The Exchanges

Q And you mentioned that the enterprise sales have also completely changed. Can you throw some light on it? How are the sales done right now? And how are the companies that you know are growing the ARR because it's not the usual contracts?

A Yeah. So a few things. One is, and especially in data, it's true where most companies want to do a POC, right? Uh, in your traditional enterprise sales, like take Workday or SAP or Oracle, they don't do POCs. Right? That's the first step of the process. Second step of the process is when you start thinking about, uh, infra companies, you're selling more to a technical audience than to a stakeholder. Coupa sells to a chief product officer. Workday sells to a CHRO, right? Uh, Salesforce sells to a CRO, right? So each of those, like, it's a very business persona or a business leader persona that you're selling to top down. Here, you're selling to a technical persona bottom-up. Completely different model. Then, if you start thinking about pricing, a lot of companies are moving towards usage-based pricing, and they're getting rid of the per-seat or per-license model. For Pantomat too, like, we have a connector-based pricing model. We're not tethered to any, like, seat count. Whether two people use it or 200 people use it, it's still the same price. So that's change, uh, which is good and bad, right? Like we, we hear both sides from the customer. The customer says, I used to like the SaaS pricing model because when I'm building my budget, I know exactly how many dollars to bake in for the contract for next year. And in data, that's very, very hard to do. Your Snowflake bill, your Dat…

AI assessment note: “a lot of companies are moving towards usage-based pricing, and they're getting rid of”

Q So, it's not just hardware, it's software also, right?

A Actually, if you Google or search on the internet for reluctance motors, they're usually called software control motors. So, if you look at control systems theory, right, there are linear systems and non-linear systems. Linear systems are equal inputs, equal increases in input, Will give you corresponding equal increases in output. Non-linear systems are not so. You do something in the input, it will do something in the output. Noise, you know, whatever, different torque and all that. So, this is classic control system problem. Um, the one way to solve it is, ah, use precise software control algorithms, which operate at a very high speed, ah, and control the motor in a very, at a very fine level. And this has been done for many, many applications. Because we have now, um, processing power, rather cheap, ah, and runs at high speed, we are able to control. And that's one more thing that came together.

AI assessment note: “they're usually called software control motors”

Q What kind of response, ah, you were getting from earlier doctors? Like, any embarrassing moment you want to share?

A Yeah, um, um, so we were telling the same story on this one. So the, the initial customers, yeah, we had a bunch of issues. The motors not starting, motors burning out, ah, manufacturability issues were there. One of the difficult things with reluctance motors is there is some difficulty in manufacturing. Ah, so there is something called an air gap. Between the rotor and the stator. The air gap is of tighter tolerance and reluctance motors, but not impossible. So we have to figure all those things out. I mean, with one of our deployments, the air gap became so small, um, it is working quite well. The smaller the air gap, it works really well. But the problem is, when the big, when the air gap becomes very small, when the rotor turns at a higher speed, there are centrifugal forces, which expand the rotor momentarily. It actually went and hit the stator, um, and it's very dangerous, and it is like, ah, so we had all those issues, so we had to figure out all those problems. I think once we figured it out, then what we did was, I think we took a step back, and we did a lot of testing by ourselves, on two-wheelers, three-wheelers, on, you know, on our own testing. We ran for hours and hours at various temperatures, and we generated a lot of data and fixed all the problems. Um, and now the customers like us because, We do everything from first principles, so the level of support we c…

AI assessment note: “The motors not starting, motors burning out, ah, manufacturability issues were there.”

Q Let's go back to our journey, um, conversation about Chara. Like what's, what's the, State now, how much motors we are making, what are our customers, revenue, any number you can share?

A Ah, thanks for asking that. We are at the classic inflection point. We have developed the technology, we have the product market fit, we have the customer traction. Our only problem is to, um, you know, sell, manufacture, and deploy, both in India and outside India. This year, um, is our real revenue start. Last year, we made a little bit of revenue. We sold a few hundred motors, uh, generated about a crore of rupees. This financial year, which is ending next month, yeah, in a month, um, uh, we will be shipping about a few thousand motors. This month, we'll be doing about 350 motors. Next month, we'll be doing 500 motors, and we continue to increase. So we are at that stage where The technology we developed has become a reality and we're shipping against, uh, revenue. Uh, of course, aided by the geopolitical, uh, tailwinds. Um, yeah, that's where we are.

