The Exchanges, every show

Q Would you be where you are today though, if that round had come together?

A No, no. Cause I don't think we would have pivoted as hard into COVID when COVID hit. Um, I mean, it would have probably been easier cause we had, at that point we actually had a lab license. So You know, in the US you need this thing called a clear license to run these kind of tests. And we had got one of these licenses over like a painstaking two year process. And then in December of 2019, as part of the wind down, I sold that license to a company in San Diego for 150,000 dollars to pay some of the creditors. And then five months later, acquired a company in Southern California to get the same license for twenty seven million. So timing is everything.

AI assessment note: “No, no. Cause I don't think we would have pivoted as hard into COVID”

Q I didn't, I used to run a lot when I was young, and my needs were wonderful, and I used to love how I built this, because they would ask the questions like this, which is like, how do you go from like cows and musculature on cows and milk yield optimization to at-home STD testing? Like, it doesn't feel that natural a jump.

A Yeah, on the back end, it's more natural, right? All of these things have DNA in them, and so if you're, if you're looking to do better DNA testing, you're just looking for markets where people care more about that, and anything human, people obviously care a lot more about, are more willing to pay for, and are much larger markets, and so we sort of did like a market-first approach of, you know, where, where could there be interesting things, and we narrowed in on Uh, antibiotic resistance in STDs as being like a particularly interesting area where they're getting harder and harder to treat because you get more and more antibiotic resistance, and if you're doing the DNA testing, you can predict what the best drug is going to be early, treat with that drug, and then you're not using the most aggressive antibiotics.

AI assessment note: “All of these things have DNA in them, and so if you're looking to do better DNA testing”

Q Would you be where you are today though, if that round had come together?

A No, no. Cause I don't think we would have pivoted as hard into COVID when COVID hit. Um, I mean, it would have probably been easier cause we had, at that point we actually had a lab license. So You know, in the US you need this thing called a clear license to run these kind of tests. And we had got one of these licenses over like a painstaking two year process. And then in December of 2019, as part of the wind down, I sold that license to a company in San Diego for 150,000 dollars to pay some of the creditors. And then five months later, acquired a company in Southern California to get the same license for twenty seven million. So timing is everything.

AI assessment note: “No, no. Cause I don't think we would have pivoted as hard into COVID”

Q It was. I didn't, I used to run a lot when I was young, and my needs were wonderful, and I used to love how I built this, because they would ask the questions like this, which is like, how do you go from, like, cows and musculature on cows and milk yield optimization to at-home STD testing? Like, it doesn't feel that natural a jump.

A Yeah, on the back end, it's more natural. Right. All of these things have DNA in them, and so if you're, if you're looking to do better DNA testing, you're just looking for markets where people care more about that, and anything human, people obviously care a lot more about, are more willing to pay for, and are much larger markets, and so we sort of did like a market-first approach of, you know, where could there be interesting things, and we narrowed in on antibiotic resistance in STDs as being like a particularly interesting area where They're getting harder and harder to treat because you get more and more antibiotic resistance, and if you're doing the DNA testing, you can predict what the best drug is going to be early, treat with that drug, and then you're not using the most aggressive antibiotics.

AI assessment note: “All of these things have DNA in them, and so if you're looking to do better DNA testing”

Q If you could do one thing to change the structure of the US healthcare system today, magic wand, what would you do?

A Um, I think you have to break up the negotiating into smaller units. Like, it's gotten to this point where I think it's, it's quite an efficient system as a market when the counterparties are small. When everything gets very consolidated, it becomes incredibly inefficient. So when we look at, for example, health systems, right, so we pay for, for care at health systems, some of that care you can get in other places. If we look at how much we pay a primary care doctor who's independent compared to a primary care doctor affiliated with a system, affiliated with a system, they get paid an average double. Same service, you know, same credentials, it's just that this one is part of a hospital system, and that hospital system will use the fact that they have a ton of beds, that they have this ultra special surgery center that you need, like we need to have that capacity in our network, because some people need to be hospitalized, some people need those services, that if you want to get access to that, you got to pay me double for my primary care doctors. And so when all of the players are small, when you have smaller payers and smaller hospitals, you end up kind of getting to reasonable negotiations. What's happened is you have these massive payers, like the market is ultra consolidated. You basically have like four large players that control the entire market on the payer side. And …

AI assessment note: “I think you have to break up the negotiating into smaller units.”

