Tales from the Trenches Podcast, Episode 5: Anmol Madan and the MIT $40K

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Molly Donovan | May 10, 2024

Welcome back to our podcast: Tales from the Trenches. In this episode, Krishna speaks with RadiantGraph and Ginger founder Anmol Madan about disrupting the healthcare industry, moving with conviction, and resilience as a serial founder.

Click play above to listen, or read the transcript below.

Krishna: Hi everyone, we’re back for another episode of Tales from the Trenches, and today I have one of my nearest and dearest friends and oldest friends: Anmol Madan. Anmol and I had the pleasure of working together at his first startup, when we were the first investor in Ginger, and now we have the pleasure of working with him on his next startup, or startups, I should say. And that’s RadiantGraph and something special we’re working on. 

And so I’m looking forward to talking about Anmol’s journey, and maybe some of that will mix in our journey together. And so welcome, Anmol, and great to have you here. 

Anmol: It’s so much fun to do this, Krishna. Thanks for inviting me, and I’m sorry it took so long. 

Krishna: No, absolutely, you’re a busy man. So tell me, first, man, you were in Rome recently from what you tell me, which as everyone knows is a great inspiration to me. Did you get any inspiration from Rome?

Anmol: Yeah, I think we just did a few days in Rome and then in Tuscany, just coming back from holiday. And it was mostly downtime. And I don’t know how you operate, Krishna, but I feel like if I take a few days off and am not on my emails and am not jumping into meetings and checking Slack, it sort of activates this second-order part of my brain. And so I start thinking about, you know, you take time to digest the events of the last six months or the last year, you start drawing things you need to work on strategically, areas to invest in. So I highly recommend everyone take like, a week every six months — it doesn’t have to be a lot of time — but thoroughly disconnect from work as much as possible, clear your brain. Because you work hard and you start looking at your business, your time, your team with a fresh lens, a fresh perspective. And it’s so crucial to get out of the day-to-day running of things and kind of have that bigger view. 

Krishna: I agree with that cadence. I try to take a week in the summer and a week in the winter. It hasn’t worked out very well for me the last couple years — calls have punctured my peace. But I am glad that you got some time. 

So Anmol, you know, one of the things I’ve been thinking about is that I’ve been thinking about Anmol the human and Anmol the entrepreneur. But I don’t know if you and I have ever really gotten into what were the sparks that set you off onto your entrepreneurial journey. I know that you’re from Pune, which is a city I’ve actually been to, and I know that you at some point came to the US, but my guess is that there’s some story here that predates, by a lot, the time when you and I met. And so I’d love to understand: what makes Anmol the entrepreneur the first time around?

Anmol: Yeah, that’s a great question. And I’ve never thought of it that way. It’s almost like if you’re on the inside you can’t see it, you just kind of gravitate toward it. In the spirit of being vulnerable, I’ll share a little bit about my childhood and background.

So I grew up in Pune. I lost my mom pretty early, so I basically grew up with my dad. And so a lot of it was seeing the workplace, seeing the professional environment. I’d be sitting in his office before and after school and doing my little thing there. And so I kind of grew around…and he’s an entrepreneur, so I grew around people building companies, I grew around the life of industry. And I loved my research. I loved building new stuff whether through undergrad and then through grad school at MIT through the PhD program, but I also always sort of had this inclination that I wasn’t going to be a professor. I wasn’t going to be a research scientist. I was going to go start something and build a company. For some reason, and I joke about this with my wife, I fall backwards and start a company as a sort of default state of what gets me going. 

So at MIT, for example, I was doing the 50K and the 100K, and this and that, and our paths crossed. 

Krishna: And we were the 40K. 

Anmol: That’s right, you were the 40K, I remember that, yeah. And so the inside joke here for people listening is that Krishna’s check into Ginger, which at that time was called Ginger.io…

Krishna: It was called Gingered, Anmol. 

Anmol: I’ve blacked out that part. That lasted about a couple of weeks, I think, and then it became Ginger.io. 

But yeah, Krishna was the first check in for $40K. And we joke about it, but for me that was like, great, I can run this company for a year. This is what valuations were in seed rounds then. 

So to come back to your question: I think it comes from an innate desire where I like building new technology, I like creating the future, but I also want to solve problems in a way that are going to have an impact on society. And the research papers are important, because they show robustness, they show critical thinking, you want to be doing things that are academically sound. But at the end of the day, it has to hit the market. People have to use it, people have to find value in it. So that’s what I enjoy about building companies. I find it to be extremely satisfying, whether it’s early on as a founder, back again as a founder, and then in between as an investor and occasional board member. In different formats, there’s nothing as thrilling as seeing a team, seeing an idea take shape. And basically it becomes a default standard for the industry. 

