Full Transcript

Nathan Labenz: (00:00) Hello, and welcome back to the cognitive revolution. Today, my guest is Micha Kaufman, founder and CEO of international freelancing marketplace Fiverr. He's recently launched an interesting new suite of AI products called Fiverr Go, staked out one of the most notable values based positions for how his company intends to use AI to empower human creators, and published what began as an internal company memo meant to wake team members up to the quote unpleasant truth that AI is coming for your jobs. Adding also quote, heck, it's coming for my job too. As fast improving AI capabilities and even faster falling prices enable startups to disrupt all sorts of markets everywhere all at once, Fiverr Go stands out as an attempt not to maximize the value to price ratio for customers, but to empower the freelancers that have powered the Fiverr marketplace over the last 15 years. Today, that means providing freelancers who interestingly, Micha notes are very often eager early adopters of AI tools and actually in some ways much better prepared for the AI era than most salaried employees with custom AI assistance that can help them engage and serve more customers more efficiently, and also personalized image generation and text to speech models that are meant to ensure that the platform's many graphic designers and voice over artists maintain control over and can continue to monetize their own distinctive styles and sounds. For a sense of just how different Fiverr's positioning is from most of what we hear in the AI space today, listen to a bit of the keynote presentation where Micha announced Fiverr Go.

Micha Kaufman: (01:35) If everything you create, the moment you create has zero value because AI sucks it and churns out generative stuff based on you without giving you credit, without giving you the opportunity to gain from it, then my fear is that people's motivation to create is going to drop to zero because there's no value. So why would we create? I think that a future that doesn't motivate people to create could be a very, very dark future. What the Fiverr team has built is truly remarkable. Very few teams in the world can build this. But this doesn't mean we think it's perfect. It will be perfect when you say so. And our commitment is to continue trying until we get it right. We always thought of Fiverr as a movement and every movement needs a reason to exist. Ours is you guys. So we know that you're gonna love them because we're not gonna rest until you do. The idea of the creation model is not to replace you. It's not taking your voice. It's not taking your art. It's not taking your content. It is providing samples for customers to make them feel more confident to make a deal with you. It's a conversion tool. You guys are gonna make more money, not necessarily by working harder, but smarter.

Nathan Labenz: (03:27) Now this is obviously an attempt to position Fiverr for success in the AI age. But as you'll hear in this conversation, it does run much deeper than that. Micha is trying to find a way to continue to motivate individual humans to contribute to the collective project of knowledge and culture building that have advanced to the human condition so spectacularly over the last 500 years. That motivation and sense of contribution, if I understand him correctly, he sees as an intrinsic good that can't fully be substituted for with AI provided abundance. Obviously, it remains to be seen how well this human creator centric model will fare in the broader marketplace. But I really do admire the fact that their approach is motivated by an aspirational sense of how the AI future ideally should be and not simply by a values free economic analysis of what is supposedly inevitable. He's humble enough to admit that he doesn't know if the current approach will work, but as all leaders must in the AI era, he promises to keep iterating as fast as possible in pursuit of an AI human hybrid model that's both successful and sustainable. At a minimum, Micha and team have done something many might have thought impossible. They've launched a suite of AI products that freelance creators don't hate. And with some luck, their example might inspire other platform owners to attempt to defy market pressures and concretize their own dreams for a positive AI future. As always, if you're finding value in the show, we'd appreciate it if you'd share it with friends or write a review. And please don't hesitate to reach out with your feedback. I expect major disruption and intensifying competition, not just in the freelance labor market, but in many parts of the economy and even at the level of international relations. My goal is to help people understand AI on its own terms from as many different perspectives as possible so we can avoid the dystopian scenarios of human disempowerment and instead, with AI's help, live the lives we've always dreamed of.

Part of the way I'm doing that is by speaking at more AI events. Coming up, I'll be at Imagine AI Live in Las Vegas, May, the Adaptive Summit in Sao Paulo, Brazil, August, and the Enterprise Tech Leadership Summit in Las Vegas, September '25.

If you'll be at any of those events, if you're interested in AI strategy, automation, or application development consulting for your organization, or if you've just got suggestions for how the cognitive revolution can be a more positive force in the AI discourse, you are always welcome to reach us via our website, cognitiverevolution.ai, or by DMing me on your favorite social network. For now, I hope you enjoyed this conversation about the future of work and the challenge of building an AI platform on the foundation of core human values with Micha Kaufman, founder and CEO of Fiverr. At a minimum, Micha and team have done something many might have thought impossible. They've launched a suite of AI products that freelance creators don't hate. And with some luck, their example might inspire other platform owners to attempt to defy market pressures and concretize their own dreams for a positive AI future.

Nathan Labenz: (06:34) Micha Kaufman, founder and CEO of Fiverr. Welcome to the cognitive revolution.

Micha Kaufman: (06:38) Thanks for having me, Nathan.

Nathan Labenz: (06:40) This is gonna be, I think, a very interesting conversation. You have, I think, for 15 years, right, been building and leading this marketplace of international kind of bite sized work projects. And I mean, you can of course elaborate and tell us more about all the stuff that goes on in the marketplace, but you find yourself in a very interesting position where, of course, you know, AI is coming for, and I say this too, coming for all of us on some timescale. And so I thought maybe it would be a great place to start. You just put out a, I don't if you intended to publish it originally or not, but a memo to the company that sort of said, okay. Hey, guys. Like, this is the wake up call. If you've been waiting for one, here it is. So I'd love to hear kinda your perspective for starters on this wake up call moment that maybe everybody should be tuning into as AI gets more and more powerful.

Micha Kaufman: (07:35) Yeah. Look. You know, one of the things that I've wrote in my email is that what's going on with AI is really the fact that it's transforming the way all of us work, but it's also redefining the maybe the new norm or the new ground zero from which we need to operate. And what I wrote in the email is what I said is that we need to understand that things that were considered easy tasks will no longer exist. And what was considered hard tasks will be the new easy. And what was considered to be impossible tasks are gonna be the new hard. And therefore, I think that this is creating a new standard where if your entry level at something or if you're mediocre or even if you're average, you have an issue right now. You have an issue. And I think that this is a wake up call for all of us. I said that, you know, AI is coming for all of us. It's coming for me. It's coming for my job. And I think that this forces all of us to adopt this AI first mentality where we force ourselves to learn new technologies, figure out how we can improve our performance. And I think on that sense, what I said is that my expectation from myself and from others is that we're gonna do we're just gonna do more. So we're gonna increase our output per unit of time and our quality as well. And those who are not gonna be able to do it are gonna find themselves out of the industry. It's not, I'm not threatening anyone. I'm not trying to scare people that maybe they're not gonna have a job at Fiverr. I'm not trying to scare our freelancers, which this letter applies to them as well, to say you guys are gonna be out of job in our platform. It's saying you guys are gonna be out of jobs in the industry, which is very worrying. And yesterday, I mean, Shopify, was I mean, we didn't I didn't do this, but they're talking about layoffs of 10%. I think it's gonna be a snowball. I think in many ways what we're seeing right now, and I may be right, I may be wrong, this is just me. But I think that this is this is the equivalent of the .com back in 2000. I mean, it used to be pets.com. It's now pets.ai. It's bullshit over bullshit of endless amount of trivial things that are gonna be with done with AI. You know, 999 companies out of 1000 are not gonna be here that are doing AI because they're doing things that are gonna be interchangeable by other things that are gonna be even cheaper, even faster, even whatever. And the reality is that you need less entry level people and you need more people that know how to increase their capacity and know how to work with technology to do more because the bar is just higher. And I think that this you know, much like the 2000, this could be a snowball effect where you see companies are starting to lay off people. And those people don't have places to go because everybody's firing people, because everybody's trying to figure out how to upgrade their game with technology. I'm not happy about this. It's just I'm calling things for what they are. And I may be wrong on this being the equivalent of the .com, but I don't think I'm wrong on the expectations that we have from ourselves to be able to use these new superpowers, super tools to do to achieve more. And that's why I thought that this was really important to share with the team because I think I believe in radical candor because radical candor comes from care. You tell people the truth because you care about them, because you want to give them the opportunity to figure out to first understand reality and then figure out what to do with it. And I've also included some high level tips of, you know, how people should think about this. But I think that the overarching idea is really to take this AI first approach of like, if if you're still working like it's 2024, you're doing something wrong because it's no longer the case, and it's evolving in a head spinning speed. And those are gonna be you know, someone asked me if I think technology or AI specifically will replace people. They've asked me this about employees. They have asked me this about freelancers. And I said, I don't think it will, but I do think that freelancers that are gonna master AI, right, are going to replace those who don't. That's essentially those are gonna be masters in their skills are going to replace those who are entry level or just, I mean, getting dragged behind.

