A very warm welcome to this very special live episode of 40-Minute Mentor. I'm thrilled to have Anish and James here. They are incredible entrepreneurs and investors, and they have had stellar careers. So I can't wait to dig in. This is a record for the podcast because James has been on — this is the third time James has been on. So I am incredibly honored and grateful and...
I've said everything I wanted to say.
Okay. So, I'm sure there'll be some spicy takes. I'm excited. And Anish, this is your debut. So, very warm welcome.
I guess we should probably, for those who haven't met you before, we should get into some intros. So I would love to hear — maybe we'll start with you, Anish, given it's your debut. Do you mind sharing a bit more about your background and current role, and how you got to where you are today?
Sure. Nice to meet you all. I'm always available on email, so anybody who's got follow-up questions. And let's try to make this as interesting and as interactive and spicy as possible, so please ask your hardest questions. I grew up in a small town in Canada in Ontario. I started my first company after spending four years at Amazon in 2008. I sold it to Google. I started another company. I sold it to Credit Karma. And then I found my way to a16z. And yeah, it's been great. It's a great opportunity to be at the edge of technology and work with the best people in the world.
Love that. James, over to you.
Awesome. Yeah. Well, I grew up in Hong Kong until I was 16. Rejected all university offers, went on the streets, became a proto-democracy student leader in Hong Kong at the time. There were massive protests where a 13-year-old kid called Joshua Wong was leading the protests on the streets, and I was trying to join as much as we could. Went from there to finally come over, studied politics, economics, thinking I was going to go back to Hong Kong and be a politician. That turned out to not happen at all, and I sold out completely and became a McKinsey consultant instead.
You're making up for it now, right?
Yeah. Make more bucks. Make more bucks. No, but I, you know, went off to McKinsey. And then went from there to SoftBank, where I worked very closely in the turnarounds team. And so we were a tiny squad team at the time. There were four of us. And then from there started my first company around six years ago. I was one of the early companies building on GPT-3 in late 2020. We tried to build an AI education platform on top of that. That was the first time it came on, I think, way back. And yeah, and then eventually in 2024 started Ethos with my co-founder Daniel, who was at DeepMind for six and a half years before we decided to create this company together. So yeah, that's me.
Thank you very much. So Anish, you've seen both sides of the table, founder, investor. Can you share with our audience why you decided to join a16z when you did, and how your experience as a founder is helping you as an investor?
For sure. Yeah. I didn't think I wanted to be an investor because most of my experiences with investors were very poor. I've kind of had every archetype of bad board member. I think I told James this when I met, you know, which is like too rich to care, didn't read the board materials, too many product ideas, and then high-anxiety new investor.
So those are all the things to avoid. There's definitely nodding going on in the room. I think this is relatable.
Exactly. Yeah. But you know, after I had sold my second company — my first company worked, which is awesome, and I think one of the reasons it worked is I had a very authentic connection to the problem I was solving. It was important to me, I think, just as you do with Ethos, and that's such a great sort of leading indicator of success. With my second company, I just wanted to start a company and be the boss again, and it didn't work, you know. And I think part of it was not having the right intentions. So after four years of Credit Karma, this investor opportunity came along, and you know, it was a point of maturation for me to realize that I just wanted to work on the most important thing that I could make a contribution to, not necessarily be the boss. So I committed, and it's been great.
Love that. Thank you. And James, tell us a bit about how you two met. I'd love to hear the origin story of what is clearly a blossoming bromance. So tell us more.
Yeah. I mean, so first of all, I've known the a16z team for a while because, you know, one of the folks on the team, James Dosta, is actually a very old friend of mine. So we met in university, we were at McKinsey for a while together. He became a founder as well. And then over time, you know, went into the Andreessen team, and so I know the team for a while. And James is always like, you know, you got to meet Anish. You really, really got to meet Anish. And I was like, ah, okay. And then on a trip to SF, finally got to meet Anish. I think we were talking about this last night, but I think it was like within the first...
Like you said, two minutes.
I think it was 10. It was like two, but we had this really electric connection where, you know, one of the challenges of this business is that Ethos is trying to build this platform to match people to opportunities with AI, right? So we really believe that one day every person will have a personal AI that deeply understands your expertise, your latent potential, your aspirations, is going to match you to all these things. But you know, the problem is that we see the whole world as like a whole bundle of opportunities, right? So like to us, there's no difference matching you to expert calls or full-time job to an AI model training project. But every time we meet an investor, they're like, okay, so are you my AI expert research bet or are you my AI recruiting bet? And some dude inevitably is going to be like, you're the AI consulting company. You're going to make it as an AI consulting company, right? And I met Anish, and Anish just instantly understood it, right? So like Anish's instant feeling was, okay, you know, there are so many people with like unique ingredients in their minds of like this latent potential that AI can unlock for them, and that there's real potential here, like over our lifetimes, to make a difference. And there was a very, very authentic belief in that, right? That really made me feel, oh my god, okay, we finally found investors that actually get it. And so yeah, so the paid ad is over, my paid incentivized endorsement. It's easier. But yeah, that was how we first met.
