Taste is your Moat (Dylan Field of Figma)

30:35So it's not distracting because an idea should be evaluated on some merits. But then I think from there, the actual exploration and making that great, That is a hard design task still. So how do we lower the floor for everyone coming in, but also raise the ceiling, make it so designers can do even more and produce even greater work? I think like, I mean, obviously, you know, it's cliche, like everything is changing, right? But I think there's just like a fundamental shift in both how people perceive software. I think, you know, Sam tweeted, Sam Oman tweeted about the fast fashion era of SaaS, but there's also like a negative connotation to fast fashion.

31:14but i feel like in software it's like man if you can get the software that you need at any moment that's not a cheap thing that's like an expensive thing that is now be made cheap and it's like still high value and i'm curious like how different products are gonna drive that even though it feels like hey i just created this for you very quickly but like there was so much that went into that you know that it's like maybe sometimes undervalued you know so i'm curious If there's something that you think about where, okay, in a way, people should come to Figma and do a lot of work, but maybe in a way, we can kind of help you from all the work you've done in the past, kind of come to the right result much faster in the future.

31:56Well, I think especially in the context of teams where they've done a lot of work in Figma, of course, there are patterns that with that team's consent, you can tap into and figure out how to help improve outputs. but I do have a little skepticism about the like fast fashion interpretation. I just think that there's, uh, where we're currently at at least with the models and, you know, of course we're on this trajectory, whether we're on an S curve or an exponential, or it's an S curve that'll turn into an exponential. I don't know. Maybe you've got a point of view, uh, but I was kind of like, okay, uh, I'm excited for the ride.

32:35And as long as I'm here today, well, my mental model and strategy is just like, your strategy should always be okay. Assume AI models get better and make sure that makes Figma better. As long as I believe that's true, I'm happy. If not, change strategy. That's the algorithm. But wherever you're at, I think that in terms of that interpretation of where models are going, I don't think the world is in a place today where the fast fashion era is here. And I also think that so much of designing software is doing it in a way where many people can use it. Like it's rare, I think, that you've got an individual piece of software that is truly just for you.

33:21I think it's awesome that more people are exploring their ideas and creating software and tools for them. But then the next step, if they want to go further is, okay, how do I make this good for other people too? And in a setting where people are trying to learn software, most people learn it from other people. So now you're in the same place you were before. You had a piece of software, you made it just for you. You decided it actually supplies to other people the problem that you solved. Now you got to have something that is probably consistent enough to actually share with others so they can learn it and it gets adopted.

33:56it. And so I don't know. I think it's like, yes, more people will create software. That's awesome. But also, I'm not sure that software will just be like disposable. And if you look at the way that people work, whether it be with cloud code or cursor or warp or whatever, so much right now is like you said, you need to have some expertise about how software is built. That lets you discretize the tasks, just like you would to an intern. And maybe it goes beyond intern level, but still, I'm not saying, okay, go build Figma and you agent are just going to go figure out all the complexities of Figma.

34:36I think that's just not something I see happening in any near-term future, even as longer-running agents start to occur and we've got better capabilities. that's a long ways out. Now, maybe that's a high bar, but you look at the actual workflows that happen with the very big SaaS applications. Let's consider Workday, for example, or Salesforce. A lot of CIOs would love to go, okay, yeah, I've a Vive code Workday and I just saved my company all this money or whatever. But okay, you actually peek into the hood of a Workday or a Rip Lane. these are very complex pieces of software that have accounted for every edge case that you can run into as you're thinking about your hris and the platform of data that you can tap into and then go build out from there into different workflows and they've done that through you know over in workday's case decades and ripleen's case you know not quite a decade but also a lot of prior knowledge about what needs there are in the market and very intentionally built.

35:46So I'm skeptical that without that knowledge of the workflows that people will encounter, people will actually make something that can scale. I think you run into the same problems that you've run into all along. And then it's a loop. Maybe that loop goes a little faster, but it's not just going to replace. I think that's the bull case for software still being helpful post-AGI, whatever that means because in a way you still need to prompt the UGI and I think you're going to end up having these interfaces that again just like you you're going to help people explore the space in design there's going to be a way for interfaces to like compress the way that information gets passed through the system I think in data analysis you're kind of seeing a lot of the applications kind of going away in a way because the models are like so good at it and it's so natural to do on a conversational level.

