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

Howie Liu: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 carnation of it

Lenny Rachitsky:For people that work for you how have you adjusted what you expect of them to help them be successful

Howie Liu:If you wanna cancel all your meetings for like a day or for an entire week and just go play around with every AI product that you think could be relevant to Airtable go do it

Lenny Rachitsky:Of the different functions on our product team PM engineering design who has had the most success being more productive with these tools

Howie Liu:It really does become more about individual attitude there's a strong advantage to any of those three roles who can kind of cross over into the other two as a PM you need to start looking more like a hybrid PM prototyper who has some good design sensibilities

Lenny Rachitsky:Do you see one of these roles being more in trouble than others today my guest is Howie Liu Howie is the cofounder and CEO of Airtable I'm having a bunch of conversations on this podcast with founders who are reinventing their decade plus old business in this AI era to help you navigate this existential transition that every company and product is going through right now Howie and Airtable's journey is an incredible example of this and there's so much to learn from what Howie shares in this conversation we talk about a very interesting trend that I've noticed that Howie is very much an example of of cos almost becoming individual contributors again getting into the code building things leading initiatives themselves 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 N Eight N Linear Superhuman Descript Whisperflow Gamma Perplexity Warp Granolah Magic Patterns Raycast Chepi RD and Mobbit check it out Lenny'snewsletter.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 creativework 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 Lucidlink.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

Lenny Rachitsky:Howie thank you so much for being here and welcome to the podcast

Howie Liu:I'm so excited thank you Lenny I've I've been a listener from afar for a while now

Lenny Rachitsky:I'm I'm really flattered to hear that I'm also very excited you've been on quite a journey over the last is it thirteen years is it is it longer

Howie Liu:Like right yeah right about thirteen thirteen years

Lenny Rachitsky:Imagine there have been a lot of ups and a lot of downs I wanna talk about all those things I wanna talk about a lot of the lessons that you've learned along the way I wanna start with what I imagine was a a very surprising down moment in the history of Airtable this is something that unfortunately something I think about when I think of Airtable I feel other people maybe feel this way is there's this tweet that went super viral maybe a couple years ago at this point where someone just shared all this data and they're like Airtable is dead they've raised way more money than they're worth they're not making enough to get from an underwater yeah Air Table rip what happened there how much of that was true how did that yeah

Howie Liu:So very I mean basically none of it was true and I mean the surprising thing to me was how viral this tweet went when frankly like I I actually looked back at this person's other tweets I think they they they worked at CB Insights and the irony is like the the whole point of that business is to have like good data good data quality around private company data and they just like literally had incorrect numbers by like a a strong multiple on like what our revenue scale was what our growth rate was like you know and and if it gave me some consolation I looked back and like this person had also tweeted about other companies like was the last like kinda takedown tweet they they had oh Flexport's dead and like you know their their you know their valuation is is you know too high and blah blah blah and so I think that the more surprising thing was just this person has been tweeting a bunch of like spicy takes that are not substantiated by real data or correct data and yet like this particular tweet went super viral and that was the perplexing part to me and then I think actually I think what what really gave it legs was on the All In podcast which is like obviously super popular you know and I listened to it like you know they they covered it they were like oh like you know latest on on this week's news like you know this tweet about Airtable what do we think about this and it 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 recent moment for both public and private markets they did also issue a correction though All In did a a follow-up episode a few few I think weeks later saying like hey like you know we got the numbers wrong like you know we we're revising our case and and kind of a a view on Airtable

Lenny Rachitsky:What's that line about how a lie gets around the world some number of times before truth has even has time to get out of bed

Howie Liu:Yeah yeah yeah well I I think I learned about memes and morality very quickly in in that experience not a very good social media person but I think I learned a little more

Lenny Rachitsky:Yeah it's tough Twitter is such an the incentives are so misaligned it's just I I tweet something people want to share not truth

Howie Liu:Well I mean especially like I mean I I there's a lot to like I would say net net I like the post Elon Twitter more than the pre Elon Twitter because it it's just bolder and like I'd you know I guess I I really admire bold product execution where you're not just kinda stuck to like the current laurels and they'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 it does I think it does result in like this kind of content like really spreading

Lenny Rachitsky: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 a huge x.com logo watermark on the top right yeah and just to like you know people are sharing these tweets all the time yeah yeah oh man never a dull moment over there

Howie Liu:For sure

Lenny Rachitsky:Okay I wanna go in a completely different direction it's something that I'm really excited to talk to you about which is this very emerging trend that I've noticed that I feel like you're at the forefront of of cos becoming ICs again it's kind of this move of I see cos cos 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 just what that looks like day to day to you versus what your life was like a few years ago

Howie Liu: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 I was literally writing code both on the back end thinking about the real time data architecture of our platform also the front end the UX and 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 a operationally heavy business like a dog walking marketplace where the tech is only an afterthought like the tech was the product right and in a very nice sense like Airtable is the platform for other people to build their own apps right so like it's all about the attack like the very intimate design decisions again both architecturally and and on the front end and the product UX choices like that is the product's value prop right like you can't separate those two you can't say like okay like I researched the jobs to be done here's the workflow here's the process and then like okay some engineer can just build it as an afterthought like it's those like little decisions and really be able to like be at the bleeding edge of what's possible both in the browser and with like you know kind of the real time data architecture that made the product what it was right I think the same is true for Figma which you know actually like had a very parallel timeline to us like we both were founded around the same time both spent two and a half years building the product like hands on you know that early team before launching and you know when I think now to like both the era in between that founding moment and then now as well as like now the the new kind of gen AI moment like I think there was a maturing era of both SaaS overall and Airtable specifically where as you scale up and you kind of learn how to build teams and organizations and 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 by default further and further away from those details and maybe for some businesses that's fine because like no longer is it about finding like the details that make for a magical new product market fit and it is really just about scaling up an existing thing that works right and using what I would call like more blunt instruments to kind of scale it up right like a more blunt roadmap a more blunt kind of go to market execution strategy regardless I think that now we're entering this moment where like every certainly every software product in my opinion has to be refounded because 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 UX patterns to be invented to fully capitalize on those capabilities and so to be continuously relevant and how to refine product market fit in this era I think you have to be of the details there is no looking at it from 10,000 foot view and saying oh we're just gonna throw a bunch of people at this problem it's actually understanding like what is the right product experience and the right business model that backs it up and the right everything else to support that engine to take advantage of the capabilities in our product domain you have

Lenny Rachitsky:This phrase somewhere where you talk about being the chief taste maker yeah and to do that have to do exactly what you're describing

Howie Liu: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 at least some part of creating the soup meeting with AI you can kind of look at the final product and say okay this feels right or not or 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 you know 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 a chat interface you're really pushing them to the boundaries because that's the only way that you really understand what these new ingredients it's like as a chef you just gained access to like amazing new ingredients but you have to like actually kinda get comfortable with them to put them into a new dish

