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

Anthony Codispoti: 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 Codispoti 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, web three and defense tech. He has helped build over 15 unicorn startups, including Oklo and Novelbeam 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, refining 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, AddBack 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 in extra cashflow 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.

Andy Tang: Thanks for having me.

Anthony Codispoti: So Andy, you received some notable degrees in your education, a master's in engineering from MIT, an 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 pull to get involved in the investment side of the

Andy Tang: I think I've always had interest in the business side of the world. As an engineer, most of us want to create things. And many of us have 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, first 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 intranet revolution. So I think that's when I got really exposed to computing and how that affects intranet and the real world application.

Anthony Codispoti: 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?

Andy Tang: I think it was really the first time you have a computer chip that enabled many customers such as Compaq, IBM, Dell, the world to make an affordable computer for everyday consumers. I remember even my parents and ourselves were able to afford a computer when Intel first came out with that Pentium processor. And at the same time, the power you could deliver from a Pentium processor was just more than anything you could imagine. You could watch video. It was a big deal. You could run a spreadsheet. You could surf the web. So it was really that first price performance the tech industry was able to deliver for the everyday person.

Anthony Codispoti: So I want to 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.

Andy Tang: come again so what time frame or any time frame

Anthony Codispoti: Any time frame, but I was we talked a little bit about Intel so something between Intel and Draper What was a career stop along the way that you know had a particularly big impact on you?

Andy Tang: Yeah, okay. Yeah, so between Intel and Draper, I worked on Wall Street, I worked for Credit Suisse First Boston. And I worked for two of the most, I would say interesting bankers of our time, you know, during that era, Frank Patrón and George Boutros. So they were the tech banker of our our times. That was the very first time I think Wall Street really turned to Silicon Valley and said, my gosh, these are great partners of ours. We could help them raise money, access to capital market. This was in the late 90s, early 2000s. And I remember the biggest challenge for us was being a 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 dot 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 &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, you know, hype curve. Any good idea, you're going to have investors getting ahead of itself, 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 gonna happen right away. But no, it doesn't happen right away. And I'm not telling anything new. So everybody knows that we underestimate how long it takes for consumers to adopt. But the second thing will probably surprise you. The second thing is that most of us, VCs included, we underestimate the impact of these technologies. Would you ever imagine?

Anthony Codispoti: That does surprise me. No, because like, 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 on this.

Andy Tang: Right. Yeah. Right. So AI, why don't we talk about something that already happened you could identify to, right? So in 1999, you and I are kind of, you were 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 have 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. the idea of no buffering, it just happens real time. You can 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. In fact, some of those fiber optics and optical component companies that we took public, the amount of infrastructure we built in 2000, it's still probably abundant even for application today. And that's a fact. All these fiber lines we lit up, 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 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...

Anthony Codispoti: So multiple channels on basically the same pipe. It wasn't possible before, but now because we're sending different wavelengths, different colors, then you can send them and they're not interfering with each other.

Andy Tang: And that was available 25 years ago. Correct. That was available 25 years ago. But 25 years ago, we had other problems. People weren't streaming Netflix on their phones. But today we are. And finally, those technologies became useful. So it goes to say a lot of these technologies have always been ahead of themselves. 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. 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. This is just the way it is, but no, it's not always been this way, right? So, and you talked 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. Because that's essentially my job is to, I call it predicting the future, but I'm cheating a little bit. It's so much easier to predict the future. It's hard to predict the time in which the future is gonna happen.

Anthony Codispoti: So what do you think the future of AI holds? What are you seeing in your crystal ball that maybe the average person isn't?

Andy Tang: Yeah, I think all of us would work differently. It's the industrial revolution 2.0, right? I think it's 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 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. I think robots and AI agents, they're going to take over white color and blue color, basic blocking and tackling jobs.

Anthony Codispoti: So you mentioned, you you've got kids who are Gen Alpha. My kids fit in the same bracket. They're nine 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?

