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Can technology make us better humans?
Greg Buckner has made it his job to find out. As partner and CTO of AE Studio, Greg and his team blend data science, computer vision and machine learning to help design and develop products that aim to further human agency.
Greg and Louis talk about AE’s clients — Samsung, Walmart & Ritual to name a few — and nerd out over neuroscience, NFTs, and why brain-computer interfaces are coming sooner than you think.
“We want to build products that increase human agency and that guides the way that we think about things… We’re working on building 20 or 30-year projects, things like BCI. Because we actually want to play a part in building the operating system for the brain in the future.”
🎙 Highlights include:
- Why do software design & data science go hand-in-hand?
- How technology can further human agency?
- What is the Steel Man theory & how does it work?
- Tips for hiring a software development partner.
- The future of software development as a service.
- The future of technology, including NFTs and brain-computer interfaces.
This Week’s Guest
Partner & CTO @ AE Studio
Greg Buckner is a two-time startup founder and web developer. He’s partner and CTO at AE Studio, a product design and development firm based in Los Angeles.
The Startup Stack’s Host
CEO, Co-Founder of Rocketplace
Rocketplace is a curated marketplace of high quality professional service providers. A 3x founder, investor, and board member, Louis began his tech career as a partner at Andreessen Horowitz. When he’s not working or podcasting, Louis enjoys cooking for his family. His pizza, he’d like you to know, is incredible.
Full Episode Transcript
Louis Beryl: [00:00:10] [Laughing] Okay. I like it. I feel like you could use that in a lot of places. Good.
Hello. I’m Louis Beryl host of The Startup Stack. This week I’m talking to Greg Buckner partner and CTO of AE Studio. A design and software development firm that blends data science, computer vision, and machine learning into products that give people agency. From incubating startups to launching enterprise technologies AE Studio has worked with Samsung, Walmart, Ritual just to name a few. Greg and I nerd out on neuroscience, how NFTs are transforming the art world, and why brain computer interfaces are coming sooner than you think. I hope you enjoy our conversation. Let’s get into it!
[00:00:51] You guys are a development design and data science firm, right? You do a lot of different things. I would love to hear a little bit more about AE Studio.
Greg Buckner: [00:01:01] Yeah. So the origins of us is I think we do design development and data science, but the best way to really think about it as we build software products. And in today’s, uh, increasingly more sophisticated world that does involve kind of living at the intersection of development and data science. So design is involved in almost all of our projects, UI/UX product design, et cetera. And obviously engineering, whether it’s mobile, front-end, back-end, et cetera, but we also do data science, computer vision, machine learning, and we kind of, you know, some projects require just one of those or two of them. And some of them kind of have all three. So we kind of have a lot of different, uh, colors on our palette that we can paint from. But it’s all really about just building incredible software products.
Louis Beryl: [00:01:51] Sometimes you launched startups yourself. Why don’t you tell me a little bit more about that?
Greg Buckner: [00:01:55] There’s this idea that we’re kind of working on, which is we’re thinking about, um, innovating on kind of a new model or a way of doing things. And so you can imagine this almost as like a new way of tapping into, um, to, uh, capitalism and tapping into the way people work. Like there’s a lot of people who exist in the world today who are incredible entrepreneurs, or they would be if they could tap into that, but maybe for one reason or another. They’re, uh, they’re kind of like overlooked, you know, you can think of like, um, first time, uh, college graduates, like first-generation college graduates is like an interesting example of this or people who maybe didn’t go to college and did a different, um, profession, or they have a non traditional path or whatever, or people who are older, they have a mortgage, they have a family. Maybe they need like a safety net or something like that. We see opportunities to basically hire people like that as team members at AE. Give them support to work with our clients to build incredible products, but then also to have the opportunity to develop their own ideas and have that like, tap into that entrepreneurial spirit within the support structure of AE.
