SFG 28: Adrian Aoun on automating healthcare with AI‍

In this episode of the Startup Field Guide podcast, Sandhya Hegde chats with Adrian Aoun, CEO and founder of Forward about the company's path to product-market fit. Forward is an AI-based healthcare unicorn that combines private doctors with technology to enable data-driven, insurance-free primary care. Forward is now present in 14 cities in the US.
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Be sure to check out more Startup Field Guide Podcast episodes on Spotify, Apple, and YouTube. Hosted by Unusual Ventures General Partner Sandhya Hegde (former EVP at Amplitude), the SFG podcast uncovers how the top unicorn founders of today really found product-market fit.

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If you are interested in learning more about the topics we discuss in this episode, please check out our resources on starting a company and iterating to MVP for consumer products.

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TL;DR: Interview with Adrian Aoun on Forward's path to PMF

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• Founding insight: Forward grounded itself in first principles reasoning to guide its strategy, product roadmap, and direct-to-consumer payment model. The company’s core insight is that healthcare should be a product, not a service, and they aim to automate everything possible with technology and AI.
• Value proposition: Forward differentiates itself from traditional healthcare systems by providing a seamless user experience. The company focuses on technology, data, and user-friendly interfaces to make healthcare more transparent and consumer-friendly. It offer services directly to the consumers to bypass traditional billing systems and eliminate unnecessary overhead costs.
• Approach to building an “MVP”: Within its first 30 days, Forward built a makeshift doctor's office to test, get feedback, and iterate on its product. Their direct-to-consumer payment model allowed them to innovate in a way that traditional healthcare cannot. Their approach to healthcare emphasizes the importance of learning every day and iterating based on consumer feedback.
• Signals of product market fit: Forward’s focus is on actual care delivery rather than being solely data and algorithm-driven. The litmus test for Forward was bringing in real customers to experience their clinics. When customers were willing to commit by paying for Forward’s services, it was a sign that the company was on its way to product-market fit.
• Growth strategy: Forward currently focuses on growth and retention by making users healthier to keep them engaged, and improving margins to lower costs for users. This ensures that the company’s current activities align to its long-term goals (providing healthcare to a billion people).
• Early team building: The company focused on hiring people (such as clinicians) who genuinely care about helping others and are passionate about making a significant impact instead of people who are experts in healthcare billing or governance.
• Adrian Aoun’s advice to AI founders: Acknowledge the difficulty of working on physical world challenges, but recognize the upside potential.Capitalize on opportunities to solve problems that exist outside of digital screens. Understand the skills necessary to address physical world challenges and have the qualifications to tackle them.

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Episode transcript

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Sandhya Hegde

Welcome to the Unusual Field Guide, where we learn from successful founders of unicorn startups how their companies truly found product market fit. I'm your host, Sandhya Hegde, and today we'll be diving into the story of Forward, an AI based healthcare unicorn that combines private doctors with technology to enable driven, insurance free primary care with a really excellent user experience. Forward is now present in 14 cities in the US. Here with us today is the CEO, Adrian Aung, who founded the company in 2017 after working on special projects for Larry Page at Google. Welcome and thank you for joining us, Adrian.

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Adrian Aoun’s inspiration for starting Forward 

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Sandhya Hegde

The inspiration for Forward was very personal to you. So maybe you could share a little bit about why you started it. And I'm curious, given how everyone talks about the massive challenge of innovating in the healthcare industry, how your convictions have been shaped over the past few years of working on this really big problem.

