Andy Tang's Blueprint for AI Agents, Blockchain, and the Future of Micro-Transactions

(upbeat music) Welcome to another edition of The Inspired Stories podcast, where leaders share their experiences so we can learn from their successes and be inspired by how they've overcome adversity. My name is Anthony Codospodi, and today's guest is Andy Tang. Andy is a partner at Draper Associates, a leading early stage venture capital firm based in Silicon Valley. Founded in 1985, Draper Associates invests in entrepreneurs who are ready to reshape entire industries with bold technology solutions. Andy has extensive experience in dual use tech, AI, biotech, Web3, and defense tech. He has helped build over 15 unicorn startups, including Aqua, and Novel Beam, and co-founded Draper Dragon, a significant early stage investment fund. His strong grasp of emerging technologies and deep experience in venture capital have made him a trusted advisor to many successful founders. Before joining Draper Associates, Andy served on the board of multiple tech companies for finding his leadership skills and industry knowledge, and he currently directs VCX, an invite-only alliance of family offices, which promotes generational relationship building, education, and co-investing amongst members. Now, before we get into all that good stuff, today's episode is brought to you by my company, Add Back Benefits Agency, where we offer very specific and unique employee benefits that are both great for your team and fiscally optimized for your bottom line. One recent client was able to add over $900 per employee, per year, and extra cash flow by implementing one of our innovative programs. Results vary for each company, and some organizations may not be eligible. To find out if your company qualifies, contact us today at addbackbenefits.com. All right, back to our guest today, partner at Draper Associates, Andy Tang. I appreciate you making the time to share your story today. - Thanks for having me. - So, Andy, you received some notable degrees in your education, masters from an engineering from MIT and MBA from Wharton, and as I look at the early part of your career, it looks like you were focused more on technical roles, like at Motorola and Intel. I'm curious, at what point did you start to feel the pool to get involved in the investment side of the world? - I think I've always had interest in the business side of the world. As an engineer, most of us want to create things. In many of us are always been curious when you make these things, how do they make an impact in the real world? So, when I was working at Intel, I worked on the Pentium processor for generation. And that's when I got exposed more to the marketing, sales side, competitive landscape. And that was really in the height of the internet revolution. So, I think that's when I got really exposed to computing and how that affects internet and the real world application. - And for those who don't remember, the Pentium chip was a really big deal at the time. Why was it considered such a breakthrough? - I think it was really the first time you have a computer chip that enabled many customers such as Compat, IBM, Dell, the world to make a affordable computer for everyday consumers. I remember even my parents in ourselves were able to afford a computer when Intel first came out with a Pentium processor. And at the same time, the power you could deliver from a Pentium processor was more than anything you could imagine. You could watch a video, it was a big deal. You could run spreadsheet, you could surf the web. So, it was really that first price performance that tech industry was able to deliver for the everyday person. - So, I wanna spend most of our conversation talking about the work that you're doing now with Draper, but maybe let's pick one career stop along the way in between Intel and Draper that was a really formidable experience for you. Picked up some really necessary lessons and skills. - Come again, so what time frame or anytime frame? - Any time frame, but we talked a little bit about Intel. So, something between Intel and Draper, what was a career stop along the way that had a particularly big impact on you? - Yeah, so between Intel and Draper, I worked on Wall Street. I worked for Credit Suisse First Boston. And I worked for two of them. Most, I would say interesting bankers of our time, during that era, Frank Protron and George Boutros. So, they were the tech banker of our times. That was the very first time, I think Wall Street really turned to Silicon Valley and say, my gosh, these are great partners of ours. Good helping raise money, access to capital market. This was in the late '90s, early 2000s. And I remember the biggest challenge for us was being in West Coast office and trying to get our clients. These are our startup founders. Get them access to Wall Street capital. And then access, we did give them. And then it was sort of the pendulum swung the other way. We got them too much access, raised too much capital. And then the rest was history. You remember the.com bubble melted. And that was really tough. It was really tough because that whole industry got transformed, the investment banking industry. We went from the happy IPO M&A days to just man trying to triage and shutting down companies. But the reality is that I look back at that time. It really was that classic garner hype curve. Any good idea, you're going to have investors getting ahead of yourself, right? And companies didn't have enough time to grow into the valuation. And over time, there's adjustment required. But two things always happen, two things. One, investors always underestimate how long it takes for adoption to happen for new technology. Whether it's internet, whether it's fintech, green tech, crypto, dual use, robotics, AI. In all cases, we love it. And we think it's going to happen right away. But no, it doesn't happen right away, right? So I'm not telling anything