The Exchanges

Q Do you have to have an FDE process to be successful selling to enterprise with AI tools?

A No, you don't. Not in our case. You're going to get to that zero to one. You're going to, you're going to get to that first product, um, in all the ways, like people in, you know, in the health systems, in the clinics and listening to the doctors and the nurses and figuring it out. And, you know, but that's not forward deployed, you know, that's not a forward deployed motion. That's just like figuring out how to build a product, um, that fits. But, you know, if, if your first product is something that is everywhere, you know, if, if you've attacked a workflow that, um, that, that can scale, then you're, you're sort of set. It's just like, you know, it's like a classic motion of we picked a first product that we knew, um, was everywhere in healthcare. There are, you know, every single doctor, practically speaking, has to speak to a patient. Great. That's our signal. We're going to attach ourselves to that spoken signal and create value. Great. What's our first bit of value? It's a note. Got it. Do they hate notes? Yep. They hate notes. We can automate them. Great. We created notes. Now let's go scale notes. Then it was like, what's next? They hate placing those orders. They have to hit all kinds of dropdown menus and like figure out what the right order is. Cool. Let's, let's do orders. They hate billing. No doctor went to billing school, accounting school, revenue cycle school.…

AI assessment note: “No, you don't. Not in our case.”

Q the shit out of you before this, um, which should make you feel very comfortable sitting in this dark room alone with me. End of the day in London, why not? Um, I spoke to Andy Weissman who led your seed round. I think market timing is one thing founders often worry about. Fundraising is another very hard thing. Was it an easy pre-seed, seed, early fundraising environment for you?

A Um, I wouldn't say it was easy, but it wasn't hard at the same time. Now this was 20, um, 1820 19. Our series seed was like, we raised five million dollars on a pre of 15. So not, not the world we live in right now, but it made sense then. Like we felt like this was market and we did a really good job. I think that there is founder market fit, but there's also founder partner fit. You know, when you just sort of like have chemistry with a person, um, at a firm, you just know you're gonna find a way to work together. So with USV and Andy, I, I stalked Union Square Ventures for years ahead of the first meeting that I had with them and with him. I would like read all their, you know, tweets when it was Twitter and they had this ritual where they would talk about music. Um, and I was always really impressed that they seemed to pattern match across Totally different genres. The country western on one, on Monday, and then, you know, indie hip hop on Wednesday, and then like Swedish death metal on Friday. And, and to me, that's kind of how I enjoy music as well. And that if they could abstract at that level, my, my thesis was they could be the right tech investor to think about healthcare in a new, different way. So found a way to get to them through an angel, through a friend at MIT. Um, and then we went in and we, we sort of pitched And I knew at the end of that meeting that we were…

AI assessment note: “I wouldn't say it was easy, but it wasn't hard at the same time.”

Q I spoke to one of your investors, who will remain nameless for this one, um, and they said, amazing products and amazing everything that you said, but if you are to fulfill the enterprise value that you have today, and that you will have moving forwards, you have to move closer to the flow of money. Is that fair?

A I think it's not only fair, it's, it's also what we want to do. So when you think about it in, in the United States, but really this is like true in many parts of the world, clinicians, doctors, they're not compensated for the care that they deliver. They're compensated for the care that they documented, that they deliver. So when we first realized that, okay, we're going after this spoken signal and the first thing that we're going to build with it before, during, after, um, we capture it. Is a note. We knew we were billing. We were creating bills too. And so you got to take that responsibility very seriously because the enterprise motion in healthcare is complicated. You have a lot of different stakeholders. You have your end users, but then you have the decision makers and there's a CMIO, chief medical information officer. There is a CIO, a chief information officer, and then there is a CFO and they all have a different lens and being able to thread the needle, being able to resonate with all three is really how you win. The day. And so being able to recognize from the, from the get that, okay, these notes are actually going to end up being bills. So let's approach this note generation architecture, that workflow, and now what's become, um, a much more agent during process. Let's, let's approach that very deliberately so that we have the, you know, the immediate extension af…

AI assessment note: “I think it's not only fair, it's, it's also what we want to do.”

Q Taste. I love that. Taste good things to have good taste. Does that mean you should taste everything?