Lenny Rachitsky:And we had Dan Shipper on the podcast he runs the newsletter and podcast to provide a company called Every and they work with companies to help them become more AI successful and adopt AI and all that stuff I asked him 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 I feel like you're describing exactly

Howie Liu:Right hourly literally hourly like or you know could even like have a measure of like inference costs the equivalent underlying inference compute cycles

Lenny Rachitsky:How many tokens they use

Howie Liu: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 extremely intentionally wasteful in the sense of I'll do something that costs like maybe hundreds of dollars of actual inference cost right like for instance doing a lot of LLM calls against like long kind of transcripts of let's say sales calls to extract different types of insights like here's the product apps identified or here's summaries etcetera and we also have now a capability that's basically like an LLM map reduce effectively even if you can't fit like the entire corpus of content into one LLM call because the context window limitations will 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 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 having better insights it's as if 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 very astute product insights marketing insights kind of positioning insights and segmentation insights that's invaluable 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

Lenny Rachitsky:Until somebody tweets how you're eating costing the company so much on on AI compute and you guys are gonna be underwater and I'm pretty just kidding

Howie Liu:It's like how we have personally taken down

Howie Liu:The the cash flow of the business

Lenny Rachitsky:That's right

Lenny Rachitsky:Okay so CEOs founders hearing this they're probably like okay I I I should probably start doing this what does this actually look like I imagine you still have a lot of other stuff you got one on ones you got all these like how do you actually how have you changed your day to day to do this

Howie Liu:Yeah so I actually cut my one on one roster by default and the idea is not that I don't wanna spend time one on one with people but rather that I found that the just like having more standing one on ones actually precludes me from engaging in more timely topics right like I like to think of you know the best types of meetings as like very urgency driven and like you know there's some timely topic like you know you've you've discovered some insight maybe I talked to some new startup right and you know I learned something from from their product or their approach and I wanna bring that into how we're thinking about like a new feature at Airtable or even just like plant the seed with like you know some different like you know EPD people within Airtable like I wanna make most meetings very timely and very informed by like real alpha right there's gotta be some kind of value and insight to seed that with now in addition to that I'll supplement with like you know when I'm in person you know with someone like I wanna carve out time for like a you know a proper like catch up and like less structured less less like timely and just more of like you know building a relationship with a human but I actually find that like you know having that com it's almost a barbell approach where it's like you know if you're gonna spend time with somebody in a free form way like actually doing a high quality not like forced weekly ritual way like go for a longer lunch or coffee walk or whatever in person when you can maybe that's like a once every month or two kinda thing and then like the the in betweens are either topical so we do have standing meetings for you know like now we have a a weekly basically sprint check-in on all of our AI execution stuff which now is like half the company or half the EPD org is working on AI capabilities we're trying to ship very quickly like you know I basically want to always ask the question like how would an AI native company like a Cursor or Windsurf etcetera like how would they execute right and are we executing as fast as them and taking advantage of like all the new stuff as well as them so like bringing that level of like kind of intensity and urgency to like how I spend my time within that's been the main the biggest shift for me

Lenny Rachitsky:What's the change you've made to help the company move faster and match that sort of pace

Howie Liu:Yeah so I mean we did do a reorg of the EP org so before we had we've gone through a few different kind of reorgs over the past call it four years the kind of original state as we just kind of proliferated I think by default or incrementally was that we had a bunch of groups that were each responsible for like a feature or a surface area so there was a group responsible for search within our table and there was a group responsible for like mobile experience and so on and so forth right and that has its benefits obviously like that team can go and get really ramped up on that part of the code base 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 a 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 the functional to GM back etcetera this was more like saying look we have an enterprise business and the MO there is more about scalability can we support the larger scale data sets and use cases do you have the core capabilities needed to be able to push out an app to maybe 10,000 seats or 20,000 seats for product operations so a lot of architecture a lot of scale not gonna 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 pillar basically infra and what we found though with that approach is that there was more kind of holistic bets being made so the teams pillar could think not just about one feature but the overall onboarding experience we're really thinking about nucs in a way that touched multiple parts of the product but it still felt like it wasn't especially as we started to execute more on AI stuff it wasn't allowing us to aggressively and quickly move as a AI native company would right like I mean when you look at the cursors of the world they're shipping like major new stuff every week and like it's not like oh well we have like this separate kind of 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 the what I call like the fast thinking group which officially is called AI platform but it really means like we wanna just ship a bunch of new capabilities on a near weekly basis and each of them should be like truly awesome value right like you should drop your jaw at like how awesome it is to use this new capability in Innertable and then separately have the slow thinking group and that's not meant meant to be like better or worse like it's it's literally like you need fast and slow thinking in the common sense to operate right like as

Lenny Rachitsky:I have that book behind me

Howie Liu:Yeah I love that book but but slow thinking is like it's just a different mode of planning and executing it's more deliberate bets that require more premeditation we can't just ship a new piece of infrastructure that has a lot of data complexity like our data store HyperDB that now can handle multi 100,000,000 record data sets that's not something you ship in a week right in a hacky prototype so we now have these two separate parts of the company and I actually think what's really cool is they actually complement each other very well right because execution the AI stuff you know that creates the top of funnel excitement that that also you know kind of inspires new use cases and new users coming to Airtable including in large enterprise right like you know enterprises can use this stuff too it's not just like a SMB thing but like the slow thinking basically allows those initial seeds of adoption to sprout and grow into much larger deployments whereas I think a lot of the challenge for many of the AI native companies I've seen is that they could have like a very wide top of funnel like get all of this AI tourist traffic you know a lot of interest a lot of like kind of like you know early usage but then you know sometimes the the challenge is how do you like turn that into more durable you know growth and and get each of those adoption seeds to retain and expand over time

Lenny Rachitsky: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 specific archetypes of people that are successful there is it a lot of like bringing in new people that are not just used to the way of working at our table what do you find

Howie Liu:We we have a mix so you know we brought in I mean we're we're always hiring right like there was never a point in the company's life where we stopped hiring that candidly even when we had to do two RIFs right that significantly kind of reduced our headcount we had just like way too quickly grown and overscaled the business at a certain point but even when we did our rifts we were still actively recruiting and hiring in I mean every major department but especially in EPD because 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 rosters day right like we're always gonna need to find new fresh perspectives new skill sets etcetera and so we've continued to hire I think we've learned as we've gone along of like what is the ideal type of hire and we've done some aqua hires and learned from that as well but I think the fast thinking part it really just requires a lot of like somebody who's able to operate with a lot of autonomy right like who's entrepreneurial in nature now it doesn't mean like they have to literally be a former founder I know some companies are like Rippling for instance a lot of actual acquisitions and gets actual founders into the company like we found that's great and we've done some of that as well but also there are some really 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 so tangibly we're doing this new thing that's about to ship where not only can you describe the app you wanna build and then iterate on it with kind of our conversational agent Omni but and it builds it with like the existing Airtable platform capabilities but we're also giving it the ability to actually do codegen to extend those apps with really final mile very bespoke functionality or visuals so you could say like hey generate me a very very specific type of map view with this kind of heat mapping and this kind of icons and when you click it do this and that's a capability that there's so much ambiguity in some of the design decisions around it 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 re prompting 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 you know kind of open endedness but like relishes in it