And so we’ll take the ideas that come from our employees and actually build those startups and incubate them inside of AE using all of the same great stuff that we offered all of our clients, you know, we have incredible data scientists and designers and strategists and product managers and developers. And that allows us to basically, like incubate and develop the own ideas of our employees and our team members and turn those into startups and then support them and launch them. And I can’t talk too much about it, but I will tease that, um, we actually had a, uh, an exit last year, which was really exciting and there’ll be more information on that, you know, coming out in the next few months.
Louis Beryl: [00:03:51] Yeah, that well, that’s incredible. Um, and it sounds, I mean, it makes total sense, right? You’ve got this incredible team, uh, put together. You’re helping companies all the time in a whole bunch of interdisciplinary areas, but you also see opportunities maybe from your own team members and you can put those together and launch businesses. It’s really exciting. Um, I’d love to take a step back for a moment and think about, maybe you could tell us the story of how you started AE but you know, what was the insight you had? What were you doing before and how did it come from to be?
Greg Buckner: [00:04:30] Yeah, so that’s a really great question and it’s a fun, it’s a fun story. So I was introduced to my business partner a couple of years ago and we had, um, we had one meal. And, uh, during this dinner, we really connected on what ultimately became the philosophy of, of a, and kind of what we do and the things that we care about, which is we, we talked a lot about how there are kind of gaps in technology today, where a lot of companies will. Kind of, you know, either manipulate people to do things that they don’t want to do, or, um, just not think about what we know out of neuroscience about like the way that the brain works, that you can’t really multitask. That we have all these like push notifications that are distracting us or that, you know, you subscribe to a product and they make it really hard to cancel things like that.
That combined with thinking about how technology is like increasingly becoming the extension of our consciousness. I mean, like I rely increasingly so much on my phone and my notes to basically be able to, uh, augment my memory essentially. And we had this conversation, this free-flowing conversation about how we think the technology products can be built in a more thoughtful way and also a little bit about the future things like brain to computer interfaces and stuff like that. And basically through that, um, we decided that it made sense. Sense to start a company that was focused on, um, building technology products that increase human agency and doing it in a way where we were a consultancy. So we work with other clients and we work with other companies to basically build either like startups or for enterprises launch new products or improve their existing products.
But we want to increase what we call human agency like this idea of, um, you know, products and the way that they operate being aligned with the goals of the end user. So. We had this really great meeting, um, and we decided to work together. Interestingly AE actually already existed at that time. Um, he had come out of the, uh, ashes of, uh, my business partner Judd and my other partner Ed, their previous startup. So they had a startup in like the food delivery space and basically. Um, that startup had failed for some interesting reasons but they wanted to keep everybody on staff. And so they, um, they were operating the company as an agency, but nothing like kind of what AE exists as today. So I met Judd and they brought me in as a partner in the business and like the business just started growing. So we kind of see it as like a refounding almost at that time. But the company that exists today is like, you know, much different than what existed then. And that idea of human agency is kind of at the core of everything.
Louis Beryl: [00:07:23] And what were, when you first joined? I mean, you didn’t really have, obviously had a lot of startup experience, a lot of technical experience, but you didn’t really have client services experience, so to speak. And I’m wondering what were some of the challenges that you faced at the beginning of that refounding of AE?
Greg Buckner: [00:07:42] I was lucky to have had a lot of previous experience, uh, working at an agency, uh, like working at a software consultancy. And, um, I also had myself kind of like a classical education and a lot of experience practicing Agile and specifically like extreme programming. Um, which is, uh, a version of Agile.
Louis Beryl: [00:08:08] What do you mean by that? I’d love to dig into that. What is extreme programming?