AI assessment note: “This month, we'll be doing about 350 motors. Next month, we'll be doing 500”

Q Got it. And why is observability absolutely necessary for AI when classic monitoring was enough for normal software?

A Yeah, I think monitoring gives you a great understanding of how your systems are working in terms of their performance from a latency perspective, from a cost perspective, and those are important dimensions to measure. I think in the case of these probabilistic systems, you also want to have a deep understanding of how your systems are behaving in response to these User intents that are typically being specified in natural language. There's a lot of variance in how people can express the same thing, and so you want to make sure that your AI system is robust enough to handle all of the various ways and people express their intent, and they are able to fulfill the intent accurately, and so it's important for AI systems to have, uh, the Observability that's beyond just these performance metrics. These AI systems need to log the entire trace of how the AI reasoned on the initial input. What were the tool calls it made? How did it interact with the LLMs? How did it sort of ultimately generate the response? And did that response actually meet the user intent? Was it accurate? Was it correct? Were there any hallucinations in the generated content or not? And so you really need to capture all of that information to be able to effectively evaluate the quality of that response, and as a result, your entire AI system. So that's why observability becomes a pretty key aspect of building the…

AI assessment note: “in the case of these probabilistic systems, you also want to have a deep understanding”

Q Now you work on pre-sales or post-sales?

A I work on post sales. Um, well, I lead the post sales field engineering team, so my team works with our customers to deploy brain trust and to build AI solutions, and so we have solutions architects as well as AI engineers who help our customers through the entire journey of onboarding to an evals platform, operationalizing observability, And then really integrating BrainTrust into their AIS DLC so that they are doing evals in a, in a fairly, um, systematic way, that they have operationalized how they do error analysis, uh, that they have built all the integrations that they need to, to automate a lot of this workflow. So my team helps our customers go through those phases. Uh, but my role is, you know, Talking to interesting teams like I really enjoy talking to any team that is either considering brain trust or considering, you know, onboarding to an evals platform to teams that have. Built AI systems and are looking at how they can now have, you know, another step function improvement in their processes, so I work with everyone.

AI assessment note: “I work on post sales. Um, well, I lead the post sales field engineering team”

Q Well, this has never happened before, right? In history of Ah, so, engineering, like on, how do you debug?

A Yeah, I mean, debugging is pretty, um, interesting in these cases because, you know, you really want to, Understand how every component of a particular trace of a conversation performed. Uh, all of that data is logged into your observability system, so in Braintrust you can see every step that was performed by the agent, you know, as a spam, and so you can have, um, you know, a full context of the spam, but you can also have scorers that can evaluate the execution of a particular spam. So you can have scoters, which are essentially functions that evaluate the quality of a particular action. You can define those as deterministic functions, you know, implemented in code, or you can use LLM as judges, but then you can evaluate like, how did each span perform? And that can give you a fairly good way to zero in on problematic areas of your agents. So within a particular span, Within a particular trace, you can quickly figure out where did the agent go wrong because your scorers can now point you to that particular place fairly effectively. But then you can also look at understanding the All your production traces holistically. You can do clustering analysis to see what are the trends that you're observing in your agents as they work across multiple different interactions. You know, where do they get things right? Where do they get things wrong? How do they get things wrong? Why do t…

AI assessment note: “you can evaluate like, how did each span perform? And that can give you”

Q And you have been for the firm with 13 years. Tell me, how did you see the firm evolve? What are the fund size when you came in? What are the different fund size that you have seen as your journey?