Well, I think, you know, what's so compelling about James that you're already picking up on this is the sense of inevitability. Like you meet this person, and within two minutes, like there's a bunch of yapping going on, but you just get the feeling that this person's going to do what they're going to do, and I'd love to be a part of it, but even if I'm not, it's going to happen. And that, like, that to me is kind of, you know, so much of the investor-founder relationship starts with the emotional and then builds into the intellectual. You know, on the intellectual point, if you look at this whole market of data labeling and human data capture, it's sort of nihilistic, you know, it's like, okay, we're going to get all the data from all the people's heads and then make them unnecessary. It's like, who wants to live in that world, you know? So I think one of the powers — well, I know we're going to talk about London later — of the approach you've taken and the person you are is that you thought about it from first principles and you've taken a much more pro-social view, and it's showing up in the business results. So...
Yeah, so true. When I first met James in a founders' retreat, and you know, there's all these people, and just there's something about — I don't want to, you know, big you up too much, James, but there's something about your energy...
You heard my business is called JBM, and you just started going JBM, JBM, and now every time I see James, he does that to me, and it's just like I feel so good. And you just have this incredible infectious energy, James, and I know everyone in this room will see it. And clearly Anish got it from minute one. And tell us a bit more about the actual business itself. Clearly you were struck and you understood it in the way that James wanted you to. But tell us a bit more about kind of what excited you and your thoughts when you first had that meeting.
Yeah, I mean, I guess philosophically, I love the view that human knowledge is highly adaptive. You know, otherwise if you think of the most high-powered attorney that makes $1,000 an hour and a new graduate attorney, why is the former, you know, why do they charge so much more than the new graduate? They both read the same textbooks. It's because they have all of this sort of tacit knowledge of how things are done, how to build relationships, when to, you know, hold versus to cave versus — so there's just so much, and a lot of the knowledge is unspoken. I think that's the majority of the knowledge actually in the world. It's also ever-changing because the sort of application of the field is ever-changing. So the idea that actually it's not about human data capture for labs, it's about economic opportunity, and then also unbundling jobs from work. You know, you can do work without it having to be — if you think of the formal construct of a job, traditionally it was like you work for 30 years, you get a gold watch, you get a pension, and now we've got people that'll work for four years, people that'll work multiple jobs. Like what is the next sort of level of granularity of work, and it's potentially doing things like the experts are doing in the network today. It's much, much bigger than just human data for labs.
Absolutely. Is that right? Do you agree that I get...
Yeah. Yeah. I totally disagree. It's like not at all in my thesis. No, it's like absolutely agree. Like I think there's a part here where we were talking about yesterday at our board meeting about, you know, how do we get people to stop selling their time and move into the position where you own your expertise as an asset, and for that asset to be scalable over your lifetime. And we never really have the technology to do this, right? How do we package up what's in your mind, all the tasks and knowledge, and help like many, many more people who need that knowledge, who need that expertise, access it, but where it turns into a form of licensing, a form of royalties, as a form of passive income for you in addition to the thing you spend most of your time on day-to-day, right? Like that's the part that we think this will truly unlock over like the next 10, 20 years. And it starts very, very basic in day one, right? In day one, it's basically you get an AI profile, we can match you to jobs with it, we can match you to projects with it, we can match you to expert calls with it. But over time, it's really about creating a new form of income for people because, you know, if we think about where the world of work is going, it's essentially that all the people who are selling their time for income have stayed stagnant for 40 years, and all the people who own assets and capital have made multiples and multiples of wealth, right? And so we got to figure out how to diversify this ownership of capital. And for the first time, knowledge can become capital, right? And that's the big transition we're trying to make.
Super exciting. I'm conscious we've already got into some of the vision you have for the business, but can we maybe take it back to the origin story? What made you go, this is the problem I want to solve? And how has it evolved since that moment, the eureka moment?