Andy Tang: 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. think they are in a inflection point. I think that generic advice that we've given the last 20 years go into computer science, right? That has basically took a 180 turn. Google, think, recently just had a big layoff, a bunch of their engineers. And I think that trend is, this is just the beginning. I think it's happening because we suddenly figured out writing code could be done by AI. 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 raise them so that they have the ability to pick up new things. The ability to learn new things is more important than knowing something and doing something, sort of a static field of expertise. That ability to dynamically. change course and become the expert in that space. And the second thing is really that love for learning. 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. Really allowing kids to explore the things they wanna learn. Yes, a lot of the liberal arts education in the last... few decades have been shunned because of how successful the science and engineering majors have been. I would argue, I think that the table may be turning, but not turning back in a way that all don't go into science and engineering. No, no, I'm just saying that I think there's 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 an AI agent or a bot. But I think the basic education and love for learning is super.

Anthony Codispoti: So you mentioned big picture, how does our relationship with government, how does our relationship with work change, robotics and AI taking over both blue collar and white collar jobs at some point down the road. If you look into your crystal ball, 20 years out, what do you think this looks like?

Andy Tang: Yeah, I think 20 years out, if done correctly, and you'll have different experiments, we're going to have how many countries are in the United Nations? Call it 200. We're to 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't 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 in... policy making, 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, right, 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 job.

Anthony Codispoti: 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. know, electrician, plumber, like robots aren't going to replace that anytime soon. Or do you feel differently about

Andy Tang: Right, right, right. I probably wouldn't go into that level of granularity, 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 you and I spoke a little bit about

Anthony Codispoti: Okay.

Andy Tang: football before the show, we're both avid NCAA fans. I think the best play is RPO, right? Run past 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 collar 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. And I think we're basically there. And I think it all depends on which industry verticals at what level they come in. So that... that sector or that side of the house is probably more predictable, which is a lot of the repeatable tasks should get 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 that burger flipper job, 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 that job transformation would happen in every industry from plumbers, electricians to doctors.

Anthony Codispoti: 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.

Andy Tang: Absolutely. Yeah, much better put, right? So they will have analytics tools that will allow them to do things remotely. By the time they get there, it's a five minute job instead of the two hour job they'd need to build. So a plumber may become a quasi blue white collar job. And I think it's actually... It makes a lot of sense. It's similar to investment bankers before Excel. We used to do work using, I don't know, calculators and whatever. You could do your job. The moment you have Excel, you become a lot more efficient. Now you have Zoom, you have PowerPoint. That side of the house, the more physical work, haven't been as well invested because of the barrier to entry for AI. But now I think it's getting there.

Anthony Codispoti: So the spreadsheet example is a really good one, 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 and more efficiently. Do you think the same thing is gonna happen with AI and robotics tech, or is this different and there's going to be a deficiency of jobs now going forward?

Andy Tang: So my prediction is this, you use a 20 year timeline, which I appreciate because I don't know how long it's going to take. Let's just say that the end steady state or that sort of the, there's probably going to be some fluctuations 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, know, my grandparents, 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 eight to five. 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. And you can barely feed yourselves, 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 gonna 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, almost seven or eight years ago. Unfortunately, it actually went under. 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 build a LLM for doctors. So it could tell you, you could say, Anthony, AI doctor, I'm this, I'm that, I have a headache. And the doctor would say, I remember seven years ago you had a headache too, but don't worry, that was unrelated. Or if I had recurring headache, you'll remember seven years ago, three years ago last month, you should probably get a brain scan. So you could do all of that. And today that's very easily done. But what's important is they figure it out. It's not about, so this AI doctor used to score higher than the human doctor even seven years ago, they would go take the US medical exam for doctors and it would perform better. And of course, because this AI doctor had wealth of information on the internet and remembers everything that needs to be remembered from medical school. Human doctors can't do that. but 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 it 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, the specific models for doctors, doctors will become much more productive. Human patients will trust the AI doctors a bit more for little things. don't need to my doctor could focus on the big things. And my doctor would become much more accurate in his or her diagnosis. So really the doctor's job is to handle that 5 % cases where it may have a difficult delivery to the patient and say, 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. So I think at least for me as a patient,

Anthony Codispoti: You still want the bedside manner of the human doctor. Where are we in sort of the timeline? Are doctors using AI now in their diagnosis? Why? What's standing in the way of that happening?