A Yeah. So, uh, fund 10 when I first joined was a hundred and fifty million dollar fund. Uh, this last one, fund 13 was a two hundred and seventy million dollar fund. So we've kind of, we've, uh, we've, uh, marginally increased the size of the fund to keep pace with round size and, uh, keep pace with kind of the growth of the B to B of the B to B world. And our take on it is the size that we're at while we want to keep kind of marginally increasing to keep pace with inflation and keep pace with the growth of the space. Um, to do early stage well, you gotta align your fund size with the stage of company that you're working with. And so it's always for us been a, been a core principle and a core, uh, core focus. Keep the fund size aligned with this, uh, with the stage you're working with. And ultimately that gives you two things. One, uh, it allows you to return capital. Uh, you can, your DPI numbers, uh, your DPI numbers look better. It gives you more flexibility in terms of the types of deals you can do, how you underwrite deals. And then the second, second thing it does is that, Uh, for a lot of the founders we meet with, I think one of the challenges that they have to navigate in today's world, especially, is taking on too much capital at an early stage. And so we try to really help them think through and be methodical about how much capital they raise from the early stage. Tha…

AI assessment note: “fund 10 when I first joined was a hundred and fifty million dollar fund.”

Q And, uh, you earlier mentioned that the web is not ready for it. Why do you think it?

A Web is not ready, not because of infrastructure. Of course, there are infrastructure problems, and we will, you know, talk about it. I think the primary reason is because commerce is broken then, because you remember I just talked about the detergent equation. If you take, uh, one of the largest, uh, in the US, the largest, uh, one of the largest is Procter and Gamble, and they make amazingly beautiful smelling, beautiful color, uh, detergent, you know, Tide and others, and they spend a lot of money on that brand. And they spend even more money on digital shelf. So it shows up in the right place with the right color, with the right vanilla fragrance and all of that. And it's all built for humans because we like the color. If it is not in the right eye level, when you walk into Walmart, you will not see it. So they fight to make sure that it's properly placed. Again, coming from Amazon, you know that game. Now imagine that robot that did the laundry is making that decision. It will say Siddharth and, um, Nancy like organic detergent. They like vanilla fragrance, but it should not have any toxins because Kabir is small, and it takes that and break that detergent into molecular level, and it will understand exactly the components required, and then say, okay, this is what I need to buy. I zero care about Like, I don't care at all about the color or the, you know, the branding or a…

AI assessment note: “I think the primary reason is because commerce is broken then”

Q And your choices of companies have been great, right? You were early member in Splunk, Cloudflare, and Arrive. Like, how did you make those choices?

A Yeah. Yeah. I mean, for me, I, I think sometimes luck plays a role, but I think broadly, when I think about the companies to join, there are a couple of things I always look for. One is, uh, I'm a big believer that if, if the market you are in, if the market has a big opportunity, you as a company will get a lot more chances, uh, to make it work, right? If you're in a, in a market with a small dam, uh, you do, do one thing wrong and you're out of business more than like, right? So, so for me, um, when I chose Splunk, I just felt that big data was something up and coming, and I felt that, you know, everything up to that point was structured data indexing, and Splunk was the first company where you can index unstructured data and make it searchable, and I just felt that the time of this is massive, and Splunk was doing great work. Similarly for Cloudflare, the market, the initial market of Cloudflare was in the tens of billions of dollars, and Cloudflare found, actually, I felt found this very niche market where Anybody on the internet who doesn't have the scale like the larger companies, you know, like think about the Yahoo's or the Googles of the world, but they still need their website to be fast. They need the website to be secure. Their website to be online. And there was nobody serving that. And I just felt that the market is big and it's just underrepresented market. And t…

AI assessment note: “when I think about the companies to join, there are a couple of things”

Q So just want to give a flashback to our audience. What has changed in how you think about technology and startups since last time we spoke?

A You know, the biggest change, of course, has been the realization that AI is going to have such a huge impact on the market. Um, when we met last time, I had already invested in companies like Concentric, Vince, Robust Intelligence, all of which are AI native companies, but at that point, they were just regular companies. Nobody thought of it as an AI company. After ChatGPT, people became aware of the capabilities of AI, and that is having a tremendous impact on the market. Now, those companies are still growing. Robust Intelligence got sold. It became Cisco Intelligence. Evinst and Concentric are now mid-stage growth companies. So, you know, the businesses continue to build, but I think the public realization of the impact of AI is going to be huge. It's a generational technology.