Nathan Labenz: (13:11) So I think it's really gonna be interesting to unpack this at kind of three levels. I mean, you obviously are leading a public company. You have very high context, high emphasis on judgment, and your role is about kind of you know, correct me if I'm wrong, but typically described as, like, making a few big decisions right, and that's really what matters most. Maybe also, you know, setting a tone and culture at the company. Then you've got a whole full time team that is, like, building the platform, and these would be, you know, by any measure considered to be, like, really good jobs. You know, in The US for the last 10 years plus, it's been sort of the ticket to the American dream is, like, learn to code. You can get a job at a tech company. You know, that'll be stable high income. You know what? We won't have anything to worry about. It'll be great. That's maybe under a bit of threat. And then, of course, you have the, like, actual freelance marketplace itself where presumably the threat is most, like, immediate if only because I wouldn't necessarily say that the freelance jobs are less skilled, but they're definitely lower context, right, in terms of how much information they really have about the client, the situation. You know, it's kind of there's sort of a low context bottleneck, right, that is is sort of assumed in these kind of freelance kind of relatively short engagement marketplaces. Should we work from the from the marketplace up, or should we work from your position down? What do you think is the more interesting trajectory?

Micha Kaufman: (14:45) I don't know. You choose. I mean, my take on this is, look, when I started Fiverr 15 years ago, 2010, freelancing was something that people mostly did in between jobs. It wasn't like a full career. And I think that this has changed in the past 15 years. And now it's a career. It's a lifestyle. It's a very legitimate choice. Some of the most talented people I know decide that this is what they wanna do. The context is an interesting question. But what we've seen from our platform is that a lot of the relationships that gets nurtured over time on the platform remains sometimes over years. And so I think that the context is less of an issue and I think in many ways, freelancers are not more exposed to risk of being displaced by technology. And sometimes in many ways, they're actually ahead of the curve because they don't have anyone to teach them anything. They don't have the safety net of an organization that does career development and all of that. And instead of it, they have a hunger to teach themselves, learn everything as it goes out. They know all the best software, they know all the best tools, all the best practices, all the best techniques. And in many ways, one of the benefits that I think our customers are getting when they work with freelancers is exactly this. You're getting the most up to date, you know, the latest version of a profession. So I wouldn't say that their exposure is higher and plus they've gained the discipline and the know how of how to be very agile, adaptive, and how to reinvent themselves very quickly. If you think about full timers, again, they have this safety net, they have the supporting environment. And in many ways, I think that if they do get displaced, for them getting, you know, getting up from the ground and building themselves is gonna be even mentally harder than freelancers who are used to gaining the next customer on doing the next project, on, you know, learning the next trick. So I'm not sure if the exposure thing is different, but I think it, you know, it finds them in different situation and different environment. And in many ways, I think freelancers are actually quicker to in the case of AI, I mean, I've seen freelancers adapting to AI much faster than our team, which is just a proof point of what I've just said. So in that sense, I think they're a little bit more self educated and they have slightly better control over their time so they can decide to set aside time to learn new things to keep themselves competitive. Anyway, I mean, we can take this from any direction you want. Happy to

Nathan Labenz: (18:09) I think that's a really good context and makes sense, though. I hadn't intuited it myself. But just the fact that sort of freelancers are responsible for outputs, you know, and are getting paid for outputs puts them in a mindset where any tool that comes along, any edge that they can get, any way that they can serve more customers in the same amount of time is going to have a very direct impact on their personal bottom lines, whereas, obviously, in full time jobs that link is often a lot more indirect at best. Right? So I that that does make a lot of sense to me. Let's maybe then do the marketplace level first and then go to your sort of executive level what you're doing and then how you're trying to translate that into the full time team at Fiverr. Maybe just for starters, could you kind of characterize the marketplace? I mean, there's, like, a ton of categories, know, and I browsed around a bunch. But, like, you know, if you if you sort of weighed it toward, like, where is the most activity in the marketplace, who are the buyers, who are the sellers, what are the most common kinds of jobs being done?

Micha Kaufman: (19:15) Sure. So historically, when I started the company, there were very few categories. I think we launched it with about 6, which is now closer to 800 different categories. The overwhelming majority are digital services. We don't do physical services. And most of them are creative. So anything from coding to design to music and audio to data related services to AI related services to marketing services. Really, it's a whole world of we've created this skew system that allows us to create this basically infinite catalog of different services. And actually, so when we started, we started from microservices for micro businesses. This was the beginning tiny services, that are really bite size. And over the years, we've been growing both the supply chain and the types and complexities of projects that we tackle. And with that, the types of customers that we had. So we started from micro businesses, went through SMBs, small, medium sized businesses, all the way to enterprise businesses. I mean, we probably entertain 90% of fortune 500 companies as customers. And actually at the beginning, Fiverr was primarily a marketplace. Right now, it's more than a marketplace. It's a platform where the marketplace is still a substantial portion of our business, but there are also other business tools that creates this whole platform. And so in cases where we run very complex types of projects for our customers, the marketplace is not necessarily the obvious choice. And sometimes it's more about orchestrating multidisciplinary projects through different types of sellers or talent, and sometimes it involves agencies into it. So you can find the simple and very cost effective types of services all the way up to the, you know, million dollar transaction that could last, you know, 6 months, sometimes a year and span through quarters and being managed much more on an enterprise level. I think that, you know, that is exactly what I wanted to do, which means I didn't wanna move Fiverr as a platform from one audience to another. I wanted to extend it from entry level all the way to the most sophisticated types of needs and the cutting edge talent. Obviously, all of it is connected with price, with time, with quality, with all of this. But this is exactly the type of skills and technologies that we've built as a platform over 15 years. Hey. We'll continue our interview in a moment after a word from our sponsors.

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Nathan Labenz: (25:42) So how have you seen AI impacting the activity on the platform? I mean, you could imagine that as we've kind of already alluded to, like, existing service providers can do more, you know, more with less. You could imagine that new people might show up and try to arbitrage the situation even if they personally, like, don't know how to do graphic design or don't know how to do voice over, they could, you know, kinda show up and try to provide it with an AI and maybe not even tell anybody. You can imagine that, like, the mix of types of jobs that are flowing through might change because people are perhaps and we've had this, by the way. I have a company called Waymark, which does video creation for small business. We used to offer a voice over add on service before we had any text to speech that was, like, good enough that it would work. And now, of course, we have the AI text to speech built in, and we have definitely seen a very substantial shift from know, it was always a minority of people that would opt in to the paid voice over service, but the volume of that service has dropped tremendously as people have just kind of found, like, in many cases, the AI is good enough for their need, and it's also instant, has a lot of advantages, included for free. So you can imagine, like, the mix of services might be shifting, or you can imagine all of the above and more. What have you observed in terms of AI impact on the platform so far?