Lenny Rachitsky:I was actually playing with it before we started chatting I made a really cute startup CRM

Howie Liu:Oh that's awesome

Lenny Rachitsky: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

Howie Liu:I will say like just as a note I consider myself like at my core like a product UX person right like that's my like passion and everything else I've had to learn to kind of run this company is almost like what was a necessary part of the journey but like my real passion is thinking about product UX right and I think of UX in a deeper sense than just like the cosmetic like design like you know what you could put into a Framer you know kind of prototype like I think of it as like literally like what should this product do and how should it represent that and behave for the user that is the product in my opinion right and of course then you have to figure out like technically what's possible and how to implement it but like I think to me what's under executed today in the world of AI products is there's so many awesome capabilities of AI and most of them are really under merchandise and there's very poor actually visual or otherwise metaphors or affordances given to users to help represent or understand what those underlying capabilities are right mean Chatuchiki obviously extremely successful products not knocking it at all but you come in and you just get this completely blank chat box by default and now they have suggestions underneath and so on but 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 and all the richness interaction you create there to better represent or or show all the different things that you can do with you know with with the underlying model right and so that's something we've tried to do with Airtable is like show like all of the different states and like use colors even to play those off

Lenny Rachitsky:It's interesting how much of this connects with I just had Nick Turley on the podcast he's head of ChatGPT at OpenAI and he had these two really interesting insights that resonate directly with what you're describing one is he has this concept of whenever something is being worked on he's always asking is this maximally accelerated how do we move faster is that if this is important what would allow us to move faster yeah and I love that that's one of the themes that's coming up as you talk is just this creating this very clear sense of speed and and you even call it the fast thinking team like you are gonna move fast yeah and then the other one is just this insight that with AI you often don't know what peep what what it can do and what people want to do with it until it's out so there's this need to get it out and that'll tell you what it should be

Howie Liu:I couldn't agree more with both of those particularly on the second point I think it's interesting like clearly there have been companies that have both both been successful in PLG and like kind of more sales led you know kind of distribution for AI products like you know the the most notable ones I can think of are like Palantir with their AIP deployments like that's obviously very sales led you're not PLG into a Palantir deployment but even you know like companies like Harvey and and and so on like you know they're doing very well and like it's primarily from what I understand like sales led right you're not self serving into a Harvey instance at a law firm and yet to me the best way to get AI value out there is experientially so you can kind of get that in a sales motion you can show a demo maybe you can 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 a real proof point that like ChatGPT is arguably like the most successful kind of PLG product of all time right just in terms of like sheer scale of users like they announced 700,000,000 like MAUs or I

Lenny Rachitsky:Think it's weekly weekly active users 10% of humans on earth use it weekly

Howie Liu:That's insane in like how many years right like a few years three. Yeah and so like I mean literally that is just like the most insane ramp curve and I don't think they would've gotten there if like you couldn't just come in and literally try the product out and 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 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 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 hard question really well but like clearly the magical like you know kind of nature of it still appeal to you enough you like you you everybody used it and so I think you know I I do have a view like we've gone through that whole you know kind of arc of we started PLG I'd like to think Airtable was one of the the kind of PLG darlings of of our era and you know it kinda started moving up market and like 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 me personally one of my goals is to shift my attention back into that you know builder led adoption and like literally showing in the product experientially not telling in like a deck the value that you can get from from AI and Airtable right like I think that's so key and it's it's you know it's NUX but it's also more than that it's not just like literally how do you onboard somebody into the product it's like literally thinking about the entire product experience itself right and in our case like we just like made the entire product experience AI centric right it used to be that we had kind of this 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 it's like now the Airtable app as you know it is almost like an artifact that's manipulated by you know and and kind of like can be tool used by the agent.

Lenny Rachitsky: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 wanna build thoughts on that as just like a thing everyone's starting to do is there what do you think comes next is this does is it working well.

Howie Liu:There's clearly an incredible magic to vibe coding and app building with AI right and this is actually like a prime illustration in my view of 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 you know kind of era models were were not nearly as smart as the current models right and so like you couldn't really ask it to one shot a more complicated chunk of code or or certainly not like a full stack app and expect it to work and so the right form factor for leveraging those models in a software creation context was GitHub Copilot right it's like autocomplete a few lines of code at a time right but you know you you couldn't chat to it and tell it like build me this entire app from scratch right and I think that like as the models got better and better you saw that the new form factors emerge like I think Cursor did a great job of like being an early pioneer of this more agentic way of leveraging the models to to do more complex things and generate more kind of larger chunks of code now with Composer you can literally just go into Cursor and build an app from scratch like build me a three D shooter game from scratch and just watch it go and 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 strongly believe that the number of people who use apps far outweighs the number of people who can actually build their own or manipulate apps and harness custom software to their advantage.

Lenny Rachitsky:That sounds very familiar very familiar these days.

Howie Liu:Yeah exactly and so I think this is like it's a different means to the same end and so 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 that we have and like I do think you have to be realistic to yourself especially as as a as a company that predates GenAI and now has to kinda find your new footing in the AI landscape like can't fool yourself and just say okay I'm gonna throw in some AI stuff on the landing on the marketing site you know put in a couple AI features and call it a day like I think you actually have to take a clean slate approach to saying 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. 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 like I don't think the answer is always yes or no I think it just depends on the product and if you can't really introspect and say like look I think I'm better off doing this with the pieces that I have for my existing business and product then I think you should sell right like you should find a buyer for that company and then go and and like you know if you really care about this mission like go and start the next carnation of it right in my case like I I I really you know thought about this and like really feel strongly that the building blocks that we have like these no code components actually do allow us to execute better on this vision than if I had to start from scratch right meaning like the problem with vibe coding especially for building business apps so I should clarify that like we wanna democratize software creation but specifically we are focused on business apps we're not trying to be the platform where you create like a cool viral consumer game this is for like your CRM or if you wanna build an inventory management system as a small restaurant or a lawyer trying to build like a case management system 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 gonna be very unreliable there's gonna be bugs there's gonna be data and security issues and then you're also gonna have a context collapse as it just cannot manage all of the code that it's written basically as the app gets more and more complex right and what we actually have are basically these primitives that the agent can manipulate and use without having to literally write the code from scratch to represent 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 a layout right or automations and business logic and so it's almost like in programming terms the Airtable pieces in our Lego kit today can be used by this agent as almost like a more expressive DSL like a domain specific language to build business apps instead of literally having to write everything down to like the SQL and HTML and JavaScript to build every part of that app from scratch and so like if we can combine the best of both worlds like we have these very reliable high quality Lego pieces now an agent can go and like assemble them for you instead of you just using the GUI to do that and by the way if you do wanna fall back to the GUI there's a really great you know kind of way for the nontechnical user to still understand and participate in what's going on whereas if you're not technical you can't inspect the code underneath a V zero or Lovable or Revlon app right like it's just kind of opaque to you and if you can't re prompt it to get what you want you're kind of stuck you know this is much more akin to like a developer using Cursor can generate lots of code but then can still drop back to the IDE to edit and manipulate it to the final production ready state so that's the play that we're making and if I didn't fully and truly believe you know we have a better shot at doing it with our existing product like I wouldn't be running this company in its forum today.