new. So everybody knows that we underestimate how long it takes for consumers to adopt. The second thing will probably surprise you. The second thing is that most of us, VCs included, we underestimate the impact of this technology, right? Would you ever imagine that does surprise me? No, because like we're in the middle of the AI hype cycle right now, it seems like it's being overinflated. So I'm really curious to hear your perception of this. So AI, why don't we talk about something that already happened? You could identify too, right? So in 1999, you and I are kind of, you're younger than me, but I bet you remember what happened in 1999. People came out and said, hey, the first time we saw internet awesome, we're going to have e-commerce, we're going to video on demand. But would you ever imagine, in 2025, the level of e-commerce penetration, the level of video on demand or Netflix streaming video, you could do it on your phone, right? You could do it anytime, and the idea of no buffering, it just happens real-time. You could watch anything anywhere with one bar even sometimes. And I think that is something that we didn't project back in the days in 1999. But we also didn't think it's going to take 25 years, right? In fact, some of those fiber optics and optical component companies that we took public, the amount of infrastructure we've built in 2000, it's still probably abundant even for application today, right? And that's a fact. All these fiber lines, we lit up, you know, we have these, what we call the DWDM systems, which allows you to essentially send different colors or laser across fiber lines. So you could have multiple channels of communication and increasing the bandwidth, right? Those things were-- here's splitting atoms back in the days. We're finally using, I don't know, a couple of channels, maybe, right? But I think we were able to-- So multiple channels on basically the same pipe. It wasn't possible before, but now because we're sending different wavelengths, different colors. And then you can send them, and they're not interfering with each other. Correct. That was available 25 years ago. But 25 years ago, we had other problems. people weren't streaming Netflix on their phones, right? But today we are and finally those technologies became useful, right? So it goes to say a lot of these technologies who have always been ahead of themselves, right? The applications took a little bit longer. In other words, scientists and engineers are really good at inventing stuff, but the rest of us consumers take some time. And then the idea of streaming video on your phone, you know, it takes some getting used to. I mean, these days, yeah, you know, our colleagues are Gen Z, Gen Alpha, my kids are Gen Alpha, right? They take everything sort of for granted that this is just the way it is, but no, it's not always been this way, right? So when you talk about AI, so some of the things that I think that could happen, people are not thinking about, it's interesting to explore as an early stage venture capitalist, right? Because that's essentially my job is to I call it predicting the future, right? But I'm cheating a little bit. It's so much easier to predict the future. I just came for it's hard to predict the time in which the future is going to happen. Interesting. Okay. So what do you think the future of AI holds? What are you seeing in your crystal ball that may be in the average person is it? I think all of us would work differently. It's that, you know, industrial revolution, 2.0, right? I think it's the probably the most transformative technology known to mankind since industrial revolution. Certainly since the internet, you could argue what's more impactful to humanity, internet or AI, but that's not important because they're both pretty impactful. But I, in my opinion, AI is probably more impactful because I think it fundamentally changes how we human in the society view work and how we think about production, how we think about a fulfilling life, how we think about career, and how we think about our relationship with each other. And to a certain extent, you could even think about sort of the social contract we have with our government, right? In terms of labor and working with each other. Because a lot of that is going to be done by non-human, you know, I think robots and AI agents, they're going to take over white color and blue color, you know, basic locking and tackling jobs. So you mentioned, you know, you've got kids who are gen alpha. My kids fit in the same bracket. They're 9 and 10 years old respectively. As you think about sort of how you want to direct them in their educational pursuits and things that they may want to think about in terms of career options. How do you wrap your head around that? Oh, I get my gosh. This is probably one of the most favorite questions people ask when I give interviews from our limited partners, our investors to just like talking to students and other entrepreneurs. That is the Holy Grail. I think they are in a inflection point. I think that generic advice that were given last 20 years going to computer science, right? That has basically took a 180 turn. Google, I think recently just had a big layoff of a bunch of, you know, and their engineers. And I think that trend, this is just the beginning. I think it's happening because we suddenly figure out writing code could be done by AI, right? So I think the direction I give to my kids have always been pretty consistent and that is two main things. One is you gotta be, you gotta raise them so they have the ability to pick up new things, right? The ability to learn new things is more important than knowing something and doing something sort of a static feel of expertise, right? That ability to dynamically change course and become the expert in that space. And the second thing is really that love for learning. It's really important. I think you gotta love to learn new things. And that's