Greg Buckner: [00:08:12] Yeah, so there’s an incredible book by Kent Beck called “Extreme Programming Explained”. Uh, and it’s basically, he was one of the original founders of, uh, of Agile, um, and basically extreme programming is a way of organizing teams and having business people and technologists. Communicate to create the best possible product. And so there’s assumptions there about like the business people express the, um, the needs and the business value, the technology, people who are closer to actually solving the problems and building the software, decide the implementation. And it creates like a framework for communication between those two sides, which neither side fully knows the context of the other. And so like extreme programming and this like version of Agile creates a really high level, um, communication framework without the business people becoming engineers or the engineers spending all their time, operating the business. So basically I had a pretty deep background in learning, um, learning Agile and how to operate that.
And so I, when I came to the business, um, I brought a lot of that knowledge with me and we actually just adapted, uh, that process that I had learned previously to the way that AE works. Um, and honestly it was there weren’t a lot of challenges there. It was like a pretty, it succeeded pretty well. I mean, um, you know, we had five people when I, uh, when I joined and we kind of re founded the business, um, a little over three years ago, and now we’ve got over 50 people. So we’ve grown a whole lot. And I think the value there really came from like having good process, um, and knowing how to deliver a really great product and how to, uh, you know, increase the agency of our clients and leverage things like agile, but also take baby steps and adapt it to the particular, thinks like…
Louis Beryl: [00:10:08] Let’s talk about good processes for a second. I’d love to dive in there. You know, how do you, um, what are some of the tips that you would have for, um, whether it’s like, you know, I don’t know, other companies out there or other agencies about building good process. How do you measure success? How do you, you know, what are the ways that you think about managing the business, um, that help. Um, help build a really good company as you. I mean, you’ve, you know, just a, a small number of years, you guys have essentially grown by 10x. Right. Um, so what does that, what does good process mean?
Greg Buckner: [00:10:48] We think a lot about is, uh, so there’s there’s process in terms of like the delivery of the delivery and the management of like the client and the project and things like that. And we’re highly collaborative. And, um, we have like an AE version of Agile that we love and like works really well. But in terms of scaling the business, it’s really interesting. I think it really starts with like two things. So one is our core values, which we care a whole lot about. And which I, I really think is like the operating system of any business and the other thing is, uh, the framework that you use to run the business and all mentioned here, an incredible book and framework is called, um, The it’s called “EOS”. So it’s the entrepreneurial operating system. And the book that is the starting place is traction by Gino Wickman. And so we’ve used, uh, EOS basically to operate our business. And it’s incredible. And I recommend anybody who’s. And running a business, whether it’s an agency or a startup, like our clients, I tell them about it. Um, EOS is a really great book and a place to start, but one of the core parts of EOS and also a core part of how we operate is with our core values. That’s how we’ve been able to scale to where we are today. It’s things like, um, baby steps.
So we pride ourselves on making sure that as we grow the business, we never take big steps that are hard to reverse. Because if you make big steps, um, one it’s hard to measure whether that step was successful or not. It’s not experimental and it’s not iterative and it’s hard to reverse it. And it also kind of like disorients people within the organization. So we always want to take like little steps, even if we have a big idea of where we want to go, because accelerating leave large little baby steps. That’s kind of like, um, It’s like interest in a bank account. Like humans are really bad at understanding compound interest, but we know that like $10 today will be a thousand dollars in 20 years or whatever. So we do the same thing with how we make decisions and how we operate the business. The other thing that we do, that’s really cool, that I want to mention is called steel manning. So are you familiar with like a strawman?
Louis Beryl: [00:13:04] Of course. Yeah.
Greg Buckner: [00:13:06] Yeah, so strong, strawman’s like taking the weakest version of your argument and using that to argue against you. The alternative is what’s called steelmanning. So Louis, if you and I are talking about something and I want to steelman, your argument, I will take, uh, your position and I will actually seek to strengthen it and to fully adopt it myself, and to actually try to improve upon your argument and stance. And when I come from a position where I actually try to improve your argument, right. One, it means that we together become like a better thinking machine. And we’re more likely to either realize that my perspective is right. Realize that your perspective is right, because I strengthen your argument and convince myself or you and I together arrive at like some third thing that neither of us even realized was an option. That’s the best possible thing.