Lenny Rachitsky: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 wow we gotta figure out something that works that could work even better and so I'm trying to pull out the threads that are consistently working across these journeys because I think a lot of companies are trying to figure this out so one that you just touched on is just if you were to start today what would you do like what would that business be plus 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 creating a sense of urgency and pace and getting people to understand this is how things move in AI and we need to create this fast thinking team I love that metaphor and framing and then there's the point you made about just talking to AI regularly as the founder an important element to truly be this ICO talking to AI working with AI regularly just on that note little bit more just to give people a sense of what this looks like day to day so you're talking to Omni all day trying to flex the power of what you can do and iterate on it is there anything else you're doing day to day that helps you figure out what to do for the business.

Howie Liu:One I try to use as many different AI products including not Airtable right like as I can and both literally for the novelty factor and just you know some new cool demo comes out like Runway released their like immersive world you know kinda engine right and so and I'm gonna go try it out when Sesame AI put out their cool interactive voice chat demo I tried that out because even though we don't have a direct and near term like you know kind of need for like really realistic and and interruptible like kind of voice mode where it's not as core to our capabilities like I just wanna understand and and like get a feel for everything that's out there right and I try to invent little like kind of almost like side projects of my own to have a real reason to use these products oh cool. A what if I were to like try to create like a funny little like you know like a short a funny video short right using a combination of like hey gen 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.

Lenny Rachitsky:Little did you actually do this.

Howie Liu:Is there something yeah like that's literally an example of something like just you know a fun weekend project like to be honest like these things only take you like an hour right if you become kind of pretty proficient with using the products like they're all so easy to use like you can literally do the deep research thing you know kickoff query make a coffee come back in twenty minutes okay like let me let me prompt it to generate me some dialogue it's 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 an HeyGen avatar and then download the video and and like play it right like and just for fun right I'm not like trying to make make that into an actual like you know kind of YouTube like video business but but I think like coming up with like these different like fun weekend projects is a really useful construct to like force myself to actually try these products in a more than just like a twitch click way and what it gives me is like a like it's not just understanding the models which is also very very important right like GDF5 came out yesterday like playing around with it a bunch just on like a variety of different like personal use cases you know but like there's a difference between just understanding the model but then also understanding like the product form factors in which they can be placed right meaning like 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 when you apply it with 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 kinda learn like you know you you really get to inspire yourself on like what are the product form factors that these new models can take so like and and plus by the way like I find it to be really fun like there is a to me like a delight and entertainment value to just using AI period because like a it's it's it's not it's not like perfectly predictable so I think the element of like you're not quite sure what you're gonna get you know it's like a box of chocolates you know and and b like it always blows my mind just to think about like wow like you know five years ago we didn't have any of this stuff right like AI was like okay it's like we can do predictive analytics it's like there's some basically very advanced kind of 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 it's like 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 right 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 of it all and combining this with our point earlier of like a lot this has to be experienced not just like read like you can't just read like the write up on TechCrunch or or you know even a tweet about like a new capability like you kinda have to try it to really get a sense of like what it is.

Lenny Rachitsky:Today's episode is brought to you by Anthropic the team behind Claude I use Claude at least 10 times a day I use it for researching my podcast guests for brainstorming title ideas for both my podcast and my newsletter for getting feedback on my writing and all kinds of stuff just last week I was preparing for an interview with a very fancy guest and I had Claude tell me what are all the questions that other podcast hosts have asked this guest so that I don't ask them these questions how much time do you spend every week trying to synthesize all of your user research insights support tickets sales calls experiment results and competitive intel Claude can handle incredibly complex multi step work you can throw a 100 page strategy document at it and ask it for insights or you can dump all your user research and ask it to find patterns with Claude four and the new integrations including Claude four opus the world's best coding model you get voice conversations advanced research capabilities direct Google workspace integration and now MCP connections to your custom tools and data sources Claude just becomes part of your workflow if you wanna try it out get started at Claude.ai/lenny and using this link you get an incredible 50% off your first three months of the pro plan that's Claude.ai/lenny for people that work for you across Airtable say the product team PMs maybe engineers designers how have you adjusted what you expect of them to help them be successful in this new world.

Howie Liu: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 in the psychological sense of like you know it's there's a difference when like you go in and you're kinda 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 know you're kind of like exploring right and it's both more fun and energizing but also I think like you learn more through that right and so I've really tried to stress the value of play with these AI products and I kind of try to lead by example by literally going and sharing out links or screenshots of the things that I'm doing in these various products so as an example 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 like visuals and everything in there right or like I'll share like you know the actual link to my deep research reports or like instead of me writing a perfect memo on a topic like I'll actually just like prompt my way into getting like a chat thread or a chat output that basically covers all the content that I care about and maybe even like ask it to like okay summarize this all into like a final kind of like memo output and then intentionally share that rather than expose the fact that like I'm using AI in this way and here's literally how I'm prompting it so you can follow along as well but really trying to encourage everyone to like go and just play with these products and I've even said look if anyone wants to just literally block out a day or frankly even a week and like like have the ultimate excuse like you can use like you know you you could say that I told you to do it right like if you wanna cancel all your meetings for like a day or for an entire week and just go play around with every product AI product that you can find that you think could be relevant to Airtable go do it like period so I think that's the most important thing is like this this play this experimentation I think there's also a lot of other kind of shifts in how we execute prototypes over decks I wanna see actual interactive demos because again it's hard to in a deck or in a PRD could say like okay well we're gonna make Omni really good at handling this kind of app building okay those are just words the real proof is in the pudding of like okay let me try it out on a few like realistic prompts that I can imagine and in a demo in a real prototype you can like instantly you know try it out on unrealistic rather than golden pathy scenarios and see how it feels too like does it feel too slow like do we need to expose more of the reasoning or steps kind of that are happening behind the scenes create a progress bar or something like that but like it's really hard to get that feel of the product with anything but like a functional prototype that really does in an open end way you know like use the the AI to to do whatever you know you put in so you know I think it's it's more like a experimentation playground it feels like how we need to execute versus I think in the past it sometimes felt like a more deterministic resourcing timelines view of execution right like we're gonna put this many people on this problem and this is the eight week timeline to this milestone and then we're gonna ship in a quarter from now and like I think now the whole thing is just like a lot more experimentation and iteration driven.