not necessarily something you would teach, I would say. That's something you cultivate, right? Really allowing kids to explore the things you want to learn. Yes, you know, a lot of the liberal arts education in the last few decades have been shown because of how successful the science and engineering majors have been. And I would argue, I think that the table may be training, but not training back in the way that I all don't go into science and engineering. No, no, I'm just saying that I think things are gonna be a bit more balanced because you might be able to just pick up science and engineering on the fly, or you could assign that task to the AI agent or bot, right? But I think the basic education and love learning is super important. So, you know, you mentioned sort of like big picture, like, you know, how does our relationship with government, how does our relationship with sort of work change, you know, robotics and AI taking over both blue collar and white collar jobs at some point down the road? Like, if you look into your crystal ball, Andy, 20 years out, what do you think this looks like? Yeah, I think 20 years out is done correctly, and you'll have different experiments, or we're gonna have how many countries are in the United Nations call it 200? We're gonna have 200 social experiments going on, right? On how governments organize their people to get ready for this transformation? AI is just like the industrial revolution can put it back in the box, right? The toothpaste is out. It doesn't go back. Some people may try to deny it. Others may embrace it, and the people who embrace it may have different ways to go about adopting it, how you deal with the people, I think that is, it's gonna be fascinating to see, right? And as an American, I really hope our leaders do the right thing and kind of manage that transition. And I'm not a, I'm not in policymaking, so I actually don't know how you would do it. I just think that 20 years later, you will see clearly some countries would do a better job than others. And I also think one thing is a given, and that is embracing it is definitely the way to go versus trying to fight it. Because can you imagine if you try to fight the internal combustion engine, or you try to fight the steam engine, and it just doesn't make sense, right? If you embrace it, you could probably figure out a way to emerge as a winner out of this. And I'm happy to also go into both the blue color and white color work, kind of what I see as the new. Yes, please, let's talk about that, because I hear more people saying, hey, rather than getting into computer programming, get your kids to learn a trade, you know, electrician plumber, like robots aren't going to replace that anytime soon, or do you feel differently about that? Right, right. I probably wouldn't go into that little granularity, but I'll share with you, because I actually don't know, I mean, I wish I knew, right? I slightly worry if people start thinking about in that kind of granularity, because the key is to maintain optionality. I mean, you and I spoke a little bit about the football before the show. We're both NCAA fans. I think the best play is RPO, right? Rumpass option. You want to maintain your optionality, right? Because you don't know, you don't know what the defense is going to show you, so you want to be ready, right? So I won't say, hey, if it's this or that, but I will say, first, let's look at the blue color work, right? The traditional sort of very hands-on type of jobs. That appears to be pretty safe, and I agree it's safer than my job, so the classic thinking is robots, right? Taking over a lot of the jobs, and I don't disagree, right? And I think we're basically there, right? And I think it all depends on which industry verticals and what level they come in, right? So that sector or that side of the house is probably more predictable, which is a lot of the repeatable tasks. I'm sure you're automated, and I don't necessarily think we're thinking about just bots walking around. It could be as simple as a hamburger flipper that doesn't look like a bot, but that takes away the burger flipper. You see, if you talk about like electrician or plumbing, I think there will be similar type of automation that happens that reduces the amount of plumbing and electrician types of jobs. But not to worry, because I think the job will be different, and in fact I think the job transformation would happen in every industry from plumbers, electricians to doctors. So it may be, you know, we still need a plumber, but now the plumber has more sophisticated tools that they can use to do the job quicker, faster, better. Much better put, right? So they'll have analytics that tools allow them to do things remotely. By the time they get there, it's a five minute job, instead of the, you know, two hour job, they need to build, right? So as plumbers may become a quasi-blue, white color job, right? And I think it's actually, makes a lot of sense, it's similar to investment bankers before excel, right, we used to do work using, you know, I don't know, calculators and whatever, right? And it could do your job. Just the moment you have excel, you can become a lot more efficient, right? Now you have Zoom, you have PowerPoint, just that side of the house, right, the more physical work, having been as well invested, because of the barrier to the AI, barrier to entry for AI. But now I think it's good enough. So and the spreadsheet example is a really good one, right? Spreadsheets didn't do away with the need for accountants, for investment bankers, for, it gave them a tool to be able to do their jobs more effectively, more efficiently. Do you think the same thing is going to happen with AI and robotics tech, or is this different and there's going to be a deficiency of jobs now going forward? So my prediction is this, you use a 20 year timeline, which I appreciate, because I don't know I want to take. Let's just say that