Andy Tang: Absolutely. Absolutely. Not yet. Not yet. I think it's regulation liability. It's all the non engineering and science stuff.

Anthony Codispoti: The tech is there, it's just the human beings aren't comfortable with it from a regulatory or from a risk standpoint.

Andy Tang: Right, right, right. I mean, you can't even do a Zoom call with your doctor unless they'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. I have to go to Texas, go see him, right? So you need that kind of, there was some,

Anthony Codispoti: Mmm.

Andy Tang: 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 policy maker. I just think that the tech is ready, the patients are ready. So once the regulator opened up the floodgate to make sure we're fully protected, I think that adoption is gonna happen and the world will be a better place.

Anthony Codispoti: 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?

Andy Tang: that isn't getting a lot attention. Most, yeah, so I'll share with you some of the investment thesis I'm looking at now. Since I'm an engineer, 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 that integration. So right now I'm looking at integrating AI, robotics, and blockchain technology. So the idea is this. The idea is that you... you know, we can make these really interesting smart AI agents that could probably do a lot of things for you already, right? You know, could ask a lot of the questions I were 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 the margin structure? What's the trend? So the AI agents can do all of that. And on the blockchain side, you you had these very efficient micro payment technologies that are already in place that could help you transact in the, you know, five cents, 50 cents without any trouble. Right. So the idea is maybe you could combine these AI agents and have them transact with each other. right? These AI agents would represent you or me, right? And they could just go do financial transactions based on their need. You and I as humans, we don't need to get in the middle of it. For example, 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, 10 cents, a dollar every time somebody listens to a podcast. But I don't know.

Anthony Codispoti: And so it would somehow be hooked into Spotify or Apple podcasts and so, or my website. And every time you listen to an hour of it, I get paid a nickel or something.

Andy Tang: Yeah, it's completely independent. Yeah. Yeah, and then 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 gonna know over time, Andy really likes business podcasts, Loves macroeconomics, loves political podcasts, but is not as much interested in entertainment, kind of boring guy. was just like sports and business, that's my thing, right? So the AI agent figures out over time, 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 gonna say, I bet he really support this initiative, right? He loves this. I happen to also be an animal welfare advocate. So this animal podcast, really is probably underfunded. Andy will probably pay a dollar an hour 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. And then I'll give you 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. 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. that's 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 both have sold your energy. Yeah, and then, so the...

Anthony Codispoti: be able to send it from one of us directly to the other.

Andy Tang: The challenge is not in the physical connection, but it's in the finance. How do I trade with my neighbor? That's where AI agent steps in again. So you have essentially the AI agent talk to each other and say, hey, I want to sell my electricity. My boss is not home. I got all this thing generated from my solar panel, but you guys seem to be home, kids playing computer games. dad cooking, right? So why don't I send over some electricity to you? How much do you want to buy? The agent can look at the spot price and figure it out.

Anthony Codispoti: So conceptually, this is an idea that you're really excited about. Are you invested in tech that is working on this?

Andy Tang: So I gave a couple examples of what could, do we have investments? I would probably have one 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.

Anthony Codispoti: And you think unlocking blockchain access is important to these microtransactions that you're talking about. You don't think it can be done sort of on the current structure of the existing payment systems.

Andy Tang: It's too expensive. And then it really, think the beauty.

Anthony Codispoti: Sorry, sorry, and yeah, 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, know, the Swift system, ACH, etc. And so with blockchain, now you wipe out or greatly reduce those costs. Now you've got a cheaper infrastructure to do it.