Q How do we determine between functions where we'll do more versus we'll be replaced?

A So what we've tried to kind of differentiate at Curative is there's like two areas where we're really investing in people. That's technical skills and relationships. Those are two aspects that I don't see going away anytime soon, is we still have a team that are actually deploying all of this AI. They use a ton of AI in all of their day-to-day work, right? They're not writing any code anymore. They're not even reading the code anymore. They're deploying all of this with code code or codex. Um, and seeing, like, incredible results out of, like, one senior engineer now is so much more productive than they were a year ago that we're investing in having those people. At the same time, there's a side, particularly to health insurance, that is relationship driven that I don't see as going away anytime soon. Ultimately, we insure a member, and that member wants to be able to call and talk to a person. We have a lot of AI they can talk to. The AI is great. They love talking to the AI. But there has to be a person somewhere in the loop. We also work with these provider groups. We have a relationship with that provider group that we're providing a chunk of your revenue. You know, we work with you. You work with us. There's a relationship aspect there that has to be maintained, particularly for the larger groups by a person. And then on the sales side, we sell through a broker and that br…

AI assessment note: “there's like two areas where we're really investing in people. That's technical skills and relationships.”

Q It was. I didn't, I used to run a lot when I was young, and my needs were wonderful, and I used to love how I built this, because they would ask the questions like this, which is like, how do you go from, like, cows and musculature on cows and milk yield optimization to at-home STD testing? Like, it doesn't feel that natural a jump.

A Yeah, on the back end, it's more natural. Right. All of these things have DNA in them, and so if you're, if you're looking to do better DNA testing, you're just looking for markets where people care more about that, and anything human, people obviously care a lot more about, are more willing to pay for, and are much larger markets, and so we sort of did like a market-first approach of, you know, where could there be interesting things, and we narrowed in on antibiotic resistance in STDs as being like a particularly interesting area where They're getting harder and harder to treat because you get more and more antibiotic resistance, and if you're doing the DNA testing, you can predict what the best drug is going to be early, treat with that drug, and then you're not using the most aggressive antibiotics.

AI assessment note: “All of these things have DNA in them”

Q Ah. Is it all, like, legacy software like Salesforce, though?

A Some of it's like that. Some of it's, like, very insurance-specific software. Um, so, like, our claim system, for example, right, is this, like, massive off-the-shelf platform that we just migrated to a few years ago. This is, again, why, like, if I'd known AI was coming, we would have probably approached things differently. Um, and it's just, it's very hard to use. Like, it's hard. Their API barely works. It's hard to get the data out of their database. Uh, they won't let us manage it. It's, it, but that's how insurance companies are running things, and so we've built our own claim system completely from scratch in-house. It's now, uh, we've migrated most of the workflows off. We'll be fully off in July.

AI assessment note: “Some of it's like that. Some of it's, like, very insurance-specific software.”

Q I didn't, I used to run a lot when I was young, and my needs were wonderful, and I used to love how I built this, because they would ask the questions like this, which is like, how do you go from like cows and musculature on cows and milk yield optimization to at-home STD testing? Like, it doesn't feel that natural a jump.

A Yeah, on the back end, it's more natural, right? All of these things have DNA in them, and so if you're, if you're looking to do better DNA testing, you're just looking for markets where people care more about that, and anything human, people obviously care a lot more about, are more willing to pay for, and are much larger markets, and so we sort of did like a market-first approach of, you know, where, where could there be interesting things, and we narrowed in on Uh, antibiotic resistance in STDs as being like a particularly interesting area where they're getting harder and harder to treat because you get more and more antibiotic resistance, and if you're doing the DNA testing, you can predict what the best drug is going to be early, treat with that drug, and then you're not using the most aggressive antibiotics.