the end steady state, or that sort of the, there's probably going to be some fluctuation in some countries, it will be good, some countries not so good. But the end steady state, what I expect, is a human race, all of us work less, right? We will work fewer hours, just like my grandparents, you know, my grandparents, they, you know, they grew up in China, they were farming, right, or they have farmers working for them. I don't think they have this idea of 8 to 5, it's that, you know, it's dawn to dusk. I don't think they take Sundays off, right? It's seven days a week, you just work, work, work, work, work, and you can barely feed yourself, right? So my quality of life is better than my parents, and my parents better than their parents. I think our kids certainly will work fewer hours, right? But I think those hours they work, it's going to be a lot more impactful, right? So for instance, we can talk about doctors. In the US, it's notorious, we complain about our doctors don't spend enough time with us. And doctors complain, they work too many hours, so what gives, right? I think what gives is, you know, I made an investment, um, almost seven or eight years ago. Unfortunately, it actually went under, right? So this is a sad story of investing in the right technology too early, and they didn't make it. So it's an AI doctor, this was in 2016, and they essentially built a LLN for doctors, right? So it could tell you, you could say, hey, Anthony, you know, AI doctor, I'm this, I'm that, I have a headache, and the doctor would say, oh, I remember seven years ago, you had a headache too, but don't worry, that was unrelated. Before, if I had, you know, recurring headache, I remember seven years ago, three years ago, last month, you should probably get a brain scan, right? So you could do all of that, and today that's very easily done. But what's important is they figured out, it's not about, so this AI doctor used to score higher than the human doctor even seven years ago, they would take the US, you know, medical exam for doctors, and it would perform better, of course, because this AI doctor had, you know, wealth of information on the internet, and remembers everything that needs to be remembered from medical school, human doctors can't do that. So, but what they, what this company discovered was, if you just make this a tool to let the doctor use it, the two combined score even better than the machine or the human, right? So really is a win-win. So I think what's going to happen is, now with the advent of all the large language model and the small language model, yeah, the specific models for doctors, doctors would become much more productive. Human patients would trust that AI doctors have been more for little things, I don't need to bother my doctor, my doctor could focus on the big things, and my doctor would become much more accurate in his or her diagnosis, right? So, really, the doctor's job is to handle that 5% cases where it may have a difficult delivery to the patient and say, hey, you got this illness, yes, it sounds very bad, but we have these options versus a AI doctor that may sound like a human, but you know it's not, right? So I think at least for me as a patient, you still want the bedside manner of the human doctor. Absolutely. Absolutely. And where, where are we in sort of the timeline, are doctors using AI now in their diagnosis? Not yet. Not yet. Why? What's standing in the way of that? That's the regulation liability, it's all the non-engineering and science stuff. The tech is there, it's just, the human beings aren't comfortable with it from a regulatory or from a risk standpoint. Right. I mean, you can't even do a Zoom call with your doctor unless you're licensed in your state. Right? There's some weird, there's some HIPAA rules about, you know, data privacy and compliance. Like, I can't, so for instance, I have an oncologist I talked to in Texas, but I don't think he could just Zoom with me, have to go to Texas, go see him, right? So you need that kind of, there are some patient protections in the way of the technology. I'm not saying it's all bad, I'm sure the regulations were there for a reason. I'm not a policymaker. I just think that the tech is ready. The patients are ready. So once the regulator's opened up the floodgate to make sure we're fully protected, I think the adoption is going to happen, and the world will be a better place. What's something outside of sort of the AI and robotics realm that you're excited about that maybe isn't getting a lot of attention? That isn't getting a lot of attention. So I'll share with you some of the investment thesis I'm looking at now. Since I'm an engineer, I typically don't, as opposed to a scientist, I don't take scientific risks. I take engineering risks and commercialization risks. So what that means is that I don't invest in things that require scientific breakthrough. So oftentimes my investment thesis involves taking interesting things and put them together. So in engineering, I call it integration. So right now I'm looking at integrating AI, robotics, and blockchain technologies. So the idea is this. The idea is that you know, we can make these really interesting smart AI agents that could probably do a lot of things for you already. You know, I could ask a lot of the questions I asked our investment analyst. I could just ask the AI agent what's the market size of this, what's the market size of that, what's the competitive landscape of this, what's the competitive landscape of that, what's margin structure, what's the trend. So the AI agents can do all of that. And on the blockchain side, you know, you have these very efficient micro-payment technologies that are already in place. That could help you transact in the, you know, 5 cents, 50 cents without any trouble. So the idea is maybe you could combine these AI agents and have them transact with each other, right? The AI agents would represent you for