36:40But again, sometimes it's like, well, how do you give it the right data? How do you ask for the right type of charts? How do you ask for the right follow-up questions? I think there's a good question of at what point is a software a piece of software, at which point it's just like, again, a latent space guide that just helps you project your interest into the model. Yeah. And it's interesting. It's like, if you look at data analysis, maybe break it up into a few things that have to go right. You need to have, first of all, trust that the right queries are being written in the correct way. And that's a lot of trust, because if you get that wrong, you have a bad, shaky foundation for the rest of your experience.

37:15And there's, okay, what's the next query? I'd probably be more bullish about AI predicting a next query or a follow-up than I am about 100 % rate on the query being constructed correctly. and I think if you were to show people some prompts around here example next queries you might want to run that might spark other ideas they have for follow-up questions that further their analysis but there's also like how do you display the data and the visualization itself yeah there's canonical visualizations we're all used to but I think visualization is fascinating And we've only scraped the surface in terms of how we can visualize data.

37:56I think that especially to get to larger data sets, more complexity, and you're really trying to communicate data to people, that is one of the most interesting design problems out there. Like, how do you communicate how much money in the budget of the federal government is spent where? People have tried so many times. I've never seen something that is clear and actually gives you any sense of scale that you can relate to. And how do you communicate the data inherent in biology to a layman person who hasn't studied biology? Again, people have tried. It's a very hard problem. And maybe you break into sub-problems, but still, there's so much to push on there.

38:42Yeah, exactly. There's almost like the two-way. So like me, how do I communicate to the model what I need? And then there's also the other side, which is like the models have like so much imbued into them that we need to get out of it that we don't quite know how to do. And like one part is like information communication. You know, one part is like once I prompt it, how do I get the response in a way that I really parse? I think, yeah, that just like, I don't know, it's been breaking my brain for the last few months just thinking about what will feel like software, what will feel like a conversation and like i know that obviously open ai you know it's like this big goal of like kind of being your companion and like you have the voice mode and whatnot but at some point you just need something that is beyond component rendered inside a chat interface you know and it's hard to figure out especially when you think about i know you do a lot of angel investing so i'm also curious about how you think about startups and like what kind of products are like now possible that maybe weren't before like what products people should stop pursuing because you think will be a part of the models?

39:43First of all, I'm hesitant to give advice on that because first of all, I think that the idea that all software will, or lots of software will exist in a session with an LLM or any model, I think that's a little overblown. There's so many different ways this could work out, whether it be, you know, kind of a back and forth of the model as an origin of a request, and then you go elsewhere to the models embedded in software, but you still have a destination you go to versus not the model. And we can think of many other ways too. I think that that's maybe a bit of a shaky assumption. And then also I think that people, it's often the case that you've got some space that like a thousand people are starting a thousand companies in, and everyone's going, oh, don't go there.

40:36It's too crowded. But then one person comes up with some really new, clever idea. And it's a totally different take and they propel from there. So I never try to say, don't do something to an entrepreneur because somebody that's listening to this podcast is going to have some insight in some space that both of us think is really dumb to work in, but then there'll be the next like, you know, trillion dollar company. So, and, you know, of course, like whoever that is, you know, let me know. Right. Yeah. Let us be a part of it. let us both know um but but yeah i think uh there is some amount of memetics around like people see other people doing something and they don't follow on and you have to have a unique insight if you're starting a company or working on a product it usually should be something that's unpopular right and this is just cliche advice at this point but like i think there's something deep to internalize there about the kind of contrarian nature.

41:34I'm going more teal language now, but I think he's basically right about this. I mean, as in, if you're investing in something, unless you're just going after momentum, which a lot of people do, but otherwise you need to have some point of view that like a lot of people would just blanket disagree with. And it should be scary to you if you're investing in something and you tell your friend about it and you say, here's my point of view on why this is really cool. And your friend is like, oh yeah, I totally agree. It makes complete sense. That should be a warning sign if you survey people and they're all saying the same thing about that.

42:12Yeah. What have you learned about yourself during the TO fellowship? What are like things that you change about how you approach, yeah, just life, thinking, learning? I think whether it be that interaction with Chris Ola where I look back and go, man, I maybe dismissed that one too soon, and then learned over time, thankfully. Or another example is I think in 2013, there was a Bitcoin hype cycle. Bitcoin went to$1 ,000 or something. And half the Teal Fellows at the time were really excited about Bitcoin. I'm just like, these idiots, how do you short this thing? and that was my default reaction.