Andy Tang: pain. Yeah. Yeah. Yeah. Yeah, you enable peer to peer, 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 microtransactions and high frequency transfers. That's one. And the second thing is about the open network. The idea of open network is really important because if you have an open network that allows people to develop these agents that could trade, because I bet you're to have a thousand agents launched by people and 10 of them really work well. And those are the 10 that survived. And I don't know if solar trading is one of them. That might be another sort of pinhead idea that doesn't work. But the important thing is you got to try these seemingly crazy ideas because if one or two of them work, they could transform humanity. Right. So the idea is blockchain and AI agent, those are the transformative technologies. They happen to become available around this time. So when you start combining them, you see some interesting things. And then you throw robotics into the mix, right? So you can suddenly have, you don't know what you're going to get when you have these enabling technologies becoming available for the first time.

Anthony Codispoti: Thanks. So 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, what's kind of the bigger vision that you and Draper are driving towards?

Andy Tang: So just as an introduction, so Tim Draper is the founder of these entities. So he has been in business. He's a third generation venture capitalist. Came from, you know, his grandfather, right? So, so he started the Draper platform 40 years ago. And over time he had created many pieces of these puzzles to serve entrepreneurs. 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, right? And Draper Dragon was one of the funds he and I created to do international investments. And then there's also a TV show called Meet the Drapers, where we have a shark tank style. 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. have venture fund and Draper Associates. That's our 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 who 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 successfully produced over seven unicorn companies from scratch.

Anthony Codispoti: Unicorn being defined as over a billion dollars in value

Andy Tang: Yeah, in technology companies over a billion dollar valuation. And Meet the Drapers, we're on our season eight and we currently have 20 million viewers around the world.

Anthony Codispoti: Where can we find this show?

Andy Tang: It's on drapertv.com.

Anthony Codispoti: Okay, online, drapertv.com. I'd like to hear a little bit about VCX, this invite-only alliance of family offices. What was the inspiration for starting that? And what are members, what value do they get?

Andy Tang: Yeah. Yeah, so this was started, I want to say 2013 or 14. And the idea was, we have limited partners in our venture fund. These are basically our investors, right? And we notice over time, our investors include pension funds, foundation, sovereign wealth funds. And then we notice this one category, family offices, been growing very fast. Then I realized what's happening was we noticed a lot of the generational transition from sort of family's 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 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 weekend 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 it down to one day, right? And that one day we talk about you know, macroeconomics, we talk about different asset classes, portfolio construction for family office. And specifically we hone in on venture as an asset class. And then we talk about our best practice in making investments. And then we talk 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 offices how to make technology investments with an emphasis on venture capital.

Anthony Codispoti: 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 gal we want to be involved with?

Andy Tang: you 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, right? Venture by nature is 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 that and then go to the other side of equation. The other side of the equation is I could change business plans, but I can't change founders or people. So the team is super important. We want to find ideally a group of people 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 investment.

Anthony Codispoti: Is that primarily what you do are 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 cap?

Andy Tang: Good question. So we do growth as well, especially growth capital for our own companies. 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. 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. Let's call it false negative. You can probably sort of realize why that is because if it's the next Robinhood or Coinbase, you would hate to turn it down at the seed stage. So you want to minimize false negative. At the lay 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 the Robinhood or Coinbase, it is priced properly. It is indeed going to become the next dick of corn, right? Because at that point, I'm kind of paying up. I'm paying a higher valuation. So I'd avoid making mistakes. So the mistake there is to make the wrong investment. And the early stage, the mistake is to not make the investment when you're supposed to be making investment. Does that make sense? So we look at the

Anthony Codispoti: Makes a lot of sense. Sure. You don't want to miss out on the, 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, more bets at that stage saying, well, we know that a smaller percentage of these are going to make it through, but, fear of missing out. I, I've been to make sure like I'm, 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.

Andy Tang: Great, absolutely, perfectly put.

Anthony Codispoti: 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.

