Every argument clarity score on this site is built from rows on this page. Each
question and answer was assessed with names hidden, the host's own answers included, on
four things from 1 to 5:
directness (does it answer the question asked), coherence (do the ideas follow),
precision (concrete details and clear references), compression (says a lot per word). The weighted
mix (30/30/25/15) is the exchange score. A person's published score averages their exchange
scores on raw tape only, at least 8 of them, shrunk toward the cohort mean.
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Answered raw tape
D 4 · C 5 · P 4 · Cm 3 4.15
Q What you saw that others didn't? Just help me understand it.
A Yeah, well, it's, it's funny, uh, that decision almost didn't happen, and I, I told, I didn't tell Neil this story until somewhat recently, um, But actually, uh, when we first invested in Green Oaks, it was back during the period where we were a bit more conservative in the VCs. Would, we would back, and as a general rule, we didn't want to back anyone who didn't already have a great brand. And of course, Green Oaks at that time was raising its first institutional fund, uh, and, you know, was not well known at that time. So it definitely didn't fulfill that criterion. Um, and I remember actually, you know, my boss, Seth, and I decided, you know, let's, let's leave this and look at fund two or something. Um, and the next, but I slept on it, and then the next day I, I decided to call my boss, Seth, back and say, you know, I think we should at least make a small bet on this to start, and we did, and which is, it's lucky we did, because that's been one of our most successful, uh, relationships of the last 10 years. But, you know, to answer your question, what did we see in him? I think one thing that stood out even then was, before he raised his fund, he'd done a bunch of Uh, individual deals, not with the fund, but sort of on a, uh, you know, a deal by deal basis raising money for each thing. And we talked to a number of the founders that he worked with, uh, like bomb from coupon …
AI assessment note: “the way founders talked about Neil was, you know, it was really exceptional”
Answered raw tape
D 5 · C 4 · P 3 · Cm 4 4.05
Q I may be veering into completely dangerous territories here, but Why not? Um, are the incentive structures financially right in endowments? When I, what I mean by that is a 120,000,007, eight X. That is a huge amount of carry if you're in a traditional fund structure. Do endowment funds have the financial incentive structure right?
A I mean, honestly, I think the answer is no. Like, uh, I think we're able to do what we do because I have to give credit to our CIO, Seth. He's created a culture where People care about doing these things and want to do these things, and I think also it helps that, um, because we had a period of success, I think we had, you know, we built up enough credibility in our own situation to feel comfortable taking some of these risks, right? But yeah, I mean, the traditional endowment or foundation, I think part of the reason they're not good at this stuff is they don't have an incentive to be right, and people, when they don't have an incentive to take risks, they're not going to want to stick their necks out.
AI assessment note: “I mean, honestly, I think the answer is no.”
Answered raw tape
D 4 · C 5 · P 3 · Cm 4 4.05
Q How do you think about deployment now? I think the media in particular likes to present a very gloomy environment. Um, I don't always agree with it, and it's not actually what I'm seeing necessarily. How do you think about deployment today, and do you think LPs are closed for business?
A People are not closed for business. I think people have to do things in smaller size or might not be able to do as many new things as they would otherwise like, but You know, I think, especially for the, the firms that have top reputations, uh, I don't think they're having that much trouble raising money, right? I think, you know, they, they always have more LPs who want to invest than, uh, than they have the capacity. So I, I, you know, I don't think the top firms are, are hurting in that regard. I mean, maybe, you know, if they try to raise too much, they'll get more pushback than normal and more critique, um, which maybe is a good thing. I, I think it's, uh, you know, it's the smaller managers or the emerging managers that are gonna have a lot more trouble.
AI assessment note: “People are not closed for business.”
Answered raw tape
D 4 · C 4 · P 4 · Cm 3 3.85
Q How do you think about the underwriting process?
A Well, ideally we, we do like to get to know these businesses. And so ideally we like to get to know them well ahead of time. And in the case of coupon, for instance, you know, when we first got, uh, interested in it, it was when we did a reference call on Neil with the company and we're very impressed with Uh, bomb. And that was a, that was something Neil actually invested in before Green Oaks won. Uh, and so we were kind of, uh, you know, disappointed actually that we were investing in this new fund where it was not going to have that exposure. Right. And so we told him if there's ever an opportunity for us to invest alongside you in this company in the future, let us know. Uh, and, you know, and sure enough, within a few years after that, Neil did see there being a potential opportunity to put the structured round together and let us know. And, You know, we had enough time to go visit, uh, the company in South Korea and tour some of the warehouses and things like that, get to know BOM a little bit better. I'd also say, I think we had a prepared mind because by that time, obviously we'd seen Amazon work in the US, right? We'd seen some other things in other countries like say JD in China or Flipkart in India turn out to be interesting as well. Uh, so that was some of what turned us on to the opportunity. And, and in that case, we were able to spend quite a lot of time getting …
AI assessment note: “ideally we like to get to know them well ahead of time.”
Answered raw tape
D 4 · C 4 · P 3 · Cm 3 3.60
Q Yeah, no, I, I get you completely. Can I ask, I, I've spoken obviously to, to many over the last few months and a lot of them regret activity in China. How do you think about China today moving forward? Any lessons?
A Well, it's, I mean, it's something we're wondering about as well. Uh, I mean, it was an area of great success for us for some period of time. You know, we're definitely, I think like many others, we're, we're doing a lot less there now. Uh, I mean, we're not gonna categorically not do it at all yet. Um, but we are reducing it, and to the things that we keep doing, we're, you know, we're, we're very careful about whether they're people that we think are gonna Keep from, uh, sensitive areas of investment, right? And, and obviously also we don't know how these regulations might change in the future. So, uh, that's another reason to keep it small.