42:53And I think that the overall meta lesson that I've learned over, not just the Teal Fellowship, but just being around tech for a while now because I was paying attention even as a kid and was in some commercials that were like for Microsoft and eToys, for example. And so then I'm starting to track like, what's this dot-com bubble? and wait, why am I not getting residual checks anymore? That became, from a monetary standpoint, I'm like, I'm going to read the newspaper. And then working in high school at O 'Reilly Media was a great point to get exposure to some of the starts of cycles, GL Fellowship.

43:32And the middle lesson I think that I've learned is don't look for reasons why things are not going to work. That's important too, but it's not the place to start from. The place to start from is like, what could this be? How big could this be? How important could this be for society? And let yourself imagine, dream. And then go and think about all the ways it's not going to work. So you can mitigate each one. But like, start with the dream. And I think if you start there, it's just a better default position to go from. Yeah, I'm really worried about the X algorithm and what it has done to optimism.

44:10Because it's so easy to get likes just being negative about things. I do think the X one seems to have changed a little bit recently. Yeah, maybe Nikita's in there. Yeah, I'm thankful for that. But yeah, I do think algo feeds reward controversy and B negative is a way to get controversy. But also, I don't know, I'm default optimistic. I feel like society just builds antibodies to different things over time. I mean, remember when we were all worried about like, oh my God, everyone's going to be a zombie playing Farmville all day? Like, well, here we are, you know, and some people still play Farmville, but like it's, I don't know anyone that does that, like, you know, all day long.

44:54And most of us kind of forgot about, you know, the social gaming era. So when I drive by the Zynga building, I'm always like, I remember in the days. How do you use X? Because, I mean, you were famously on IPO day, responding to product feedback on X. What's your routine for staying on top of that? Oh, I mean, I try to just like search for Figma a lot and see what people are saying. But also I've like trained my algo feed to show me a lot of stuff that's relevant to Figma. And there were ways, I don't know if they still are as powerful signals with whatever algorithm shifts have happened. But it's like you kind of find out what signals matter, you know, like ironically.

45:37Right. Not interested in this post seems to not do anything, you know, like or bookmark. I'm not sure how much that matters, but copy link. Turns out that really matters as a signal, or at least it did. So, you know, I wasn't always sharing the link, but I'd copy it whenever I saw something. I want a signal boost in my feed. It's like, okay, the more you learn as X for the algo feed, better you can train it, better you can make it useful. And then, you know, I think feedback across any surface, not just social media, but support, sales conversations, conversations in our community. We gather people together and then just talking with folks, research both qualitative and quantitative.

46:11These are extremely useful signals for our team. And I think of intuition as like a hypothesis generator, then you have to test the hypotheses. So using feedback to be part of that test is important. But also I'd always rather give feedback to the Figma team by surfacing the voice of a user rather than being like, I have this point of view. I'd do the latter as well. But the former is my preferred method. And so I'd much rather champion user feedback or a user bug report or a feature request and then dive in with that person than just have it come from me. And the other thing is I'm always looking for those visionary users who are a step ahead of everybody else.

46:58They know just kind of intuitively what is needed. and I think that when you can find them and separate them out, that's signal that is just amazing to get. I remember early days of Figma, there was this one user test that I literally brought a bottle of wine to because Figma is so slow yet at that point. I mean, to complete the user test, I knew it would take hours. So it was kind of a tough one to administer. We went through the bottle of wine during the user test and the person that we were doing the user test with this guy named Payam, who's an amazing designer, then was working at Coursera.

47:40And the next day he followed up with this super long doc. It was eight to 10 pages. And it laid out basically a lot of what ended up being our roadmap. Not like we literally follow the doc, but I look back and compare contrast. And yeah, he's an example of someone who was a visionary user. and for a person like that, there's a lot of people that will give you more local feedback but some people can see the big vision too. And that's always really exciting because it's validation for you and the team about where you should go but also a source of new ideas and insights as well. How did you think about hiring and building the team back then?

48:18Because I remember I was working at a YC company and we were all on Sketch, Kickback. Okay, cool. And we were all on Sketch, right? And so I think a lot of people are maybe like, well, why isn't Figma just going to be like sketch and blah, blah, blah. How did you figure out who are the right people to bring on the mission? Because I think the same thing is happening in AI, which is kind of like the, you know, the meme of what should be built. And then maybe there's like some more missionary people. What were some things that you think people should take on early stage recruiting, especially? Early stage recruiting is so hard.

48:48So first of all, just don't give up. Right. That's my first piece of advice. Second piece of advice is just think long-term. You know, there are folks that I talked with in the first year or two of Figma and they didn't join until like year five, year six. But those relationships, it's amazing how if you're consistent and just spending time together with people you like, how eventually it turns into something that could be they join the company or actually just they're a friend outside the company, but someone that inspires you. And that's great too. But yeah, I think taking the long view is super important.