So I think that’s sort of the innate thing that I can’t turn off no matter how hard I try. 

Krishna: What kind of company did your dad build? 

Anmol: So he’s in old-school engineering for manufacturing, for capital equipment, at the time it used to be oil and gas. There’s something fun about going off and running deep…I wouldn’t call it “deep” in today’s world, but at the time in the context it was a deep technology, so there’s something exciting about that. And he’s 78, and he’s still running it. 

Krishna: That’s amazing. And I can empathize. I grew up with — my father ran a consulting company, which was doing quality control, Six Sigma, and he left Motorola when they started doing that. So I got my entrepreneurial itch by going to his office on the weekend and watching him deal with personnel issues and the ups and downs of running a small business. And yeah, that plays a major role, I’ve found: how entrepreneurs grew up, what they prioritize, how they think about the world. 

Speaking of hard tech: the day I spent in Pune, the person I visited was Baba Kalyani. I don’t know if you know Baba Kalynani, but he started this company in Pune called Bharat Forge. 

Anmol: Yeah, I know Bharat Forge. 

Krishna: Yeah, and he’s an MIT alumn. And so I was 21 years old and it was fascinating for me to see an Indian entrepreneur trying to build world-class manufacturing out of India. And obviously now it’s much more prevalent. So awesome, very interesting. 

Anmol: I want to say one thing on this, Krishna, and sorry, this is why I think it’s ambitious that we’ll be able to do this in 30 minutes. I’ve been thinking a lot about this, and I think there is something — and I can speak about this in the Indian context for sure, maybe it generalizes across different cultures, too — but there’s something about growing up in a family where people are used to talking about businesses, used to talking about scaling companies. Because all these things that people learn later in life in, say, business school: cost of acquisition, LTV, unit economics. If you’re growing up and learning a business as a conversation around the dinner table as a teenager or a young kid, you get exposed to it and it becomes second nature. And these things don’t then intimidate you; you kind of understand that they’re just different formulations. 

I’ve had this discussion with a few of my friends who are my age, and we talk about what made us who we are. And a lot of it is this being exposed to a culture where this is acceptable. Where you hear: this is what we have to do, and this person’s not working out, and da da da. And you build that muscle as a child, then you carry that, hopefully, for the rest of your career. 

Krishna: 100%. I mean I think it’s so cultural, it’s so sub-cultural in India, and anywhere. You know I’ll finish this segment with a little joke. When I think about the girl I want to marry, I often ask girls what their fathers do, and my perfect answer is they run a small business — not a big business, a small business — and they’ve seen the ups and downs of what an entrepreneur’s life is. Because I have no clue who else would put up with me otherwise. 

Anmol: So my wife does not come from the entrepreneurial world. 

Krishan: And so you must drive her nuts. 

Anmol: No, but I think it’s a good balance actually. 

Krishna: That’s true. 

Anmol: The counter point is the entrepreneurial risk-taker side can dominate. And you know, people should find the partner for them. But for us what works well is you know, she is a clear professional, both her parents are clear professionals. You know, I joke about the North India/South India contrast here: everybody is highly educated in her family. But there’s something about the stability that that kind of person brings, where I’m like, let’s swing for the fences, and she’s like, well…you know, let’s get a handle on this one. So it’s a good balance to have. 

Krishna: Agreed. So I think from that, when we talk about balance and complementarities in partnerships, the same is true about business partnerships. You and I have both lived through some interesting business partnerships: ups and downs, and I think we have both come out learning a lot from them. Do you take a similar lens when you think about business partnerships? And how has that view evolved over your time as an entrepreneur? 

Anmol: I think each experience teaches me about myself. I learn who I am by each experience. So that’s really powerful. So when I think about…I’ve had some great experiences. I’ve had some incredible experiences. Incredible people I’ve worked with: obviously you, but across every job, whether at Ginger, Livongo, Teladoc, the MIT Media Lab — incredible people. But there are also people where I haven’t worked well [with them] or it wasn’t a productive relationship. 

And I think what it has taught me is it’s almost always inevitably we’re optimizing for different things, or we’re seeking different things, or we have a different value system. So an example is what I value is building teams where people are excited, they’re empowered, they’re having an impact, they’re driving things forward. And that takes time, that takes effort, that takes a lot of sort of hand-crafted, artisanal people management skills. And I think it’s easy for folks to sort of not want to do that. They can say that’s too much work, I want to do this or that and make this decision or that decision. So there’s often whiplash in the investor community in particular. So I think it teaches me that my values are unique. 

So at this stage of my career, you have the privilege of being able to choose whom you work with, and you pick the ones…you know, everybody’s smart, everybody’s successful. But you pick the ones who you know you can work through ups and downs with them, and they will optimize for the same things that you do. 

