible and like what is the product, you know, kind of, you know, kind of story around this, this, uh, feature. I love that.

And to do that, one piece of advice that comes up again and again in what you're, what you've been describing is using, use the tools constantly to see what's possible and That will teach you a lot of these things.

I think use, well, use the tools gives you exposure to what's possible, right? It's kind of like if you wanted to be a great industrial designer and let's say, like, I mean, the chair is kind of the ultimate, like, hello world of like industrial design, right? It's like the, the like canonical design object. Like you wouldn't just sit there in a vacuum and with no familiarity with like the materials that you can use, plywood, steel, whatever, or like existing form factors of chairs, trying to invent the world's best chair. a vacuum, right? Like, you should go and first do a study of like all of the best chairs out there today. Like, go look at an Eames chair, sit in it, like try to examine it to kind of reverse engineer how it was made, right? And like, you know, and just look at the prior art for that type of product. Like, that's how I see the go out and play with these products. And also, I think like actually going and designing or implementing or executing is the best practice. So you can't just only go and look at other people's chairs. Eventually you have to go and actually try building your own and then try building another one and another one and another one. And so I think that's where, when I think about how I honed my own product UX sensibilities, I never, I mean, and at that time that I was in school and kind of learning about this stuff, there wasn't really any good curriculum for UX, right? It's not like there were great college classes to learn product UX. I mean, even CS was like very academic in nature at that time. It wasn't applied software engineering, like build an app or whatever. Maybe now at like some of the schools like Stanford, MIT, they have like actually UX-y type courses, but it's 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, 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 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 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. Um, and like in the future, maybe do things like actually generate a like prototype, like of, of a, uh, of a feature, you know, from a PRD or from like a feature idea. Uh, and, you know, I'm telling them like, look, like there's an 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. 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 in Field Agent 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 en masse across the entire, like every speaker you have lined up to do deep research, like powered by ChatGPT's own deep research on each of the speakers and have them all laid out side by side in this table, right? Like go prototype that and see how it, like, you know, see how it feels and looks like. And so I think some of this 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, uh, for ChatGPT deep research yet.

There is now. There is now.

There is. There we go.

It ends up being, uh, and I think they only recently exposed it. It ends up being like something on the order of like a dollar plus per research call, which, 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 a human.

Like, not only that, I actually have a researcher that I pay to He'll give me background on guests that was like $400 or $500 and the dollar sounds great.

And I've been doing this manually. He's smart. He would be using deep research and then just collecting the article.

They might just be. Oh man. Okay. There's one more, uh, skill I wanted to talk about real quick. This comes up a lot in these conversations is evals. Okay. The power of getting good at evals. I know that's something you value highly.

Talk about just why you think this is something people Yeah, I mean, and I listened to your episodes with Yann LeCun and Mike who talk about this. I think it's interesting that both heads of OpenAI and Anthropic have converged on this point. I mean, look, I would add a slightly different or additive take though, which is, I think for a completely novel product experience or form factor, you should actually not start with evals 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, 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 As you vary the prompt or the model or the agentic workflow used to generate these outputs, and you have to define what does good look like, right? By definition for the eval, I would first start with a much more open-ended and ad hoc style of just throw stuff against the wall, try different prompts and see how well it does. And to me, evals are more useful, A, once you've converged on the 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, if you're product market fit finding either for an entirely new company or for like a new, a pretty dramatically new or bold new capability that doesn't really have like, it's not an incremental improvement on something that exists in Airtable 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. It's similar to deep research, but what it actually does is instead of outputting like a, you know, kind of a report, It's actually going and compiling a list of things. The things could be companies or people or anything else, right? Like, find me every Marvel movie ever made. Find me every DC Comics spinoff series, right? Literally anything. And you have to go in at first, just try out a bunch of random, use your own brain to think of 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 evals are useful once you have like a sense of like, what is that cluster of useful use cases? You can start then more, um, like, um, uh, programmatically like measuring the changes that you're making to improve like the, the, uh, the, the output for that, right? Um, but like by that point, you've probably already scoped the product and maybe the way we would merchandise it in the, the, uh, in Airtable is not like a completely open-ended capability, but like, hey, like here is a specific capability that can research one of these X number of entity types, including people and companies. And here's even like the filter conditions or criteria that are more explicit that you can define. to give it the prompting to search for that thing. But I kind of think it's more useful as a way to iterate your way to improvement. And you can start really testing stuff empirically. You can A/B test, especially if you have the scale of a really large product like Anthropic or OpenAI. You can just test everything and see, oh, this model actually performs better than this one. This prompt performs better than this one. But I think early on, you don't have that luxury and you're in a much more open-ended discovery process.