A No, but, but I do think it means you got to be discerning, but if you're not exposing yourself to certain flavors, then you're just not going to be aware of it. I think the way we translate that in the company, for example, is we should be leading, reading the latest archive papers, um, about some new type of machine learning model that maybe we can leverage. Um, we should be, you know, thinking about the latest UI UX patterns out there, um, and, and where we could take these primitives, you know, in our, in our own specific space. You know, we should be just sort of like living, um, at the edge of culture, um, if we also want to create it. And I think like also the best companies in some way, shape or form are creating culture.

AI assessment note: “No, but, but I do think it means you got to be discerning”

Q Would you have died on this hill? And what I mean by that is sometimes you can have a thesis, you can even be right, but the market doesn't move fast enough.

A Yeah. I, I would have died on this hill. I was willing to pivot on the specific product in what specific order we'd put a feature out. I was willing to pivot on go to market. Certainly we learned so much. Healthcare is incredibly complicated. Figuring out go to market is, is a really big part of, of how you, um, uh, how you win, but I wasn't willing to move on the thesis. And for us, that thesis that healthcare is about people and they're having conversations, I think was just like core to the identity and it would just have to be an entirely new thing. We just sort of shut it down and start something new. If there was something else we could get really passionate about.

AI assessment note: “Yeah. I, I would have died on this hill.”

Q And everyone talks about taste today. Yeah. That's the difference between those that are truly special and what separates humans and AI. How do you reflect on taste being the differentiator?

A When we created our company values, this is before this whole taste cycle. We created our company values and like maybe the, the most recent variant in 20, 21 or 20, 22. One of them is that you have to taste good things to have good taste. And this idea of taste, I think makes a ton of sense to us. It's not just judgment, but it's being able to sort of see patterns, but put things together in interesting ways that hit different. That feel different, that feel authentic, that really represent, you know, a person or people. Um, and I, I think that's where the really, truly magical companies, you know, are these days, like where you can kind of feel like the human behind this product, um, and feel like the decisions that they made, the things that they said no to, um, the strong opinions held tightly, um, that they died on the hill for.

AI assessment note: “where you can kind of feel like the human behind this product”

Q Taste. I love that. Taste good things to have good taste. Does that mean you should taste everything?

A No, but, but I do think it means you got to be discerning, but if you're not exposing yourself to certain flavors, then you're just not going to be aware of it. I think the way we translate that in the company, for example, is we should be leading, reading the latest archive papers, um, about some new type of machine learning model that maybe we can leverage. Um, we should be, you know, thinking about the latest UI UX patterns out there, um, and, and where we could take these primitives, you know, in our, in our own specific space. You know, we should be just sort of like living, um, at the edge of culture, um, if we also want to create it. And I think like also the best companies in some way, shape or form are creating culture.

AI assessment note: “No, but, but I do think it means you got to be discerning”

Q Would you have died on this hill? And what I mean by that is sometimes you can have a thesis, you can even be right, but the market doesn't move fast enough.

A Yeah. I, I would have died on this hill. I was willing to pivot on the specific product in what specific order we'd put a feature out. I was willing to pivot on go to market. Certainly we learned so much. Healthcare is incredibly complicated. Figuring out go to market is, is a really big part of, of how you, um, uh, how you win, but I wasn't willing to move on the thesis. And for us, that thesis that healthcare is about people and they're having conversations, I think was just like core to the identity and it would just have to be an entirely new thing. We just sort of shut it down and start something new. If there was something else we could get really passionate about.

AI assessment note: “Yeah. I, I would have died on this hill.”

Q Is that right? And how would you advise other founders on how to handle that?

A I don't think that there's any playbook, honestly. I think it depends on who's around you too, like what, what, what executives around you. Um, who can do a lot of that work, um, as well. I think culture is critical, and no matter what the founder CEO thinks, they're, they have a big, they play a huge part in setting it, and there are a lot of different ways you can, you can kind of convey what you believe is going to, the culture that's going to help you win, achieve your mission, and meeting every single candidate isn't necessarily, in my estimation, one of them. I think if you really trust your hiring managers and you really trust your executives as carriers of that culture, Um, you can, you can work it out.

AI assessment note: “meeting every single candidate isn't necessarily, in my estimation, one of them.”

Q I think lessons are often learned from reflecting on what you did that you shouldn't have done. What did you do that, on with the benefit of hindsight, you're like, hmm, it would have been better to choose an alternative path?