Lenny Rachitsky:Of the different functions on a product team PM engineering design who has had the most success being more productive with these tools and how do you think this will impact each of these three functions over time

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

Lenny Rachitsky:Do you see one of these roles I don't know being more in trouble than others just like you need fewer of these people in the future potentially

Howie Liu:I think overall you can get more done with fewer people and that's not to say like we wanna go and make the team smaller but rather like the really cool thing for us and I think a lot of other companies is it's not like you have a finite set of things you need to do and execute on from a product standpoint and okay now I can do that with a tenth of people I mean you could do that in a lot of cases but for us maybe it's also because we're a very meta product right like we are the app platform with which you can build now any AI app with AI right the apps themselves leverage AI capabilities at runtime whether it's to generate imagery for a creative production workflow or you know kind of leveraging deep research or AI based like you know kind of crawling of the web to search for companies that match a certain criteria for your deal flow app right or something like that like we can effectively leverage all of these 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 kind of almost infinite set of possible AI capabilities that we could execute on and I'm always telling the team look the great news is 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 kinda walk over 20 feet and pick it up instead of having to climb the really tall coconut tree to grab like a hard coconut from like 50 feet up and so like there's so many watermelons on the ground just go out and like start finding the biggest ones and attacking those right and like and what that means is that like if we can build this culture and I do think like it's a learnable way of operating like I I I really like to believe in like the like the growth potential of like any human right like and any individual like I think if you really have a growth mindset 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

Lenny Rachitsky:And I think then what

Howie Liu:We get is a team that can just go and work on more things in a much more leveraged and fast way so I like to think like you know people who are willing to jump on the train are just gonna become more and more effective and it's not like oh like as a PM my role is becoming entirely irrelevant right like no it means that as a PM you need to start looking more like a hybrid PM prototyper who has some good design sensibilities and by the way like I think some of the best NG PM and design cultures respectively over the past even few decades have always been multidisciplinary in nature right like the original PM spec at Google required the PMs to actually be somewhat technical so they could understand the engineering kind of limitations of the product designs they wanted to make they had to be kind of design y right like I remember my co founder Andrew when he was in the APM program was always reading books about design even down to visual design and color theory and that kind of thing right and so I think it's just a reminder that designers as well some of the best designers if you're a designer at Apple including hardware designer 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 the DRI isn't always the PM right as is traditionally the case in kind of that triangle it's like sometimes it's actually the engineer who's taking the product lead and saying like this is what we need to build

Lenny Rachitsky:So what I'm hearing is essentially if you want like the trend across product engineering design is each of those functions needs to get good at one of the other functions at least yeah ideally you can do them all but if if you can just do one additional so PM becomes better design and engineer becomes better at product management

Howie Liu:Well would actually go further and say like I to get like decently good at all three like there's just a minimum baseline of like if you're any one of those roles you need to be like minimally good at the other two and then you can go deeper into your own kind of specialty right like you know you could be a designer who's really good at thinking about UX and interaction design and then just like good enough to be dangerous on thinking about like what's technically possible and like what is the product you know kind of you know kind of story around this this feature

Lenny Rachitsky:I love that and to do that one piece of advice that comes up again again in what you're what you've been describing is using use the tools constantly to see what's possible and that will teach you a lot of these things

Howie Liu: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 wanna 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 cherries trying to invent the world's best cher in a vacuum right like you should go and first do a study of like all of the best cherries out there today like go look at an eatons chair sit in it try to examine it to reverse engineer how it was made and just look at the prior art for that type of product that's how I see the go out and play with these products and also I think 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 shares 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 never and at that time that I was in school and then kinda learning about this stuff there wasn't really any good curriculum for UX it's not like there were great you know college classes to learn product UX I mean even CS was like very academic in nature at that time it wasn't applied software engineering like build an app or whatever maybe now at like some of the schools like Stanford MIT they have like actually UX Y type courses but it's 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 wanna build like a Yelp style app with a map view and then also a list view and I want it so that when you pan around in the map for it to automatically update the list view and maybe there's some UX improvements I can make on top of that but I can also like test my technical skills to to figure out like which parts of this are hard to implement and 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

Lenny Rachitsky: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 will be fun to do have like a problem you're solving that forces you to actually do this thing for

Howie Liu: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 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 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 go and analyze a document and like in the future maybe do things like actually generate a prototype of a feature from a PRD or from like a feature idea and I'm telling them like look there's a almost infinite number of things you could superpowers you can give these field agents I'm not gonna tell you which specifically to do now you can ask me to weigh in for sure but you should go and just experiment and prototype a few different versions of like a few different directions we could go what if you prototype what it would look like to have a deep research implementation in field agent so that for any given row of data let's say in your case it's podcast guests you can just click a button or click a button on mass across the entire like every speaker you have lined up to do deep research like powered by chop cheapity'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 the stuff can also be like in your daytime job especially if that daytime job is literally to go and build AI functionality

Lenny Rachitsky:I actually tried to do exactly that the problem I ran into I wonder if it's changed is there's no API for chatGPT deep research yet

Howie Liu:There is now there is now.

Lenny Rachitsky:There is there we go.

Howie Liu:It ends up being and I think they only recently exposed it it ends up being like something on the order of like a dollar plus per research call which

Lenny Rachitsky:What a deal.

Howie Liu:Like mean again exactly I mean some people would say my god that's so expensive and you rack up 50 of those you've cost $50 a month I think it's like well it just saved you like hours of research by human.

Lenny Rachitsky:Not only that I I actually have a researcher that I pay to help give me background on guests that was like 4 or $500 and the dollar sounds great and I I've been doing this manually.

Howie Liu:You'd be smart you'd be using deep research and then just collected the

Lenny Rachitsky:They might just be oh man okay there's one more skill I wanted to talk about real quick this comes up a lot in these conversations is evals okay the power of getting good at evals I know that's something you value highly talk about just why you think this is something people need to get good at.