AI assessment note: “the biggest change, of course, has been the realization that AI is going to have”

Q And how did it shape your GTM and your all decision making?

A Yes. So we have never done open source before. Like, I don't think our team has experience in open source or what do you do with this? But I'll tell you, it was a chance meeting with, uh, Parag Agarwal, who now runs Parallel, who was the ex, uh, CTO of Twitter. And I was sitting with him and I was just generally chatting about the things and I had a question to him saying, should I just open source bit of this? I don't know what to do and why should I even do it? And he said that there's only two reasons you should open source. One, it is giving you, so you're building a product that you can't build in isolation and you need the community to help you contribute, et cetera. And second, it helps you build developer trust. So don't think of this as a distribution channel or a marketing channel. It builds, you want to build solid developer trust on your product. And that flipped our switch saying we want to do both of these. We don't know how to do open source, but we want to do both of these. We're building a gateway which will have, and today we support 2300 models. And this was probably 50 then. We're like, this is going to increase. Everybody will want to do new things. I can't solely say I will build everything. I will need to have the community help in building. And second, we want developers to trust the technology. Like all core technologies have to be trusted. So we decide…

AI assessment note: “we decided that we're not an open source company... we want to open source the core”

Q And usually the vegetables are, you know, tightly packed in those, you know, plastic nets. And, ah, it is said that for every trend, there is a counter trend. So First Club is, ah, Trend or counter trend? How do you see it?

A Very clearly a counter trend. Uh, because everybody has been talking about price. You go and look at the one line tagline of all the platforms. At least now with the latest regulation and all of that, people cannot speak about 10 minutes. But otherwise, just try differentiating, right? If you take the color off, you cannot differentiate one app over the other. So everybody was so obsessed with, like, delivery in 10 minutes, last minute app, and I'm here for your urgency. So it was all about that. So we flipped it, and we said, like, yeah, we understand speed is important for the consumers, and it's changing. The world post-quick commerce versus the world peak-quick commerce are two different worlds that we are living in, uh, but that cannot be the reason why consumers should be shopping from you. So for us, uh, multiple things we question, by the way, right? So it's not just about the speed. I'll start with, uh, uh, uh, the selection itself. We don't have, like, 10,012 thousand products. We have 4000 to 5000 products on the platform, right? Number one. Uh, number two, in any product you take, there are maximum of two or three brands. You would not find, like, 20 options for the consumers to come and shop. We don't have reviews and ratings on the platform, uh, right? And, uh, ours is the only platform which tells the consumers that less than one 99, you cannot check out. You nee…

AI assessment note: “Very clearly a counter trend. Uh, because everybody has been talking about price.”

Q How it happened, like, across categories, is quality, when it comes to quality, is India, one India, or we have different layers? Quality.

A The understanding of quality, Would be very different for different sets of people. For somebody who has never used A cream biscuit, for example. I've just lived on the Parleji glucose biscuit. For that kid, you go and ask what is a better quality product, they'll say that Dark Fantasy Chocophils, or Milano, or something like that, right? For a consumer who is like, I've used all of this, but for me, a biscuit, which is without maida, without sugar, without artificial preservative, palm oil, this is what is good quality biscuit for me, right? The third one will say that, no, I have Experience like international products, local products, everything. The aftertaste needs to be very different. So the cohorts of quality understanding is going to be different. It will not be one size fit all sort of a philosophy. But when it comes to certain categories like fruits and vegetables, sweetness is sweetness for everybody. The quality parameter is exactly the same. Freshness of vegetables is the same. Dry fruit, when you have almond or cashew, it needs to be crunchy. It needs to be bigger. It is not going to change from, I will not say, oh, I need lesser crunchy. Uh, versus you telling her better crunchiness, right? So that I would put it as a commoditized categories. Quality is fairly homogeneous. With respect to other categories, the quality parameter is different basis the exposure tha…

AI assessment note: “The understanding of quality, Would be very different for different sets of people.”