me, right? And they could just go through financial transactions based on their need. You and I as humans, we don't need to get in the middle of it. [BLANK_AUDIO] So, I really like your podcast, right? But for you to set up a subscription, that's just too much, you know, overhead, right? Why not set up some sort of interesting structure where you could just take five cents, ten cents a dollar every time somebody listens to a podcast, right? But I don't think so. It would somehow be hooked into Spotify or Apple Podcasts on my website every time you listen to an hour of it, I get paid a nickel or something like that. And the pricing could be different. It could be just based on like, I might have an AI agent. I give the agent a budget, right? The budget may be 50 bucks a year. The agent is just going to know over time, Andy really likes business podcasts, right? Love macroeconomics, political podcasts. But it's not as much interested in entertainment because I'm kind of boring guy, it was just like sports and business, that's my thing, right? So the AI agent figures out over time, right? Andy's will be happy to pay five cents per hour, right? And then maybe over time it creeps up to six cents per hour of the podcast I listened to. And that just happens in the background without me knowing, right? And if I keep listening to more, the agent's going to say, "Oh, I bet he really support this initiative." He loves this, you know, I happen to also be an animal welfare advocate. So this animal podcast, he really, it's probably underfunded. Andy will probably play a dollar in it because there are no other supporters. He really wants to step up. So those are the things I think is suitable for AI, sort of integration, AI plus blockchain. Right? And then I'll think of another one. I used to work for ABB, one of the biggest power generators in the world. The challenge has always been, how do we generate power where it's consumed? And you say, "Well, that's easy, we got solar panels." But the problem is, when you generate solar power from a solar panel, that power logically goes back to the grid, you sell it back to the grid, and the grid sell it to your neighbor. Right? Because the grid is this thing that has a steam power generation. It literally boils water a couple hundred miles away. You fire some gas turbine, boils water, and that turns into a steam turbine and generates mechanical power. Convert that to electricity. Right there, and then you lose about 30 to 40% of your energy. Right? Wow. And then, I mean, that's not just the beginning. By the time it gets through transmission distribution to your house, you lose another 30%. So essentially, you're down to, I don't know, 30% of what you started with. So really, the goal is you and your neighbor start trading energy. You won't be able to send it from one of us directly to the other. Yeah. And then, and then, so the challenge is not in the physical connection, but it's in the, it's in the finance. Right? How do I trade with my neighbor? That's where AI agent steps in again. Right? So you have, essentially, the AI agent talked to each other and say, "Hey, you know, I want to sell my electricity. My boss is not home. I got all this thing generated for my solar panel. But you guys seem to be home. Kids playing computer games and, you know, dad cooking, right? So why don't I send over some electricity to you? Well, how much do you want to buy? The agent could look at the spot price and figure it out. So conceptually, this is an idea that you're really excited about. Are you invested in tech that's working on this? Well, so I gave a couple of examples of what could, we have investments and I would probably have won investment in the decentralized solar trading. But I think it will happen more. And I tell you a lot of these things would happen in this cycle with the current administration. They really lifted the blockchain technology trade in the US. So you're probably going to see more of that. And you think unlocking blockchain access is important to these micro transactions that you're talking about. You don't think it can be done, sort of, on the current infrastructure, the existing payments. It's too expensive. Right. And then, really, I think the point. Sorry, sorry, I want to come back to that point for a second. It's too expensive because of the current players who control how money can move around visa, mastercard, you know, the Swift system, the ACH, et cetera. And so with blockchain, now you wipe out or greatly reduce those costs. Now you've got a cheaper infrastructure to do it. Yeah, you enable here to here, right? Really two things. One is just the overhead. The legacy technology is just more expensive. It's not like they're trying to. I don't think they're gouging us, right? I just think that the technology is more expensive. They need to charge you 3%. For them to make a profitable living as a public company. And I respect that. So it's really just the next generation of technology doesn't take 3%. And that is really helpful for micro transactions and high-frequency transfers. And that's one. And the second thing is about the open network. The idea of open network is really important. Because if you have open network that allows people to develop these agents that could trade. Because I bet you're going to have a thousand agents launched by people and ten of them really work well. And those are the ten that survive. And I don't know if solar trading is one of them. That might be another sort of pinhead idea that doesn't work, right? But the important things. Is to try these seemingly crazy ideas. Because if one or two of them work that could transform humanity. So the idea is blockchain and AR agent. Those are the transformative technologies. They happen to become available around this time. So when you start combining them. Do you see some interesting things? And then you throw robotics into the mix. So you can suddenly have. You don't