A During the pandemic, I think everybody's just sort of figuring it out. I think perhaps we could have doubled down on research and just sort of hibernated for a beat into a research caves. And, um, we started a company and a lot of the tech that we leveraged at first was, um, or we were fine tuning BERT models, BERT and BioBERT, Long Farmer and Pegasus and T five. And, um, we had published a paper in 2021 around how you could actually do some of the jobs we do today at scale, but do it with models that predated LLMs. Um, and so we, there's a world where we could have done more R&D, but the decision that we made pretty early on, even before the pandemic, was that the barrier to entry on the doctor side was so high, let's go build for patients. So we built a direct to consumer app that would allow any one of us to ask our doctor, hey, can I record and capture the conversation and create a summary for themselves? I remember when we first pitched USV for that seed round, one of our slides had a doctor on one side, a patient on the other, There's like this mobile phone in the middle and was like, we can help both. Um, both sides need help. Both sides want agency. Both, both sides want to own control the story or have that story. And we can do that. We can serve them with AI. Um, and so we, we started on one side and there's like a part of me that thinks that we could have perhaps, um…

AI assessment note: “perhaps we could have doubled down on research and just sort of hibernated”

Q the shit out of you before this, um, which should make you feel very comfortable sitting in this dark room alone with me. End of the day in London, why not? Um, I spoke to Andy Weissman who led your seed round. I think market timing is one thing founders often worry about. Fundraising is another very hard thing. Was it an easy pre-seed, seed, early fundraising environment for you?

A Um, I wouldn't say it was easy, but it wasn't hard at the same time. Now this was 20, um, 1820 19. Our series seed was like, we raised five million dollars on a pre of 15. So not, not the world we live in right now, but it made sense then. Like we felt like this was market and we did a really good job. I think that there is founder market fit, but there's also founder partner fit. You know, when you just sort of like have chemistry with a person, um, at a firm, you just know you're gonna find a way to work together. So with USV and Andy, I, I stalked Union Square Ventures for years ahead of the first meeting that I had with them and with him. I would like read all their, you know, tweets when it was Twitter and they had this ritual where they would talk about music. Um, and I was always really impressed that they seemed to pattern match across Totally different genres. The country western on one, on Monday, and then, you know, indie hip hop on Wednesday, and then like Swedish death metal on Friday. And, and to me, that's kind of how I enjoy music as well. And that if they could abstract at that level, my, my thesis was they could be the right tech investor to think about healthcare in a new, different way. So found a way to get to them through an angel, through a friend at MIT. Um, and then we went in and we, we sort of pitched And I knew at the end of that meeting that we were…

AI assessment note: “I wouldn't say it was easy, but it wasn't hard at the same time.”

Q I spoke to one of your investors, who will remain nameless for this one, um, and they said, amazing products and amazing everything that you said, but if you are to fulfill the enterprise value that you have today, and that you will have moving forwards, you have to move closer to the flow of money. Is that fair?

A I think it's not only fair, it's, it's also what we want to do. So when you think about it in, in the United States, but really this is like true in many parts of the world, clinicians, doctors, they're not compensated for the care that they deliver. They're compensated for the care that they documented, that they deliver. So when we first realized that, okay, we're going after this spoken signal and the first thing that we're going to build with it before, during, after, um, we capture it. Is a note. We knew we were billing. We were creating bills too. And so you got to take that responsibility very seriously because the enterprise motion in healthcare is complicated. You have a lot of different stakeholders. You have your end users, but then you have the decision makers and there's a CMIO, chief medical information officer. There is a CIO, a chief information officer, and then there is a CFO and they all have a different lens and being able to thread the needle, being able to resonate with all three is really how you win. The day. And so being able to recognize from the, from the get that, okay, these notes are actually going to end up being bills. So let's approach this note generation architecture, that workflow, and now what's become, um, a much more agent during process. Let's, let's approach that very deliberately so that we have the, you know, the immediate extension af…

AI assessment note: “I think it's not only fair, it's, it's also what we want to do.”

Q Is the talent marketplace as hard as everyone suggests it is?