Yeah. So I think the fundamental inspiration for it was how do we build something that could advance social mobility at scale. That was actually the core problem. So actually when you look at the entity name of Ethos, the US entity that holds the parent entity is called Somo Labs, and what SOMO stands for is actually social mobility. And I still own the domain for socialmobility.ai, which one day is going to come back out. So, and so it was really the foundational idea of the company, right? How do we advance social mobility at scale? And the reason why it mattered so much to me is that, you know, I grew up in a really weird family where my dad was super successful before I was born. And so he was like an insurance company CEO and all that. I, you know, the moment I was born, I was born into this like three-story mansion in Hong Kong, which is crazy in Hong Kong. And I had like — one of my first memories is actually I was like driving a little mini Ferrari like in the house. You know those like little cars that you just — like completely insane. And then in my, you know, when I was three years old, the Asian financial crisis hit. My dad lost his job, made a bunch of very terrible investments. And then suddenly we went from, you know, super rich to all the way like straight down. And so most of my childhood was basically moving from bigger houses to smaller houses. And so we ended up in a flat that was lent to us by one of our uncles. And so in a weird way, I was surrounded by nepotism, right? So I went to one of the best high schools in Hong Kong because the headmaster went to the same high school class as my dad, right? And so I got in with that. And I was like paying my school bills by like working for my headmaster in the shadows, and then he was basically paying my school fees in the back. It was like completely crazy. And so surrounded by nepotism, my dad's like, you know, friends were all kind of, you know, rich dudes with like rich kids. Meanwhile, we were like in this constant decline. And so by the time I went to protesting in Hong Kong and so on, most of my rich friends were not on the streets, right? They were criticizing all of this stuff. Meanwhile, you know, like everyone who's fighting on the streets were like losing opportunity and so on. And so the fundamental DNA for the last like 30 years of my life has been, you know, how do we fix this, right? Like opportunities are incredibly unevenly distributed. And in my first business, what I learned was that it turned out education was not the answer to this because most people go, you know, education is the answer. And it turned out education was so reliant on motivation, and the people who need that are not the people who could pay, and so you just fundamentally do not have a business model that could sustain this over time. And so it then became a question of, you know, what is like AI unlocking now that could give us the ability to advance social mobility at scale? And it became increasingly clear to me that actually AI is the first technology that can truly have almost infinite tokens to understand an individual, right? We've gone from a position where nobody will ever understand you to the depth that AI can. And at the same time, AI can actually understand the landscape of economic opportunities to a level that no other technology has enabled us to do, and that in fact we could match people to opportunities with AI much more efficiently than anything that has ever been created. And so that's when it sort of started clicking to me that you could actually start advancing social mobility at scale in this way. And then it became quite clear that we need to build something like this.
Yeah, it's so powerful. I love the mission. It's so impressive. I'd love to get into some of that detail. But also, you've done all this with a team of six people. Like this is incredibly lean and very exciting. Not great for a headhunter, can I say, but you know, respect it for sure. Can you walk us through how you've approached growing at such velocity in such a lean way? Because I think the founders in the audience, the founders listening to this, you know, will really appreciate hearing kind of why you chose that approach.
Yeah, for sure. The fundamental — like the fundamentals of this was we were trying to think from first principles, how do we build a company in the age of AI? And it became quite clear that we have to build almost like a centralized intelligence of the company. And so when we first started building the company, we built this knowledge graph of people, companies and products, right? So we bought around 500 million profiles, 60 million companies. And we sort of figured out, okay, how do we build a graph of this? Then we basically loaded a bunch of agents on top to like, you know, operate on top of this. And every single thing we then did, right, our Slack, our, you know, Linear, which we eventually dropped because we didn't need it anymore, like Notion, our CRM, our internal management of the company, so on and so forth, all of those became vibe-coded tools actually. So we just built on top of our own system, we basically stopped like outsourcing any of this. And we plugged all of that context into like the group of agents that are working for the company. Then as, you know, the sort of models got better and better, we started plugging, you know, essentially the agents into Slack for the whole company to use, right? So, you know, showing it yesterday, but literally our entire non-technical team are in Slack every day talking to Cursor, right? So like literally they're just like, I need to build this into the product. I need to build this, you know, into the support system. I need the admin panel to change in this way. And at the same time, you know, for the experts that we work with, the support agent is fully automated, but it's not just like automated on fixed data, right? So as the project evolves, as people talk on the system, all of that context is being ingested and then, you know, leveraged by the support agent to support the experts with live information on what's going on, right? So essentially we built this centralized intelligence that allows us to use agents to do most of the work. And for the company, then we were very focused on having an extremely, extremely high quality bar. And our thesis there was that the sort of human coordination was actually the biggest sort of cost to the company. So like if you have lots of people in a hierarchy and they're debating and they're going, I need gated approvals to do this and that, you slow down the company immensely. But in our company, we flattened it entirely. And you know, in engineering, you know, Daniel is basically at the same level as like the other engineers. Everybody can just make decisions autonomously and go do something. Everybody's been given like a very high level of ownership compared to like comparable companies elsewhere as well. And for me with the ops team, it's like, you know, at this point like Ashin and our team is basically running the company, and like Sam is running the company as well. Like each of them own like functions that they're just driving. And they don't really need my approvals for anything, right? So we are almost like a collective running the company. But what that relies on is extremely high quality bar for talent. That is not just about their experience, their skills, but it's also about their personality, about their ethics, about their conviction in the mission, all those types of things. And so one of the reasons why like every engineer took roughly five to six months to hire so far, right? And we're just going on and on just looking for people. And we've met so many people from top companies, and still we're continuing the search.