AI assessment note: “All of these things have DNA in them”

Q If you could do one thing to change the structure of the US healthcare system today, magic wand, what would you do?

A Um, I think you have to break up the negotiating into smaller units. Like, it's gotten to this point where I think it's, it's quite an efficient system as a market when the counterparties are small. When everything gets very consolidated, it becomes incredibly inefficient. So when we look at, for example, health systems, right, so we pay for, for care at health systems, some of that care you can get in other places. If we look at how much we pay a primary care doctor who's independent compared to a primary care doctor affiliated with a system, affiliated with a system, they get paid an average double. Same service, you know, same credentials, it's just that this one is part of a hospital system, and that hospital system will use the fact that they have a ton of beds, that they have this ultra special surgery center that you need, like we need to have that capacity in our network, because some people need to be hospitalized, some people need those services, that if you want to get access to that, you got to pay me double for my primary care doctors. And so when all of the players are small, when you have smaller payers and smaller hospitals, you end up kind of getting to reasonable negotiations. What's happened is you have these massive payers, like the market is ultra consolidated. You basically have like four large players that control the entire market on the payer side. And …

AI assessment note: “I think you have to break up the negotiating into smaller units.”

Q What do you know now, sorry, that you wish you'd known when you made the pivot into insurance?

A I think I wish that I knew AI was coming. Because I think, like, the way we designed the business in 2022, when we first started, we had no idea that this wave of AI and LLMs was coming. Like, we were building a health insurance business because we thought it was a good business to build, and we thought it needed to be built, we needed better alternatives in the market for health insurance. And then in the last, like, 18 months, how we do pretty much everything is now a completely different workflow. And we, there's so much, I mean, all health insurance does is like moving bits around, right? Like we don't have a physical product. We give you a little plastic card. But apart from that, our product is that we move bits around in a database that means care is paid for. That's it, right? And we do a lot of managing, kind of managing a marketplace. We work with the providers to negotiate prices. We work with employers to negotiate how much they pay. And then we try to work with employees to keep them healthy. If we can get people to stay healthy, we can avoid the long-term downstream cost of care. Essentially it's marketplace business. Um, and that has been fundamentally like shifted by AI, but when we first started building, we didn't know that was coming.

AI assessment note: “I think I wish that I knew AI was coming.”

Q That is extraordinary. What is the margin profile on a COVID test?

A So really good during surges and then really bad not during surges. Um, so what we found was when, when there was a peak, right? So we get a new variant or You know, it's usually winter was the biggest peak, but then we started having these summer peaks, which was kind of weird. Um, everybody would run to get tested. Um, and these were all public testing sites. So these were in parking lots. These were the drive through tests. That was what we were doing. So if you went to a drive through testing site, like the biggest one was the, uh, Dodger stadium site in LA. It was seven lanes of traffic, seven AM to seven PM, seven days a week. So they were testing at the peak about 10,000 people a day coming through their cars, getting tested, and coming back to the lab. So when you're at peak capacity and you're filling all of the lab's volume, it's very profitable. Then those, ah, basically surges subside, right, and you end up back at testing, you know, using 20 or 30% of your capacity, all your fixed costs the same. You're still paying 7000 to people. Now you don't have to buy as many consumables, but all of that infrastructure has to be maintained for the surge. And so this is again, where it's like the opposite of the traditional lab industry, where they have a very flat volume. Every year people do roughly the same amount of blood work as they did last year, or maybe they do like p…

AI assessment note: “really good during surges and then really bad not during surges.”

Q When people think that I'm an AI because I respond very quickly on email, and to the point where I'm like, no, I just have no life. You said about kind of the different data inputs of like, oh, you can just send us anything now. I always was like, data cleansing, data structures would be the biggest inhibitor to enterprise adoption of AI. Is that totally wrong bullshit VC?