Or in places I’ve had conflict, it’s because we’re optimizing for different things. The other person’s optimizing for how the world sees them, or how the world perceives them. And I think to me, that’s not what drives me as much. What drives me is: do the right thing, show real results, build something that is objectively a new category of product or company, and so then when I see people I’m working with today, within the first hour or the first day of us working together and I get the sense that this isn’t gonna work well, I’m much more decisive about calling it. And the difference between Anmol today and Anmol, say, 15 years ago is I will still have the same kind of interaction or gut feel about, like, hey, this isn’t the right fit for what we’re going after — because inside a company you have to protect the culture. You have to curate the culture. The thing that we talk about every single time is the way we work together, the culture we have, the way we operate. And so that’s really apparent when someone has a different view of the world. And I’ve been in situations where I started working with someone and I knew in, like, an hour this isn’t going to work out. And I’d say, hey, this isn’t the right place for you. 

And five years ago or 15 years ago when I had that experience, I was like, oh, maybe I’m wrong, maybe I’ll give them a month, maybe I’ll give them three months. But time just makes you more decisive, experience makes you more decisive. I think getting to know who you are and how you work with people and what you value in people is really crucial. 

So I’d say that’s the biggest lesson that I take. You’re just better at making those people decisions today with a decade or two of experience. And what’s funny is that for entrepreneurs, and even for people like you, I’m sure — you always had the gut instinct. You always knew that this thing is off, this relationship is off, this person’s not the right finance person, this person’s not the right product person, whatever you felt. It’s just that you were maybe questioning your ability to make that decision because you were still early in your career. 

Krishna: That’s a great observation. I think you’re right. For me, I think the inklings have been there, but the ability to have conviction in that intuition and act on that intuition in some way took a lot longer than it should have or would if I were to be in the same situation today. 

So getting to that — one of the most interesting decisions you made over the last year, year and a half was to start a new company. 

Anmol: Yes. 

Krishna: And I remember you and I were chatting about this desire of yours for probably a year before that. You were sort of in this mode of, hey, at some point I want to start something new. But then it all came together at once, and I felt like it was a very quick decision. 

I remember sitting down at this coffee shop, which is the one we usually go to, and it was right after JP Morgan healthcare conference, and you were just like ok, you know what, I’m going to go for it. 

I admired that moment, and it sticks in my mind because it was just the culmination of lots of conversations and lots of thought, but it was very clear. It was a moment of clarity. 

And so how did that happen? What brought you that clarity? Just walk me through the personal journey through Anmol the entrepreneur who sort of ended his journey with Ginger and Anmol the entrepreneur who started RadiantGraph. 

Anmol: Look, I’ll start here. After my PhD I spun out Ginger.io, which became Ginger, from the work I was doing for my PhD thesis. And I was the founder/CEO there for about 7.5, 8 years. Grew that business through different chapters and a number of lessons learned and had a great run doing that. 

And after that, Krishna, I was thinking about what do I do after Ginger. And I got really excited about joining a company called Livongo. And the reason I went to Livongo is I had been running my own company, little startup, 100-odd people or whatever it was at the time, for 7-8 years, and Livongo was an incredible team where I would get to be part of the executive team, which was run by some incredibly talented people, and so Glen Tullman and Lee Shapiro had taken a couple of companies public. They were CEO, Lee is also a friend. We had some incredibly talented people from very successful companies in healthcare and outside. 

And I looked at the caliber of people in every area, and it was like, this is a group of people I can learn from. I think of it as kind of my graduate school education in company-building. 

And Livongo very quickly went public, which was awesome to be part of that journey. After that, Livongo was acquired by a company called Teladoc. And Teladoc, in case you haven’t heard, was the largest player in the space at the time. And as part of the acquisition, I had the opportunity to be the Chief Data AI Officer of this global company, of this $2.5B company, which had presence in 30 countries and supported 80M consumers across nine different product lines: everything from primary care all the way to chronic conditions, mental health, other use cases. 

So it was an incredible chance, one, to be part of a multi-billion-dollar revenue business in a leadership role, which I hadn’t done before. And you know when you think that Teladoc at the time was growing 10-15% year-on-year, but 10-15% year-on-year is still, like $200M, $300M in new ARR every year. I think any one of us at smaller companies would take that in a heartbeat. And so how do companies work at that scale, how do you build commercial functions, how do you build the business to run that way was a great kind of graduate school education for me. 