Andy Tang: Yeah, I'll share a 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 is 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. I got to really learn about America's healthcare system and our pharmaceutical industry and drug development and realized 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 and a 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's it? And almost a hundred percent of the time, right? They'll come up with a reason and say, all right, 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 in the fab. and then there was one gas valve didn't turn on, so it didn't provide the right doping for the chip. So the electrons weren't 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. On the healthcare side, if you go to your doctor and say, doctor, my head hurts, First of all, don't think the doctor would probably tell you, right, 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, I want a refund. Your mom will be 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 away from this more of a art and science, you know, and I think we're now probably closer to engineering, but I wanted to be at the manufacturing and retail experience. It's, it's inexpensive, it's affordable, right? It's deterministic and it's not scary, right? So it's not a block.

Anthony Codispoti: How do you do that? How do you get there?

Andy Tang: I think it's entrepreneurship and venture capital. I really think it's really.

Anthony Codispoti: So those are two ingredients, but what is some of the in-between stepping stones look like, do you think?

Andy Tang: Yeah, I think a lot of the technologies are, I wouldn't say they're available. I think they're getting there, right? So for instance, 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, even 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 sentence, may need attention, right? That's both scary and unhelpful. Of course it needs attention. So my radiology report was ignored for two to three years because the doctor wasn't paying attention. There was a tumor there. The doctor basically just... It 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 in going read their medical. I assume you haven't pulled your medical records and try to read it, right? No, exactly. So when I apply for life insurance,

Anthony Codispoti: I wouldn't even know how to do it.

Andy Tang: insurance agent said, hey, 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 low hanging fruit. There's a lot of things AI could just do and just alert you, all doctors are busy. And I went to Stanford Medical Center. This is not like Andy went to some county clinic, right? Andy went to Stanford Medical for my primary care. So these things happen. It's not due to lack of talent, right? It's due to the lack of...

Anthony Codispoti: We're human beings, we get distracted, we miss things.

Andy Tang: Absolutely, absolutely. There's no finger pointing. We all need a little help. I want to create an AI agent that could help me become a better investor. I'm going to have bad days.

Anthony Codispoti: 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?

Andy Tang: Yeah, so I think the biggest challenge is actually the trust for the medical system. That's probably the biggest challenge. I suddenly realized our doctors are spread thin and they cannot be fully, I could not fully rely on 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. Which is a kind of interesting conclusion to reach because I know if I tell you, you cannot rely on your professor for learning, you cannot rely on your whatever. pick your plumber for this or that. You say, yeah, of course, I cannot. But if I say you cannot rely on your doctor for your health, you'd be like, what? What am I going to do? But that's the state of American health care. You have to take ownership. And most of us just don't have the time, the resources, and even know how to do it. And that's why I think using... AI is a way to go. so I personally dealt with it just over time, right? Kind of Yeah. I say concierge medicine is a stopgap, right? Essentially, you got to pay. I mean, I to say it, but you know, it's just that's our system. If you if you don't pay, you get the minimum sort of level of service and that

Anthony Codispoti: Any support systems, don't know, outlets that you found that were helpful?

Andy Tang: 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. But what happened to me? I don't think it's good enough. I think you gotta either pay or ramp up AI so everybody's got someone doing the risk management for their health care.

Anthony Codispoti: Andy, how would you characterize your superpower?

Andy Tang: I think my superpower is super transparent, direct and analytical.

Anthony Codispoti: sums it up pretty neatly. I've just got one more question then for you 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 Draper Associates and I want you to continue to get more wonderful content like this. Andy, also want people know the best way I could get get in touch with you directly or to continue to follow your story. What would that be?

Andy Tang: 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.

Anthony Codispoti: 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 Draper 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 in a year from now, we reconnect and you're excited and you're celebrating something. What's that thing?

Andy Tang: you said in a year, right? I am hoping I could play better tennis with my son. I have an 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, know, he's spending more time on tennis. So I got to figure out a way to be more efficient at acquiring skills.

Anthony Codispoti: 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, know, soon to be 12 year old son in tennis. That's awesome. That shows a great focus on life priorities.

Andy Tang: Yeah Thank you. And it was great speaking with you. Thank you for the great.

Anthony Codispoti: Yeah, thank you, Andy. I want to 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.

Andy Tang: Thank you, Anthony, for your hospitality.