That is very wise. Eval can constrain you too early. I think about just the double diamond, I don't know, IDEO kind of framework of like be divergent first and then converge and then maybe that's where you want to start eval.

Yeah, 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. And let me see if I'm missing anything that you think is really important. So one is there's this sense of just like reset the expectations on pace and urgency and help people understand in AI, things move incredibly fast. This is how we need to operate. And then there's also a piece of get stuff out so that you can learn how people use it and what it's capable of versus polishing it endlessly.

Mm-hmm.

Um, forcing people almost, I don't know if forcing is the right word, but encouraging people to play with the latest stuff. And like giving them a chance to take days off to, or block out calendars, cancel meetings, just like stay on top of this stuff.

Yeah.

Uh, to play as you talked about it and then sharing things they've learned, get the vibes of what's possible. There's also this idea of just rethink, okay, if we were to start today in this world, what would we do to achieve the same mission we have achieved, we are trying to achieve? And ideally it leverages this unfair advantage we have with things we've been working on for a long time. And then there's just talk to AI constantly every hour as you described.

Yeah, multiple times an hour.

Multiple times an hour. It keeps going up. Is there anything else that I missed there that you're like, you need to do this too to have a chance?

I think just to really try to break down role silos. And I think that's true certainly for EP&D in the typical EPD triangle, but I also think 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, and I think our marketing team is like you know really leaning into actually is is like you know if you can just do all of the thing yourself. Like traditionally, you know how a marketing team might operate is like okay you have one person who's kind of responsible for executing the performance marketing 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 budget and like kind of conversion tracking, et cetera. And then somebody else is actually responsible for like coming up with the specific ad copy, right? And somebody else yet was responsible for coming up with like the seed content or positioning guide, like written by a PMM that feeds into the ad creative. And so on and so forth. Maybe they're promoting some new demo asset that somebody else created. And I just think that in the same way that you can collapse the roles in EPD and the ideal person, maybe they're very specialized and deep in one dimension, like engineering, but they're well-rounded enough to be dangerous on the other 2. I think that's kind of true in almost every other function. Sales as well. I think you should start to be able to play more of an SE role. Traditionally, salespeople didn't necessarily know the product that well and relied on the SE to come in and be the product experts. I think it's really hard to sell any kind of AI product now without actually being fluent in the product and be able to demo the product, right? So AEs need to be SE fluent as well. So I just think that concept of collapsing roles, everybody needs to become more full stack to do the thing, like being more outcome-oriented, right? Like your outcome as an AE is to show customers, convince customers of the value of your product and close deals, right? Okay, well, in order to do that, like you used to have dependencies on having assets created by marketing and like you know, an 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? Um, and I just think that's a new way, like, it's a new operating mentality overall for every AI-native company or company that wants to compete in this new arena.

That is, that is a great addition. It almost feels like you go back to startup times when everyone's doing a bunch of stuff. There's no, like, here's the head of product. Hey, there's a head of engineering. We're just doing stuff.

Totally.

Totally. Yeah. I'm kind of seeing it as this is like upside down T where there's like the thing you're really strong at and then you just have to, as you described, the minimum of being good at engineering design or, and SE, by the way, sales engineering, imagine is what that stands for. Um, that you just like, they're adjacent roles. You need to start having a baseline. The baseline is increasing of how much you need to understand that everyone's Venn diagrams are kind of converging.

Exactly.

Amazing. 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, what's the most counterintuitive lesson you've learned about building Airtable, building a company, building teams that maybe goes against common startup wisdom?