I also got to play a leadership role in my area. So what I got between Livongo and Teladoc: by the time I left, I’d built out a team of a couple hundred folks, 100+ PhDs in machine learning and data science and AI and statistics, another 100 in data engineering and ML ops and things. But about 40% of my team was women across the stack. About half of my leaders were women. I built out the director layer, the VP layer, the different levels of management. 

And it was fun because we were essentially learning everything, from a lot of the core data systems all the way down to all the machine learning/AI personalization capabilities, including some new research projects at the time inside Teladoc across all the products. So that was a fun, exciting journey. 

I think when I knew it was time was there was a period in December of 2022, right before JPM, when I spent a fair amount of time doing things like strategy planning and these things you have to do in these larger public companies. And I was looking at my time spent for that period, and I was basically filling out spreadsheets: managing people and filling out spreadsheets. 

And it was an: I know I love building companies, I know I love building products, and I think it’s important to spend 3-4 years to really understand things. And if you’re going to do something, it’s worth committing to it for a while, that’s how great things are done. I felt like I’d done that. I’d learned a fair amount. I’d built some great relationships. I needed to take that experience and translate that into doing something earlier stage and go back to the early-stage piece. 

So a lot of this is timing. The same person, all of us across the years, go through different journeys. I do think it’s important for people to reinvent themselves every 4-5 years. And what I mean by that is, you don’t have to go off and become an artist, but ask yourself: are you doing the right thing? Are you in the right job? Are you in the right stage of business?

Krishna: Have you ever thought about being an artist? 

Anmol: No. I would be a terrible artist. I’d be the most goal-oriented artist ever. The exact opposite. Our goal is to maximize art sales this quarter! The artist community would banish me. 

Krishna: It’s true. You are a strong J, as they would say in Myers-Briggs. 

Anmol: Yeah. But I think it’s harder to do that as a VC, because you’re running 10, 20 year fund cycles. But if you can…I mean, I’m still passionate about the same problems. The problems I’m working on today are, in many ways, the same problems I was working on across different jobs the last 15 years. Is this the way you do it? The venue you do it? The scale at which you’re operating? The role you’re playing inside the organization? I think it’s worth asking yourself, every four or five years, is this where I’m learning the most? 

And I’ll say one last thing on this, and you may have heard me say this before. But I did the math once, and I was like, 25 or 30 or something. I did the math that I have 10,000 days in my professional career. Every day where you’re not learning, you’re not working on something interesting, or you’re not pushing yourself is a day that’s not coming back. So I think you have to ask yourself as a leader or a person starting companies or a person investing in companies, as a person in research, whatever your path is: am I spending this time, am I spending this effort in light of that? 

And so I think that urgency, that kind of drive — and look, I learned a lot of fun stuff being in different businesses, and it’s very interesting to see how companies scale, but it was time to take those lessons, apply those back to early stage companies, and go start something new. And that was the genesis behind RadiantGraph. 

Krishna: What excites you most about RadiantGraph? And what do you think excites customers most about RadiantGraph? 

Anmol: So, I’ve had three different experiences, Krishna, first in mental health, then in chronic conditions, then again in primary career and all the other disease areas across different jobs, where we created a category-defining product or company in healthcare. And you look at those experiences and you’re like, Anmol, you’ve been successful! And I’m like, actually, we haven’t. For all its success, Livongo helped 400-500K people with diabetes when I was there. There’s 30M people in diabetes in our society. For all the innovations we’ve seen in mental health, the vast majority of people aren’t using these digital products — they’re going straight to SSRI, psychiatry, and other things. For all the innovations you’ve seen in MSK and back pain, the number of people who are actually going and getting back surgeries is still really high, and the percentage of the population that’s actually managing with physical therapy and preventative interventions is really low. 

So what I’ve seen again and again is these really cool technologies and machine learning engagement and all these things, but a sliver of healthcare consumers engage with them, because they’re being shared through one company or one product. 

And the insight for me was: if I want to take the success we’ve had across these three different companies and make that happen for the bulk of the US healthcare system — for the $4.6T of spend in the US healthcare system, for the millions or hundreds of millions of Americans who are not using existing products, you have to create a platform. So that’s the thesis behind RadiantGraph. 

I think there is a huge opportunity with the new generation of AI, machine learning systems, bringing those inside larger healthcare organizations, health plans, large healthcare organizations, and helping engage consumers more effectively, helping drive better care, helping consequently drive better outcomes downstream, and I think it’s a problem you can look at from multiple lenses, and it’s pretty broken today. 