Q It must have been crazy, right? You just closed around an acquisition, which you passed on and then you got a term sheet and then term sheet closed in a month or how much time?

A Term sheet closed like literally, like we just took a week to sort of negotiate on something from the first conversation. Yeah. The first, I mean, when we got the term sheet from Seligman, it took us a week. I mean, they obviously wanted to, Us to sign them. I think we were kind of completely okay with most of the terms. We just had to make sure we are on the same page regarding a few things, nothing major. We closed it in a week and, uh, yeah, like, uh, that's, that's basically how quickly things moved. Right. So I went back to India after that, because we had to tell it to the team. Um, there are a lot of people who have been there with us early on. We want to make sure that with this one raise, they are also rewarded. Their goals are understood, et cetera. So we did that.

AI assessment note: “when we got the term sheet from Seligman, it took us a week.”

Q And which are the largest name in this industry? Like in terms of, let's say if you think about hotel industry, you think about Marriott, you think about Hilton, you think about a few other names.

A So, I mean, by, by size, you know, like you will have, you'll have the Brookdales of the world and you will have the Ericsson's of the home. So there's that, but it's a very, very long tail, you know, so obviously the, the, the Brookdales and those would be like seven, 800 facilities or homes, but I would say it is a very long tail industry. So it's not like, it's definitely not like how hotel industry of like, Hey, Marriott or Hilton, two or three have, have like consolidated that. And that's not necessarily a bad thing, by the way. I think there is value in standardizing and adding in, but there's also value in, you know, like being much more, it's a very high touch service industry.

AI assessment note: “you'll have the Brookdales of the world and you will have the Ericsson's”

Q But still it was a services company building web and mobile apps. So how did you differentiate?

A From, from mobile, how we differentiated was that we have a design team here in Silicon Valley. And design is such a thing, it's very hard to offshore, because it's so cultural. Just imagine if, you know, someone has not experienced Disney, and they have not experienced how healthcare system works, or they have never bought an automobile insurance in their life, they can never connect with these companies. And these were our clients, some of the biggest ones. So what we realized, this is so cultural that we can offshore. And we built a 150 people design team here in Redwood City. And customers loved it, and where customers wanted to work with us for our design team, and they stuck around, you know, because our engineering team was good, and they were delivering at a cost-effective price, and it was sustainable, and we became almost like a startup within a, you know, a Fortune 500 company.

AI assessment note: “how we differentiated was that we have a design team here in Silicon Valley.”

Q as the new chairman of Tata Sons. And that was the year when Indian economy was also, you know, got liberalized and was open to the world. How was that time for him? And because even the most successful businesses and including Tata Sons, it was a time When big shift was taking place. So how he navigated that time, and how he made Tata son's future ready for the...

A Very, very interesting question, Nancy. So you're quite right. 1991 is when JRD Tata handed over the reigns of the Tata group to Ratan Tata, and Ratan Tata became the chairman of the Tata group. You're also right, that is the year in which Manmohan Singh, as finance minister, under the prime ministership of PV Narsim Rao, announced his famous budget. If you remember with Victor Hugo's words, you cannot stop an idea whose time has come, and the Indian economy was suddenly liberalized. This was still the first year of Ratan Tata's chairmanship, but I think Ratan Tata grasped the impact of this budget on the Indian economy. He knew the Indian economy was going to be far more open in the years ahead. He knew licensing was on its way out. He knew that this would be an era of heightened competition, and he knew that many Tata companies would have to up their game to face the competition and become best in class in India and globally. So a lot of his focus in those early years of his chairmanship was about making the Tata Group future ready. He did many things, but I'll describe three or four things that he did. Uh, I was a young manager in the group at that time. One of the first things that he did, Nancy, was, uh, he wanted the group to be You know, inspired with the spirit of excellence. So he established what was called the GRDQV program, which later became the Tata Business Excel…

AI assessment note: “So a lot of his focus in those early years... was about making the Tata Group future ready.”