You know, I, I've heard, um, uh, you know, you're interview with Brian Chesky, and then later you talked about founder mode in that kind of YC retreat. And the points there really resonated with me. And I feel like maybe less eloquently, I kind of deduced 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 the early days of building a company, you're 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 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 team that's like, tight-knit team that's thinking full stack about all of this combined. And obviously, that's the only way, in my opinion, to create that magical product market fit in the first place. And then I think as you scale up, the default guidance that you often get from operational experts and larger scale company investors is like, okay, you got to industrialize the process of all of this stuff, right? It's kind of like going from like a bespoke artisanal, like one person made an entire item of clothing to like, we gotta like factory produce this thing, right? And what that means in an organizational context is like, you then create these different fiefdoms, you hire all these execs, and like, 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 then 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 using the factory metaphor, there's an argument that that's actually kind of an efficient way to scale up production for each of these different swim lanes, right? Like each one can kind of operate in a more autonomous and 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 liked his point about like the CEO has to play a CPO role, right? You have to care about the product. Like ultimately, like the product is the thing, right? And you can't just coast on scaling up go-to-market around the product forever. Like you gotta keep innovating in the product. And by the way, the best way to innovate on the product is not incrementally split over all these different little surface areas, but actually to have a bigger, kind of more step function vision of how this product needs to make a leap, right? Or what's the next big kind of either act of the product or new capability of the product or reinvention of the product, right? And so 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 is actually exactly the same as how you need to operate in this like constant product market refining of fit state. So like, could not agree more with that concept of, you know, kind of you gotta, you know, think ambitiously and move the organization holistically towards these bigger outcomes, but also like ship and learn and experiment a lot more in this era. And then, you know, maybe the meta learning I had from all of the above is that like, you know, the specific advice obviously was like, okay, go scale up in this way or go hire these types of people, experienced operators, et cetera. Obviously, there's some truth to that. The people giving this advice are not incompetent. They had some reason for giving it, and in certain contexts, that is the right thing to do. But I think my meta-learning is that it's not enough to just trust the recommendation, like, here's the action you should take, from a lot of people, because everybody has different priors. It's almost like we're all our own LLMs. We all have different training from a different corpus of data informed by our own experiences. And maybe you're trained on the ServiceNow or the Oracle training corpus, right? And this person's trained on the Facebook corpus and I'm trained on the Airtable one, right? And I think what I've tried to do more and more is not to just ignore advice from smart people. Obviously, that's not the right answer. But to take their— it's almost like in an LLM, you can now, with a reasoning model, actually inspect the chain of thought and see how it's thinking. Why did it come up with this answer? And to me, that chain of thought, like, why did you recommend this, is actually more informative than the actual just do this recommendation. So the answer might be like, hey, at so-and-so company, This is how we eliminated the PM role entirely, right? For, for Brian, like at Airbnb, like made sense. Like we're no longer having PMs in their traditional form. Now we have program managers and product marketers. And, but like more than the actual decision, 'cause I don't think it's a one size fits all, like everybody should do the same. Why did you do that? Right. And the why actually was very informative. And then be able to take that and say like, okay, like how would I apply that? And maybe it yields a different outcome. But the reasoning actually is very informative.

It's interesting how this idea of founder mode is not so different from this IC CEO trend that you're following. And it's, yeah, it's like being in the weeds, being in 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? 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 Brian conception of founder mode is to like micromanage everything and like not trust anyone. But I think it's more about like finding that right balance of being unabashed about caring about the details that do matter and where the tying together of details across 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 I think the really cool thing about CEOs as ICs and frankly any leader playing more of an IC-like role and being in the details is I think for the right type of person, it's 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, an 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? 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 everything underneath it is going smoothly, then like I'm able to do that, right? And everything looks good. And I just think that's a— maybe again, it works in a certain type of very mature type of business. Like, you know, even then though, like I can't imagine that like at a CPG company, like in Procter& Gamble, you wouldn't want to have a CEO who still actually goes and tastes the soup and tries the products and sees literally the details of what the new product innovation pipeline looks like, as well as how it's being experienced on the shelves and so on. So I don't know, I guess I'm just more and more skeptical that that hands-off, pure delegation and process management role ever works as a CEO. Like maybe you just like, you go through a long enough period of like where the business is coasting that like nobody notices. But I gotta say, like for me, like it's just much more invigorating to get to play that role. And I think for 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 want to have like an 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, 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 gonna have to do some of that. You can't just completely eschew all your responsibility as like an at-scale CEO. But like, don't lose the essence of like the thing that you love doing and that, you know, has like really made this product happen, uh, and gives, you know, this company, as many companies that like were founded on like a, you know, kind of a magical product market fit finding insight, don't like step too far away from that, right? And always make sure that is still your like number one, even if like other stuff has to also add to your plate.

I think people don't talk enough about this, how Someone starts a company, it's an idea they have, they're excited about, it takes off, and then you're stuck on that for a long time. And then even if things are pushed in a direction you're not as excited about, and so this point about just remembering what you actually love about it and coming back to that is so important because that's the only way to keep doing this for, for a long time.