Howie Liu:Yeah I mean and I listened to your episodes with and Mike who talk about this I think it's like interesting that like like both heads of OpenAI and Anthropic have converged on this point I mean look I think I would add like a slightly different or additive take though which is like I think for a completely novel product experience or form factor you should actually not start 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 like does this even work in kind of like a broad sense so as an example for our custom code generation capability instead of defining evals that get repeatably tested you know as you vary like the prompt or the model or like the the agentic workflow used to generate the these outputs and you have to define like you know what does good look like right by definition for the eval like I would first start with a much more open ended and like ad hoc style of like just throw stuff against the wall like try different props and see how well it does and to me evals are more useful a once you've converged on the kind of like basic scaffold of the form factor and you kind of know what are the use cases you want it to work well for and what you want to test against it whereas in the early days especially if your product market fit finding either for an entirely new company or for a new a pretty dramatically new or bold new capability that doesn't really have it's not an incremental improvement on something that exists in Airtable today I think you have to just be a little bit more creative initially and throwing stuff at it seeing what works to understand okay let's use an example we're implementing this new capability that can use basically a long running AI crawler agent that goes and researches the web for a specific type of object or entity 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 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 right ever made find me every like you know kind of DC comics like spin off right like series right literally anything you have to go in and first just try out a bunch of random use your own brain to think of what are all the what's the range of use cases I can test this against and then you get back some results and you're like okay well it's clear that where it does really well are these types of searches right people and companies with this kind of parameter and I think to me evals are useful once you have a sense of what is that cluster of useful use cases you can start then more programmatically measuring the changes that you're making to improve the output for that but by that point you've probably already scoped the product and maybe the way we would merchandise it in Airtable is not a completely open ended capability but hey here's a specific capability that can research one of these x number of entity types including people and companies and here's even like the filter conditions or criteria that are more explicit that you can define to give it the prompting to search for that thing right 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 like empirically right you can ab test especially if you have the scale of a really large product like Anthropic or OpenAI you can like just test everything and see like oh this model actually performs better than this one this prop performs better than this one but I think early on like you don't have that luxury and you're in a much more open ended discovery process.

Lenny Rachitsky:That is very wise evals could constrain you too early I think about just the double diamond I don't know IDO kind of framework of like be divergent first and then converge and then maybe this yeah the last.

Howie Liu:Exactly I hadn't heard that before but that completely resonates.

Lenny Rachitsky: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 then there's also a piece of get stuff out so that you can learn how people use it and what it's capable of versus polishing it endlessly forcing people almost I don't know forcing is the right word but encouraging people to play with the latest stuff and like giving them chance to take days off to block out calendars cancel meetings just like stay on top of the stuff yeah to play as you talked about it and then sharing things they've learned get the vibes of what's possible there's also this idea of just rethink okay if we were to start today in this world what would we do to achieve the same mission we have achieved we are trying to achieve and ideally it leverages this unfair advantage we have with things we've been working on for a long time and then there's just like talk to AI constantly every hour yeah multiple times an hour multiple times an hour yeah it's going up is there anything else that I missed there that you're like this is you need to do this to to be really to have a chance.

Howie Liu:I think just to really really try to break down role silos like and I think that's true certainly for EPD in the typical like you know EPD triangle but I also think it's probably true even for like non product roles right like I think it's true in marketing right like I'm seeing something I'm really pushing for in marketing I think our marketing team is like really leaning into actually is like if you can just do all of the thing yourself like traditionally how a marketing team might operate is like okay 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 tweaking the parameters of targeting and budget and kind of conversion tracking etcetera and then somebody else is actually responsible for coming up with the specific ad copy and somebody else yet was responsible for coming up with the seed content or positioning guide written by a PMM that feeds into the ad creative and so on and so forth maybe they're promoting some new demo asset right that somebody else created and I just think that like you know in the same way that you can collapse the roles in EPD and like the ideal person maybe they're very specially you know specialized and deep in one dimension like engineering but they're well rounded enough to kind of like be dangerous on the other two like I think that's kinda true in almost every other function right like you know like sales as well like I think you should start to be able to play more of an SE role like traditionally salespeople didn't necessarily know the product that well and like kind of relied on the SE to come in and be the product experts like I think it's really hard to sell any kind of 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 that concept of like collapsing roles everybody needs to like become more full stack to do the being more outcome oriented right 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 you used to have dependencies on having assets created by marketing and an SE to help you demo can you collapse more of those dependencies so that if you had to you could do it all yourself right and I just think that's a new way like it's a new operating mentality overall for every AI native company or company that wants to compete in this new arena.

Lenny Rachitsky:That is a great addition it almost feels like you go back to startup times when everyone's doing a bunch of stuff there's no like here's the head of product here's the head of engineers we're just doing stuff totally needs to be done totally yeah i'm kind of seeing it as this is like upside down t where there's like the thing you're really strong at and then you just have to as you describe the minimum of being good at engineering design or an se by the way sales engineering imagine is what that stands for that you just like they're adjacent roles 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 company building teams that maybe goes against common startup wisdom i heard

Howie Liu:Your interview with with brian chesky and then later you talked about founder mode in in that kind of yc retreat and the points there really really resonated with me you know and i i feel like maybe less eloquently kind of like deduced you know some of the same principles just in my own experience which is like i think when you're scaling up and this relates also to what we talked about before around like the early days of building a company you're like in the details you're finding product market fit you kind of have to be like you know pretty versatile right like you know all these decisions from a technical standpoint to design to even commercial and like what's the freemium model gonna be like and like you know how are we gonna market this product what does the website look like like they're all very intertwined right you can't like compartmentalize and then like you know almost like factory produce you know kinda each of these things separately like you they're all intertwined right and you have a very small tight knit meme that's like a tight knit team that's thinking full stack about all of this combined and 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 it's kind of like going from a bespoke artisanal one person made an entire item of clothing to we gotta factory produce this thing and what that means in a organizational context is you then create these different fiefdoms you hire all these execs and each exec just manages their own swim lane and there's relatively looser coupling between all of those different groups so then you've got sales of executing on its own thing marketing is executing on its own thing products 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 purely scale up 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 gonna go and ship ship ship more stuff to improve search and so it's not completely crazy 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 in a company that is really serious about product first of all i really liked his point about the ceo has to play a cpo role you have to care about the product ultimately the product is the thing and you can't just coast on scaling up go to market around the product forever 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 service 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 refinding new product market fit on a regular basis i think it necessitates a completely different operating and leadership model throughout the organization and all of the stuff we just talked about in terms of how to operate in the ai native era i think it's actually exactly the same as how you need to operate in this constant product market refinding a fit state so i could not agree more with that concept of you gotta think ambitiously and move the organization holistically towards these bigger outcomes but also ship and learn and experiment a lot more in this era and then maybe the meta learning i had from all of the above is that the specific advice obviously was like okay go scale up in this way or go hire these types of people experience operators etcetera obviously there's some truth to that right the people giving this advice are not incompetent you know they they had some reason for giving it and in certain context it that is the right thing to do but i think like my meta learning is you know it's it's not enough to just like trust the recommendation like here's the action you should take a lot of people because everybody has different priors and it's almost like we're all our own llms right and like we all have different training from a different corpus of data informed by our own experiences and maybe you're trained on like the like you know kinda servicenow or the you know kind of a oracle you know kind of you know training corpus right and you know this person's trained on the facebook corpus and i'm trained on like you know the airtable one right and i think what i've tried to do more and more is like not to just like ignore advice from smart people like obviously that's not the right answer but like to kinda take their it's almost like in an llm you can now like with the reasoning model like actually inspect the chain of thought right and see how it's thinking why did it come up with this answer right and to me that chain of thought why did you recommend this is actually more informative than the actual just do this recommendation right so the answer might be like hey like at so and so company this is how we eliminated the pm role entirely right for for brian like at airbnb like made sense like we're no longer having pms in their traditional form now we have program managers and product marketers and but like more than the actual decision because i don't think it's a one size fits all like everybody should do the same why did you do that right and the why actually was very informative and then be able to take that and say like okay like how would i apply that and maybe it yields a different outcome but the reasoning actually is very informative