know what you're going to get. But when you have these enabling technologies, becoming available for the first time. Let's take a step back for a second, Andy. And I mean, I want to talk a little bit more about sort of the big picture of Draper. There's Draper University, there's Draper Dragon, Draper Associates. What's kind of the bigger vision that you and Draper are driving towards? So just as an introduction. So Tim Draper is the founder of these entities. He has been in business. He's a third generation venture capitalist. Came from his grandfather. So he started the Draper platform 40 years ago. And over time, he had created many pieces of these puzzles to serve entrepreneur. So for instance. So Draper Associates was the oldest entity he started. Which is just a pure investment platform. Early stage venture capital. Over time, he added on pieces. So he added on Draper University, which is a school for entrepreneurs globally. And Draper Dragon was one of the funds he and I created to do international investments. And then there is also a TV show called Meet the Drapers, where we have a shark tank style. The TV show for entrepreneurs to come and pitch to the investors on Meet the Drapers. And the difference from shark tank is that these are actually venture backable ideas versus product companies. So these are the key components. We have venture fund and Draper Associates are flagship fund. Early stage seed series a venture fund. And then we have Draper University, which provides entrepreneur education for young people. Call it 20 to 30 something year old first time or early entrepreneurs. We just want to learn about that Silicon Valley magic. And we have been in business since 2012. And have over 5,000 people who have gone through the program. And drawn from the 102 countries. We recently finished our 30th cohort at Draper University. And we have produced successfully produced over 7 unicorn companies from scratch. Unicorn being defined as over a billion dollars in value. And technology, technology companies over a billion dollar valuation. And Meet the Drapers were on our season 8. And we currently have 20 million viewers around the world. And where can we find this show? It's on DraperTV.com. Okay, online. DraperTV.com. I'd like to hear a little bit about DCX. This invite only alliance of family offices. What was the inspiration for starting that? And what are members, what value do they get? Yeah, so this was started. I want to say to you. 2013 or 2014. And the idea was, you know, we have limited partners in our venture fund. These are basically our investors, right? And we notice over time, we have, we are investors include pension funds, foundation, sovereign wealth funds. And then we notice this one category, family offices, we're growing very fast. Then I realized what's happening was, we noticed a lot of the generational transition from sort of families core business, like grandfather, father made money in paper, pulp, industrial, real estate, whatever. And then second generation took over, ran the core business, the third generation took over and they want to do something different. And oftentimes I would say probably 100% of the time they want to get into tech investing. So what we did was we first started this really, you know, what I call a technology retreat. We can program just to show our family office partners how we think about investing in technology. And it's a program, it started over, you know, sort of three day duration. We have now successfully condensed down to one day, right. And that one day we talk about, you know, Mac for economics, we talk about different asset classes for fuller construction for family office. And specifically, we hone in venture as an asset class. And then we talk about our best practice in making investments. And then we talked about how to select entrepreneurs and CEOs. And then we actually put them through an actual series of pitches when we interview entrepreneurs, they get to see how we kind of make our decisions. So it's a technology retreat is a way to just bring more awareness into family office, how to make technology investments with the emphasis on venture capital. So what are you looking for in an entrepreneur and a founder? What are some of the telltale signs that this is a guy or a guy we want to be involved with? Yeah, so we really try to narrow down to two main things, right. And these are two main things I think you'll find in every company, just to keep it very high level. That is we look for opportunities in the very large market, very large market. Venture by nature is highly risky. So the success rate sometimes is not so high. So the idea you want to, if you are able to make a successful venture, you want to make sure it really counts. So oftentimes the size of the exit is directly driven by the size of the opportunity. So that's one thing, essentially looking for a big market or big potential market. And we can kind of dig in some other characteristics, but I want to kind of leave that and then go to the other side of the equation. The other side of the equation is I could change business plans and I can change founders or people. So the team is super important. We want to find the ideally a group of people, right, who are passionate about the mission, but also experts in their space. And these people could essentially take you into that market they're going after. So that's sort of the very simple formula for early stage investments. Is that primarily what you do or early stage investments or are you also getting involved with companies that have kind of proven themselves a bit more and they're just looking for some growth capital? Good question. So we do growth as well, especially growth capital for our own companies. So I'll just describe this in the slightly nerdy but technically accurate language for both early stage and late stage criteria. So in statistics there's something called the false positive