Louis Beryl: [00:14:02] I love this idea about steel Manning. Um, at Andreessen Horowitz, Marc Andreessen used to do, we didn’t call it steelmanning by any stretch. But we used to do something very similar where people would take both sides. People would take, uh, you know, the alternative side of the argument, maybe that they were, you know, you might be advocating for one thing and, and very, uh, very often it was Marc himself. He’d be advocating for one thing. And he’d be like, well, let me take the other side of the argument. And he would make this great argument against something and it was so compelling. And I remember this one time he kind of takes the other side. It’s very compelling. And then he kind of is soliciting feedback, post arguing against this. And everybody is completely convinced we shouldn’t do this thing. Okay. And it’s like, it’s like dead silence. Everyone’s completely convinced. And then he’s like, Well, no, I still want to do the other thing. I was just making the other side of the argument. The problem was he was just, he was too smart for us. He was too smart for us, but, um, I th I love that’s a great, I love this concept of steelmanning. It’s great. I’m going to completely unapologetically steal that.
Greg Buckner: [00:15:13] No, yeah, please do. And then you can literally like imagine a scarecrow and then imagine it like being sheath and armor and it being like the best version of itself. And it doesn’t even have to be an argument and it can actually be like you and I together on one side, uh, like myself and my business partners and everybody at AE. We do this all the time and we’ll just say, let’s steal me on the other side. And then we’ll like rattle off a bunch of points on the other side. And we might say like, actually I think we should do the other thing. It’s a powerful and kind of compelling way to think about it. So, yeah. Steal, steal away.
[00:15:48] Louis Beryl: [00:15:48] Hey, do you like our show? I do too. If you want to support The Startup Stack, the best way to do that is by subscribing and rating us on Apple Podcasts or wherever you listen to us. Also send Dad jokes, or if you have them actual good jokes to firstname.lastname@example.org. Feel free to send us feedback there too.
I mean, this is great, you know, uh, baby steps and steel Manning, you know, but, uh, you know, those, those sound like good ways to make decisions, good ways to build a comp you know, a company. But I imagine that the, you know, kind of EOS as much more than that. I mean, how do you think about judging outcomes for yourself and your clients?
Greg Buckner: [00:16:25] So we always try whenever we’re starting a new project, for example, we want to think about like, what are the metrics for success? And for us, it’s about deeply empathizing with whatever the client wants to accomplish and then actually helping, however we can, um, bring our own expertise to their, uh, vision and work with them to kind of co-create what the best possible outcome is. We’re in a position where we work with a lot of entrepreneurs who don’t have tech backgrounds. Themselves, maybe they’re a first time founder or they’re not an engineer. And, um, our ability to help them understand what’s possible. Um, knowing what the north star is that they’re trying to accomplish is really important. Cause you’ve every entrepreneur or intrepreneur inside of an organization or CIO or CTO at an enterprise, they have a big goal, but we also want to figure out like, what is the intermediate goal that we’re working towards right now? And how do we make sure that we hit all of the marks that we need to there?
So like for startup it’s launching an MVP, for an enterprise it might be like building a proof of concept and we measure success by making sure that, um, we’re headed in the right direction from the get-go. Sometimes there’s metrics that back that up, you know, sometimes it’s like, hey. Uh, at the end of this first three months engagement, we want to have 10 people use the proof of concept and validate whether it like it works or not.
Or, um, at the end of this data science project, we want to roll out the beta of this thing and have a thousand people prepay for it or whatever. So the metrics can change, but we always want to make sure that we’re working towards, uh, either a really solid concrete goal. It’s a step in the right direction or some like particular metric that we want to measure against.
Louis Beryl: [00:18:13] I don’t meet a lot of agencies that do data science projects and software dev projects. For example, can you tell me like it’s in particular data science projects for clients, what are some of the unique challenges that you face for those?