So, 2.4% of all healthcare premiums are spent on member engagement and outreach. And arguably, we’re not seeing the biggest bang for the buck. On the digital health side, the average utilization of a digital health company inside a health plan is 2, 3, 4, 5%. So you’ve got all these clinical interventions. You know, I will take partial credit for starting the early digital health companies. And we’re sitting here on the other side, we’ve built companies across all these different disease areas, but the adoption of these products is very low. And then on the plan side, it’s not like they don’t want these companies to be successful — they do! They do want better member experiences, they do want people to discover the right support at the right time. But the data is messy, the AI systems are hard to put into work, there’s clinical complexity, there’s how do you design this for healthcare, how does it work for value-based outcomes. All these things are really hard. 

And so what I kind of walked out realizing after JPM in the month of Feb last year, wow, which feels like forever, but it’s only Feb last year, is saying there’s a need for a platform, and I think there’s a company here as big as a Salesforce or an Adobe, specifically for healthcare, that’s going off and building systems that help these large, behemoth, single-digit margin healthcare companies build better experiences for their consumers. Put AI and machine learning to work. I put together the team that had worked with me in my last couple of jobs, so a bunch of our folks — RJ and me, Dan, all came with me in my previous two jobs, came with me. And we went off and built a product that we wished we had when we were off spending $15-20M/year building these capabilities in-house in our last roles. 

And so that became the genesis for RadiantGraph. RadiantGraph has been on a rapid, busy trajectory. We took money last year, as you know, and we had initial goals for what we wanted to achieve in the seed. And I just looked at the data for April: we’re now supporting…we’ve grown 400% in the last six months from what our target was. 

Krishna: Amazing. 

Anmol: So what I think is being apparent is there’s a need for this kind of platform. And I think every health plan, every large health organization is like, what are we doing with ChatGPT? And whatever, and I think we all know that deploying these technologies in healthcare in a way that translates into better engagement, better outcomes, that translates into business impact, that translates into clinically relevant support, is hard, and I think that’s the platform company we’ll create. 

Krishna: How do you avoid having these customers that are just running toward: hey, we want the latest and greatest cool AI thing that we’re hearing about? How do you differentiate that from: hey, let’s make sure we’re providing you a real, tangible valuable proposition? 

Anmol: Do you want a dirty secret? 

Krishna: Yeah. 

Anmol: I don’t think healthcare is as ready for these crazy AI things as everybody else thinks they are. I’m talking about the front office, I’m talking about the member experience — I’m not talking about a clinical note-taking software or other things for the back office. But in the space that we are: we are pitching our clients, you know, we can do generative AI content, and we can do billions of unique journeys inside your population, and we can do all these things. And most of them are like, hey, can you just help me look at my claims and send marketing campaigns to different segments? 

And I hate to say this, but healthcare is so far behind. And these organizations, I think what happens inside these organizations is there’s some incredibly talented people, incredibly passionate people, but I think the complexity of applying machine learning and AI to healthcare use cases is quite high, and so there’s this tension where on one side the board member or maybe an executive or an innovation person is out there saying, at JPM, “We’re going to use AI!” And then there’s the team that’s actual leading product or marketing or clinical on the ground, and they’re like, “hey, we can’t even identify or better understand our members using these different data sources and say, let’s put them in different marketing campaigns or marketing segments or connect them to product experiences or benefit design.” So there’s a disconnect, often, between the public positioning and the guts of these organizations. And I think that’s where we see organizations kind of like…where we’ve seen some attraction is that our thesis has been: let’s meet healthcare organizations where they are, and I fundamentally believe that you’re going to see a hype around these AI point solutions in healthcare, and I think some of that is going to fade, and I think the company that wins is going to be the one that actually builds a comprehensive platform that is the default way that product managers or growth marketers or clinical leaders inside these organizations come in and do their job every Monday. 

And the AI capabilities will get better, but you have to be the tool that they’re running their business on. That’s where you’re really helping them be successful in adding value to their jobs. 

Krishna: Kind of building the picks and shovels, or the infrastructure for people to be able to unlock the value of some of what’s happening over time. 

Anmol: Healthcare cannot adopt AI in the space we’re in without a platform approach, without the picks and shovels built in. 

Krishna: Right. 

Anmol: If you just show up and you’re like, I’ve got this real cool model, and why don’t we just use this, they’re like: how do I land you in my stack? I’m outsourcing my data claims warehouse. I’m outsourcing this part, and this part is something we built in 1985. So you have to solve the whole thing. 

And by the way, there are very similar parallels to the mental health space with Ginger. This is very reminiscent of 2013, 2014 in that space, where we were really cool technology, but to be successful we had to go solve the entire problem. 

Because I think healthcare’s usually a service business. Not a lot of it is investment in the technology function, unlike a typical tech company. So if you’re going to fix this, you have to fix the whole thing. And that’s also what makes it an interesting business, and the dam’s really big, the market size is really big, but it also means you’re building a really broad product — and you can hopefully charge a significant amount for it. 