Lenny Rachitsky: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 for yeah it's like being in the weeds being in the details trying things yourself not delegating to execs

Howie Liu:Yeah and like i think anything taken to an extreme can be problematic right so like there is a world where like you know you are so in the details and in every detail that you're basically just micromanaging and you're you're you're kinda creating like you know kind of euphemism for that and that's not really what founder mode is about right like that's not like the the brian conception of founder mode so like micromanage everything and like not trust anyone but i think it's more about like finding that right balance of being unabashed about caring about the details that do matter and where the tying together of details across different groups or departments actually is the only way to yield a non incremental outcome because otherwise each person is just optimizing within their own domain right but you'll never get to the global maxima or the global breakthrough and i think like the really cool thing about ceos as ics and frankly any leader playing more of an ic like role being in the details is i think for the right type of person it's actually more fun that way to be honest for me the times where i felt most disintermediated from what i felt was the substance of this company was when i thought that was almost forcing myself to step away from the details because i thought that's what a atscale ceo was supposed to do there's some famous ceos who have talked about the less decisions i could make the better the less details i'm exposed to the better i just wanna inspect at the topmost layer how this business is running and if everything underneath it is going smoothly then i'm able to do that 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 even then though like i can't imagine that like at a cpg company like in procter and gamble you wouldn't want to have a ceo who still actually goes and tastes the soup and 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 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 i think for the types of operators and leaders that i most admire like it's it's like that's what makes the job interesting like they don't wanna have a automated away you know kind of role as a leader

Lenny Rachitsky: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

Howie Liu:Don't step away from the details that both you love like i mean first of all like if your passion is building product and product design even if it feels like at times the company needs to do all this other stuff like scale up go to market and operations and just have a large people organization that itself creates a lot of you know kind of you know need to to do things and manage and like there there there becomes a new job invented just to like manage a larger group of people right and obviously you're gonna have to do some of that you can't just completely askew all your responsibility as like a atscale ceo but like don't lose the like the essence of like the thing that you love doing and that really made this product happen and gives this company as many companies that were founded on kind of a magical product market finding insight don't like step too far away from that right and always make sure that is still your like number one even if like other stuff has to also add to your plate

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

Howie Liu:I think that's so true and to me that's why there's always been a difference between entrepreneurs who love the act of building a product or the business too versus those who saw just purely business or financial opportunity that they felt like they couldn't pass up exploiting or going after and look no knock on people who are more of the latter and there's entire industries where it's all just about alpha generation you can go into private equity business and so on it's just purely it's rationally about how do i find the alpha and i think that some of the best companies product central 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 like i think genuinely just loves like working on ai right like if you could spend a 100% of his time on like just being close to the ai and the research i mean he won and he's even said as much right like you know but but ranging to like the bryans with airbnb like like it's pretty clear you know that you know people like this are not motivated like airbnb was not founded because like oh my god we we wanna make a lot of money off this like arbitrage opportunity against hotels they just needed to pay their rent yeah well that that and like i think they loved the the product and i think 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 and that's what gives you like the continued joy of of working on you know what could be the same company for a very long time

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

Howie Liu:I just wanna reiterate you know especially for for listeners here who who are in you know an ep or d role and especially in the p role you know i really do believe that this is not a you either have or you don't like in terms of the skill set needed to be relevant and ai needed but i do think it's a call to action to go and bolster your skill sets where they may be less refined right now right think everyone like even programming i really believe like everyone could learn how to be a software engineer if they wanted to now like obviously like some people just as with like great writers are never gonna be like 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 that boot camp you could do like some like coding kind of exercises on on the side etcetera and the point there is that like you know sometimes i think we treat these disciplines like you know hard hard skills that like if you're not already if you're already halfway into your career and you're not already an engineer 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 like the only thing stopping you is like just going out and doing it

Lenny Rachitsky: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 are super intelligences that you can talk to that do a lot like as they're building can help you learn

Howie Liu:I mean like i literally i mean i go into chat sometimes and i ask it just like hey how would you build this app i'm just curious i'm like how would you build manus right like the agent open ended agent bot literally how would you build it you can ask me 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 20 fourseven 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 to your point when i think back to the earliest era that i experienced of building apps first i learned c plus plus then i learned php and javascript and even building javascript single page apps in the early days like 'eight through 2010 it was a dark dark art i mean there were some you just had to go and learn some of these things there wasn't great tutorials for it 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 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

Lenny Rachitsky:You remember spacer.gif

Howie Liu:I remember

Lenny Rachitsky:Yeah invisible one pixel thing that you just stick in places yeah no I don't oh my god what a time to be alive Howie with that we've reached our very exciting lightning round I've got five questions for you are you ready yes here here we go what are two or three books you find yourself recommending most to other people I've been trying

Howie Liu:To read fiction more partly because I think it's just a really nice mental reset I will say like Three Body Problem like for anyone who hasn't read it it's a mind expanding book I like sci fi and fiction that kind of opens your brain so this is my cheat card but you know it's a three book series those are those are three great books

Lenny Rachitsky:I love that series and my tip there is it gets good one and a half books in is my tip so just keep reading that's where it's like whole cake and how I'm

Howie Liu:I liked even the first one okay but I do like it I felt like it was like inception where every book every subsequent book was like you dropped into another like you you incepted into like another layer right

Lenny Rachitsky:Awesome okay what's a favorite recent movie or TV show you've really enjoyed