Greg Buckner: [00:18:28] Well, looking back at the Agile framework, I was talking about previously, the challenges with data science is that, um, you often don’t know if the thing you’re working on or the goal you have is actually accomplishable. So it’s a lot more of a research and development thing. I mean, if you tell me, Greg we want to build an awesome app for Rocketplace. I can tell you with like a decent degree of confidence, we can build this thing. There are things that are similar like it, and we have a rough idea of how long it’s going to take to build. And maybe we’ll be plus or minus five or 10%. But software technology is so sophisticated that like it’s, it’s pretty clear we can build or not build something on the data science side. You have to do research and development and there’s risks because you don’t know if the thing can actually be built.
Now, the benefit there is that all of our data science projects, whether it’s computer vision or machine learning or NLP, we’re creating valuable proprietary intellectual property. And that actually creates a moat around the business of our client. Because the thing we’re building has never existed before, and it requires, you know, smart people with PhDs, from Caltech and Stanford working on those things to create it. But the challenge is like over communicating with the client, making sure they kind of understand that, uh, there’s R&D involved here. But we’re going to do our best to, um, to yes. And the thing we’re trying to build into the best possible thing and the way that we do that in terms of like, you know, nuts and bolts of the project
is we always operate off of hypotheses. So when you’re thinking about building software, you’re usually building features when you’re thinking about building data science solutions, you’re thinking about answering hypotheses, like, okay, we want to build this thing. Here are the five questions we need to answer to get there. I’m going to focus on this question first. And then that answer is going to lead to this question or that question, and it’ll lead to this or that. And as we get closer, we then can actually start building like the proof of concept and actually figuring out what the thing is that we’re going to do put into the world, but it starts with a lot more questions than a than answers.
And so we just have like a rigorous way to think about that. And that kind of takes the abstract idea of data science. It makes it more concrete and easier for our clients to understand it. And for them to know what we’re building and how we’re working towards that thing. And also what’s possible. And that creates a ton of value.
Louis Beryl: [00:21:02] I want to transition a little bit to maybe you giving advice to other companies out there, you know, potential clients of yours that you might work with. Um, when they’re thinking about working with a, you know, design development or data science shop, you know, what are the questions that they should be asking when they meet a firm like yours and how do they even know they’re ready to work with a firm like yours?
Greg Buckner: [00:21:31] I mean, I think it’s important to understand, uh, like what you are hoping to accomplish and like what your, what your goal is. Definitely. Um, I also think it’s really important too, when you’re talking to, um, agencies or vendors and things like that, get a sense for their philosophy, get a sense for their kind of opinion and view of the world and what they think about, you know, for us.
Um, as I mentioned earlier, like we want to build products that increase human agents. Yeah. And that’s a really compelling vision and it guides the way that we think about things. And we truly believe that like using that perspective, um, we’re going to build better products than would otherwise be built if you’re just building the thing without kind of having like an underpinning to how it works. Um, We also think a lot about the future. So, you know, one of the things that we’re doing is we’re working on building, um, and this is a 20 or 30 year project, but we’re beginning to do research into BCI. Because we actually want to play a part in building the operating system for the brain in the future.
Louis Beryl: [00:22:41] Sure. Right. So BCI being brain to computer interaction?
Greg Buckner: [00:22:46] Brain, uh, brain to computer interface. Okay. So like a Elon Musk’s Neuralink is like a good example of this. There’s also Kernel, which is here in Los Angeles. Um, we’re thinking about the future like that. And we think a lot about human agency. And then, as you mentioned earlier, like we have these, um, skunkworks projects that we work on, and those are all things that I think point to like our, our ethos and the way that we care about things and this skill and care that we’re going to bring to client work. Um, and that, that I think give, gives clients a lot of like confidence and helps them understand that we’re far off thinkers that are thinking about the future and we’re going to bring that same kind of care and thought to their product.
