The Exchanges

Q And what prompted the decision to move back to Bay Area?

A Couple of things. Um, one was from a professional perspective, it turns out in the software investing, Um, practice that we'd started at Lightspeed in, you know, 2016, 17 had grown. Um, about a quarter of our Lightspeed India funds over the years have gone into software investments. We've got about a hundred total portfolio companies in the region, so about a quarter of that are software. And, uh, many of them had moved to the US, and many were threatening to move to the US. Um, and so, from a fund perspective, It made sense for us to have somebody there who'd had 10 years of runtime in India, new software, um, and could help these companies, uh, uh, bridge over to the US. And there's so many things that companies that need, we can talk about that. Um, and that trend line has strengthened since then. We can talk about that as well, but we are so closely integrated with Lightspeed globally. And Lightspeed started off in Menlo Park and San Francisco and has spread to Europe and Israel and, um, Southeast Asia and so on, um, and India, of course. And so it helped us on that front as well, because as a platform, Lightspeed can help these companies move there and plug into the Lightspeed platform globally, which is exec hiring, customer introductions, uh, partnerships, and obviously connecting with all of our Uh, partners there in the US and globally, as well as all our portfolio com…

AI assessment note: “from a fund perspective, It made sense for us to have somebody there”

Q And, and are you satisfied the way that India is playing the AI wave right now?

A Not yet. I'm not yet satisfied. Um, I think I posted about this about a year, a year or two ago when post two years ago when GPT, 3.5 came out. It was like every wave of sort of innovation out of the U S or China. There has been, I think, a, a legitimate excuse for founders in India to say, we didn't have access to whatever. So either they didn't have access to the cloud, or to smartphones, or to venture capital funding when that market was small in India, or to large consumer bases, um, or, you know, um, playbooks to scale, or mentors to advise. There's also, these were issues in the past, but today none of these are issues. There's enough capital, mentors, hyperscalers, you know, uh, playbooks, You know, second, third time founders to help you. It's all there. Right? But we're not seeing anywhere close to the amount of innovation or even applications companies built on innovative infrastructure out of India that we're seeing in the US and to some extent Europe and China as well. Um, It's been a bit of a lag effect that's in play here. Maybe two to three are lag. I don't know why, but it's not a hard, it's not a, a hundred percent case. There are lots of interesting companies and we've backed a bunch. We backed Sarvam, um, in the foundation model space. Uh, we seeded that company Pratyush and Vivek, um, I'm going to say 18 months ago. Uh, and then, um, I think Khosla and Uh, L…

AI assessment note: “Not yet. I'm not yet satisfied.”

Q But the question still remains, uh, why have we haven't been, you know, able to, to repeat it? Like we have examples in corners. Fresh work is only one company, which has achieved what it has achieved. Rubric is one company, right? So, so it becomes hard for even global investors to figure out like what really works in India, especially in this cross border thing.

A Are there any, we are excited about it. I don't think, I think we have to just, Not again, apply a framework of the U S the framework from the U S can be, Oh, enterprises, 50% of the market or more actually right now, consumers been in a bit of a sort of doldrums for the last few years, but is enterprise going to be 50% of the startups in India? No. Yeah. I think maybe 20%, 30% is sort of where it might settle at the most because India's got such a huge consumer opportunity, right? Um, if not for anything else. And so if you put that frame in mind and then put the frame in mind, you know, keep the frame on that you might have a lot of compounders from here, right? Then it's just a different flavor. Yes, you will have the, High flyers. Um, and there the founders probably have to move to the US and tap into that market. But if you're sitting here selling into Asia or selling into India or, you know, going as a fast follower, you know, you're not gonna, it's gonna be tough to get very, very large. Yeah. And, uh, it's just a, it's, it has to be a mindset shift more than anything else, and it takes time.

AI assessment note: “I think we have to just, Not again, apply a framework of the U S”

Q Yeah. And, and what is the outcome that you are underwriting when you are making these investments? Is a hundred million ARR company or much, much larger than that.

A Are you talking about any company we back at light speed or specifically in these AI services and AI services? Um, so it's early days, uh, but if I had to think about the investment thesis, broad brushstrokes, and we, as investors, we like to think about what is the investment thesis for investing in a company. There are three or four key points that we need to believe to invest in a company. Um, so one is large markets, um, and these markets, and I'll get, I'll get to, to, to your answer in a second. So large markets, if you think about Customer service as a market, which is a sort of very sort of a bubbling market these days with AI. Um, that's a trillion dollars a year spent on customer service globally. It's a lot. Um, and, um, can AI make a dent there? Absolutely. I don't know if you saw the announcement today from Zomato. Yeah, they, they launched a customer service thing because they've already built it internally for their own consumers. That's an exciting thing. And, um, so it's a very large market. Uh, the reason I mentioned this is because you can imagine building multiple hundred million dollar revenue company in a trillion dollar market, right? Uh, even if you think that a trillion dollar pre-AI market compresses to a A hundred billion dollar post AI market or a five hundred million dollar post AI market, right? Or the billion dollar, the trillion dollar market exp…

AI assessment note: “you can imagine building multiple hundred million dollar revenue company in a trillion dollar market”

Q And what are the, the few companies after that?

A After that, um, uh, we had a Truecaller clone that I invested in. I thought it had a different positioning. Um, I had, uh, invested in, um, a bunch of these utilities, mobile utilities, which I liked to do in the, in, when I was in the US, but didn't make sense here. And there was a learning curve first two, three years where I had to readjust to the market. That time what was happening here was all the early e-commerce companies were starting up. Some of the vertical commerce companies were starting up. Software. I mean, there was maybe, maybe a handful of interesting companies, but that was about it. Um, and so yeah, the first three years were tough for me, uh, readjusting, but then after that sort of there's a thought pattern I went through with my colleagues and then changed sort of what I'd focus on.

AI assessment note: “we had a Truecaller clone that I invested in”

Q So what, what did you realize after those three years, maybe after four, five investments that, that what really worked in India?

A Yeah, a couple of things, and this is a learning for our firm as a whole, and something that we really sort of, you know, make sure that we do as a firm, which is keep in touch with what's going on on the ground in reality, rather than think in an ivory tower and sort of imagine what might be happening or what should be happening. Um, what changed for me was, one, understanding the business models that work here. Um, and we can talk about the different business models that are different here than, let's say, the US or China or Israel and so on, because I think the Indian venture ecosystem has just, um, grown up in a way that's different from these other venture ecosystems, and you can't just say, let's do the, you know, something that's successful in China, let's do that here, or the X or Y that people used to talk about.

AI assessment note: “one, understanding the business models that work here”