Micha Kaufman: (27:07) You know, it's kind of like asking a captain at mid sea how is he experiencing the storm. I mean, it's ongoing. And I think that what we're seeing right now, like, it's gonna be very hard to make, like, very deterministic judgment statements on the current state of things because it's rapidly evolving. And I think that we're kind of in the eye of the storm, And I think that it's gonna take time to figure out where this is gonna start stabilizing and where you know? And there and we're also preregulation, so it's like it's basically, it's wild wild west right now. And we can talk about this because I think that this is I mean, a lot of it is crazy just because it's breaking constructs of 500 years. Like, it's but there's obviously dynamics that we're seeing, which, by the way, is not new for us. I mean, as I've told you, we started the company 2010, launched with 6 categories. We now have close to 800. It doesn't mean that we didn't have, like, hundreds of them go away, but many, many new hundreds of ones appearing. And so the dynamics of a marketplace that is horizontal, which by the way, is the reason why we can sustain a very successful business, is because we can shift between different categories very, very fast. And what's interesting is we always, as human beings, not necessarily as a company, but as human beings, we always fail to predict what's gonna be the future jobs that are gonna be around. Not even in, like, 5 years, in 6 months, in a year. Like, it was impossible for me to see the explosion around crypto and NFT. Right? NFT burst into our lives. It lasted a year, but this was a crazy year. Everybody was all around this. And then it, you know, it went away and that's fine. I read research in The Economist that was done in 2018, which stated that in 2018, and this was pre modern gen AI LLMs, That 60% of jobs that exist in 2018 didn't exist 50 years ago. 60%. It's mind blowing. I mean, about the, you know, the jobs that sustain over generations, but now it's gonna be even shorter cycles. And so I think that the dynamics, the only thing that changes is the velocity of change. But as long as we as a market base can respond very quickly and the talent in the market can respond very quickly, then this is just ordinary course of business. It's not it's not like, oh, I'm shocking. It's not. It's just the way things are. And it's very you know, people talk about the risk of work being displaced and living in a world without jobs and all of whatever. And I appreciate where this is coming from, and maybe it's right. Like, who knows? I'm not trying to predict. I don't think I'm presumptuous enough to make a, you know, a statement that I think is half right. But the reality, if we look historically, is that every wave of transformation that came from technology eventually created more jobs than it displaced. And there's a lot of research about this. Maybe it's wrong. Maybe I'm wrong. Maybe someone else is wrong. Whatever. I don't know. It's like I'm a captain and mid sea and it's stormy and it's hard. It's hard to see. But if you apply common sense and you apply history and I'm not saying it's the same. I'm not saying it's the same like the industrial revolution or the automation revolution where, you know, people had the fear of humans being displaced and essentially it created more jobs than it displaced. AI is a little bit different in the sense that it is not just producing stuff, it's actually self generating, and it's generating on its own without being being prompted to do. And if it's not doing this enough right now, it's gonna do a lot more of this in the future. And so it's slightly different than previous transformations. But my assumption is whatever technology will go to the place of humans to continue feeding that technology, refining it, developing it, adopting it, applying it, whatever it is, is gonna be such where we just don't imagine what those jobs are gonna be. But here's the news, they're gonna be on Fiverr. That's for sure. Right? And they're gonna be on Fiverr probably first because that's the machine that we've created where we can you know, if there's a new job that was invented a minute ago, you will find it on Fiverr. And then that's kind of how we allow our community to stay relevant.

Nathan Labenz: (32:43) So do you have any I mean, one that I can't resist floating is the AI scout. That's sometimes what I describe myself as, which is just, you know, in a fast moving environment, what is the right tool for the job? What is AI even capable of right now? What's still out of reach? You know, what's the best example of somebody who solved a similar problem? To me, that feels like a job that more and more organizations are gonna need. I kind of do that on a ad hoc freelance basis myself. These days, it feels like more companies will bring it in house, but a lot will probably also need just kind of point solution expertise to kind of scout out a particular problem set. Do you see any of that? And what other new AI jobs are you starting to see flicker onto the platform?

Micha Kaufman: (33:28) Yeah. Look. I think, you know, scouting is one, but you can always claim that you can create an agent to scout for stuff and whatever. So what I do think is that, at least on our space, I think that the future belongs to the hackers. That to me is like, I think that those are gonna be the most resourceful of people. And you know you know one when you see one. It's very easy. Because one, they're naturally born as scouters, which means that they always know what's the latest and greatest. Two, it's not just that, but they took the latest and greatest to its boundaries and then broke it. And they know how to mesh things. They know how to connect different things and make them work together. They always find the use cases that the actual developers of the tech didn't think of, I think that the future belongs to these guys. And like, I have many of them, many of these people on the team and it's like, I mean, these guys are not scared. Like, you know, they're not even concerned. This email wasn't for them. Like they're there already. And so I think in any area, I mean, having this hardcore hacker mentality is gonna be on very high demand. And these are gonna be the people that you pay for and you pay generously. And I don't know. I mean, there's as technology develops, there's mean, not everybody is a scholar. Not everybody is familiar. Not everybody is a prompt engineer or at least a good one. You know, it takes time. It takes time. You need to familiarize yourself with different tools and master them. And so I think that there's a lot of opportunities for people that are like that to provide this service to others. So we're seeing some of that on our platform. We're seeing all kinds of things that related to modeling and training and fine tuning and building specific, you know, gen AI applications for customers and doing all kinds of funky stuff with mobile because it has AI chips on it, and you can potentially you know, I think and maybe we're going way off, but, you know, AI is being commoditized as we speak. Like, it started from like, it went out for free. So like and you can't get cheaper than free. So essentially, what you do is because of scale, you can it's a race to the bottom. It's micro sense for GPU cycles, whatever. That's the that's a very basic technology. But there's incredible applications that you can actually build on top of it, which is gonna be the golden era of AI. I don't know where we are right there. We're not there for sure. I told you it's like the dot AI bubble. I don't know how long it's gonna last, but eventually there's gonna be I'm interested in finding out where the next, like, killer app is gonna happen. Like, if you think about social as an example, you think about Facebook, Meta, or you think about Instagram, you think about, you know, how the high bandwidth of cellular plus the iOS has enabled this entire ecosystem and you say, okay. So this you know, if you take the accumulative worth of apps on the App Store, they worth a lot more than Apple itself. Right? But that's the power of the so Apple is the underlying tech or the, you know, iOS plus cellular network. But, essentially, what's interesting is what's gonna be built on top of it. And we're not we're pre, you know, the WhatsApps, Instagrams, Ubers that were built on top of that tech. And I think that right now, we're in an exploratory mode, and I think a lot of our customers are in that mode, and they need people to help them with a big variety of things. Plus, they do need to continue buying what we call the ordinary services, like graphic design and writing, believe it or not, and marketing and whatever it is. And again, the reason is, and this is something I've been trying to explain to people, is that AI is incredible. No doubt. It's giving all of us superpowers, but all of us. And so it's basically, it's ground zero. We don't have an advantage. Like, Nathan, you don't have an advantage over me or over someone else just because you use AI. Because everybody uses AI. And so it gives oh, you can design yourself? Well, so can I? Like, but what would make your design or mind stand out? What is the competitive advantage? And I think that people go to people in many ways for that. Actually, I can give you a framework of thinking why people go to people with things? And it's very simplistic. But I think it speaks a lot to what we're seeing with AI. So there's probably 3 things, 3 reasons why people go to other people for something. And by the way, it's true today. It was true 15 years ago when we started the company. Even with AI and everything that happened along the way. First reason is arbitrage of time. Right? Can I do something on my own? Sure. Do I need to learn how to do it? Maybe. Do I need to take time to perfect it? Yes. I don't know. Maybe it's 3 hours. Maybe it's 3 days. There's a dude that knows how to give me this in 2 hours and it costs $200. What's my time worth if I spend 2 days? Like, it's a lot more. That's a good arbitrage. Do it for me. That's plain simple. It's easy. So that's the first reason. The second reason is because even if maybe I can do something, maybe I can't, there's one thing for certain. I don't know how to be a master at doing that task. Okay? And I need a competitive edge. Like, need to be I need to be able to produce something that is better than others so I can compete. Right? You want the prettiest girl in school, you want the fanciest car, you wanna fly business, you need an edge. You need to compete. It's a competitive like, I'm not inventing anything. This is human beings. So you go to someone who's actually who has better taste than you, who has better command over the fanciest and best tools. You do it because they they've gained tremendous amount of experience in things that you're not experiencing. So this is number 2. So arbitrage of time and then competitive edge. Number 3 is complexity. It's just maybe I can't, probably maybe I can't, but it's freaking complex. Okay? It needs orchestration. It's multidisciplinary. It's like, it's too many things. And maybe it connects to number 1, it's not worth my time. Maybe it connects to number 2, I'm not good enough at it. But it's complex. It's like it's a and this is why you go to someone who's actually gonna take this out of your hands and just give it to you. These things haven't changed. Maybe the content of what's considered to be complex or easy, maybe the type of specializing that you need to, but it's the same thing, it's the same thing. And these fundamentals haven't changed. Maybe as I've said, the categories of content have changed, maybe the definition of what was easy or what was hard is now easy or whatever, But these are the motivations, and those stayed constant in my view. And what AI has done is just elevated the starting points where no one, none of us has an advantage. Hey. We'll continue our interview in a moment after a word from our sponsors.