and false negative error, right. So early stage I want to make sure I minimize false negative error. Translation, I want to make sure if it's a good company, I don't inadvertently make the mistake of turning it down. That's called a false negative, right. You could probably sort of realize why that is because if it's the next Robinhood or Coinbase, you would hate to turn it down to the seat stage, right. So you want to minimize false negative. At the late stage I want to minimize false positive and the reason is I'm typically writing a larger check. So for me I actually want to make sure if I'm investing in let's say the growth around a Robinhood or Coinbase, it is priced properly, it is indeed going to become the next thick coin, right. Because at that point I'm kind of paying up, I'm paying the higher valuation. So I rather avoid making mistakes, right. So the mistake there is to make them wrong investment. And the early stage, the mistake is to not make the investment what you're supposed to make investment, doesn't make sense. So we look at the. Makes a lot of sense, sure. You don't want to miss out on what could be the next big thing but they're harder to spot at that stage because they're just kind of a kernel of an idea. So maybe you're making more bets at that stage saying we know that a smaller percentage of these are going to make it through but fear of missing out, I make sure like I'm involved in this if it does hit. Yeah, right. And then those later stage companies, you're writing a bigger check. The valuation is not so much in your favor at that point. So you want to be a little bit more cautious there. Right. Absolutely. Perfectly put. Yeah. Yeah. You know, somebody who's done and seen as much as you have Andy, obviously you've seen a lot of successes, you've been involved in a lot of unicorns. I'm sure that you've had your fair share of challenges, whether they're personal or professional. I'd be curious to hear about a particular instance, a big challenge that you've had to work through and what you learned kind of going through that process. Yeah, I'll share personal obstacle I went through and it kind of changed the way I look at the world. So I was diagnosed with cancer in 2011. And unfortunately, you know, there's no evidence of disease now. But I think what that changed me the way so I think how I've changed from there was, A, I became a lot more interested in the confluence of computer science and biology. Right. I got to really learn about America's healthcare system and our pharmaceutical industry and drug development and realize they're they're about to go through a transformative change in those industries. And that's how I actually got into the AI doctors. I looked at, you know, AI-based drug discovery companies. Right. Because I feel like coming from the electronics industry in an electrical engineer, you know, one of my love for science is quantum mechanics. I love the idea of being able to study atoms and electrons and particles down to the molecular level. Right. And the ability to predict statistically where these atoms are going to be. That's physics. That's engineering. But when it comes to biology and medicine, people say it's an art. I think it's more of a science now. But I would like to see the art and the science become engineering and then become manufacturing and becoming more of a retail product. Right. Have you ever had an iPhone issue? You go back to the Apple store and you say, hey, how does this work? How is it? And almost a hundred percent of time. Right. They'll come up with the reason and say, all right, this is because you need the new software upgrade. Oh, because this phone is actually broken. There's a component. And then I bet if they take that phone back to their manufacturer, they'll say, oh, yeah, this component went through the diffusion chamber and the fab. And then there was one, you know, gas valve didn't turn on. So it didn't provide the right doping for the chip. So the electrons were moving as fast. So you have a short circuit here. That's why the application doesn't work for the client. There is a deterministic solution for a consumer, a retail problem. Right. On the healthcare side, if you go to your doctor and say, doctor, my head hurts. Right. First of all, I don't think the doctor doctor probably tell you, like, great, you know, stress, dehydration, rest, take some Tylenol and let's observe. Right. You certainly can go back to the manufacturer. Your mom and dad and say, hey, mom, you know, I want to refund your mom and dad. Get the hell out of here. So I think my goal is to move our healthcare system closer to manufacturing and retail experience. Right. And oh, away from this more of a art and science, you know. And I think we're now probably closer to engineering, but I want it to be at the manufacturing and retail experience. It's inexpend, it's affordable, right? It's deterministic and it's not scary, right? So it's not a-- - How do you do that? How do you get there? - I think it's entrepreneurship and venture capital. I really think it's really-- - So those are two ingredients, but what if some of the in between stepping stones look like, do you think? - Yeah, I think a lot of the technologies are-- I wouldn't say they're available, that I think they're getting there, right? So for instance, like the diagnosis, right? I think for what I went through as a cancer patient that the amount of time it takes for uncertainty, the tests, the invasive tests, a lot of that should be, could be shortened, you know? The amount of time, if you're going to doctor get an x-ray, it takes, you know, at least 24 hours, and then you look at the radiology report, you're like, what the heck is that? By the way, every radiology report at the end of it, you'll have the sense, may need attention, right? That's both scary and unhelpful, you know? Of course it needs attention, right? So my radiology report was ignored for three to three years, because the doctor wasn't paying attention, there was a tumor there, the doctor basically just overlooked it, and you know who discovered it? It's somebody who took an economic interest in me, it's an insurance underwriter, the insurance underwriter looked at it, because I was applying for life insurance. Most of us have no business and go and read their medical, I assume you haven't pulled your medical records and try to read it, right? I wouldn't even know how to do it. Oh, exactly, right? So when I applied for life insurance, insurance agents said, hey, you know, fill out this form, and I did whatever, I didn't know what he was doing. And then a few days later, it came back with a 70 page report. Now it's probably 700 pages. 