Howie Liu:TV show I just started watching The Studio the it's like the Seth Rogen Rogen Rogen

Lenny Rachitsky:So stressful

Howie Liu:Yeah it is very stressful and you know I I just kinda let I mean Silicon Valley was too close to home you know it came out so like I watched it but it was like just cringey The Studio is kinda fun to watch because like it's it's it's a little bit about like inside baseball of of Hollywood and yet like I'm not in Hollywood so it's like entertaining to watch and it's just you know it's it's a I thought smart and funny show and you know because I split time between LA and SF like I also feel like it's it's very real to me I see a lot of the like literal characters out there in the world that that it's characterizing

Lenny Rachitsky:Do you have a favorite product you recently discovered they really love could be an app could be gadget could be a clothing

Howie Liu:So okay so I'll give two because I feel like I have to say some kind of software product right I mean I'm a really big fan of Runway the product and the company I just think like every like new model they come out with they just came out with with a new one just I think like two days ago that gives even more like controls and refinement on like creating exactly the video scene that you want and so like I think just the photorealism in in what you can generate now and like they also built this like cool demo thing that's like an immersive world generator I mentioned before like I think it's just cool to see I also like the underdog story I'm like clearly like Google's gunning gunning in space has VO three and so on and like you know as is OpenAI but like I love the underdog story of this like sub 100 person company still punching above their weight and building like really awesome you know video experiences right so that's the software one and then a very very kinda nerdy real world answer on product is I kinda just recently got into like this whole cottage industry of artisanally produced you know basically clothing you know by like small scale like Japanese manufacturers that use like like literally like 100 year old looms to to make clothes like the old fashioned way like you know or or the old fashioned industrial way right like they have these like loop wheeler machines and they spin the the cloth in like a very slow pace so it's completely impractical from like a production scale standpoint but you know I just like I've gotten like some of these T shirts and they like I just love the no I guess ed you know in a world where it feels like everything is becoming so much faster moving and like you know even tech from five years ago is obsolete like I love a little bit of the throwback to like you know old things sometimes can be even more cherishable in this new era right so like maybe that makes me a hipster but like I I love the you know the the vintage the retro increasingly these days

Lenny Rachitsky:I feel like anything that starts with artisanal small batch Japanese is gonna be really good stuff is there is there a brand you wanna share that is that or is this like because you wanna keep it yeah on the radar

Howie Liu:Actually so Self Edge which actually has a a storefront like main storefront is on Valencia Street in SF they carry a lot of these items of kind of like that's kind of their whole mo and they have like jeans and like T shirts so I've gotten a lot I mean they they basically curate a really good selection of different actual makers like one of them is called Studio Dartizan another one's called actually it's cool there's this company called I think the 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 postwar brand that was kinda like Hanes like one of the like big like four or five like you know kind of menswear like you know kind of undershirts and athletic wear brands called Whitesville I don't know where the name came from but you know it it it basically it's a bunch of like basic clothing like T shirts etcetera and and they this Japanese indie company Mitsui bought the like defunct you know basically name you know and and now like is reproducing clothes almost made to the exact shape and stack and even with like the exact recreation of like the graphic packaging on these tees but like you know today right so I just think there's something really funny and ironic about like you know they've taken like an American postwar aesthetic and literal brand but like it's actually like a indie you know a small scale Japanese manufacturing approach to to to making those clothes

Lenny Rachitsky:I feel like we just tapped into what could be a whole other podcast conversation about clothing and craftsmanship but let's I'm gonna pull us out of that the the next

Howie Liu:Podcast franchise

Lenny Rachitsky:Or just Howie and Lenny talking about clothing.

Howie Liu:Sure.

Lenny Rachitsky:Okay two more questions do you have a life motto that you often find useful in working your life share with friends or family?

Howie Liu:I stumbled on this guy Paul Conte who I think he's an MD but also like a psychologist and he has a book but also like he did this long form podcast with Andrew Huberman and he actually ends up talking a lot about like just how to think about like your life outlook and kind of your framework for thinking about life but grounded in a kind of like scientific and kind of neurological and cognitive science basis and you know I found one particular point really really powerful it stuck with me which is like you know if you live your life in a way that's you know foundationally built around humility and gratitude right and and look like you know everybody has different circumstances like you know I think like I fully own that like you know even though you know I didn't come for money like my family was was very very financially modest like growing up like I still had an incredible resources and opportunities afforded to me even just by virtue of growing up in the US where I'd be born in and growing up in the US like you know but also like having access to a computer and the internet and like even all the free resources I could then access and and learn about from there but you know like I I still feel like you know whatever you have or don't have to start with like if you kind of approach the world and and you know kind of the future with a spirit of humility and gratitude rather than I guess the opposite of that you know it just I think I felt like it it makes like it kind of like becomes a self fulfilling prophecy right like you know you're you're you're you're open minded you're kind of grateful and then like more opportunities actually come your way right and maybe it's because of the energy you're putting out into the world and you know and other people and like you're kind of attracting like you know good opportunities and and good people and good things but I know I I think like you know there's a lot of other parts of like his framework but like the one that you know is easiest to remember is just how do I approach each day even if like I'm going through a tough moment and you know maybe we had to like you know I had to fire somebody today or maybe like I got disappointed because we lost a customer deal or something broke or whatever

Howie Liu:But like to still try to look at the entire situation from an overall feeling of humility and gratitude think just really does shift your like it spills over into everything else for that day and maybe even for like the whole lifetime.

Lenny Rachitsky:That super resonates that is really powerful advice that's hard to internalize but important.

Howie Liu:Yeah easily said hard to practice.

Lenny Rachitsky:Where can folks find you what should they know about Airtable and how can listeners be useful to you?

Howie Liu:Okay so I am on Twitter Howie TL I don't post that much but I am a I'm a lurker so I listen and and watch and you can always DM me there you can also email me directly howie@airtable.com anytime if you have ideas feedback etcetera you know on Airtable like just go try it like the whole point is we wanna make this an experiential product right like you know that's why we're we're really leaning into the PLG roots we talked about like the homepage literally says like just start building right now what do you wanna build go like it starts building and so use the product give me feedback and you know if you have ideas of your own and and you wanna rip on them like I I love because my passion is thinking about product and like product UX especially in the AI era if you're working on or inch you know thinking about something interesting in that space and even if it's just purely to riff on a concept that's something I enjoy doing and maybe I get to learn and sharpen my own skill set from so feel free to reach out yeah mean you know tell your friends and family to to try Airtable as well like that's that's the main thing.

Lenny Rachitsky:Sounds like you're looking for people to nerd snipe you and yes Howie thank you so much for being.

Howie Liu:Here awesome.

Lenny Rachitsky:Thank you Lenny this.

Howie Liu:Was fun.

Lenny Rachitsky: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.