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Adrian Aoun

Yeah. So you mentioned it a little, but before Forward, I was over at Google. I had started an AI company that Google bought. And this was interesting because I'm working on developing AGI, Artificial General Intelligence, the pinnacle of technology in every way, shape, or form. And then my brother, who lives out in New York, had a heart attack. So just picture my experience. One day I'm working on AI, the next day I'm in his exam room, and there's people standing over him writing on clipboards and post it notes. And I'm like, guys, where's the AI? And I quickly realized that honestly, just the product of healthcare as it is today is just a pile of crap. What's even worse is it's not just this antiquated thing. It's an antiquated thing that not even most of the world has access to. Right? About 8 billion people on the planet, less than 2 billion of them have access to something you and I would call a real form of care. So I'm just sitting here in this completely juxtaposed world, and I'm like, wait, when's AI going to hit health care? And what I realized is it's probably not going to hit it by itself. We probably have to go do something about it. Now, as you mentioned, I don't have a healthcare background. Right. I actually know shockingly little about healthcare. And frankly, I certainly am not an expert in the regulatory environment of healthcare. So most of our kind of convictions, most of our insights, most of our strategy just comes from first principles reasoning. Right? Right. We just sat down and said, hold on, if we knew nothing but we had a generally good understanding of how technology works, how the world works, and where we'd like the world to go, then maybe we could just intuit where the world should be headed as pertains to health care. And what we did is we actually sat down and we just did the thought experiment for ourselves. We just listed a whole bunch of dimensions and then we took those dimensions to an extreme. So, as an example, we said, what do we want the cost of health care to be? Do we want it to be a billion dollars per person or $1 per person? Obviously we want it to be $1 per person. How much data do you want healthcare to use? One piece of data or all the data? Okay, probably all the data. How accessible do you want it to be? Do you want healthcare to be in one doctor's office in a city or like on every street corner? Probably on every street corner. And what we did is we worked through all these dimensions and at the end we said, okay, what's healthcare look like when it's on every street corner? Costs one dollars, uses all the data and on and we had about 20 of these dimensions or so. And that's the guiding light. That's what pushes us towards the products that we build and the strategy that we employ. 

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Sandhya Hegde

I love the kind of full stack innovation approach to an industry where it's very hard to have a point solution to the problem because there's so many systemic constraints to solving anything. Really curious kind of what the early product vision was and how you balance the service element of what you are offering with the technology element of what you offer.

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Adrian Aoun

Totally. So we didn't ever actually know how a doctor's office should work. I had never built a doctor's office before. The most I knew was I had been a patient. So what we did was we actually, in our first kind of 30 days of starting the company, we actually built a doctor's office. It sounds pretty great. But on the other hand, this is probably the shadiest doctor's office you've ever seen. It was in a warehouse in Soma, in the condemned part of Soma, not the good part. And what we did is we rented a warehouse. There a pretty big warehouse, and in middle of it we built a doctor's office, but we built it out of foam core and two by fours. So think of it as it more looked like a movie set. And the best part, it actually had no roof. And what we would do is we would set it up. We'd bring patients in. We were just like, here's some free healthcare. Who wants to try it? We'd bring patients in. And then what we would do is the engineers, the operations, the product people, we'd all watch from upstairs, watch literally through the ceiling, while real doctors had real appointments. 

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And every day we would just huddle right after every appointment. And we'd say, what can we change? And we'd literally do everything from moving walls around to, hey, that nurse seems to be taking somebody's vitals. Why don't we just create a body scanner? Hey, this person seems to be filling out a bunch of forms. Why don't we create an iPad that you can check in? Hey, the doctor is trying to explain information. Why don't we put a screen on the wall with an interactive model of their body overlaid? And so what we did is we just started with the existing and then said, how would we tweak it every single day? Now, there was one kind of key insight or key premise here, which is in normal healthcare, you're paid for by the employer, you're paid for by insurance. And so actually, creating a better experience or using more data or driving down cost are not things that are rewarded. It's this really odd kind of behavior, right? There is a billing code for a nurse taking vitals. If I replace that with a body scanner, I'd make less money, not more. And that's why healthcare doesn't want to innovate. So instead, in our world, we said, let's just go ahead and let's attach ourselves directly to the consumer. So consumers pay us directly. It's pretty novel in the world of healthcare. Certainly when we went out to fundraise everybody's like, that's never going to work. All the luminaries, from the Mark Benioffs to the Eric Schmidt's to the Ashton Kutcher's, everyone, that won't work. Well, fortunately, they still decided to invest anyway. 

Forward's mission: A transparent and incentive-driven healthcare system

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Sandhya Hegde

Funny enough, that's exactly the model in private healthcare in India, which is the dominant urban healthcare. And when I grew up, I remember not a lot because my parents were still relatively young. But you could essentially do comparison shopping for healthcare. You could say, hey, this doctor has this track record, comes referred by this person, works in this hospital on Tuesdays, and this will be the total cost of the surgery and the recovery. But if I go to this other hospital, less known doctor, here's what it will cost. Everything was so transparent. And while I knew in theory that an insurance-driven model doesn't work that way, it was still shocking to know that I never know what the bill is going to be when I walk in.