I, I, I think that's so true. And to me, that's why there's always been a difference between entrepreneurs who love the, the act of building a product or the business too, versus those who saw just purely a 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 there's entire industries where it's all just about alpha generation, right? You could go into the private equity business and so on, and it's just purely rationally about How do I find the alpha? And I think that some of the best companies, product-centric companies, at least in my opinion, are run by those people who actually just love the product, right? I think you get a feel for that from some of the AI companies. Like Sam, I think genuinely just loves working on AI, right? If he could spend 100% of his time on just being close to the AI and the research, I mean, he would. And he's even said as much, right? You know, but ranging to like the Bryans 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 would want to make a lot of money off this like arbitrage opportunity against hotels.

They just needed to pay their rent. Yeah.

Well, 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 working on, you know, what could be the same company for a very long time.

Howie, is there anything else that you wanted to touch on or leave listeners with before we get to our very exciting lightning round?

I just want to reiterate, you know, 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 you either have it or you don't, in terms of the skill set needed to be relevant and AI native. But I do think it's a call to action to go and bolster your skill sets where they may be less refined right now. Right. I think everyone, even programming, I really believe everyone could learn how to be a software engineer if they wanted to. Now, obviously, some people, just as with great writers, are never going to be a published author, right? Or like the Hemingway, right? But like everyone can gain a good enough proficiency of software engineering if they really wanted to. You could take Dev Bootcamp, you could do like some coding kind of exercises on the side, et cetera. And the point there is that like, sometimes I think we treat these disciplines like hard, hard skills that Like, if you're not already, if you're already halfway into your career and you're not already an engineer, if you're not already a designer, like, okay, well, you can never be one. And I just think like, you know, our brains are malleable. I think 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 of like, as they're building can help you learn.

I mean, like I literally, I mean, I go into ChatGPT sometimes and I ask it like, 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 Manus, right? Like the agent, open-ended agent. Like literally, how would you build it? You can ask it 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 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 had to like go and like learn some of these things. There wasn't great, like, you know, tutorials for it. You know, you had to reverse engineer certain things. Like there were just like weird things. Like if you wanted rounded corners in your UI, you literally took Photoshop, opened it up, created like a rounded corner in pixels, and then cut that pixel up into an image that you dropped onto the page.

I remember that.

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? Uh, it's like to create, like to align stuff. You just—

Yeah, I remember.

Invisible 1-pixel thing that you just stick in places. Yeah.

No, I—

oh my God. What a time to be alive. Uh, Howie, with that, we reached our very exciting lightning round. I've got 5 questions for you. Are you ready?

Yes.

Here we go. What are 2 or 3 books you find yourself recommending most to other people?

You know, I've been trying to read fiction more, partly because I think it's just like 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. So maybe this is my cheat card, but you know, it's a 3-book series. Those are 3 great books.

I love that series. And my tip there is it gets good 1.5 books in is my tip. So just keep reading. That's where it's like, okay, now I'm in.

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 incepted into like another layer, right? Awesome.

Okay. What's a favorite recent movie or TV show you've really enjoyed?

TV show, I just started watching The Studio. It's like the Seth Rogen, Rogen, Rogen, Yeah, so stressful. Yeah, it is very stressful. And, you know, I just kind of like, I mean, Silicon Valley was like too close to home when it came out. So like, I watched it, but it was like just cringy. The Studio is kind of fun to watch because like, 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, I thought smart and funny show. And because I split time between LA and SF, I also feel like it's very real to me. I see a lot of the literal characters out there in the world that it's characterizing.

Do you have a favorite product you recently discovered that you really love? Could be an app, could be a gadget, could be clothing.

So, okay, so I'll give 2 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 a new one just, I think like 2 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 photorealism in what you can generate now and they also built this cool demo thing that's like an immersive world generator I mentioned before. I think it's just cool to see. I also like the underdog story. Clearly, Google's gunning in this space, has VO3 and so on, and has OpenAI. But I love the underdog story of this sub-100-person company still punching above their weight and building really awesome video experiences. So that's the software one. And then a very, very nerdy real-world answer on product is I kind of just recently got into like this whole cottage industry of artisanally produced, you know, basically clothing, you know, by like small-scale, like Japanese manufacturers that use like literally like 100-year-old looms to make clothes like the old-fashioned way, like, you know, or the old-fashioned industrial way, right? Like, They have these like loop wheeler machines and they spin the cloth in like a very slow pace. So it's completely impractical from like a production scale standpoint. Um, but you know, I just like, I've gotten like some of these t-shirts and they like, I just love the, um, no, 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 5 years ago is obsolete. Uh, like I love a little bit of the throwback to like, you know, old things sometimes can be even more cherishable in this new era. Right. Uh, so like maybe that makes me a hipster, but like, I love the, um, you know, the, uh, the vintage, the retro, uh, increasingly these days.