A I think if you approach it in the right way, then the cleanliness doesn't really matter that much because the models are so good at cleaning up the data if you give them the right context. And so that's one of the things we found actually with migrating away from some of these SaaS vendors is, uh, we, we moved away from Looker, um, right? Google's Looker product for visualizations. It's super expensive. Um, and we moved to do it in Snowflake. Um, and It's been a lot cheaper. It's worked really well. Part of that migration is moving all of our dashboards and all of the things that fed from Looker would have taken like probably like a year and a whole bunch of engineers and data scientists. We did most of it with an agentic workflow that would spin up, find the next dashboard, figure out how to convert it into what we needed, and then close it down on the Looker side and boot it up on the other side. And it ended up being like a project for, uh, one or two people, and it took, it still took a couple of months, but it was a lot more doable because we didn't have to have somebody ingest or like figure out that data. You can just feed that data into a model and let it figure out how to structure it going forward.

AI assessment note: “cleanliness doesn't really matter that much because the models are so good”

Q Ah. Is it all, like, legacy software like Salesforce, though?

A Some of it's like that. Some of it's, like, very insurance-specific software. Um, so, like, our claim system, for example, right, is this, like, massive off-the-shelf platform that we just migrated to a few years ago. This is, again, why, like, if I'd known AI was coming, we would have probably approached things differently. Um, and it's just, it's very hard to use. Like, it's hard. Their API barely works. It's hard to get the data out of their database. Uh, they won't let us manage it. It's, it, but that's how insurance companies are running things, and so we've built our own claim system completely from scratch in-house. It's now, uh, we've migrated most of the workflows off. We'll be fully off in July.

AI assessment note: “Some of it's like that. Some of it's, like, very insurance-specific software.”

Q That is extraordinary. What is the margin profile on a COVID test?

A So really good during surges and then really bad not during surges. Um, so what we found was when, when there was a peak, right? So we get a new variant or You know, it's usually winter was the biggest peak, but then we started having these summer peaks, which was kind of weird. Um, everybody would run to get tested. Um, and these were all public testing sites. So these were in parking lots. These were the drive through tests. That was what we were doing. So if you went to a drive through testing site, like the biggest one was the, uh, Dodger stadium site in LA. It was seven lanes of traffic, seven AM to seven PM, seven days a week. So they were testing at the peak about 10,000 people a day coming through their cars, getting tested, and coming back to the lab. So when you're at peak capacity and you're filling all of the lab's volume, it's very profitable. Then those, ah, basically surges subside, right, and you end up back at testing, you know, using 20 or 30% of your capacity, all your fixed costs the same. You're still paying 7000 to people. Now you don't have to buy as many consumables, but all of that infrastructure has to be maintained for the surge. And so this is again, where it's like the opposite of the traditional lab industry, where they have a very flat volume. Every year people do roughly the same amount of blood work as they did last year, or maybe they do like p…

AI assessment note: “really good during surges and then really bad not during surges.”

Q What do you know now, sorry, that you wish you'd known when you made the pivot into insurance?

A I think I wish that I knew AI was coming. Because I think, like, the way we designed the business in 2022, when we first started, we had no idea that this wave of AI and LLMs was coming. Like, we were building a health insurance business because we thought it was a good business to build, and we thought it needed to be built, we needed better alternatives in the market for health insurance. And then in the last, like, 18 months, how we do pretty much everything is now a completely different workflow. And we, there's so much, I mean, all health insurance does is like moving bits around, right? Like we don't have a physical product. We give you a little plastic card. But apart from that, our product is that we move bits around in a database that means care is paid for. That's it, right? And we do a lot of managing, kind of managing a marketplace. We work with the providers to negotiate prices. We work with employers to negotiate how much they pay. And then we try to work with employees to keep them healthy. If we can get people to stay healthy, we can avoid the long-term downstream cost of care. Essentially it's marketplace business. Um, and that has been fundamentally like shifted by AI, but when we first started building, we didn't know that was coming.

AI assessment note: “I think I wish that I knew AI was coming.”

Q Is it worth, because argument back, I always like to do both sides, I'm never, is it worth the engineering hours to vibe code that, and then to maintain it?