A Yeah. Yeah, absolutely. You know, I think we have the benefit of being able to release a good amount of oxytocin for candidates. We're, we're, we're like a purpose company. We are a meaning company. You can be post money, but still want to put Get your best years into this company because we're at scale and we're trying to do three things. We're trying to save time for the people who matter most in healthcare. We're trying to save money for the system. We need deflationary economics in healthcare. We talked about the portion of GDP it represents, but we also want to save lives. You talked about the greater good. We want to help clinicians feel like superheroes. We have a feature, for example, we just released where a doctor goes in and we give them cues on what questions they should ask or diagnoses they should consider. And we're doing it in a totally differentiated way, unlike a lot of clinical decision support products out there, we're using context. We're engineering the context about who this patient is, that context comes from all those different systems of record and from the conversation.

AI assessment note: “Yeah. Yeah, absolutely. You know, I think we have the benefit”

Q You have three children as well. I'm always contemplating family. I think it's one of the most important things. Do you have any lessons to me on how to be a great CEO and how to be a great parent?

A I think that it's, there's trade-offs and there are sacrifices and the folks who say you can have everything are lying and you just have to be eyes wide open on what you're giving up. So also have to be eyes wide open on high level perspective. Like I have a mentor who said, just go to sleep at night thinking about PPG perspective, purpose, and gratitude. The perspective I have is that this is, um, This is, this is what I, you know, this is what powers me. Like, I, I have to do this work, and I also, you know, love my family, and they come first, but sometimes there are trade-offs, and I can't be at the, the kid event. I live on the road. I'm traveling five days a week. I'm in San Francisco Monday, Tuesday, Wednesday, and then I'm probably seeing customers, and then Saturday and Sunday I'm with my wife and kids. Um, and, uh, It's, there's, I'm missing a lot, but it's just one of those things that you have to, like, come to peace with and, um, recognize, too, that there are times of life, and this is, this is one of those. Remember when, you know, Luis von Ahn?

AI assessment note: “there's trade-offs and there are sacrifices and the folks who say you can have everything”

Q I want to unpack a load of things. How important is being first?

A I think it is critical in, um, in vertical AI. I think being one of the first, um, I think being early, I think being late doesn't work. Um, but you know, there's that refrain that being early is also being wrong. I think we're a good case study and being resilient, like you can sort of, you can, uh, overcome, you know, that issue of, of being perhaps too early. There's like three variants of, of like, AI-native company maybe. There's like, um, we started three months after the Transformer paper. There's, in my head, there's like a post-Transformer paper pre-LLM company, there's post-LLM, pre-agent company, and there's post-agent company. And anymore, depending on your vintage, you have to make sure that you become the latest variant as fast as you possibly can. And that might mean that your product evolves pretty significantly. It might also mean that the way you organize your company and you operate your company evolves pretty significantly. As we're seeing, you know, in this, in this new era with agents. Um, but we were a post transformer pre LLM. And as soon as like the LLM moment like happened, we became that as fast as we possibly could in all the different ways. And, you know, now we've been doing the same thing in this, in this new world with agents.

AI assessment note: “I think it is critical in, um, in vertical AI.”

Q What could you make a large amount of money on today, but for some reason you do not? And why is that?

A We don't make any money selling data. And we don't because trust is everything in healthcare. Like the industry moves at the speed of trust. And you, it takes, you know, all the, all the, all the, you know, the platitudes, but it, it really does. It's like takes so long to build up. And we've been able to build it up, I think in record time, relatively speaking, in, in this industry. I think we've done in four years what a lot of companies take 15 to 20 years to be able to, to be able to do, and that's all thanks to the people inside the company and the relationships that they build, and at the core of the product that we've been able to deliver, and the value that we've been able to create.

AI assessment note: “We don't make any money selling data. And we don't because trust is everything”

Q Do they not have a competitive product to you?

A They have a, they have a product or a feature, they have something out there now, even, that's been out for a beat that helps with notes. But, you know, what I was explaining to you earlier is really, really critical. For us, it was never about the note, it was always about the signal, the conversation that we were using as the wedge. That conversation, that spoken signal allows us to now build into any number of workflows, even beyond notes. And when you're building notes with, for example, all of the revenue cycle that comes next, you build them differently. And so it's a, it's a, it's a moment where kind of like the foundation model company, like we don't ever want to be an electronic medical record. And by the way, like I grew up with Epic and there is, Um, and I was at a health system that had multiple medical records, and I was always the happiest when I was using Epic compared to any others out there. So we build on top of them, but the layer of the stack that we are building is the intelligence layer. And the wedge that we've chosen is the conversation because it's that sacrosanct moment in healthcare where the actual value is getting exchanged, where the doctor and the patient or the nurse and the patient, where they're talking. About the care plans, and so being able to capture them, um, in a, in a way that's not just clinically useful but compliant is a way to build …

AI assessment note: “They have a, they have a product or a feature... that helps with notes.”