Krishna: Yeah, that makes sense. And I mean, you’ve been doing machine learning from the time I met you. I mean, I remember reading your machine learning papers back in ’09, ’10. It’s kind of wild to imagine, because at that point you would say machine learning to someone, and they would look at you like, what the hell are you talking about. So it’s been interesting to watch. 

Anmol: The number of times at dinner parties where I said I do machine learning for healthcare and people have quietly walked away to the next table. 

Krishna: Yeah, I’m sure. Let’s double click for a second on the Ginger journey. We like to talk on this podcast about being in the trenches. I’m curious about how you think about the trenches going forward. But in Ginger, can you give us an example of a time when you really felt like you were in the trenches, in the middle of war — you really were at the end of your rope, didn’t know what was going to happen. How were you responding? What were you doing to cope in that situation? Give us a little snapshot. 

Anmol: Yeah, it’s a great question. Trying to think of examples of when that happened. 

Krishna: Maybe to jog your memory a little: I think there was probably some sort of existential moment when you went from B2C to B2B? 

Anmol: Yeah, that’s a great one. 

Krishna: Because I remember a time I walked into the Ginger office and you guys were really excited about trying out the B2C use case. And my guess is it didn’t work. And somewhere along that journey, there was some kind of existential moment. 

Anmol: Yeah, there’s some nuance to that one. And so look, I think what we had working for us at Ginger — and this is the naivete of coming in as a technologist in healthcare — we were early tech. We were the first to use machine learning for behavioral health. I think that’s what got you excited in the early days. Incredible technical DNA, we built a great product. And what was kind of counter was, if you look at healthcare being a fee-for-service system, which at the time 80, 90% of behavioral health was fee-for-service, if not greater, and I think it’s still a significant part of behavioral health that’s fee-for-service. If you come in with tech that automates, reduces a need for visits, helps people bend the cost curve, you actually go counter against the incentives of a fee-for-service system. And so part of it was realizing that. We were deployed with 8 of the top 10 academic medical centers, we were doing some really interesting work with these large hospital systems and things. And they do all these research projects, but we couldn’t convert them to commercial contracts. So learning was trying to understand the incentive structure. 

And the unfortunate truth about healthcare is that most technology companies die in healthcare because they don’t quite understand the complex incentive structure. Even inside a health plan: the line of business, medicare vs. commercial — different incentive structure. There’s very different ways in which business decisions can be made because of what the goals are and how revenues cross different lines. 

And so I just didn’t know that. And we as an organization were naive in that regard. So there was a really interesting board meeting where at some point I was like look, we’re not going to be successful selling this tech to healthcare providers. We have to build the whole car. And the example I used was, we’re selling this incredibly effective electric motor, but in order to sell it, we have to sell the whole car. Because if you’re selling the electric motor, there’s only three companies that can buy it. And it’s in their interest to not buy it sometimes, because they’re doing fine. 

Krishna: That’s right. 

Anmol: But if you’re selling the whole car, you suddenly have millions of people that can buy. I remember going into our board and saying hey, we just raised $20M for a Series B on the technology play. And I said, we have to go build a whole clinical service arm. So let’s hire the therapists, let’s hire the psychiatrists, let’s hire the coaches. Let’s put it all together. And everybody thought I was insane. 

Krishna: Of course. It was a radical departure from what you guys had been talking about before. 

Anmol: It was unheard of. Literally the comment was: what does a person from MIT know about running a healthcare services business? Psychiatry, for example, is really hard. We’ve been doing it for this many years, this and that. And I was like, you’re right! But like everything else, we look at this with first principles. We’ll figure this out. We’ll build the clinical team. And so we pioneered — we were the first to do tele-psychiatry in 45 states. Even Teladoc didn’t have tele-psychiatry at the time. 

And then the other powerful insight was, the industry looked at all these things as different. They were like, this is the AP, this person’s a therapist, this person’s a psychiatrist, this person’s coaching, they’re all different. I’m like: they’re different to you as a clinician. But they’re not different to a consumer. I as a consumer have the same need: I’m stressed out, anxious, down, depressed, whatever. And different consumers will move along differently on that journey. There will be some consumers who will just meditate and sleep and work better and manage their health that way. There will be other consumers where they do need to be on SSRI, they do need to be on prescription meds. There are going to be some who go to therapists. 

Each person is on their own unique journey, and this is different kind of configurations of this system that should be built around them. Or there is an area that got a lot of pushback, which is that we should just have 24/7 care. Offices are open from 8-5; how can we serve care after 5:00? I’m like: the person’s super busy. When are they stressed out? 8pm on a Saturday, 10pm on a Saturday. They had a fight with their spouse. They’re opening up the bottle of wine. Whatever else they’re doing — that’s when they need help. 