49:28Of course, you need conversion today. You got to hire. And I think the kind reality of being early stage and having a lot of risk is you have a natural filtering function. Only the true believers are going to get on board. And I'm a fan of just not selling too hard. It's like, make sure people understand what's going to go on and what's going to happen and where you're pushing and what you're going to do. But like, if somebody needs to be sold so hard, it's usually a sign they're not going to stick around. Yeah, I think you have to have a really good process. Best of recruiting advice I got in the early days.

50:09Yeah, I told John Doerr one day that, you know, I was having a lot of problems with recruiting. I wasn't very good at it. He's like, well, do you wake up in the morning and is the first thing you think about recruiting? I'm like, well, no. I'm thinking about coffee. OK, well, then it's mid-morning. Are you thinking about recruiting? I'm like, no. I'm probably thinking about what snack I'm going to have. He's like, OK, it's lunch. Are you thinking about recruiting? I'm like, no, I'm probably thinking about what emails I got to do. OK, it's the last part of the day you're about to go to bed. Are you thinking about recruiting?

50:43I'm like, no, definitely not. I'm tired. uh he's like well just like if you're thinking about recruiting all these moments where you just have a moment uh have a second to pause and you're acting on it then it'll fix itself and the way that i think can manifest as a process is you just basically make a spreadsheet of here's my funnel and you obsessively look at it all the time and go okay like how do i make sure that this funnel keeps going, just like you would with sales. If you're a salesperson, you have to continue to feed the funnel. You have to move people through it. And if you're not doing that, you're not recruiting.

51:24So yeah, you have to be very disciplined, which is something that I have to push myself to. I like to kind of be in the clouds. Definitely like to have coffee. How has that changed now? Now you have a public company that you're on obviously would make. I'm sure you have to build a new team to kind of lead that. How has that changed? And also like, you know, this is a great call for recruiting for engineers listening. What are like the type of people that succeed at Figma today? One thing that's been interesting is that, yes, of course, we've hired amazing researchers who are pushing the boundaries and thinking in a way that's, you know, on its own life cycle in terms of not as tied to, okay, we have an explicit date we're trying to release on because that's just not how research works.

52:08But what I've found is very good engineers who are just more full stack and oriented towards learning new things, they can be quite successful on AI products. There's some reorientation they might need to do. They might need to, of course, learn new skills, just like designers need to learn new skills. But in general, we're looking for smart, high agency people who have product sense, who care about design, who see the world the way that we do and want to learn skills and keep growing and work on hard problems. I think that's the filter that's always been the case for Figma. And if that resonates with people, then yeah, please apply.

52:53One question I have from Zach from Warp was, how do you position Figma making the universe of this prompt to app, prompt to creation? How should people think about how you fit? Do they feel like competitors to you? Does MIG just feel like an extension of the design team? What is the competitor universe for you? It depends on how you define it, right? I think engineers feel much more comfortable in IDE than non-engineers. And as we get to more agentic environments, perhaps that's a different vibe. But still, I think most people feel like an IDE or code code, if they're not engineers, they feel like that's not made for them.

53:37And I think that with the platform we have and the visual metaphor, the opportunity for freeform exploration, ideation on an infinite canvas and being able to try out lots of things and then also see the big picture of what are the different paths I can go down. that is a metaphor that I think works for a lot more people. And in that sense, as we tie Macon even further than just, okay, I can copy a state and put in figment design and tweak it, that's what we launched today. But there's so much further we can go. And the further you go, the more you're able to then, I think, bring more people into this sort of surface.

54:18So in that case, it's just like we're trying to brace against ourselves. I think if you evaluate Make as it launched, we raced towards launch as prompt to code. And not a lot around that, not a lot of integration with the Figma platform. Then sure, there's a million other tools and more coming every day that you can evaluate against. But I don't know if that's the right way for us to think about it. I was listening to the Brett episode he did, and he had this one line that just stuck with me, which is he was talking about, you know, do you want to resell coffee beans as roasted coffee beans? Or do you want to like go make the amazing like special latte?

54:59Obviously, I'm going to make a special latte. You know, everyone does. But like, how can you make something that is unique and plays the needs of designers and does that in a way where we can really bring advantage to people? And I think there's so much we can do there. So many different tiers that are coming that I'm just really excited about. Yeah, nice. I know we don't have too much time left. I want to just talk about some outside of tech. So you always have a CryptoPunk as your Twitter PFP. It's actually a Chainrunner, not a CryptoPunk. See? But it's okay. We'll go through NFT education later.