Louis Beryl: [00:23:29] I mean, I meet founders all the time and you’re working with non-technical founders. Um, often not always, I’m sure a non-technical founder out there very often. They’re they’re, you know, they come to us and they say, hey, do you have an agency that can help me build the, you know, the first version of my app, for example, right. You know, what are the, how do they even evaluate whether or not, you know, certainly alignment is something, but how do the, you know, how do they think through areas of. Um, quality cost, uh, speed. Um, you know, how do they, you know, how would you advise founders out there, especially non-technical founders, um, on evaluating firms and agents?
Greg Buckner: [00:24:14] Yeah, that’s a great question. I think that, uh, so one, obviously looking at the work that the company has done and, you know, I’m in the general stuff, like references are always great. And looking at the work that’s been created by the company, but also honestly just asking those questions. Um, we sometimes have clients who just ask us, like I’m, non-technical, I’m evaluating what makes the most sense here? Um, how do you guys think I should evaluate you? Or like what sets you apart from another agency that I’m going to work with?
Louis Beryl: [00:24:49] Great. So I would love to hear how you answered both of those questions.
Greg Buckner: [00:24:53] The way that I typically answer something like that is like, You know, you can speak to the other people that we’ve worked with. But the way that we think about doing things is we want to help increase your agency. And we want to work with you to build the best possible thing that you can, and the best way to do that, is for example, like everybody at AE is client facing. Um, we literally become your team and something that a lot of agencies do that we think doesn’t lead to the best possible product is they’ll ask you for a 35 page word document. They’ll throw that over the wall and then they’ll come back in six months and maybe they built the thing, or maybe they didn’t.
Like real life example. We had a client who said, uh, I had, I worked with an agency, gave them this document. It came back, there was no log-out button. I asked where the lockout button was and they said it wasn’t in the document. We didn’t build that because you didn’t put it in the word document. And instead of doing things that way, we actually just become your team. And I’m in the greatest compliment that I can ever.
Louis Beryl: [00:26:00] That example you make is particularly frustrating because I think that a really good agency understands, you know, I, I remember some of the agencies I’ve worked with, right. And there’s there’s Oh, you know, a really good agency and, you know, good designers, et cetera, under, uh, you know, the, you know, the client might have one particular goal they’re trying to do, but. There’s a lot of other user behavior that happens when you’re building technology. You know, things like, okay, um, you have to sign in and maybe you have to reset your password, for example. Right. And it’s like, well, the client might not have specified. We need to build reset password functionality. It’s not the goal of their company, but it’s something that is critical to, you know, just building technology products or, you know, account management or other things. And so, yeah, that would. Stuff like that logging out, um, or, or signing in is, is stuff that, yeah, I think sounds like almost like table stakes, if you’re going to be a, uh, high quality, uh, design and developers.
Greg Buckner: [00:27:07] Yeah. I mean, you want to, ultimately, I think you want to find somebody who’s going to be a thought partner with you and who like, like, who almost feels like they’re actually a co founder. Or they’re like, they’re your first hire. And they are just as invested in the business as you are. And that’s how we operate because it’s kind of the only way that we know how to do things.
Louis Beryl: [00:27:29] Can you give us an example of a, maybe a client project? Maybe that was really challenging or, or that, but that ultimately you’re very proud of? Ultimately that you had to come up, you guys came up with solutions that were innovative and maybe that, you know, you were part of the team, the client didn’t even think that it could be like this. I’d love to hear a story of, of one of these projects that you think a outperformed.
Greg Buckner: [00:27:53] Yeah. So I think a, a good example is, uh, we have a company, um, who’s a client of ours. They’ve been a long-term client and they’re, um, in the biotech health space, And basically, um, this is interesting because it was a development and data science project. Um, they needed help developing, uh, their computer vision algorithm. Um, you know, so in biotech health, they essentially have a, um, It’s like a pee stick and you pee on this thing on either a daily or weekly basis, then you point your phone at it. And it measures, um, key biomarkers that you can get from urine analysis.