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Adrian Aoun

And that's exactly the world that we want, right? We think it'd be a much better world if consumers got to choose the product. Then all of a sudden the product is going to innovate. So if you look at our kind of history over the last ten years, what have we been doing? We have 150 engineers, whatever the number is. And every single day they're working on new ways to make you healthier. We have programs around preventing cancer, programs, around preventing heart attacks, programs around managing even the simple stuff, your prescriptions, your vaccines. But think about what every other healthcare system on this planet, when they have engineers, what are they using them for? New ways to bill you right. It's like from the HSAs to the FSAs to the high deductibles, to the amount of financial innovation in healthcare. Blows my mind. On the other hand, it's, yeah, but where's the innovation in the actual care? Think about it this way. We've known about genetics for quite a few decades at this point. Go up to your doctor and say, sequence my DNA and tell me what my risks are. And they will say, we don't do that. Are you kidding me? Like I've got wearables. From the Stravas to the Apple watches to the Oura. And how many doctors do you walk up to are like, of course I ingest all that data and use it? None of them. And so you have to start asking yourself, but why is nobody building these products? We know how to build these products. It's not like these are novel concepts at this point. And again, it's because the incentive stack makes no sense. And so we started with trying to just say, let's fix the incentives. And that has given us the right and the privilege to be able to go after building better and better products every single day for our consumers.

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Sandhya Hegde

Got it. And what was the first kind of twelve months? Like, when did you feel like, okay, we now have an MVP? That is truly something that we can start advertising and have people walk in. We would feel comfortable charging for this product. Like, we have a level of quality we are proud of. How long did that take and how did you know you had enough? Because with software, we do the opposite. Right? We want to be a little embarrassed by what we have shipped because otherwise we sat on it too long and it's never the same with healthcare. 

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Adrian Aoun

Okay, so obviously there's this whole notion of the Lean Startup, and I love those folks, I'm friends with them, but let's be real, it doesn't work in a lot of things. I don't want a lean nuclear manufacturing startup. I don't want a lean automotive startup, and I certainly don't want a lean MVP healthcare system. That seems like a really bad idea. So the MVP of somebody who's going to be your medical provider is pretty real, which means early on we had to raise a pretty decent amount of dollars. Now, on the plus side, we had a little more time to go develop. On the negative side, that money was running out, and that money was running out fast. So we had to ship. There was no choice.

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It's like we had roughly our one chance. And if that didn't work out, we were frankly a bit screwed. We didn't have a plan B. So what we did is, from the day we started the company to the day we launched, was almost perfectly twelve months. Now to build a healthcare system end to end in twelve months is not for the faint of heart. I will be honest. We didn't take weekends, we didn't take holidays. I mean that, Christmas Eve, everybody's here working their ass off because we had a launch coming up because we had no choice. We knew that it was life or death for us and we really wanted this to live. Now, what we did was very early on, remember how I told you 30 days in, we had built a doctor's office? We were a little different than most companies. Most companies say we're going to go ahead and build our product and then show it to the world on February 12th, right? And that's our launch date. We never really took that stance. We have always taken the stance of we need to be live, operating every single day to know how to build a good product. 

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So what we did was, in that same warehouse we had that first clinic we built, let's call that the Alpha Clinic — foam core, two by fours. Eventually we actually tore it down and we built the Beta Clinic. The Beta Clinic was, let's just call it an illegal construction project in middle of San Francisco. It had real walls made of concrete, et cetera. And we built it in our warehouse. It looked like a normal doctor's office. Candidly we iterated and we brought people in, et cetera. And then we actually at some point tore that down and we built what we called the Showroom Clinic. And the Showroom Clinic was what you can think of as pixel perfect representation of the real clinic that we launched in January of, I want to say 2017. And the trick here was we knew that we needed to build it and have people come in and use it to be able to know that it can actually work at scale in any material way. So every single day we were bringing people in. In fact, we had paying customers ever before we went live, because that was our litmus test. We'd bring people in, we'd show them around, we'd let them use it. And then we'd say, give me your damn credit card. And if they didn't, then we knew it probably wasn't at the bar. And once we started getting a bunch of credit cards and a bunch of revenue, then we said, okay, maybe this is at the bar, maybe this meets the threshold of success. 