A The maintenance is, is definitely one of the most challenging pieces. Um, I agree with that. I think for most businesses of, of any reasonable scale, yes, it is worth it. Now, whether they will have the tech resources to do that soon, I think that's like the bigger question. It's kind of, when will this happen? But when you build those things custom to your workflow, they work better. Like most of these big, you know, systems, you're paying an administrator. Like we had a full-time Salesforce administrator. Right? You're paying people whose sole job is to manage this, like, archaic software platform. Not that Salesforce is archaic, but, you know, we have a few other, like, internal apps that we were paying for, like, industry software that is taking multiple FTEs to maintain it. You can transition that into one great engineer, and then whenever you want a custom feature, you just go build it.

AI assessment note: “I think for most businesses of, of any reasonable scale, yes, it is worth it.”

Q That makes me so happy to hear. Ok, final one. What was the best advice that you've been given?

A I think one thing that I have learned is to always try and get a lot of different perspectives on a problem. I think I, I would historically have sort of approached things from like one scientific viewpoint. And sometimes people would say, no, like take a step back and think about that problem more broadly. And one of the things I learned during the curative COVID push is we had to bring together a bunch of people from very different backgrounds. We hired a bunch of former military people who were just like incredible at deployment. But they speak a different language, and then we're trying to get them to talk to scientists, and then we hired a bunch of Silicon Valley developers, and they all, like, think about the problem. They're all trying to solve the problem, but they all come at it from, like, a completely different perspective, and a lot of times I wouldn't have considered that point of view on doing it, and I think what I found is that the more of those perspectives that you can kind of get on a problem, the closer to ground truth you get. Like, you're never gonna, no, no one of those people is gonna give you the ground truth, But if you hear a lot of perspectives, you can kind of get to that ground truth faster.

AI assessment note: “always try and get a lot of different perspectives on a problem”

Q Is it worth, because argument back, I always like to do both sides, I'm never, is it worth the engineering hours to vibe code that, and then to maintain it?

A The maintenance is, is definitely one of the most challenging pieces. I agree with that. For most businesses of any reasonable scale, yes, it is worth it. Now, whether they will have the tech resources to do that soon, I think that's like the bigger question. It's kind of, when will this happen? But when you build those things custom to your workflow, they work better. Like, most of these big, you know, systems, you're paying an administrator. Like, we had a full-time Salesforce administrator. You're paying people whose sole job is to manage this, like, archaic software platform. Not that Salesforce is archaic, but, you know, we have a few other, like, internal apps that we were paying for, like, industry software that is taking multiple FTEs to maintain it. You can transition that into one great engineer, and then whenever you want a custom feature, you just go build it.

AI assessment note: “For most businesses of any reasonable scale, yes, it is worth it.”

Q Do you know now that you wish you'd known when you made the pivot into insurance?

A I think I wish that a new AI was coming. Like, the way we designed the business in twenty-twenty-two, when we first started, we had no idea that this wave of AI and LLMs was coming. Like, we were building a health insurance business because we thought it was a good business to build, and we thought it needed to be built, we needed better alternatives in the market for health insurance. And then in the last, like, 18 months, how we do pretty much everything is now a completely different workflow. There's so much, I mean, all health insurance does is, like, moving bits around, right? Like, we don't have a physical product, we give you a little plastic card, but apart from that, our product is that we move bits around in a database that means care is paid for. That's it. And we do a lot of managing, kind of managing a marketplace. We work with the providers to negotiate prices, we work with employers to negotiate how much they pay, and then we try to work with employees to keep them healthy. If we can get people to stay healthy, we can avoid the long-term downstream cost of care. Essentially, it's marketplace business. And that has been fundamentally, like, shifted by AI.

AI assessment note: “we had no idea that this wave of AI and LLMs was coming”

Q What one change would you make to Europe if I made you president of Europe in this very strange title to stay in the race for competitiveness?

A You have to have some kind of, like, burden for passing regulation. There needs to be some penalty. Like, right now, you pass a regulation, that's like, okay, you, you did a good job. Like, the goal is to pass regulation. There has to be some penalty. Like, the, if you pass regulation, your country must pay some tax, additional tax, for having passed that regulation. Just adding and adding and adding, without, like, refining what you've got today, and, like, really going and digging in, how is this regulation affecting things on the ground? Like, just more additive regulation is bad. You need to be looking at the effect of what you've done, and refining it, and iterating on it, and not just trying to add some new landmark regulation.