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Nathan Labenz: (43:51) Yeah. I sometimes describe AI as a great leveling of know, a lot of different playing fields. One video I would honestly recommend people go and watch is your announcement of the Fiverr Go platform. I thought it was a really interesting positioning where you're introducing a bunch of new AI tools to the marketplace, but also very much centering the existing community that you have and saying, like, we want this to work for you. If it's not working for you, it's not it's not gonna be working for us either. So you've described kind of the the buyer's motivations for why people wanna delegate and hire work done by other people. Tell us about your strategy for bringing AI to bear in service of the community that you have as opposed to what so many others are trying to do, which is create an alternative to working with humans. You're creating a sort of a new way to work with humans.

Micha Kaufman: (44:50) Yeah. So, I mean, to explain my motivation or why we have done it in the first place, I need to get a little bit philosophical. I don't know if you have the Yeah.

Nathan Labenz: (45:01) We've got time.

Micha Kaufman: (45:02) Okay. So here's my take and why I think it's important to have an informed way of thinking about technology and how you use it and the implications that your decisions are gonna have, not just in the immediate term, but also slightly longer term. So what's interesting is if you think, and look. I'm thinking well, obviously, I'm the CEO of a public company, which is very much tied into technological and, you know, trends and developments. And you talk about exposure or people would work to different differences, but I'm also a human being. I'm also a dad. I'm also a creator. And as I was thinking about what's really interesting in how AI burst into our lives, even though we're, as a company, we're using AI for like, 10 years. It wasn't called AI. It was called, you know, machine learning. It was called algorithms, whatever. But what's interesting is this. If you think about the advancements that we've made as a species, right? Homo sapiens have been around for 300000 years. But if you look at the arc of advancement, it started accelerating about 500 years ago. That's it, out of 300000 years. It doesn't mean that we didn't advance as species before that, but it was very gradual and pretty linear. And 500 years ago, it started becoming exponential. And what was triggering this was the revolution of the printing press, the Gutenberg, what was it like 470 years ago or approximately that. And what this allowed is really more widespread access to knowledge, which made people more intelligent. But it also inspired people to think about things that they didn't even imagine they didn't know existed. And this really accelerated how we progress as human beings. And I think the latest manifestations of that is the actual Internet. And if you look at the motivation to share as a way of progress, look at open code, open source code. It's like, it feels almost altruistic, but it's not. People get recognized for it, they get opportunities because of it, and their work is being continued and it evolves over time, which I think is really incredible. And this is how we've progressed. This is how we came up with AI eventually because of this arc, this exponential arc of advancement. But here's the thing. This is because people are motivated to create and share. Okay? The British actually understood that very early on after the invention of the printed press, and they decided to put the copyright act in 1710. And the idea was and this was called the act for the encouragement of learning or whatever. But the idea was that you wanted to motivate people to create and share by actually telling them, okay, great. So if you created something, your name is gonna be buried on like the creation is gonna bury your name forever, for eternity. And so people know that you like, you're special, and you can actually see how you impact others. And you can always you can also commercialize it. You can decide what to do. What's really interesting in what happened with the way AI was designed in past years is that it just eats up everything. You know, everybody ever created, everyone ever created is just getting eaten by AI. It's getting regenerated and just, you know, churned out. But there is no reward. There is no recognition. You know, AI doesn't tell you anything. Who made this? Like and it doesn't give you any compensation. And I'm thinking, alright. Well, okay. That's great. It's a buffet. It's all you can eat. It's amazing. Who cares? Well, you talk to creators and they say, I kind of care. You know? Will I be motivated to continue sharing my creation if this has zero value the moment I just, you know, I publish something and it has no value, it's getting eaten. And this made me concerned, or at least I don't want to have a blind spot on the longer term implications of AI, the way it's designed right now. So what we've done with Fiverr Go and the keynote that you've mentioned, is really to talk about this and say, we to decide because I think that there is a burning question here, which some might say, okay, great, we're going over philosophical. But in my view, the way I'm looking at it, there's one question, and I've alluded to it in the keynote. And I said, there is one important question, and that question is who's in the center? My view, and maybe some people hold a different view, my view is that humans are the center of the universe. And everything else is just I mean, we should preserve our environment, but everything serves us. I mean, we're the center. And as long as we are, like everything else should serve us. And I think that the way AI is designed right now, I'm not sure that this is the case. AI is still not a being. Okay? But over time, it will have its own thoughts, ideas, you know, it's gonna teach itself whatever. And it's gonna be it's gonna be like an entity. Does this entity revolves around us, or do we revolve around that new entity? And if we do, then we're not the center of the universe. It is the center of the universe. And by the way, right now, the way AI is designed is like, we are the product. It's not AI is the product because it's free. So what we're doing is we're training it. We're contributing stuff to make it better. Do we gain in the process? Yeah, you ask a question and you get an answer really quickly. Who gains more? Like who's becoming better? You or it? And my view is, at least let's think about this and figure out if there's other ways of actually doing this. And what we've offered with Go is just a different approach of saying, you know what? We think we love the technology. We think it's incredible. But we wanna give also experiment with giving this technology to our creators and saying instead of, you know, giving away your creation to train this infinite model, train your own model. It is gonna be Nathan's model for creation, and it's gonna have your its corpus is gonna be your world of creation. It's gonna be your body of work. And it's gonna be very, very true to your unique signature and style. And what's interesting about this is for customers, it gives them a very predictable outcome. And for creators, it's your model. You do with it as you please. You get the reward because basically, I mean, sure, the model is doing regeneration, but it's regeneration just based on you. I mean, Michelangelo had, like, 9 or 10 people working in his workshop. It doesn't make his creations less Michelangelo. Like right? So essentially, this is how we experimented with it. And instead of, like, being, you know, being a threat, it becomes your tool to do more to extend your capacity and to, you know, turn one person into a production house, but also give instant gratification for the customers. And the other portion is really to design this super, super powerful personal assistant, which is not just assisting you by interacting with customers and answering the same questions over and over again and, you know, giving offers and getting doing the intake of information and all of this, but it's also a business partner. It allows you to do all kinds of things that you had to manually do, like research on the platform to figure out how to reposition yourself or fine tune your services, your offerings. And this is by the way, this is going completely crazy. I mean, the performance that we're seeing on the personal assistant on Fiverr Go is just mind blowing. Like, this is beyond expectations for such an early product. But this is as I've said in the keynote, this is just a you know, it's an early version of a take on how you can design AI. I don't know if it's the right I'll know it's the right one when our community is gonna, you know, say it is amazing, and we'll get there. It's an iterative process, but at least I think it's a call out to other AI thinkers and designers of maybe we can do it. Maybe we can have a different take on AI. Right now, I think it puts a lot of creative people in a situation where they're confused. They don't know what's you know, and they're discouraged from creating and sharing. And I don't wanna go back to living in a world where people are not sharing freely because they're, you know, because they feel that it's devaluing them.