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I'll tell you, we're actually doing it right now. We have some products that we haven't announced are pretty exciting products and we have a history of launching these products in other cities where, you know what, the Silicon Valley tech press and tech elites aren't around, but we've got real consumers using products that are, let's call it unlaunched products. Because again, we need to learn every single day. And once we get them to a good enough point where we say we know what we have, there's no more question about it tean we like to launch. These days, we're fortunate enough to have a little more than 30 days of runway in the bank. There's no huge gun to our head, but there's certainly still pressure every day.

Forward's product roadmap and long-term strategy

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Sandhya Hegde

I love that you're still using the language units of software development like an alpha and a beta, but the actual work is extremely different. And maybe to continue in that vein, how do you think about the product roadmap? What is a feature or a product at forward?

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Adrian Aoun

Yeah, so we always start by trying to triangulate kind of two things, right? So the first thing, and maybe the most important, it really comes back to those thought experiments that I mentioned at the beginning. If we don't have an understanding of what healthcare looks like at the limit, 100 years from now, 1000 years from now, et cetera, if we don't have a very visceral, intimate understanding of that, it's very hard for us to ever get there. So we always start with this kind of long-term view and say we know at the limit that healthcare is probably going to be everything down to micro, little nanorobots in our body, monitoring our health, et cetera. I'm not saying we know how to do that today, but we know that at the limit, that's probably where it's going to go. 

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We know that there's going to be robotic open heart surgery and there's going to be AI running, everything, et cetera, et cetera. Okay, so we start with this long term. But it turns out capitalism doesn't give a sh*t about your mission. It doesn't give a sh*t about the long term. And so every single quarter we need to make our numbers. And so now you've got to triangulate this like this long-term goal with this short-term goal. And this is really a struggle for companies because companies usually end up erring too much to the short term and thus never achieving their kind of long-term ambition. So the real trick here is if you can align both of those, then all of a sudden working on the short term is working on the long term. Now, that's really hard to do, but when you get it right, boy, does it seem to work out. 

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We are from the capitalist perspective, we're a subscription business right now, like any subscription business. What are the metrics that we care about? If you're Spotify, if you're Netflix, go look at their 10Ks, right? They all care about the same thing. They care about getting customers, keeping customers, and doing it profitably. So we sum these up as growth retention economics. Got to get you, keep you, and do it profitably. Okay, that seems great, but that doesn't seem aligned with your mission. So how do you map those? So our kind of internal updated mission is we want to get health care to a billion people for free. That almost sounds absurd, right? But now think about it. That growth metric is that billion, right? I want to get health care to a billion. Okay, great. Just work on growth every single day. Get more and more users. Okay. Remember how I said after you get users, you have to keep them? That's the retention metric. Again. You say, how am I going to keep you? I'm going to make you healthier. That's the world's best healthcare part. And then remember how I said, hey, I want to do it for free? The better my margins are, the better my economics are, and the more I can lower my cost for users. So what we did is we mapped our kind of long term strategy to these short term metrics. That way we're sure that when we work on these short term metrics, we are making progress towards our long term goal.

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Early user-feedback and developments in the healthtech industry

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Sandhya Hegde

You don't have clear visibility of every step, but you still have clarity of direction in terms of how it aligns, how your activity today will align to what Forward might look like in 15 years, which I think really great attempt to square that triangle, because I do think that's a very hard challenge for most companies to do well. But yeah, I'm really excited about your mission and maybe going back to the first center. What was the user feedback? What were the reactions, especially from strangers? I'm curious whether there were any surprises there for you.

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Adrian Aoun

Yeah. Oh, boy. It was a roller coaster for sure. I'll tell you, one of the ones that is seared in my memory was maybe a month after we launched the CEO of Kaiser, literally the largest healthcare system in the United States, CEO of Kaiser comes in. So I show him everything that we're doing, and he had a few reactions. His first reaction was, this will never succeed. You should just let us acquire you. You need us. And I was like, I don't think so. I think we'll be okay. But his second reaction was, look, this is the most advanced healthcare system I've ever seen. And I'm sitting there and I'm like, what the hell? First off, I'm like patting myself on the back. Of course I'm a genius. I'm the next Einstein. But of course that's not the case. So you have to ask yourself, why did a bunch of people who have no healthcare background with a few million bucks, be able to put together such an advanced health care system in just twelve months? When Kaiser with its quarter million medical professionals, they weren't able to. And obviously you immediately iterate to what we mentioned earlier, which is they have the wrong incentives, right? If you just created the right incentive structure, these quarter million people would be developing technology that would blow all of our minds. And so I always come back to, if you understand people's incentives, you can almost always predict their long term path incredibly easily. From us, we will continually try to lower our price. It's like any tech company, we'd rather sell for less so we can get more people from us every day. We're going to improve our product offering because that's the core of what we do. Our product offering, what's it trying to do? It's trying to get you to live a longer, healthier, happier life. And you know that we're just going to continually try to expand to more and more audiences. We're trying to get to that last little kid in the middle of India who's sitting there going, I don't have health care. That's where we want to go.