AI assessment note: “You have to have some kind of, like, burden for passing regulation.”

Q That makes me so happy to hear. Ok, final one. What was the best advice that you've been given?

A I think one thing that I have learned is to always try and get a lot of different perspectives on a problem. Um, I think I, I would historically have sort of approached things from like one scientific viewpoint, and sometimes people would say, No, like take a step back and think about that problem more broadly. And one of the things I learned during the curative COVID push is we had to bring together a bunch of people from very different backgrounds. We hired a bunch of former military people who were just like incredible at deployment, but they speak a different language. And then we're trying to get them to talk to scientists. And then we hired a bunch of Silicon Valley developers and they all like, think about the problem. They're all trying to solve the problem, but they, All come at it from like a completely different perspective. And a lot of times I wouldn't have considered, you know, that point of view on doing it. And I think what I found is that the more of those perspectives that you can kind of get on a problem, the closer to ground truth you get. Like you're never going to, no, no one of those people is going to give you the ground truth. But if you hear a lot of perspectives, you can kind of get to that ground truth faster.

AI assessment note: “always try and get a lot of different perspectives on a problem”

Q Is it worth, because argument back, I always like to do both sides, I'm never, is it worth the engineering hours to vibe code that, and then to maintain it?

A The maintenance is, is definitely one of the most challenging pieces. Um, I agree with that. I think for most businesses of, of any reasonable scale, yes, it is worth it. Now, whether they will have the tech resources to do that soon, I think that's like the bigger question. It's kind of, when will this happen? But when you build those things custom to your workflow, they work better. Like most of these big, you know, systems, you're paying an administrator. Like we had a full-time Salesforce administrator. Right? You're paying people whose sole job is to manage this, like, archaic software platform. Not that Salesforce is archaic, but, you know, we have a few other, like, internal apps that we were paying for, like, industry software that is taking multiple FTEs to maintain it. You can transition that into one great engineer, and then whenever you want a custom feature, you just go build it.

AI assessment note: “I think for most businesses of, of any reasonable scale, yes, it is worth it.”

Q What one change would you make to Europe if I made you president of Europe in this very strange title to stay in the race for competitiveness?

A Uh, you have to have some kind of, like, burden for passing regulation. There needs to be some penalty. Like, right now, you pass a regulation, that's like, okay, you, you did a good job. Like, the goal is to pass regulation. There has to be some penalty. Like, the country, if you pass regulation, your country must pay some tax, additional tax, for having passed that regulation. Just adding and adding and adding, uh, without, like, refining what you've got today, and, like, really going and digging in, how is this regulation affecting things on the ground? Like, just more additive regulation is bad. You need to be looking at the effect of what you've done and refining it and iterating on it and not just trying to add some new landmark regulation.

AI assessment note: “you have to have some kind of, like, burden for passing regulation”

Q How do we determine between functions where we'll do more versus we'll be replaced?

A So what we've tried to kind of differentiate at Curative is there's like two areas where we're really investing in people. That's technical skills and relationships. Those are two aspects that I don't see going away anytime soon, is we still have a team that are actually deploying all of this AI. They use a ton of AI in all of their day-to-day work, right? They're not writing any code anymore. They're not even reading the code anymore. They're deploying all of this with code code or codex. Um, and seeing, like, incredible results out of, like, one senior engineer now is so much more productive than they were a year ago that we're investing in having those people. At the same time, there's a side, particularly to health insurance, that is relationship driven that I don't see as going away anytime soon. Ultimately, we insure a member, and that member wants to be able to call and talk to a person. We have a lot of AI they can talk to. The AI is great. They love talking to the AI. But there has to be a person somewhere in the loop. We also work with these provider groups. We have a relationship with that provider group that we're providing a chunk of your revenue. You know, we work with you. You work with us. There's a relationship aspect there that has to be maintained, particularly for the larger groups by a person. And then on the sales side, we sell through a broker and that br…

AI assessment note: “two areas where we're really investing in people. That's technical skills and relationships.”