Nathan Labenz: (55:30) Yeah. I think that I mean, first of all, I applaud you for getting philosophical. I think, you know, more business leaders should be getting philosophical. And for that matter, more business leaders should be, I think, being more candid with their teams about just how big of a deal they perceive this whole thing to be. Because I think a lot of that is sort of, you know, happening at the executive or the board level or whatever, but then it's sort of, well, is it really time to tell the team and we don't wanna scare them, and we don't necessarily feel like we have the right inspirational message yet. So I think personally, society needs more leaders to just get out there and take some shots at various strategies. And as you said, like, is this the final form? Maybe, maybe not. But I think we're all well served when people try something because burying our heads in the sand and denialism is not gonna work for all that much longer.

Micha Kaufman: (56:25) No. I agree. And I think I mean, it's when you think about conception, I mean, there is the way we interact with devices, with different form factors, with technology, with the internet is changing. Look, 2 years ago, up until 2 years ago for 20 years, the internet was Google. That was it. Like, I mean, this was the starting point. I mean, you what do you do? You open a browser and it's Google and it's like the search bar and it's this is how you do it. Right now, if you do a keyword search and get links, what is that? Like, it's like 9 it feels like 1990. It's like who wants to get links and click on stuff? Like, it feels outdated. Right? And there's much more of LLM form, you know, which, by the way, I think is gonna last for a while, but it's gonna be replaced by different forms of interrupting. Like, is texting with AI the best way of the like, I don't know. Maybe not. And this also begs the question, does what we know to be the things that existed forever gonna stay the way they are? I don't know what market base. Like, will we continue going on Amazon and doing a search and seeing 1000000000 results and, like, will we? Like, is this gonna be the experience? Like going in a very ordinary catalog. I don't know the answer, but I'm betting it's gonna be slightly different, if not very different. And so I think that all of us as companies need to challenge the status quo or the conceptions and iterate and be, you know, be very, very quick, have very high velocity of testing. And there's not yet any, like, best practice, like, formulas that like, blueprints that work. But that's also the fun in being an entrepreneur right now. It's a it's a fucking playground. It's amazing. It's amazing. So this gets me like, you've mentioned I'm doing this for 15 years. It doesn't get old. It feels like the like day 1. It's like it is a playground, and I think that this you know, there's obviously, there's threats and concerns, blah blah blah, whatever. But the upside of this, oh my god. It's like, it's incredible.

Nathan Labenz: (59:10) Could you give a little insight into sort of how you picked the initial product suite for Fiverr Go? You've got the assistance, which is sort of, you know, as you said, kind of the customer service agent slash business partner for the freelancers. You've got the models that they can train, which I've seen applies to visual art, like presumably taking a foundation model and fine tuning it or some sort of LoRa technique on the individual creator's previous output and then a similar thing for voice over and music as well. How did you sort of go out and say, okay. There's a, you know, infinite universe of things we could try to bring to the marketplace. You know, which ones actually make the most sense? What was that sort of framework to ultimately reach that launch bundle?

Micha Kaufman: (1:00:02) Yeah. So the personal assistant was pretty obvious, and it's not like, I don't think it's just like customer service or customer care. It's your salesperson. And it allows our creators to actually spend less time doing the things that they like the least. It's like, responding to initial messages and collecting information about the customer. It's not that they don't love their customers, but this is like this is just the intake. This is the filtering. This is like and in answering, I mean, the same questions all over again, the fit to their skills, their availability, how to price things. So it's much more than just being like, you know, attending to customers in a very simplistic way, and it's super powerful. Like, the assistant knows when the freelancer is actually online. So sometimes the assistant would decide on their own to ping the freelancer saying, you know, Nathan, there's a really interesting customer, and I think you should join us. And they will ping you to join the conversation. So it's like and sometimes it's just allowing you to sleep and get recharged. It's and it's really important. And it frees up more of your time to actually create, which is your what you're passionate about. And look, this is like a conversion machine. This is like incredible. I mean, it converts so much better than the sellers themselves. And by the way, it's them because it's, I mean, the personal assistant is trained on you, just on you. Your offerings, your profile, your entire, sometimes it's tens of thousands of conversations with customers, your orders, everything, it knows everything about you. And so, and it's instant, it's like, it always, it's always up and awake and available and it's And what we find what we found is through humanizing the assistant, we eliminated the, I think, initial propensity. Like, I mean, people hate talking to bots. Okay? Let's clear that up. So if you create a bot, they'll hate it. So we humanized it. We've made like, I think we've really smart things on the tech behind this, which people love it. They sometimes they get confused because we don't disguise the fact that it's an AI assistant. And sometimes they're like, are you really AI? It's like sometimes they ask the question because they're not sure. It's like it's like a human being and it has the characteristic, it responds to all kinds of I mean, it's really interesting. And so this was obvious. Then we had the creation models and we said, okay, great. I mean, we've found like 60 different categories of services that we can apply AI to, Gen AI to. And by the way, there isn't AI for everything right now. Maybe over time, there's gonna be more and more and people talk about the idea of agentic AI and ultimately AGI and all of this. I'm happy to talk about my view on this, but it's not gonna be very different than things that you've heard before. But we focus on really the areas where we think AI can give results that are gonna be at least 90% accurate or true to the actual creator. So if you don't get if what we've created, the AI tech that we've used and manipulated and built on top and mashed with other technologies, if this doesn't produce like a 90% score of accuracy to your specific signature, it's not gonna be there. And so we started rolling out those different categories where we had sufficient confidence that we're not because we don't want the Gen AI to misrepresent the creator, That would be terrible. And it's not perfect. You know, there is I mean, since we launched Go, the way I'm approaching this is that Go is an app. So we issue app updates. Like, every day we launch new versions of it. We add capabilities. We fix bugs. We make it simpler to use. We make it quicker. We make it cheaper. We get all of it so that you know? And over time, I mean, it's gonna be able to do more stuff, and we're gonna add more capabilities into it. But this was the strategy. It was it was really and plus all these categories that you've mentioned we have, which also includes, like, complex text as well, like business planning and stuff, these are all categories that are large sized categories. I mean, graphic design is if you think about it, it's one of our biggest categories because it's one of the biggest categories out there in the world. The same goes with, like, music and music productions and voice over in particular. And, I mean, these are big categories. And this is where we've also seen AI doing some really nice progress, but we wanted to take it even a step further.

Nathan Labenz: (1:05:32) How do you think about upgrading these things over time for people? I understand that you have a sort of commitment to, like, you as the freelancer on Fiverr shouldn't have to worry about all the technical details of this. Right? This is one of the big value ads that you wanna provide is, like, making it simple for freelancers to take advantage of this stuff. One thing I have observed though in some other context, I don't know if it will apply here or not, is that sometimes a model quote unquote upgrade comes along and people have very different feelings about it. You know, this famously happened with the app replica, which, you know, special case because it's like your AI friend. But when they upgraded the model, it got smarter, but people were like, this is not, you know, my friend anymore. And I sort of wonder, you know, as you create these sort of bespoke highly individualized models that people have sort of deemed like, yes, this represents me well enough that I'm willing to, like, have it be the first taste of my creation that a potential customer might see. Do you have a concern or is there a process for how the foundation model gets swapped out and, like, you know, will everybody need to opt in to the next version? Or how do you think about that sort of, you know, for most people, it'll be an upgrade, but for maybe some people, it'll feel like off somehow.