Q What could you make a large amount of money on today, but for some reason you do not? And why is that?

A We don't make any money selling data. And we don't because trust is everything in healthcare. Like the industry moves at the speed of trust. And you, it takes, you know, all the, all the, all the, you know, the platitudes, but it, it really does. It's like takes so long to build up. And we've been able to build it up, I think in record time, relatively speaking, in, in this industry. I think we've done in four years what a lot of companies take 15 to 20 years to be able to, to be able to do, and that's all thanks to the people inside the company and the relationships that they build, and at the core of the product that we've been able to deliver, and the value that we've been able to create.

AI assessment note: “We don't make any money selling data. And we don't because trust is everything”

Q Anything that guides your principles? It's less obvious, special counterculture.

A You know, like the Joshua from Lux, I remember years ago, um, meeting him, and I think he says this a lot, but chips, chips on shoulders makes chips in pockets. And I think that's, it's a hard thing to kind of be able to assess in a person, but there are just certain people who, who have insane slope and that slope is coming, coming from something very, very deep and core to, you know, to who they are. Um, they just have, they're, they're on a mission and you see them and you just want to, you want to invest in them. You want stock in them. Um, and you, you sort of feel it. So I think like, It's not that you're looking for, uh, I don't, it's like, there's a bunch of VCs out there looking for broken people, um, and we were talking about psychological assessments, I think, before we started, and how some VCs will do that, and I had one before we, we, we took money from one of our investors, but I, I think it's just looking for a level of, um, of, of fire, um, that's gonna translate into not only those SLAs you talked about, but, you know, resilience and grind and, You know, it's, it's always wartime, and it's a different kind of war now than ever before, and not everybody's a warrior.

AI assessment note: “chips, chips on shoulders makes chips in pockets”

Q And everyone talks about taste today. Yeah. That's the difference between those that are truly special and what separates humans and AI. How do you reflect on taste being the differentiator?

A When we created our company values, this is before this whole taste cycle. We created our company values and like maybe the, the most recent variant in 20, 21 or 20, 22. One of them is that you have to taste good things to have good taste. And this idea of taste, I think makes a ton of sense to us. It's not just judgment, but it's being able to sort of see patterns, but put things together in interesting ways that hit different. That feel different, that feel authentic, that really represent, you know, a person or people. Um, and I, I think that's where the really, truly magical companies, you know, are these days, like where you can kind of feel like the human behind this product, um, and feel like the decisions that they made, the things that they said no to, um, the strong opinions held tightly, um, that they died on the hill for.

AI assessment note: “It's not just judgment, but it's being able to sort of see patterns”

Q Is that right? And how would you advise other founders on how to handle that?

A I don't think that there's any playbook, honestly. I think it depends on who's around you too, like what, what, what executives around you. Um, who can do a lot of that work, um, as well. I think culture is critical, and no matter what the founder CEO thinks, they're, they have a big, they play a huge part in setting it, and there are a lot of different ways you can, you can kind of convey what you believe is going to, the culture that's going to help you win, achieve your mission, and meeting every single candidate isn't necessarily, in my estimation, one of them. I think if you really trust your hiring managers and you really trust your executives as carriers of that culture, Um, you can, you can work it out.

AI assessment note: “if you really trust your hiring managers and you really trust your executives”

Q Um, what does that mean for you then if we take that?

A Yeah. So like healthcare, we say this is a vertical AI company, but you think about it, healthcare, 5.3 trillion dollar, you know, market. It's about 18, 19% of US GDP. It's a big part of the US economy. So, um, in a sense, I, I don't know if it's vertical AI company, like we are, we are like, we are an AI company in my head. Um, serving one of the biggest opportunities that is out there. And, you know, in this market, you can go millions of miles deep. So especially on the enterprise side of the spectrum of healthcare, you can go millions of miles deep in a regulated industry with proprietary data sets that you can build, you know, into very, very, you know, specific like workflows, um, in a way that's really, really hard to replicate. But being fast, getting scale very, very quickly is crucial because like the scale enables you to not just build more products and just get more surface area. But, um, you know, we, we do a lot of mid training and post training in the company on the post training side. It's being able to learn from all the users edits on a daily basis. It's being able to be useful for all the different types of doctors and all the different settings they deliver care and all the different spoken languages, you know, they might, they might use with their patients. And so that like people, I think in 20, 23 thought that was like last mile. That's actually most of …

AI assessment note: “we are an AI company in my head. Serving one of the biggest opportunities”

Q What did you not expect in GTM that surprised you most?

