The Exchanges

Q And, uh, can you tell more about your investments like Coher and Harness specifically talk about Coher? Why did you make it? And you know, uh, how does it differentiate with the other LLM providers?

A So. I'm a very thesis-driven investor. Before making any investment, I look at that particular area, which segments of the market you should invest, and which are the best companies, and your thesis about investing. So Coher, there were about three or four reasons why I invested in Coher. Coher was very early, just like OpenAI and Anthropic at that time, so I could pay. Coher was from the beginning focused on enterprise revenue. They were not focused like OpenAI and Anthropic on consumer, which is a large market and they're done well, but focused on, um, enterprise. Second is they wanted to do only on-prem secure AI. And the reason for that is As you all know, LLMs have to be trained on proprietary data. So when the enterprise have their proprietary data, they're very concerned if it's not secure, it's not on-prem, just like on-prem cloud when it first came out. So we felt that was the differentiator. They're focused on enterprise, they're focused on on-prem, making it secure. Also, we felt they were the snowflake Of the market. They didn't take investment from any of the hyperscalers. They had opportunities to do that, but they chose not to. So give the user and the enterprises a choice of any cloud. Rather than be tied to one cloud. And then they had the fourth thing which was really exceptional they did is the strategics who invested in them.

AI assessment note: “there were about three or four reasons why I invested in Coher.”

Q So, and there are so many companies which are between a hundred to a billion and are wondering, you know, where to?

A Great question. The markets were closed for last three, four years. So venture capital and private equity companies through the two of 20, 20 boom invested so many dollars in all kinds of infrastructure and application companies. But the market window last two years used to open and close, open and close, like Arm went public and few other companies went public. Then Astera Labs went public six months later and market closed. So it was opening and closing. Because of what I do, economic issues, political issues, and everything. However, I feel this year is different. I feel it. There's so many IPOs which have gone, I think it's about 14 or 15 IPOs in the tech world which have gone. The M&A has accelerated in AI, cyber, everywhere. And I feel fundamentally all the big companies are doing well, the acquirers are doing well. There's tremendous amount, number of smaller companies. Some of them are being acquired for high prices because they're doing well and it's strategic. Some of them are acqui-hires, we have seen, because there's too much money and too many companies doing the same thing. I think it's acceleration in the second half of the year. I was at the conference, uh, last, uh, 10 days back, and The banking conference they said there were over 500 companies waiting to grow IPO just in the software space, which are over three hundred million in ARR. So pipeline is there. Th…

AI assessment note: “The M&A has accelerated in AI, cyber, everywhere.”

Q So Umish, like you are saying this wave, and everybody's also agreeing to that, that this wave is bigger than the previous waves of internet, mobile, right? And happening at the fastest pace that we have ever seen. So how do you differentiate, you know, with your experience between noise and signals?

A It's a great question. It's getting tougher and tougher compared to 20 years back. Uh, I think depends on where you invest. I do the seed A, B. I used to do late stage. And those, um, investment philosophies are different. So early stage, it's all about team, team, team. Meaning there's no substitute for having complimentary team with the right experience. So the first thing I look for is the founder, the co-founders. Are they Um, have they worked together? Are they complementary and others, and do a lot of due diligence on that, so that's important for me, the most important thing. Then, Coming from engineering background, I do technology stack, um, detailed due diligence, because ultimately, if you don't have a differentiation on your tech, doesn't matter. Someone's going to catch you. Another 10 smart people somewhere else are going to do it. So I look at tech stack differentiation. Look at the, look at the competitive landscape with The other competitors in that space. Then I look at, is the market large enough? There are two types of opportunities. Existing market, which is large enough, and there's a disruption happening, so I take care of, look at that inflection point, or a new market like AI coming, growing rapidly. So analyze the market to see what the dynamics are there, what the disruptions are there, and see whether these entrepreneurs are really Uh, solving that p…

AI assessment note: “early stage, it's all about team, team, team.”

Q If you can share right on the recent merger between Sale Loft and Clary, how did it happen? How did the synergies come together and what's the ultimate goal here?

A Yeah. So when, Since I invested in Clary in 2018, they grew more in 2018. It was a series B investment at very early. Um, they've grown since they are 20 X on ARR. However, The competitive market around them, um, started becoming heavy, so their growth rate slowed down. And there are five, six companies around that sales enablement area, which were all growing slowly. So each one of them could not go public. So getting scale and expanding the TAM was the goal for Clary. So with this sales laugh in Clary, there's three things that happened. Expand the TAM, you get synergies, cost synergies, and they can get to cash flow break even faster. So now with combined companies, as they take the cost out and start performing and growing again, uh, with unit economics being good, I think the ultimate goal is someone may buy them or they could go IPO because they've not started to reach scale.

AI assessment note: “the ultimate goal is someone may buy them or they could go IPO”

Q So earlier in the fast, you know, the last 20 years, the thesis was at least to make a big company, you need a very strong CEO with business expertise and a very strong tech co-founder. Has it changed in AI? Because what I'm hearing is, you know, people are focusing more on deep technical founders and You know, their assumption is these founders will learn their business.

A Great question. You know, there are two types of founders. I've invested over 40 private companies now, and I've seen the trend. The repeat founders is 75% of my investments, and the reason is they've gone through it once, and so they've learned from it and don't make the same mistake again. However, in AI, there are a lot of first-time founders. So, The technical founders and their technical, um, differentiation is extremely important. But ultimately, if you want to build a company which you want to go to IPO, the management team around it needs to complement these founders. A CRO who has done it before to scale from zero to billion dollar revenue. A CMO to get the demand engine going. The customer success team around it To keep the customers and making sure they're listening to the existing customer for product roadmap. The operations team, the finance team, all those become very important as you grow to billion dollars. And some of these companies are growing so fast that I think they're having trouble keeping up with hiring of the right talent around them. But the most core factor for me to invest is always the team. It's all about team, team, team, no matter where you go. Early stage, seed, A, B, later stage. It's all about the team because you want to bet on the best team because best team focused on a large market will figure out ways how to get there. A team which is ah…

AI assessment note: “technical differentiation is extremely important. But ultimately... the management team around it needs to complement”

Q And how did you partner with Jyoti at Harness?

A Yeah. So Jyoti started AppDynamic, which was a phenomenal company he built and sold it for 3.7 billion. I think Jyoti felt he could have built it two billion. Um, so once he I was done with AppDynamic. I sat with him at the same coffee shop. You and me sat at Cafe Venezia, and I wanted to talk to him. I said, I want to get engaged with you with your next venture whenever. And he said, I'm going to right now do an incubator. Uh, which he did call unusual ventures. And then I'm going to pick two companies and I'm going to run those two companies. And he did it for three years later. He did exactly that, which is phenomenal. And so he started traceable and hardness and random. Now he merged them. So when this was going on, his vision of DevOps CICD pipeline, which were competitors like GitLab and GitHub were closed systems. And he articulated a vision saying, amongst all these six or seven CI, CD, CV, all these modules, CD is broken. I want to be the best in CD, continuous development. And he came out with that product. And then I said, once that happens, I'm going to go across the stack and do all seven or eight models. And he executed over the last five years. Um, So when he was doing that, he called me in 20, 20, and said, Dimesh, I'm raising money. You wanted to work with me. I want to work with you. This is the opportunity. And that's when I went in. There was very easy decis…

AI assessment note: “he called me in 20, 20, and said, Dimesh, I'm raising money.”