Micha Kaufman: (1:06:52) Yeah. Look. You're touching on a, I think, a big vulnerability of AI in general and those who design it, and that is inter compatibility between different versions or models. And since we said that this is on us, meaning we need to make sure that you have the latest and greatest tech, but in a way that would not do you harm, It's on us to put the right processes in place to make sure that if we do change the underlying tech, bear in mind that it's never like the pure tech. We're always building technologies on top of it, which means that we're somewhat a lot less exposed to differences in models. But this is, generally speaking, it's an issue. And if you think about, I don't know, if you think about the difference between shot GPT 3 and 4, it's interesting because one of the issues was that the, you know, GPT 3 was insubordinate. Like, you would tell it to do stuff, and it would just laugh in your face. It would just do the opposite. It's like and then came version 4, and 4 was really compliant. Like, it was just doing but there's nuances in that, and this is one issue. The other issue that is very big is giving models boundaries. We're like, okay. This is what you do, but these are the things that you will never do. It doesn't matter what they tell you. No. You don't do it. And if you've played the RAF with LLM, you know that it's like, it's super it's, like, embarrassingly easy to break them, to do stuff they're specifically designed not to do. So I think that this is another area of complexity where you need to not just make sure that they produce good quality stuff and they're staying true to their basic function, but that they don't go outside of that function. And for us, it was really important because, I don't know, take graphic design as an example. And let's say you're a graphic designer and you in your service, you said explicitly that you're not gonna do anything that is not safe for the office or whatever. Or you're not gonna do you're not gonna do political stuff. But AI is AI. Whatever. I mean so you can't have AI be not compliant with its creator. And when you have potentially millions of creators that have AI, it's like you need to make it compliant with each one. So there's quite a few challenges when you think about AI. And obviously, every time a model upgrades or updates, it's like you need to run checks again and you need to do the same, you know, the same stress testing all over again. I think with time, I think also the creators of these base models are gonna be a little bit more thoughtful on how to figure out what not to break from version to version.

Nathan Labenz: (1:10:19) Yeah. We can hope for that. Although the amount of alchemy that is going into the models today suggests that they might have a couple breakthroughs needed before they're gonna have a real command of that sort of nuance because right now they are, I think, many cases, you know, discovering what the new model can do right along with the rest of us.

Micha Kaufman: (1:10:41) True. And it goes back to what I've said earlier. We're training it right now, and we're obviously human beings are so creative that they're coming up with all kinds of new use cases, but also new hacks and new vulnerabilities and new I don't know. And this I mean, at least the good news on Nag is that it really informs the model creators on how to do a better model, but it also creates, like, a very powerful tool where, again, we're the product. You know, if you're getting it for free, you're the product, period. So that's a reality right now.

Nathan Labenz: (1:11:33) So in the long term, let's pause it for the sake of analysis that the models are gonna continue to get better. I assume no argument there. And let's imagine that they do get to a point where, you know, arguably, we're starting to see some of these thresholds being hit right now with GPT 4o image creation. You know, now you've got the ability to do sort of a high fidelity, but still, like, pretty holistic change to an image that you put in. And with things like Sesame Voice AI that was recently debuted, it's like, man, these are starting to get very, very lifelike. If we imagine a world in which, like, the AIs really are sort of performing at the same level as the humans, and it's no longer the case that this is sort of an on ramp to or no longer has to be the case. Right? That, like, the only way to get the real true top notch service is to go to the human, but, actually, you could just get the same quality from an AI. Do you think that there is enough sort of solidarity or willingness to pay for these personal models that people will continue to do it in volume because they want, you know, to see a human compensated on the other end of that, or do you think that there needs to be some other solution which could be regulation or otherwise put in place in order to preserve this sort of centrality of the human creator?

Micha Kaufman: (1:13:05) I don't know. I don't know. I'm not I don't even think about this from a solidarity standpoint. Look. When YouTube became what it is because it had illegal downloads of, TV series and movies. Because sharing videos on YouTube back then was not as easy as it is right now because there wasn't broadband at large, and it was so people mostly consumed, you know and then over time, they whatever. They got sued, they've made peace with the publishers, whatever, and they made it into an incredible business. And it's amazing. We used to steal music. We used to, you know, to download stuff, you know, Napster, before Napster FTPs, like whatever, we had our way of doing that. But eventually you have Spotify and you have Apple Music, you know. And I think when it makes sense and you have a very easy way of consuming creation and it gives you the type of pleasant or even higher than you had to do when you didn't do this legitimately. Then you pay for it. I mean, people pay for Spotify. They pay for YouTube premium. They do whatever. I don't know if it's gonna be the same case. I don't know. I'm not a regulator, and I'm not you know, I don't know where this is gonna be going to. And I'm not sure that the way we've done the personalized models is the right answer. I'm not I don't pretend I know. And we're already making changes to our own model as a result of the learnings that we've had since launch, you know, 2 months ago And the way we use it

Nathan Labenz: (1:15:08) Learnings that you would highlight?

Micha Kaufman: (1:15:10) Well, I don't wanna spill the beans too much. But yeah. Yeah. I mean, there's there's a lot. There's a lot. There's a lot in the way people interact with creation on their own. It's you know, you understand the limitations of it. You understand how people perceive this is do they perceive this as like, oh, I wanna generate something myself and buy it versus, oh, I wanna play with it, but then give me an opportunity to talk to a human being. Like, seriously. Like, I enjoy playing with LGBT and ask it to create an image, but seriously, this is my business. I wanna, like, I wanna do something that I need an advice. I need a professional advice. I need, like, I need a good eye. I need, a good hand too. And sure. So we've learned a lot around this. So I don't know if this is like if having these personalized models is gonna be the thing and it's gonna be forever and it's gonna be the answer, you know, the cure for cancer in this space, but we'll keep iterating and coming up with ideas. I think that at some point, the regulator is gonna catch up. I don't know if, like, they're always behind, but they're gonna catch up at some point and they're I think they're gonna do some regulation of stuff because, like, everything is outdated. So now, you know, copyright law is practically being disregarded, but at some point, they'll just need to update it and figure out if you know? Because I think that, again, as I've said before, humanity has a vested interest in its continued progress and advancement. And if you demotivate people from if you close people up instead of opening them up, if you make them create less and just be all of us as just stupid consumers that are not contributing anything, then you know? But it's I mean, talking about the future has become really hard because it's like the rate of change is just people ask you, like, where do you think you're gonna be 10 years from now? Was like, are you crazy? What do you mean? What do you mean 10 years? Who the fuck knows? Seriously. Like, can you can you extrapolate what's gonna happen in 2 years from now? Dude, like, this is like, I think people who have very high confidence in how what the future is gonna be like are charlatans because it's like seriously. Like, how can you there's too many opportunities for different futures depending on all kinds of things. And so I think that in this reality, which is why, like, I've laid out the 3 reasons in my view why people go to other people, So go back to first principles. Go back to fundamental truths of, like, how do we behave as human beings? Why do we, like, why do we enjoy working together? Why do we trust many times a person more than a machine? Even though sometimes a machine is better than a person at conducting stuff. It's like eventually machines churn out stuff that we need to consume. We need to have the judgment of is this good for us, for human beings or not. A machine doesn't understand. It doesn't know and doesn't give a fuck. Like, it doesn't even understand that it's an image. It's just zeros and ones. It's like it's patterns. It's algorithms. It doesn't know, which is incredible that it can produce such incredible things without actually understanding stuff. But who knows? I mean, it's mean, it's not gonna be boring. That's for sure.