Q Very interesting. So, I think this is the one last question I have for you, Harish. You have finished writing eight books. This is your eight book. What goes into writing a book? Like, how did you, you know, approach this whole book writing process? We'll just take this book's example. Like, how many interviews you conducted?

A So, so, you know, Nancy, uh, After I had returned from Bombay, after paying my last respects to Mr. Ratan Tata, I kept thinking about him, and I keep thinking about what has driven him in his life, and thereafter, last November, I was invited to deliver a lecture by XLRI Jamshitpur, and this was the JRD Tata Memorial Lecture, And, ah, after thinking carefully, I chose to speak on the subject of doing the right thing. How Mr. Ratan Tata can inspire us. So I put a small speech together. That was the first step towards writing this book. Um, and I think some of the basic framework of the book was built in that speech, and then when the professors at XLRI Jamshitpur told me that they liked the speech very much, there were lessons in that speech, they wanted to print it in one of their in-house magazines, um, then I came back and said, this looks like a good framework for the book itself. By then I had interviewed three or four people,

AI assessment note: “That was the first step towards writing this book. Um, and I think some”

Q So how and when Tata Suns became a global business?

A So, you know, uh, Tata's have always had some global businesses, uh, even during JRD Tata's time. Uh, for instance, TCS was a global business. Uh, but during Ratan Tata's period, I think Tata Sons took some very, very firm steps towards becoming a truly global company in terms of owning global brands, in terms of owning global businesses. Ah, you would have surely read about the acquisitions of Tetley, the acquisitions of JLR, the acquisitions of Chorus, ah, the acquisitions of Tata Daivu, ah, in, ah, in Korea, and many such acquisitions. So, acquiring global brands or global businesses was one route to becoming global. But the other route to becoming global was to build companies in India Which could compete with the best in the world, which were benchmarking themselves to global businesses. For instance, you know, at that time, I was part of the Titan business, and I know in Titan, we were already market leaders in India, but we started benchmarking ourselves against Swatch, which is, ah, one of the largest global watch companies, and saying, why can't we reach their levels of profitability? Why can't we reach their levels of innovation? Why can't we reach their levels of branding and marketing excellence? So I think globalization was not just the acquisition of companies or going to more countries. Of course it was that. But it was also a global mindset, Nancy. Saying that w…

AI assessment note: “during Ratan Tata's period, I think Tata Sons took some very, very firm steps”

Q In SPC, in the US, in the Bay Area especially, has existed for the last seven years, right? What are the some of the known companies that have come out of SPC, if you can share those journeys?

A Yeah, yeah, absolutely. You know, one of our companies, um, thinking back to, like, Fund One, um, this was, you know, some of our earliest companies that, you know, um, we're proud of our, like, great companies, Base 10. So this is kind of one of the leading kind of like AI inference companies that really kind of built out, um, I mean, like a great product that is allowing enterprises to really kind of like deploy a variety of kind of models within kind of like their applications. And you've seen phenomenal growth. They recently kind of raised around valuing them at like, you know, multi billions of dollars. Like I think a two billion dollar valuation that, you know, I think has been announced publicly. Another one of our great companies is render. So this is kind of building a, Uh, a modern kind of like essentially, uh, platform as a service kind of app. So basically instead of building on bare metal, kind of like on the cloud services, you can use Render to manage kind of your compute and your data, your databases and so on. Also doing phenomenally well. Um, another one of our early companies is Pilot. So this was started by Waseem. Um, Waseem, Jessica, and Jeff, and they're basically building out , they started doing this a while ago, but like what would AI enable bookkeeping look like, right? Like from scratch. Um, we also have in our portfolio Gamma, which is one of a very…

AI assessment note: “one of our earliest companies that, you know, we're proud of our, like, great companies, Base 10.”

Q So, so enterprise infra, what are the areas for founders to tap in? What are your learnings from your existing company? You have invested in some of the fantastic companies like Nile.