AI assessment note: “we're doing a lot less there now”
Partly raw tape
D 3 · C 4 · P 4 · Cm 3 3.55
Q The tables are turned now, so this is going to be fun. Uh, the LP world is an interesting one. How did you make your way into the world of fund investing and being an LP and come to be at MIT?
A Well, it's definitely not a job that you, uh, you think of as a kid or something and say, I want to be an LP, right? I mean, I didn't even know the job existed probably till my early twenties. Uh, you know, not to be too meandering, but maybe to explain a little why I got interested in technology as well. Um, you know, originally I thought I would be an engineer, and I was lucky. I had this interesting job in high school where I worked at HP and Intel working on microchip design on this project called the Itanium processor. And so I, I assumed when I went to college, I'd probably do double E and, uh, you know, be an engineer after that. But I wound up at Sanford and, uh, started in double E and About four summers into my internship at HP and Intel working on this process, so I decided I didn't really like working as an individual contributor engineer in a cubicle somewhere and wanted to do something different, so I switched to something at Sanford called Management Science and Engineering. In retrospect, maybe what I should have concluded is I just didn't like working at a big company. But anyway, I did that, and I was also part of a lot of entrepreneurship activity at Sanford, if you will. There was this club called Bases that helped organize the career fairs and speaker series and things like that. So I got to meet a lot of interesting VCs and entrepreneurs through that. Um, …
AI assessment note: “not to be too meandering, but maybe to explain a little why I got interested”
Partly raw tape
D 3 · C 4 · P 3 · Cm 3 3.30
Q How do you think about deployment now? I think the media in particular likes to present a very gloomy environment. Um, I don't always agree with it, and it's not actually what I'm seeing necessarily. How do you think about deployment today, and do you think LPs are closed for business?
A People are not closed for business. I think people have to do things in smaller size or might not be able to do as many new things as they would otherwise like, but You know, I think, especially for the, the firms that have top reputations, uh, I don't think they're having that much trouble raising money, right? I think, you know, they, they always have more LPs who want to invest than, uh, than they have the capacity. So I, I, you know, I don't think the top firms are, are hurting in that regard. I mean, maybe, you know, if they try to raise too much, they'll get more pushback than normal and more critique, um, which maybe is a good thing. I, I think it's, uh, you know, it's the smaller managers or the emerging managers that are gonna have a lot more trouble.
AI assessment note: “People are not closed for business.”
Partly raw tape
D 3 · C 4 · P 3 · Cm 3 3.30
Q I, I totally agree with you. Incredibly different profiles there. Uh, in terms of like, I think we learn a lot from mistakes actually. When you think about picking mistakes that you've made in the past, what did you see or not see that with the benefit of hindsight you wish you had or you missed?
A It's, it's funny. I mean, That's a question we get asked a lot, and it's hard to, I can't point to that many things that are like the common things that go wrong. It seems like it's kind of idiosyncratic in many cases. Everything goes wrong for slightly different reasons. I mean, one thing is just, I think sometimes we underestimate how badly people want it, right? Like, it takes a long time to be successful at this game, and it's, I think it can be probably a slog for the first five to seven years. I think the, the feedback loop you have to get going as a VC is, You need to have some wins that make you super credible to other people, right? And then that allows you to have better deal flow, have better winning ability, et cetera. And then you have that positive feedback loop. Um, you know, some people may be very impressive and have an interesting thesis and work really hard. And then for whatever reason, after five to seven years, they just, they didn't, uh, get a lucky strike and they, it's harder for them to stay relevant at that point, right? Because people point at that person and say, well, they've been doing this a long time and they haven't been successful yet. Maybe they're not that good, right? But there's other people who do get lucky more quickly, uh, and they, you know, they're lucky enough to get that, that feedback cycle going. So, you know, I, I, sometimes I th…
AI assessment note: “I can't point to that many things that are like the common things”
Partly raw tape
D 3 · C 3 · P 3 · Cm 3 3.00
Q I, I totally agree with you. Incredibly different profiles there. Uh, in terms of like, I think we learn a lot from mistakes actually. When you think about picking mistakes that you've made in the past, what did you see or not see that with the benefit of hindsight you wish you had or you missed?
A It's, it's funny. I mean, That's a question we get asked a lot, and it's hard to, I can't point to that many things that are like the common things that go wrong. It seems like it's kind of idiosyncratic in many cases. Everything goes wrong for slightly different reasons. I mean, one thing is just, I think sometimes we underestimate how badly people want it, right? Like, it takes a long time to be successful at this game, and it's, I think it can be probably a slog for the first five to seven years. I think the, the feedback loop you have to get going as a VC is, You need to have some wins that make you super credible to other people, right? And then that allows you to have better deal flow, have better winning ability, et cetera. And then you have that positive feedback loop. Um, you know, some people may be very impressive and have an interesting thesis and work really hard. And then for whatever reason, after five to seven years, they just, they didn't, uh, get a lucky strike and they, it's harder for them to stay relevant at that point, right? Because people point at that person and say, well, they've been doing this a long time and they haven't been successful yet. Maybe they're not that good, right? But there's other people who do get lucky more quickly, uh, and they, you know, they're lucky enough to get that, that feedback cycle going. So, you know, I, I, sometimes I th…
AI assessment note: “I think sometimes we underestimate how badly people want it”