70 pages were when I was quote unquote healthy, a healthy 39 year old. And so he said, well, what's this? And I said, what do you mean? And I started reading, as a layman, I started reading, I was like, this needs attention, this needs attention, right? So I think there's a lot of longing for it. There's a lot of things I could just do and just learn, doctors are busy. And I went to Stanford Medical Center, this is not like I Andy went through some, you know, county clinic, right? Andy went to Stanford Medical for my primary care. So these things happen, you know, it's not due to lack of talent, right? It's due to the lack of-- - We're human beings, we get distracted, we miss things. - Absolutely, absolutely, right? There's no finger pointing, it's just, you know, we all need a little bit help. I mean, I want to create an AI agent that could help me become a better investor, you know? - So Andy, you talked about how your cancer diagnosis generated this interest in computer science and biology sort of coming together. But I'm curious what impact it had on you, sort of on a personal side, like mentally, emotionally? Like how did you sort of deal with this heavy news? - Yeah, so I think the biggest challenge is actually the trust for the medical system. That's probably the biggest challenge, right? I suddenly realized our doctors are spread thin and they cannot be fully-- I could not fully rely on them, right? And again, it's not finger pointing, it's just a reality. They got lives, they got kids, they got busy stuff going on, I can't rely on them. If you want, which is a kind of interesting conclusion to reach because I know if I tell you, hey, you cannot rely on your professor for learning. You cannot rely on whatever pick, you know, your plumber for this or that. You say, "Hey, of course, I cannot." But if I say, "You cannot rely on the doctor for your health," you're like, "What? What am I gonna do?" But that's the state of American healthcare. You have to take ownership, right? And most of us just don't have the time, the resources. And even though how to do it. And that's why I think using AI is a way to go. And so I personally dealt with it just over time, right? Kind of-- - Any support systems? - Yeah, I don't know, outlets that you found that were helpful. - I say, "Consiered Medicine" is a stop gap, right? Essentially, you got to pay. I mean, I hate to say it, but, you know, it's just, that's our system. If you don't pay, you get the minimum sort of level of service. And to me, that is not good enough for anybody. I don't care how rich or poor you are. I just think that it's not adequate for what happened to me. Right? I don't think it's good enough. I think you got to either pay or ramp up AI. So everybody's got someone sort of writhing the risk management for their health care. - Andy, how would you characterize your superpower? - I think my superpower is super-transparent direct and analytical. - That sums it up pretty neatly. (laughing) I just got one more question that I'm pretty Andy, but before I ask it, excuse me, I want to do two things. I want to invite anybody listening today to, go ahead and hit the follow button on your favorite podcast app. We've had a really great interview here today with Andy Tang from Traper Associates. And I want you to continue to get more wonderful content like this. Andy, I also want people to know the best way I get in touch with you directly or to continue to follow your story. What would that be? - LinkedIn, I'm very active on LinkedIn. So a lot of thoughts that I share with you here, either have been published on LinkedIn or will continue to share. I found that to be a great community of people. And it's a decent publishing platform for thoughts. - And we'll include a link to that in the show notes here on our site, folks. But if you're just listening, you can look up Andy Tang and it's a Traper Associates on LinkedIn, you'll be able to find him pretty easily. So last question for you, Andy. You and I have had a nice conversation here today. I hope that we keep in touch. Let's say, any year from now we reconnect and you're excited and you're celebrating something. What's that thing? You said in a year, right? I am hoping I could play better tennis with my son. I have 11 year old and he keeps beating me. So I need to figure out a way to get better at tennis. And it's not an easy, he's growing. He's spending more time on tennis. So I got to figure out a way to be more efficient at acquiring skills. I love this answer. You're a man who's battled cancer. You're a man who's helped build multiple unicorns. You're investing in some of the leading tech in the world. You are right on the bleeding edge of everything. And the thing that you want to be celebrating a year from now is beating your 11 soon to be 12 year old son in tennis. That's awesome. That shows a great focus on life priorities. - Thank you, and it was great speaking with you. - Thank you for the work. - Yeah, thank you, Andy. I wanna thank you for setting aside both the time and the energy to share your story today. I'm grateful for it. And folks, that's a wrap on another episode of the Inspired Stories podcast. Thanks for learning with us today.