Nathan Labenz: (1:19:04) Yeah. For what it's worth, I'll take a little bit the other side of the AI understanding debate and say, I think there is some meaningful understanding going on inside certainly the latest systems, but that might be a topic for another day.

Micha Kaufman: (1:19:18) Well, it's just better algorithms. It's like I mean, it's not chemistry, and it's not it's not seeing itself in a human eye. It's like essentially, I mean, what's interesting is that the way AI continues to progress is that because we train it more. We give it more information. We give it more training assets. We give it more datasets. Because essentially without it, it's just regenerating based on what it knows. And if it creates new ideas, who knows what these new ideas would be? Even if they're like, are they good, bad? Are they like, do they make sense? You can have computers compute forever, but, like, it doesn't mean that they're gonna produce good stuff. So I don't know. It's it is going to change our lives. It's gonna make us do you know, spend our time in a different way. But I think that this is, I mean, this is overall, it's a good thing.

Nathan Labenz: (1:20:21) Do you have a framework for, like because I'm struck by on the one hand, you know and I think it is definitely the right big picture question to be thinking about. How do we sort of keep humans in a, you know, centered and flourishing environment or environment that's suitable for their flourishing? How do we not, like, take away and sort of I always think about the old, you know, paved paradise and put up a parking lot song. Like, do we not sort of pave the paradise of artistic creation and put up the parking lot of AI doing it all at hyper scale super cheaply, sort of taking away something that too many people feels like in a really important source of meaning. On the other hand, there's sort of the customer service, you know, top of funnel type stuff. Right? Where it's like, yeah, most people would rather delegate that to an AI if they can. Is there any framework that you could muster for, like, what things ought to be protected and what things are sort of, you know, long term, like, should be the sort of special, you know, space for humans versus the things that, like, we won't be sorry to have delegated? Yeah.

Micha Kaufman: (1:21:38) Look. I'm I don't, again, I'm not taking I'm not putting the heart of a regulator and thinking, oh, what should we protect?

Micha Kaufman: (1:21:51) In my view I mean, you've mentioned a few different types of tasks. Any task that a human being should not do because it's repetitive and computer can do better, we should stop doing. Like, it's whatever. I mean, accountants used to calculate on paper 20 years ago, just 20 years ago, 25. They have pencil and paper. They would do balance sheets. And then Lotus Notes and Excel, and now we have these funky sophisticated models and whatever. Should they continue calculating by no. They shouldn't. Stupid. Stop doing it. You're not better and you're not faster. And I think the same goes with any other task. I think that it's not about protecting. I told you, I don't think that you need to you don't need to enforce a protection on anything. I think that the creativity of human beings is going to remain the creativity of human beings. You don't need to protect it. They're gonna be very creative, which means that if there's it's like, if you have a smarter person, they have better taste than you, they're more knowledgeable in a space, they're more creative in a space, then you'll go to them. Okay? If their only advantage is how they operate stuff and you can operate the same stuff, you don't need people for that. And that's fine. You don't need to protect it. I think that this is gonna arrange itself naturally. You don't need to do an unnatural intervention in this. And very simple tasks that doesn't require a lot of skill are gonna be are gonna be gone. But I think that in some cases, I think, you know, what's gonna be interesting to think of is I think that there is a chance that in a few years from now, if you think about the largest brands in the world, they would not necessarily want to produce stuff with AI because this is like everybody has it. They would like the more handcraft things that involve, like, the, you know, the most creative, smartest, unique people that you can get one of. Like, you can afford it. Like, I remember when they said that Coca Cola did their first ad with AI. It's like a Coca Cola doing an ad with AI, which is like, it's wow. And you go read the behind the scenes of the ad and it's like 500 people. It's like, sure. AI was involved, but there's like I mean, there's like there's like 3 of the best agencies in the world, you know, and they have their compliance teams and legal teams and whatever. It's gonna be so I think orchestrating the most unique things that are gonna be that are gonna be mind blowing that are gonna be it will always require this. You don't need to protect it. It's gonna happen by itself. It's like people that do special art on Etsy. I don't know. It's gonna be it's the bespoke things that maybe we consumers don't need to like, we don't understand why you should pay for it because it's like, who cares? It's, you know, it's, you know, it's a birthday invitation for my kid. Okay. Whatever. I'm not like you don't need to take the best in class person. But if it's mission critical and I wanna be better, I don't think you need to protect it. And the same goes with like the types of jobs. I don't know, maybe like if you need if you give your, you know, the task of customer support algorithms, to AI, you need to supervise it, you need to continue refining it, you need to some people hate this, you need to let them actually speak to a human being and scream on them and like stuff out and you need to figure out how to integrate this better with your specific tech stuff and your product and whatever it is. And so again, it goes back to this. It's gonna be just new types of jobs that require human beings rather than just machines. Machines should do what machines are good at, period. That's it.

Nathan Labenz: (1:26:19) Maybe 2 more questions if you have time.

Micha Kaufman: (1:26:22) Okay.

Nathan Labenz: (1:26:24) How about on just creating liquidity in the marketplace? This is one area where I think AI could be you know, I just heard a definition of an efficient market the other day, which is that in an efficient market, all positive some transactions that could happen do in fact happen. In reality, obviously, discovery costs, search costs, matching costs, negotiation costs are all huge impediments to actually seeing that happen. What is your outlook for just greasing the wheels of the marketplace by doing potentially orders of magnitude more AI matchmaking? Do you think that that can, in fact, like, scale the marketplace to previously unimaginable scale? Or, you know, what's your kind of outlook for AI facilitated commerce broadly?

Micha Kaufman: (1:27:17) That's an easy one. The answer is yes. It's just I mean, it's a simple yes. I think, and I've kind of alluded to it previously when I said that the experiences of how we consume stuff, how we find things, how we convert, how we get comfortable, how we create trust, how we make a decision are gonna change. And, I mean, we're doing deep and extensive use of AI in the matchmaking. It's like I'm not gonna go into details here for obvious reasons, but it's like we're doing deep stuff with it and we're seeing the change. And I think that this is just gonna become better and better over time. So definitely I mean, improving liquidity absolutely yes without a doubt.

Nathan Labenz: (1:28:07) Okay. Then in that makes a lot of sense to me. I'm if anything, just kinda feel like I should be seeing more of that in the world than I do see you wait, and it feels like it's a little

Micha Kaufman: (1:28:17) It's in the making. You'll see you'll see Amazon doing experimentations that are bolder, bigger. You're gonna see other platforms doing the same. I think it's just a matter of time. We're in the very early innings of it.

Nathan Labenz: (1:28:37) Yeah. Okay. So then maybe going, back full circle to kind of where we started in terms of, you know, AI coming for all of us, coming for you at some point, and the sort of wake up call that you gave to your team. I guess I'd be interested to hear just, like, what your leadership experience has been like in recent months. You know, what has been effective for you? To what degree are you leading by example? To what degree are you putting, like, mandates in place? Are you making this, like, part of performance reviews? What's your overall you know, are people, like, excited for it? Are some resistant? What's the, you know, speaking about the full time team at Fiverr, what's the dynamic when it comes to making or perhaps not quite, you know, eagerly making fullest use of what AI can do for people?