So things like, you know, keytones, vitamin a vitamin D, uh, hydration, et cetera. And, um, they needed help, uh, developing their computer vision algorithm. So we started there, um, and basically we were able to get them to a place working together where they were actually able to raise follow on funding because of the work that we did. And they were able to launch their beta all with us, kind of serving as their data science team.
Louis Beryl: [00:28:58] And let me ask you a question. How did the technology already exists? Because you know, you’re talking about urine analysis. I imagine that traditionally that is done, uh, chemically, not, not based on vision had like, was there some question that, um, it was even possible to do it, uh, with computers?
Greg Buckner: [00:29:24] Yeah. So that’s a really good question. It was definitely. It was known that, um, it could be done with computer vision, but the algorithm wasn’t there yet, and it wasn’t performing at the level. It needed to. So the question was understanding like, um, what are the technologies we need to develop to actually get there?
One of the hardest things actually was like white balance, like a lot of people. So first of all, most people are doing this in their bathroom. Some people have daylights, some people don’t, some people have like a warm light. Some people have a halogen light. Some people have very little light. And so understanding and baking that into the algorithm so that it would work in a wide variety of circumstances was, was super important. And the cool thing, you know, I’m, I’m proud of that relationship because the early work was difficult and we were working on what is literally like a core part of the business, but we’ve also continued to expand the relationship now where, you know, almost two years later, We have multiple data scientists and multiple developers and engineers working on the project. And we kind of feel like we are a partner in the business. Um, you know, I talked to them myself on a weekly basis and, um, We basically like work together to help figure out the best way for this Startup to move forward in terms of strategy, but also in terms of the day to day, sometimes in terms of like, Hey, I’ve, there’s things about you process that could be like better.
And I want to give you advice on that, et cetera. I mean, we consider ourselves like a real stakeholder in the client. And sometimes that involves like giving the client themselves, like advice or input on various things and also accepting advice and input from them on things we could do better. Cause we, you know, we ultimately think that we’re doing a great job, but we’re also 1% as good as we could be. And that’s a perspective that we use with ourselves and we also use with our clients. Um, and I think things work really well when you have that humble idea of like, we’re great, but we could be even better.
Louis Beryl: [00:31:28] 2020 so much changed and we’re all, you know, working remote in an hour. Now we’re a quarter through 2021. Where do you, where do like, what do you see changing in 2021? What are your clients asking you for what’s different and in particular what’s different this year, even from, and last year?
Greg Buckner: [00:31:49] Well, I think, uh, one really interesting thing is, uh, is like or NFTs. Um, like there…
Louis Beryl: [00:31:59] And just for our audiences, what are NFTs?
Greg Buckner: [00:32:02] Yeah. So NFTs are non fungible tokens. Um, it is essentially. And uses the same underlying blockchain technology that exists in things like Bitcoin, et cetera, but it enables you to have a file that can only ever be represented once. And so the interesting thing about it is it’s getting a lot of traction, for example, in like the art world, because you can just have like, even though there are, um, literally infinite versions of a, uh, a digital piece of artwork. There’s only one specific file that is tied to that NFT token. And that means that you can buy and sell that. Specific file as though you’re buying and selling actual art. There’s a lot of other use cases as well, but the, the, the art world and this idea of actually having files that can’t be infinitely reproduced, there’s obviously copies, but there’s only one that’s tied to that NFT, um, is like a huge thing right now. And so, um, we’ve had a lot of clients who want to see how they can leverage that in, uh, in their projects.
Louis Beryl: [00:33:12] Can you give it some examples? You don’t have to share any client stuff, but some examples of outside of art, where do you think NFTs could, uh, be really useful and proliferate?