A This is where strong ideas held loosely. You know, when you first raise capital, maybe you hear an investor give you advice about starting down market and swimming upstream, disrupting over time, you know, get, get that PMF, um, find those fast feedback loops. And it's true to an extent, but you just have to be really careful and mindful because healthcare specifically in the United States, It's, it's not one 5.3 trillion dollar market. It's a bunch of different markets, and depending on who you're trying to serve, you have to be really careful about how you segment. If you're trying to serve clinicians, doctors, there's about a million doctors in the country, maybe 800,000 of them are actually practicing. The vast majority of them are concentrated in large care delivery systems. They're called integrated delivery networks or payer providers. They also have like payer arms, insurance arms, Or their academic medical centers, like the Emory's, the Yale's, um, the, the UCSF's and beyond. And so when they're concentrated there, um, you have to think about getting there as fast as you possibly can, because obviously you've got huge ambition. You want to create as much impact as you, as you want, um, as you need to. And so the, I think the, the, the trap that a lot of, I think healthcare founders fall into is that they stay down market. They don't figure out, they don't like Time the…

AI assessment note: “advice about starting down market and swimming upstream... trap... is that they stay down market”

Q What's the hardest role to hire for today?

A I just think getting really amazing executives, like really high judgment executives into a company like ours is, is critical. And A part of it is because we are, you know, this is pretty unprecedented this moment, and I think being able to have folks who can serve as guides, who have a lot of patterns that they can match against priors, but the right person who can kind of go against those priors, but can kind of reflect upon them. The, the time between a decision and an action is getting compressed. Obviously product development, we do things differently now than we did a year ago even, and I think every layer of the company is getting compressed, and I think high judgment people, um, incredible executives is, is still a thing that, you know, I'm, I'm working on.

AI assessment note: “getting really amazing executives, like really high judgment executives into a company”

Q Who do you think is the most underappreciated CEO today?

A Um, that's a good question. I honestly like, cause we talked about that Costco CEO. I think it's that guy. What's his name? Ron something. I think, um, I see he's a guy who went from the, the forklift to the executive office, like all the way up. He's a lifer over there. He carries the, the, the, the torch of culture. Um, and he's managed to continue to grow a business that obviously like he inherited or he, Was already awesome, but they've only had what three or four CEOs. Um, but that's like one of those businesses that you don't read about enough. I think, um, that is absolutely amazing. Obviously I have my idols. Like I have people like Ali Ghazi, who I think is an absolute legend, um, in the way he plays chess and navigates his market. Um, and I just try to learn as much from, from a side outside in, but, um, that guy I think is pretty, pretty awesome too.

AI assessment note: “Costco CEO. I think it's that guy. What's his name? Ron something.”

Q Do they not have a competitive product to you?

A They have a, they have a product or a feature, they have something out there now, even, that's been out for a beat that helps with notes. But, you know, what I was explaining to you earlier is really, really critical. For us, it was never about the note, it was always about the signal, the conversation that we were using as the wedge. That conversation, that spoken signal allows us to now build into any number of workflows, even beyond notes. And when you're building notes with, for example, all of the revenue cycle that comes next, you build them differently. And so it's a, it's a, it's a moment where kind of like the foundation model company, like we don't ever want to be an electronic medical record. And by the way, like I grew up with Epic and there is, Um, and I was at a health system that had multiple medical records, and I was always the happiest when I was using Epic compared to any others out there. So we build on top of them, but the layer of the stack that we are building is the intelligence layer. And the wedge that we've chosen is the conversation because it's that sacrosanct moment in healthcare where the actual value is getting exchanged, where the doctor and the patient or the nurse and the patient, where they're talking. About the care plans, and so being able to capture them, um, in a, in a way that's not just clinically useful but compliant is a way to build …

AI assessment note: “They have a product or a feature, they have something out there now”

Q What's the hardest role to hire for today?