So why not design a system that meets people where they are, on their terms. And at the time we had 60-second response time. These were human coaches, not AI coaches, so it was a big deal. So there were a lot of these pioneering, first-in-the industry things that we did and that ultimately became the standard of the industry. 

So you look at all these companies: they’re all following this idea that you could package these different things in one consumer experience, create a comprehensive experience fro consumers, was essentially a new way of thinking about this entire space. And I’ve seen that travel across a number of different digital healths, not just mental health. Livongo and diabetes was doing a similar journey. I think I see that in many other digital health companies today. So I think in many ways, we became the playbook for how these things come together. 

And it’s kind of interesting to be, you know, I was sitting in these meetings, and there were all these people, and I said this should all be one thing. I remember having that whiteboard discussion. And you know, it takes time. 

But I think this is why when you’re doing things that are transformative in an industry, it’s hard to see them in the moment, because people think you’re insane. They think this person is nuts! There are even times at RadiantGraph where I’ll say things and I’ll have very seasoned experts in healthcare, investors in healthcare, say, how could you! That’s now how it works? And I’ll say: that’s not how it works today. 

Krishna: Right. 

Anmol: But what if we are right? What if we are successful? What if this is the future? What if five years from now, everyone who’s running a healthcare company is like, hey, what’s your personalization stack? Are you using RadiantGraph? Are you using something else? 

Krishna: Is that the healthcare trend you’re most excited about? Personalization? 

Anmol: Yeah, I mean I think I use the word personalization because it’s easy to relate for all of us. I think we all intuitively know what that means from our experiences in social media or content or news or whatever else. But I think the idea that frustrates me about healthcare is that one size fits all marketing, one size fits all experiences, one size fits all engagement. And everyone gets the same direct mail thing in their mail that says, you’re turning 65 — welcome to this new health plan. There’s no insight there that says, hey, Krishna, you’ve had a history of these needs, why don’t we help you here? Anmol, you have these other needs — why don’t we call up a member support line? Why doesn’t every individual have a unique experience with their member support line? Why is there just one call center that answers these things? 

I think we deserve to live in a better world as healthcare consumers. I think again and again you see that the limiting factor is can you get people to adopt and engage and use these healthcare products and services? When I look at the $4.6T in spend this year, rising at 7% YoY, 8% YoY here in CA, and when I look at what’s going to bend the cost curve, it’s getting people to adopt these technologies, getting people to change. That’s going to bend the cost curve. And that’s why you need a platform company that can do it for the 97, 98% of healthcare that’s got a higher AI scientist like me in my last job. So that’s the thesis behind RadiantGraph. 

And you look at the spend, how much is the spend? It’s a massive, massive market. But also, I think it’s the only way to actually fix the healthcare system in our society. I don’t think launching 1100 primary care companies is going to solve the problem. 

Krishna: Last question here, Anmol. So, you’re a second-time founder, you’ve been through lots of journeys. I think one of the things that defined your journey at Ginger was this resilience, sticking through it. It was a tough journey: lots of pivots, lots of learnings to get to where you needed to get to. How do you think about that at your next chapter? Do you feel like you can be equally resilient? You’re at a different time in your life. You’re obviously successful. You have a family. How should we think about that concept of resilience and being in the trenches in your second act? 

Anmol: I think it’s actually easier to be resilient…well, we’ll find out, we’ll see how this goes. I think on the surface, it’s easier to be resilient in your second act, or your third act, or your fourth act. I think for a couple reasons. 

The decisiveness. If you’ve had good experiences, if you’ve learned what good looks like, which I think I have had some exposure to that, you can make decisions faster. You’re more decisive. You understand, you appreciate your blind spots. You understand where you need complementary skills.

For example: I know I love building technology, but I also know that I want to bring in a really strong commercial team. And so we brought in Kirk and Kim very early on in the company, because I knew where the team would need more help. Versus, if I had brought on a super star CTO, there might not have been as much for them to do, because you have some really senior engineers and it’s a high-performing team. So I think you have that. 

I think it’s interesting you ask this question, and I again, in the spirit of being vulnerable, I have a kid. I have a family. I’m not sleeping in the office like I used to. Even if I wanted to, it’s hard to do right now, because my daughter’s up at like, 7am. Not that I can not sleep through the night and function as effectively as I could in my 20s. 

But what that also does is…you value every 30 minutes or every hour of time a lot more. So if I sit in a meeting — and this was true even before starting a company again. If I’m running a large organization of a few hundred people and you show up and you’re not prepared, and you used up 30 minutes of my time, you don’t have a plan, you don’t have a clear strategy, you know, that’s rough. 