Greg Buckner: [00:33:22] You know, I think we all know that gaming is becoming an increasingly sophisticated and big area. And you can actually imagine use cases where you sell goods, but there’s only one version of that particular sword or upgrade or, you know, armor or spaceship or whatever. Um, that’s one interesting example. Another is like it’s adjacent to art. But, um, and this actually ties in a lot with the pandemic and COVID, we have all these digital experiences right now.
And so you can imagine things where you have a digital experience and you actually take a screenshot or you capture a little moment in time from like a concert that maybe you’re visiting remotely. And that can be turned into an NFT, things like that. So really any kind of, any digital experience and a lot of those are happening increasingly today. You can have an NFT that captures that and you can sell that thing as like a memento of that experience.
Louis Beryl: [00:34:21] It is fascinating. You know, we, we live in a world also at the same time of, you know, we’re talking about NFTs and this unique thing of one, um, you know, I feel like a unique thing of one, people are unique, things of wine, and we live in this world of technology. Where we have all these deep fakes and all, and all sorts of ways to reproduce people. And I’m wondering if there’s, if, we could use NFTs almost for like identity verification, if like you, personal NFT could follow you around the internet. And you’re like, Oh, that’s really, you.
No, they’re like, there are super interesting ramifications for things like identity or in the future. Things like, um, thought, I mean, the w you know, original, like the original version of a thought or an idea, um, if you can use something like an NFT to, uh, capture and kind of, you know, prove Providence for that particular thing, the way that that could be applied to things like. The reproducibility crisis right now in, um, in academic research. Um, if you can actually prove and verify through the blockchain or through NFTs, um, that, that research is that this is the actual data that was used in that study and then reproduce it. Um, it kind of, it, it helps kind of create greater ground truth for, for all of science or for things like deep fakes that you’re talking about. Like, You know, proving that this is the actual version of the conversation Louis and Greg had, and there’s no different version where, um, you know, they were saying stuff that didn’t make sense or whatever.
Greg Buckner: [00:35:59] Last question for you. If you could go back to before you joined AE and you could give yourself some advice, what would be the advice you would give to yourself, you know, many years into it, um, when you were just starting.
Louis Beryl: [00:36:16] Yeah. I think that it’s really important to make sure that you surround yourself with, um, people who you can think well with. I mean, we, so we think about ourselves, um, as like, At any given moment, there’s kind of like a thinking machine that is like the people in a particular conversation and the way that you think, and the people that are around you, I think has a big influence on the ideas that are going to come out of those conversations. We talk a lot about like group think as something to be avoided, but I think there’s, there’s also like, positive versions of that, where you can have the best possible group of people. And I think like myself and my two business partners, um, Judd and Ed, we are a really, really strong thinking machine. And we actually spend time making sure that we kind of like protect and foster that.
Greg Buckner: [00:37:13] And then we also with other people at AE. We try to create really good thinking machines in various different like, uh, meetings and, and various different relationships and opportunities. So that’s a thing I didn’t know, as important a few years ago that I think would have influenced the way that I think about, uh, like interpersonal dynamics and, you know, co-founders and past businesses and people that I work with. It’s like, Are we a good thinking machine and if not, how can we use tools like steel Manning and things like that to improve that? Um, I think that’s like a really valuable thing to, to think about. And I think it also probably spills into like, you know, significant others and personal relationships and, and friendships and things like that.
Louis Beryl: [00:37:55] Greg. It was really great talking today. Thank you for all the insight. Yeah thank you for joining us on The Startup Stack.
Greg Buckner: [00:38:01] Yeah. Thanks Louis.
Louis Beryl: [00:38:02] For more on our conversation today, visit www.rocketplace.com/podcast. We upload a new episode every week, so if you haven’t yet make sure to subscribe to The Startup Stack in Apple Podcasts, Spotify, or wherever you listen to them. Thanks again for joining us. See you next week.
Announcer: [00:38:21] The Startup Stack written and edited by Hannah Levy produced by Leah Jackson.