A I just think getting really amazing executives, like really high judgment executives into a company like ours is, is critical. And A part of it is because we are, you know, this is pretty unprecedented this moment, and I think being able to have folks who can serve as guides, who have a lot of patterns that they can match against priors, but the right person who can kind of go against those priors, but can kind of reflect upon them. The, the time between a decision and an action is getting compressed. Obviously product development, we do things differently now than we did a year ago even, and I think every layer of the company is getting compressed, and I think high judgment people, um, incredible executives is, is still a thing that, you know, I'm, I'm working on.

AI assessment note: “getting really amazing executives, like really high judgment executives into a company like ours”

Q Um, what does that mean for you then if we take that?

A Yeah. So like healthcare, we say this is a vertical AI company, but you think about it, healthcare, 5.3 trillion dollar, you know, market. It's about 18, 19% of US GDP. It's a big part of the US economy. So, um, in a sense, I, I don't know if it's vertical AI company, like we are, we are like, we are an AI company in my head. Um, serving one of the biggest opportunities that is out there. And, you know, in this market, you can go millions of miles deep. So especially on the enterprise side of the spectrum of healthcare, you can go millions of miles deep in a regulated industry with proprietary data sets that you can build, you know, into very, very, you know, specific like workflows, um, in a way that's really, really hard to replicate. But being fast, getting scale very, very quickly is crucial because like the scale enables you to not just build more products and just get more surface area. But, um, you know, we, we do a lot of mid training and post training in the company on the post training side. It's being able to learn from all the users edits on a daily basis. It's being able to be useful for all the different types of doctors and all the different settings they deliver care and all the different spoken languages, you know, they might, they might use with their patients. And so that like people, I think in 20, 23 thought that was like last mile. That's actually most of …

AI assessment note: “I don't know if it's vertical AI company, like we are an AI company”

Q I think lessons are often learned from reflecting on what you did that you shouldn't have done. What did you do that, on with the benefit of hindsight, you're like, hmm, it would have been better to choose an alternative path?

A During the pandemic, I think everybody's just sort of figuring it out. I think perhaps we could have doubled down on research and just sort of hibernated for a beat into a research caves. And, um, we started a company and a lot of the tech that we leveraged at first was, um, or we were fine tuning BERT models, BERT and BioBERT, Long Farmer and Pegasus and T five. And, um, we had published a paper in 2021 around how you could actually do some of the jobs we do today at scale, but do it with models that predated LLMs. Um, and so we, there's a world where we could have done more R&D, but the decision that we made pretty early on, even before the pandemic, was that the barrier to entry on the doctor side was so high, let's go build for patients. So we built a direct to consumer app that would allow any one of us to ask our doctor, hey, can I record and capture the conversation and create a summary for themselves? I remember when we first pitched USV for that seed round, one of our slides had a doctor on one side, a patient on the other, There's like this mobile phone in the middle and was like, we can help both. Um, both sides need help. Both sides want agency. Both, both sides want to own control the story or have that story. And we can do that. We can serve them with AI. Um, and so we, we started on one side and there's like a part of me that thinks that we could have perhaps, um…

AI assessment note: “perhaps we could have doubled down on research and just sort of hibernated”

Q What do you expect that to be in two to three years?

A It's a great question. So I think this is where we're all kind of, um, nobody knows the answer, but you just have to be, um, you know, principled in how you approach this. So there's any number of different problems we solve as a company with our product. Some of those problems you, you can kind of imagine ringing the bell relatively easily. Like, okay, if we just help the nurse with this piece of data, getting into this discrete field at this time in their workflow, we won the game. It doesn't need to be, there's no like bells and whistles around us. It's like, once you do it, you've done it. It's kind of binary. Like, you know, um, and those sorts of tasks, being able to just crush it with an in-house model makes total sense for a lot of different reasons, but most importantly for the user. Chances are it's going to be faster. Um, you can kind of optimize that model over time from not just a latency perspective, but also from a cost standpoint. Once you've done it too, you can kind of set and forget to some extent, like, okay, let's move on to the next challenge, you know, inside this new product that we're delivering for nurses. But then there are certain challenges in your product suite that you're never going to be perfect on. But every week, Every month you want to be able to look back and say you're less imperfect than you were before, and it's going to matter. It needs …

AI assessment note: “nobody knows the answer, but you just have to be, um, you know, principled”