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On the other hand, if you look at the existing healthcare system, they make money off of billing codes. So at the end of the day, they're going to sit there and they're going to say, we want more billing codes. We will do anything to get more billing codes running through our system. It's funny, I had a startup, I won't give their name, but I had a startup pitch me yesterday. It's a few people, I do a lot of angel investing. And so they pitch me. It's a very hot startup, getting a fantastic round and everything. It's three people out of DeepMind, which I worked very closely with. And I'm like, what are you guys doing? They're like, Well, LLMs, this is the future, this is the time. What we're going to do is we're working on upcoding charts. So what this means is after you visit the doctor, they look at the notes, they use AI to add more billing codes. And I just looked at them and I was like, you are like three of the smartest people on this planet with the most opportunity to improve the world, and you're going to go spend your next ten years, literally making people's bills worse. Come on. I believe it's a good company, but come on, do something that the world will be thankful for, not annoyed at. And from our perspective, what we're trying to do may work, may not work, but we know at the end of the day that we can hold our heads up high, that we're trying to do the right thing for as many people as possible.

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Sandhya Hegde

I love the story. I think, to me, the equivalent, because I spend a lot of time in go to market tech, is when I meet a really amazing ML engineer working on Robocalling for Sale. I want to love it. I'm a venture capitalist, and yet I hate it. What do I do with you? I totally, totally resonate.

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Adrian Aoun

I tend to try investing only in things that I want to exist in the world. I'm not perfect at it, but I tend to veer much more there.

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Economic challenges and Forward's approach to scaling up clinics

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Sandhya Hegde

I'm curious, how have you thought about the challenges around just the cost? Because there's so much overhead right. To do one clinic, that's like an extremely expensive first clinic.

And you must have spent a lot of time on the economics to figure out what is the fundable scalable path here at all. So I'm curious. Must have been challenging. Even with your credibility, you have to show people what a medium term, realistic future can look like. And this is just for very notoriously challenging space to do that. We're really curious to learn more about that.

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Adrian Aoun

Yeah. So the big challenge at the end of the day of healthcare is that it's a service based business. Right. And it just turns out it's incredibly hard to make the economics of humans, especially highly trained, expensive humans, scale very well. But the whole kind of premise of Forward at the end of the day is we said, look, if you truly want to build, let's say, a billion person healthcare system, you very quickly realize you're never going to do that based on a bunch of humans. If I look at Kaiser, 75 years old, they have 11 million members. Kaiser is a tech company. You would have never heard of them. You wouldn't have the app on your phone. Right. So obviously, if we want to get to the scale of things like the iPhone, we have to think like things like the iPhone. And what that means is that at forward our kind of core insight, the one thing that we believe that others don't believe is that we believe healthcare should be a product, not a service. We just want to take every single thing that doctors, nurses, et cetera are doing and just migrate it over from humans to technology to hardware to software, all powered by AI. Now, it's easy to say that it's a total nightmare to actually do it, as it turns out. But what we've been doing is just every single day since the day we started. We're just watching everything that the people are doing inside of our system, right? From the doctors to the nurses, and we're just saying, hey, every time they do something, can we automate that? Can we go ahead and add some hardware, add some software? Now, it's actually pretty great if you're one of these doctors, because you're like, wait, you just got me out of all the routine nonsense, low value, uninteresting stuff, and now I can go work on the really fast. Like, I want to cure cancer. That's what I want to do. I don't want to be talking to somebody about their flu all day. You ever think about the fact that we've seen the flu billions of times on this planet, and yet you still go to a doctor and have an appointment with somebody who's paid a quarter million a year to talk about your flu? It's like, why has nobody just built the flu algorithm? Like, this is absurd. Your flu is not a snowflake. Pardon my language, but it's not right. And so at the end of the day, what we're trying to do is we're trying to, in essence, by productizing healthcare, improve its economics every single day. Now, you're right. The way the majority of the money is made today is with a bunch of regulatory capture. It's a bunch of overhead, basically. It's a bunch of nonsense that we shouldn't even have in the world, right? So we start by saying, let's just go direct to consumer. That allows us to eliminate all that. And then we say, okay, great. Now how can we bring technology to trade the analog dollars for digital dimes?