Before having a family or having a child, you’re more forgiving. But now I’m like, that’s 30 minutes that’s not coming back. So let’s make this count, let’s move fast. 

So I think it’s a different flavor of resiliency or grit, and the nice thing of having had a couple of good runs is you sort of naturally gravitate toward taking a bigger swing. So I think when we started working together on RadiantGraph, I said, look, for me this is only worth it if it’s a really big swing. I’m walking away from the Chief Scientist job of the largest public company in our industry. So if I’m going to go spend five years, seven years, eight years at my next company, it’s because we’re going after a big swing. And that changes how we think of hiring, or capital, or efficiency. 

And I think we should talk about AI and capital in a minute, but you’re building for the long term, and that’s what I need to do. Because there’s nothing else that I’m super excited about doing. I’m not going to retire. I thought for a brief moment, maybe there’s a fund, but that’s not exciting for me. What I love is building and starting companies. And so, that’s what we’re doing. 

Each person is unique. I’m not sure every person in my age group or my stage of life is thinking the same way. But if you’re going to start a company, you have to be really clear that it’s going to take a lot of time, it’s going to be hard — especially in healthcare, it’s going to be really hard, but that’s how great things are done. 

Krishna: Agreed. I think you pointed to some last comments on AI. What are your thoughts on AI in the industry, or how it works in this capital environment? Are people spending too much money, too much time on the wrong things? 

Anmol: I think we’re sitting here, it’s 1999, the internet is just getting invented, and everybody is investing like it’s 2007 and they don’t know what Facebook is. 

These models have been around for a year. Yes, they’re great at some things, as far as language models go, they’re significantly superior to the status quo. There is something about how these models work that makes it feel more human-like in conversation, and I think we as a society have gotten really excited about that. Silicon Valley and investors are really excited about that. 

And I think that is transformational, I don’t want to take that away. I think it’s transformational in the broad, horizontal phase, it’s also transformational for health care in many different use cases. But I think the place where you’ve heard me say this is just because the technology is better, doesn’t mean that the business friction, the buying motion, the complexity of technology adoption, the selling cycle — all these things have suddenly changed. Healthcare has had a chance to adopt technology for like, three, four, five decades. We saw what happened with past technologies and how long they took. We saw what happened with the previous generation of machine learning use cases. We’re dealing with a very complex industry, and rightly so: we’re talking about human lives, we’re talking about a very secure workforce of doctors and nurses. There are so many things here.

So I’m in the camp of — and I may sound like a dinosaur — but I do think it’s like, take your time, be thoughtful. The companies that win are the ones that actually want to survive. You don’t want to be the Netscape of 1999, where you’re the star and then two years later, you’re gone. And so I think how you think of that, how do you adapt, how do you manage your burn, how do you manage your capital structure, how do you build a business that has revenue associated with it — those are all things that I value at this stage. Again, and not saying the other folks making investments are wrong. This is my criteria. I could say that a large fund might decide to go spend $1B a year on some company that has some really foundational chip technology or fine-tuning tech that they think will be the industry standard. I can see why they would make that bet, but that’s not the bet that I want to make. I want to make the bets to build a lasting company. And that takes time, that takes patience, that also takes enough time to understand the selling motion, the case studies, the proof points, all that stuff.

So I think if you have a big ambition, you do have to be cognizant of just throwing more money at the problem, because it won’t always make you grow faster. At least in healthcare. At least not in my experience in the past. 

So that’s kind of my broader view. But do I think the tech is interesting? For sure. Do I think the sub-clinical use cases like the ones we’re going after, or like the ones you’re seeing in the back office that are like, prime-time, ready today? Healthcare companies are still learning how to adopt them and when to adopt them. So that’s probably a whole other podcast we should do. And then there’s the other side of it, which is there is clinical triage, decision-making, the actual treatment decisions. Those things are going to take some time, because the bar is a lot higher. The complexity is a lot higher. There’s some kind of thoughtfulness there that we have to kind of work through. 

I think it’s going to be interesting. And I had a time axis prediction about a year ago. I have thrown my time axis prediction out the window, because it seems every week I’m surprised. So I think at this point, I’m holding off on when machines are making triage decisions and treatment decisions. But I think a lot of what I call coaching, subclinical, product and marketing engagement, back office note-taking — that kind of stuff, that definitely feels ready for prime time. 

Krishna: Awesome. Well, this has been a lot of fun. Anmol, thank you for making the 49 minutes and 35 seconds that will not come back in your day. 

Anmol: No, this is fun. This high value. 

Krishna: This is a lot of fun. Thanks so much, and looking forward to the next time we chat. 

Anmol: Awesome. Thank you, Krishna, for having me.