Micha Kaufman: (1:29:24) So when I send this I send this more than maybe 36 hours ago, and the reception of it was, I think, very good. For some that are just, you know, ahead of the curve, it was just stating the office. For some, it was just a validation of their fears. For some, it was a complete wake up call. Probably very few because, I mean, we've been obsessing about the usage of, like, maximizing the usage of technology. But overall, I'd like, I don't think anyone thinks that I'm bullshitting. Like, it's like, oh, like it's to create panic or try to faking, you know, faking motivation to it's like, I think people people understand this, but this is I think it invigorates people to have conversations around this. I've in a day, you know, almost 2 days from it, I've had so many conversations. I've said, you know, my door is open. Like, just take time. Come. Let's sit down. Let's have a conversation. I've had so many people from different teams coming and saying, you know, we wanna share some of the stuff that we're doing, blah blah blah, whatever. How should we measure ourselves? Like, what do you think is a good KPI for it? What do you think is a good measurement? And, you know, it is scary for people, rightfully so, by the way. And I think this is just it is just what it is. It's like a wake up call that we need to do it. Like, I you know, when the first version of ChatGPT came out and when they started thinking about talking about APIs and stuff, I went back to coding. Like, I wanted to play with it myself. I used to be a hacker on the pre HTTP types of the Internet. It was the pre web. And I've been hacking for, you know, most of my life. I love it. Like, I wrote some of the code for the initial version of Fiverr and all the way to version 2 of like, I love playing with it. So for me and it wasn't really just about, like, setting personal example. It was I wanted to understand how powerful it is and how easy it is to actually do stuff. And in some cases, I would have an argument with the team and saying, like, you know, we should we were talking about something and they would say, okay. Okay. Great. So you should probably see it ready in like 3 weeks. And I said, fuck you. What do you mean? What do you mean? Like, 3 hours. Like, why? No. It's not as simple as you think, blah blah blah, whatever. So I went back home. I just, you know, installed stuff on my computer and just came the morning after. And I said, I put, like, a stopwatch on myself. I gave myself 3 hours. This is what I could generate. And I suck. Like, I'm not you know, I'm rusty. I don't think I'm, like, a cutting edge developer. I was always, like, a mediocre one, like, because I never I never did the 10000 hours. But it's like, if I can pull this shit in 3 hours, no. Not 3 weeks. No way. No way. So there is some setting of an example, but it's also under like, really understanding, not just, like much like you don't, like, you don't create companies by taking an MBA course. Like, you need to be in the trenches. You need to be an operator to understand the actual, you know

Nathan Labenz: (1:33:08) and so it's the same with this. And yeah. And I think that this is I don't know. I think that it's a good time for a wake up call because I think that there's gonna be changes in the industry. I think it's gonna affect a lot of people, and it's the time to wake up. And I think we're doing ourselves a favor by doing this. But, look, I think we have a very aligned organization. It's not that there's people resist it or people you know, they're scared, but they're scared on themselves. I mean, it's not their job at Fiverr. It's just their job, period. Right? But yeah. I mean, we have an incredible team. I think that the vast majority are going to do this full transformation, and it's gonna be incredible because it will allow us to push, you know, either 5 times faster or 5 times the amount of things that we're pushing. You know, I'm seeing how the pace is picking up. And I'm always optimizing for velocity. So I think that this is, you know, it excites me more than anything else.

Nathan Labenz: (1:34:17) Is it impacting your hiring plans? Like, are you still you know, in most organizations, junior developers, junior marketers, like, these were sort of high volume roles across the technology industry. My sense is that the volume is already kind of dropping and in particular, in some cases at least because people are sort of looking at like, can does this like junior developer or junior marketer allow me to move faster or do they kind of slow us down in the AI age? What's your outlook on kind of the fate of the, you know, just starting out in their career professional in today's world?

Micha Kaufman: (1:34:57) I think that the question of interestingly enough, the question of being, like, a seasoned professional or junior, maybe it's less than an issue because the juniors are the people that are the best talkers because I mean, they're making the most effort to stand out. They've been if they went for education, they got the most up to date education that includes machine learning and AI and all of it, which people didn't learn like 3 years ago, 5 years ago. It's less about that in my view and it's more about how proficient are you with like with the new tech. Like, I mean, it doesn't matter. Like, you we might be hiring for a legal position in our legal team. And if you're not versed in how not to work like it's 2024, then you're out. I mean, you don't stand it. You're not gonna I mean, you're not gonna get in because it's like you're taking someone who you need to now train. And I don't wanna train anyone. And this is also my because you don't need to. It's fucking it's like it's all available online. Like, just take a course. Like, do whatever. Hack and figure it out. Like, there is no manual and I don't need to, like, I don't need to feed you. No one, the world doesn't owe you shit. Like, learn it on it. Like, there is no barrier to learn on your own. And so if you're if you're unfamiliar with the latest technology and its capabilities and the latest products and solutions and whatever, then you're I mean, you're not gonna pass. This has changed, you know, materially in the past maybe 2 years.

Nathan Labenz: (1:36:58) Yeah. Never been a better time to learn, but, never been a worse time for people that want to get on a very predictable path and just, like, do what they're sort of prescribed to do and trust that we'll take them where they wanna go. It does seem like I agree with you also that the senior versus junior distinction is maybe less important than sort of what mindset are you actually bringing to the day to day challenges and, like, are you personally just always obsessed with finding a better way to do things at any stage of your career? I do really worry at the same time. I mean, I don't know what universities you're hiring out of, but, man, I talk to people coming out of a lot of, like especially just rank and file American universities even out of CS programs. And it's like, still to this day, in a lot of cases, they're sort of prohibited from using AI in their, you know, corporate courses.

Micha Kaufman: (1:37:54) These guys are logging. It's not open minded enough. It's dogmatic. It's like it's conservative. No. Like,

Nathan Labenz: (1:38:09) it's just So would you go as as far as advising people, like, not to go to an undergrad program in today's world? What alternative?

Micha Kaufman: (1:38:19) If you yes. No. Just sit down. Like, I mean, if you care about the socializing aspect, absolutely yes. I mean, it's a good networking. There is this alumni mafia, which is great, and it's like whatever. But if you wanna get ahead fast and you wanna start earlier and you know that you can become obsessively curious and deep dive into stuff, I mean, you can and certainly now, I don't know, maybe in a few years, it's gonna change as things are just gonna I mean, again, there's gonna be new professions. They're gonna be very complex. There's gonna be you'll need, like, crazy scientists and whatever, and it needs some more formal training and education right now. No. It's there's so there's so much out there that you can just it's just go peak. You don't need to even pay for anything. It's just it's amazing.

Nathan Labenz: (1:39:23) Yeah. It is a strange world, but I would agree that in many cases, Internet hustlers that are selling courses on how to use Cursor or how to use ChatGPT, whatever it may be. And I agree, probably don't have to pay for anything, but those folks that are often selling that stuff at pretty affordable prices are in many cases outperforming universities in terms of how actually, you know, job ready you're gonna be coming out of those, out of those experiences. So it is a strange new reality to say the least. It is. Well, I really appreciate how generous you've been of your time, and it's been a great conversation. Is there anything else that you would wanna leave people with? Any advice for other company leaders, job seekers, freelancers, you name it?

Micha Kaufman: (1:40:10) Yeah. No. I think we've had a very extensive discussion around all of these topics. Maybe the one message I wanna leave you with is my optimism. Like, I'm not pessimistic about the future. I don't think it's doomsday. I don't think we're on our way to a dystopic future. I'm very optimistic, and I'm having fun. Like, this is seriously, you know, intellectually challenging and which makes it so much fun. Yeah. Appreciate appreciate you having me. It was fun to, to talk. Yeah. Thank you.

Nathan Labenz: (1:40:51) Likewise. I appreciate you doing it. Micha Kaufman, founder and CEO of Fiverr, thank you for being part of the cognitive revolution.

Micha Kaufman: (1:40:59) Thank you, Nate.

Nathan Labenz: (1:41:00) It is both energizing and enlightening to hear why people listen and learn what they value about the show. So please don't hesitate to reach out via email at tcr@turpentine.co, or you can DM me on the social media platform of your choice.