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Adrian Aoun on the future of AI in healthcare

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Sandhya Hegde

That's maybe a good segue to LLMs. You brought it up first, not me. And I think you were doing AGI research, like, way ahead of the times before it became trendy and realistic at the same time. I'm curious how you're thinking about some of the work Google is doing with Med-PaLm, some of kind of the early conversations being had around not maybe the more tactical things like taking or health records, but the more important things like, okay, what does this mean for diagnosis? And actually being able to scale that to more patients cost effectively. I would love your take on what is plausible and what is Forward being focused on, especially given kind of the new developments around foundation models in the last few years.

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Adrian Aoun

So I'm both far more optimistic than probably anybody else out there, but in some ways far more pessimistic. And by that, what I mean is I think that most of the approaches today of healthcare, of applying AI to healthcare, basically, we take a very Silicon Valley view. And the Silicon Valley view is, just give me a bunch of data and I'll give you the answer. But it turns out, like, you know how when people say for startups, the idea is worthless? It's the execution. That matters. Turns out it's the same thing in healthcare. 

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The tech companies love to love to say, we have the insight, we know the diagnosis, we know this. But until you can execute upon that care, until you can be the care provider and deliver that care, it’s worthless. The tech companies, I like to say they're really not into drawing blood. Like, healthcare is messy. At the end of the day, you have to become someone's doctor if you truly want to have the impact. Doesn't mean that that doctor can't be a digital doctor. It doesn't mean you can't use things like body scanners and screens and sensors and diagnostics. But you have to be willing to go end to end if you really want this to work. Today, what we're doing is we're taking the world's most advanced AI and we're saying, hey, here's doctor's notes from the 90s. Can you go ahead and operate? As opposed to really reimagining the system from first principles. So what we said is, okay, look, we obviously think that the AI doctor is a fantastic world. We all want to get there. It will make healthcare ubiquitous and universal. But to do that, you actually have to start by building infrastructure that the AI can operate on top of. And this is why we build an enormous amount of hardware and an enormous amount of locations, et cetera, because we know that if we can't deliver that care, the world's best algorithm sitting in a room isn't going to do anything.

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Sandhya Hegde

Yeah, I need all the sensors to capture data and then actually deliver care. I remember this was, I think, 2008, and I was like on some sort of field trip project, something in rural India where they were trying to roll out telemedicine.

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And obviously the biggest issue was connectivity. It took like sometimes a 50 minutes wait for someone to be like, is the Internet working? Is this call going to go through? And they had a couple of sensors, like they had stethoscope and a few things there, but most of the time people were sent back home because the Internet wasn't working.

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Adrian Aou

Imagine, you know how we distributed ATMs to all of Africa, right? What if I just built the kind of ATM of healthcare, right? What would that look like? What we do is we bias towards saying, hey, let's just build the algorithms and then we'll let some other doctor somewhere deliver it. But at the end of the day, what you need to do is you need to be the one delivering that care. And so if we just imagined what healthcare could look like as a product, what would the product look like? That dealt with everything from my cold and my flu, the uninteresting stuff, to hey, it's just going to go ahead and scan my body and tell me what from my genetics to my skin and everything in between. Tell me what are the parts that are pretty likely to develop cancer or not, and tell me what I should be doing. If I need a prescription, give me that prescription. If I need to track a metric over time, let me track that metric over time. We have all the technologies to build this, and that's a little of where we're trying to go.

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Building Forward's early team

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Sandhya Hegde

I'm curious, maybe taking a step away from product to team building. How did you think about early team building? I'm sure you had a lot of pressure to consider, how many healthcare experts does my team have versus engineers, versus even the core team? You need to cover all of the expertise required. I'm curious, what was the early team and what were some of the trade offs you had to make?

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Adrian Aoun

I think we've always biased towards hire really smart people who really care to help other people. That's the magic at the end of the day. Now, all of Silicon Valley hires really smart people. We're good at that, right? But I don't think all of Silicon Valley does a really great job hiring people who actually give a shit about the mission of the company. We know that we're working on a company that is harder than most other companies. We are not here because we said, oh, this is where we're going to make our quick buck. We're here because we said, this is where we can have the most impact. So we start with those two, right? Just hire somebody who's really smart and really cares to help as many people as they can. 