55:35How do you think about, in the digital world especially, you're going to have this huge divide between scarcity and abundance, right? Like, how do you feel about the future of like these digital collectibles and like communities? And like, yeah, how that fits into the universe of like, hey, you can generate anything at any time. You know, Enzo Ferrari used to say a Ferrari can never be readily available to be desired. I'm curious how you think about the distribution of things people will see on the Internet between the super niche tailored just created for you and like these kind of like iconic cultural properties.

56:09The paradox of digital scarcity is what made me excited about NFTs before they were called NFTs back in 2017, whatever it was. And I think that not everyone has that collector gene, but some do. And for those that do, whoever it is, they're collecting digital items. They're scarce and people will enjoy getting into whatever collector aspect they want there. But I think in general, I've found myself wanting to distance a bit from the NFT space. It's kind of interesting. It actually has some parallels, I think, to AI. I got in it so early. And to that point, it was this niche community on the internet of weird people that thought digital stuff could be scarce and you might want to collect it and pay real money for it.

57:01But it was not expensive. And so anyone, for example, in the States, like, could be part of that. And you really, it was gated more on just, like, do you know about it and do you get the idea of it? And is that idea exciting to you or does it repel you? And then, like, over the next three or four years, it went from this, like, very idealistic, let's think about what the future of creation and digital items and scarcity could be, to get rich quick scams and just sort of this overall vibe of like flipping stuff and trying to make money. And I don't know, it just the whole meta of it changed. And I, that's when I peaced out, you know, I realized at some point I was like, Oh, I get excited about collecting some NFT project because I think it's the art is cool.

57:55I think that the creators are awesome and And there's some intention behind the work that's unique. And then if I talk about it online, the project might do worse. It might attract people to buy it. And folks can, I learned, do scams where they basically pump and dump and create trading behaviors that are no good. And so I stopped talking about things I'm excited about for the NFT space. the parallel that I think is kind of interesting is, you know, you compare AI to that. And it's like, there's been a long era of people that I think are very on mission and thinking about the big picture, the risks, the opportunities, the possibilities.

58:41And that's kind of meeting in this moment, the get rich quick. You know, if you look on YouTube, there's a lot of people making videos about like, okay, how do you use AI to make passive income? And I'm not trying to dismiss that because great, if you can make money using AI, that's great for you. And some people certainly will. But I think there's too much just like do it because it's going to make you some money, energy in the space right now that makes me like a little bit nervous having been through that NFT cycle and seeing where it ended up that has been on you know i own a card store in san carlos so i do like magic the gathering pokemon and there's similar thing happening where like you know there's a lot of speculation just because everything is the gathering like super cool now it is oh fuck yeah well i've been waiting for this moment let's go we'll do we'll do a magic the gathering event draft night i'm down nice we used to have in the early days of figma we used to do draft nights nice yeah what sets were coming out then do you remember i don't remember okay yeah sorry there's a guy named andrew on our team and he wowed me so much with his expansive encyclopedic knowledge imagine the gathering that i was like wait a second like can we move you from support to product education uh and then he killed it at product education because he has just an encyclopedic knowledge effectively.

1:00:08But yeah, it was like basically Magic the Gathering draft night that gave me the confidence and insight of, oh, wow, like these skills are transferable. So that's funny. Magic the Gathering, career opportunity. Exactly. You know, I should go around. I'm going to play in the regional championship for the Americas in November. I should just go around and say, OK, you should go to the regional championship. Yeah. So you're like really hardcore. I think to me, that's like the best way to like disconnect because you have to be so focused on the game. that you're not actually thinking about things. But there's kind of like, obviously, the collectible side, but they're still at the core, like a community.

1:00:42Let's come together at the store, hang out, play games. And I hope that that's what we'll see more out of AI, which is enabling more of these small communities locally to have more entertainment and support themselves in a way that doesn't have to be, oh, is this going to make money? Is this going to be profitable? I think the more you can go from a mode of, Like I go on social media app of choice and mindlessly flip through my algo feed to I'm going and making things. Like that is good. We want to move consumption behavior to creation behavior. And yeah, I think that will happen. I just a little nervous about the Get Rich Quick lives.

1:01:24Right. Yeah. Awesome, Dylan. We'll have you for draft night at the new kernel space. Looking forward to it. But thanks so much for the time. Thank you. Thanks for having me. Thank you.