I feel like anything that starts with artisanal small batch Japanese is going to be really good stuff. Is there, is there a brand you want to share that is that, or is it like you want to keep it under the radar?

Um, actually, so SelfEdge, which actually has a storefront, like the main storefront is, uh, on Valencia Street in SF. They carry a lot of these items. Like, that's kind of their whole MO, 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 d'Artisan. Another one's called— actually, it's cool. There's this company called— I think that the umbrella company is actually just Toyo, T-O-Y-O Manufacturing. Which sounds like it's a big, like, you know, kind of like large-scale conglomerate, but it's anything but. It's like a really small-scale Japanese, you know, kind of like vintage manufacturer of clothing. And, but they have a few sub-brands. They actually bought the rights to this, like, American post-war brand that was kind of like Hanes, like one of the, like, big, like, 4 or 5, 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 basically it's a bunch of basic clothing like t-shirts, et cetera. And this Japanese indie company basically bought the defunct name and now is reproducing clothes almost made to the exact shape and spec. And even with the exact recreation of the graphic packaging, on these, uh, tees. Um, 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 an indie, you know, small-scale Japanese manufacturing, uh, approach to, to, uh, to making those clothes.

I feel like we just tapped into what could be a whole other podcast conversation about clothing and craftsmanship, but let's— I'm gonna pull us out of that.

The next podcast franchise.

Or just Howie and Lenny talking about clothing. Um, okay, 2 more questions.

Yeah.

Do you have a life motto that you often find useful in work or life? Share with friends or family.

I stumbled on this, uh, this, this guy, um, Paul Conti, who I think, uh, he's an MD, but also like a psychologist. And, um, He has a book, but also he did this long-form podcast with Andrew Huberman. And he actually ends up talking a lot about just how to think about your life outlook and kind of your framework for thinking about life, but grounded in a kind of scientific and neurological and cognitive science And I found one particular point really powerful. It stuck with me, which is like, if you live your life in a way that's foundationally built around humility and gratitude, right? And look, everybody has different circumstances. I think I fully own that even though I didn't come from money, my family was very financially modest growing up. I still had incredible resources and opportunities afforded to me, even just by virtue of growing up in the US, being born in and growing up in the US, but also having access to a computer and the internet and even all the free resources I could then access and learn about from there. But I still feel like whatever you have or don't have to start with, if you kind of approach the world and 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 open-minded, you're kind of grateful, and then like more opportunities actually come your way, right? And maybe it's because of the energy you're putting out into the world and, you know, and other people and like you're kind of attracting like good opportunities and good people and good things. But I think like, there's a lot of other parts of like his framework, but like the one that is easiest to remember is just like, how do I approach each day? Even if like I'm going through a tough moment and maybe we had to like, I had to fire somebody today, or maybe like, I got disappointed because we lost a customer deal or something broke or whatever, but like to still try to Look at the entire situation from an overall, you know, feeling of humility and gratitude, I think just really does shift your, your like, you know, it spills over into everything else for that day and maybe even for like, you know, the whole lifetime.

That super resonates. That is really powerful advice. That's hard to internalize, but important. Yeah.

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, Howie TL. I don't post that much, but I am a lurker, so I listen and watch, and you can always DM me there. You can also email me directly, howie@airtable.com, anytime you can have ideas, feedback, etc. You know, on Airtable, 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 really leaning into the PLG roots. 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 you want to riff on them, like I love, because my passion is thinking about product and like product UX, especially in the AI era. If you're working on or thinking about something interesting in that space, like, and even if it's just purely to like riff on a concept, like that's, that's something I enjoy doing and maybe I get to learn and sharpen my own skillset from. So Feel free to reach out. And and yeah, I mean, you know, tell your friends and family to to try Airtable as well. Like that's that's the main thing.

Sounds like you're looking for people to nerd snipe you. And yes, Howie, thank you so much for being here.

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 Podcasts, 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 lennyspodcast.com. See you in the next episode.