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Now, from there, you have to say, in some roles, it's helpful to have some expertise, and in some roles, frankly, it doesn't make a difference. And frankly, in some roles, it hurts. And this is really a key notion. So if you want to be a software developer, it helps if you know how to code. Okay, great. You want to be a doctor? It helps if you know how to be a doctor, great. But you know where we don't hire? We don't hire people from the healthcare system. Why can you imagine walking up to Larry Page at Google and being like, hey, I've got somebody here who's an expert in the Dewey Decimal system. You should hire them. He's not trying to build a library. He’s trying to build Google. Yes, Google is the modern incantation of a library, but it's reimagined from first principles. You don't want the expert in the old world. Could you imagine if Uber was like, ah, we're hiring the taxi commissioner? It's, no, don't do that. And so what we did is we said, actually, to this day, we have not hired anybody from the kind of healthcare industry. We do hire clinicians. They know how to practice care. We don't hire people who are experts on billing codes and government regulations. That's not interesting to us, right? No way. Why would we want that?

Adrian Aoun’s advice to founders building AI products

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Sandhya Hegde

And maybe like wrapping up a question for you would be, what would be your advice for new founders who are working on what I would call problems that involve real physical world challenges, right? Whether it's logistics, healthcare, robotics. There's a lot of industries where the kind of gospel of software startup stuff just it doesn't translate at all. And I'm sure this was like the first time you were doing that as well, where you weren't just doing bits and the zeros and ones anymore. So I'm curious, were there any guiding principles for you? And what comes to mind when if we're talking to founders who are like, going after these harder, full stack kind of problems?

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Adrian Aoun

The first thing is acknowledge that it's harder. It is. There's zero question. Now, if you think about it, the upside is pretty real, right? If I were to go and look at the largest companies on the planet, in particular the largest tech companies, right, from the Apples to the Teslas, these are companies that have massive logistics. Think of Amazon. Amazon has a fleet of jets moving boxes around all day. What the hell? Amazon has a fleet of vehicles. They have warehouses everywhere. Apple's sitting there and they're like, all we do is hardware. That's our thing, right? And obviously Tesla is like, actually factory automation is our magic, right? And so if you look, it's a hell of a lot harder to get them going. But once they get going, wow, do they get big. 

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Because it turns out that to this day, yeah, I know, our phones are incredible and our phones are amazing, but the vast majority of the world is outside of your four inch screen. It's still not in. Even simple things like the vast majority of advertising dollars are still out non online. And that's just an indication that we still live our lives. We still go to dinners, we go out, we still see people in person. And so the good news is there's a lot of upside and the bad news is there's a hell of a lot of brain damage. It's very hard. 

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The main thing that I would just encourage people to do is make sure that you've the way I always think about going after problems is you want to make sure that you're qualified to go after that problem. And the analogy I always use is, do you remember how Batman had the Bat belt, right? And he had his Gatling gun and who else knows all sorts of things on his Bat belt. I always think of skills that I'm developing over time. I had actually done some things in the regulatory environment when I was at Google, okay? I knew a little about regulation. I had raised a bunch of money before, so I knew a little about fundraising. I had done some hardware, so I knew about hardware. I had done some construction, so I knew about construction. So those are all on my bat belt now. 

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At the end of the day, I don't think you need to have 100% of everything. I'd never done medicine, for example, but you want to make sure that, I don't know, 70, 80% of the skills necessary to go after it are things you're familiar with, or you end up just drowning and never getting off the ground. But I'd encourage people with kind of one simple kind of insight, which is it's just as hard to start something big as something small. If you sat down and said, I'm doing a startup and we're going to build the world's best spoon. Literally, we're going to reinvent the spoon. What are you going to do? Raise a couple of million bucks, get some people in a room, come out with a product a year later. Great. On the other hand, if you said, I'm going to rebuild healthcare for the whole planet, what are you going to do? Raise a couple of million bucks, get people in a room, come out with a product in a year? At the end of the day, they're all a nightmare. And once they're all a nightmare, you might as well work on something that's got some upside. And that upside could just be like, you're really proud of what you did and you changed the world for the better. It doesn't have to be like an IPO or things like that. We only have one life, so let's be really conscious in how we live it.

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