A Yeah, Nile, Yuga Byte, Acryl, which is now called Data Hub. Um, so I would say in enterprise infrastructure, which is a vast stack, includes data, includes security, includes orchestration, includes site ops, SI, you know, many departments, many personas. One particular sub area which is a legacy area that I am super excited about to see how LLMs will impact them is in all things observability. So, the area say that today Datadog, Splunk, Elasticsearch, all of them play in the old New Relic and the massive budget. You have to opt their software that you pay for to operate your business and to know if your site is working okay, right, and then debug problems. I feel, and the underlying infrastructure is using, Mongo in some cases it's using Clickhouse in some cases, but a lot of it is based on the backend of Datadog. It's based on Elasticsearch, on the Elkstack. I think this area requires a couple of new companies with LLMs as their backbone. Um, so, throwing a challenge out. And the interesting thing about this area is, what kind of founders do you want to find there? I think this area is both hard with massive upside is because the DNA of founders needs to, there has to be a co-founder who knows applied AI really well. There has to be a co-founder who knows the observability and the whole thing about what we call MET, the nature of data. It's like metrics, and events, and logs…

AI assessment note: “One particular sub area which is a legacy area that I am super excited about”

Q So last thing is, you know, what are you doing beyond work in the India-US corridor? What is, what are your passions?

A Yeah, right. I would say I've always been fairly involved in the nonprofit sector. You know, we have been backing projects, whether they're in the South, whether they're East, Urissa, Bengal. So, in terms of, ah, you know, I have a nonprofit called Saxa, and we have always been big into women's and children's education and healthcare related initiatives in India. That is always true. Education remains a huge passion of mine. And I think education for a changing India, and for a changing US for that matter, is very important to me. And new modes of education, coursework, how do you teach differently, what are the skills that you want more from a trade side versus fundamental learning, remain very important to me. So, backing nonprofits and, you know, groups like Pratham in India, which works with the government, these are very important to me. A second is, you know, big into arts, especially music. Try to support a lot of the India-US corridor on music. Ah, also very passionate about the sacred music traditions of all over the world, especially India. Ah, music traditions which bring people together, you know, bring people together at a spiritual level. Ah, want to call out, there's a beautiful music festival that we, ah, we've been supporting for, for six, seven years now in New York City called Raga's Life. I'd be proud to say it's the only 24 hour Indian theme music festival …

AI assessment note: “I've always been fairly involved in the nonprofit sector... big into arts, especially music.”

Q So bringing on to my next area where, you know, does perplexity make IVP more bullish on, on the India-US corridor?

A Absolutely. Yeah. Now, to be fair, like, it's not that we were not bullish before. As I, as I remind people, like, we were investors in Jyothi's company, AppDynamics. Jyothi started two companies afterwards, Harness and Traceable. You know, for me, he's an iconic Indian entrepreneur, you know, humble roots, went to IIT, came out here, and has been Probably in some ways almost like the Andy Bechtelschein or Steve Jobs equivalent in, like, infrastructure software and what he's done with three companies in the last decade. Uh, the Rubrik team I'm really proud to work with. Glean, of course, Arvind Jain came from Rubrik. Glean's been an amazing success story in the enterprise. But, um, I think what's cool now is that a founder who was born in Chennai can come to Silicon Valley and build something to compete with the biggest of the bigs, right? And I think that part of consumer markets or healthcare markets with Shiv Rao being Indian born founders or Indian educated founders is also why I'm so bullish. And I think what, what gives me pride is that fundamentally they understand the greatness of the United States. The United States gives you an ecosystem that's hard to replicate anywhere else. Where we're sitting right here, people have tried for decades to completely recreate Silicon Valley, you know, in different parts of the world. There's a magic about this place. Every time you f…

AI assessment note: “Absolutely. Yeah. Now, to be fair, like, it's not that we were not bullish”

Q And this is very interesting. You went ahead and interviewed 200 people, right? How, how is it possible? Like, how can somebody set up meeting for you? You said that the founder has to go ahead and set up all these meetings for yourself.

A No, so this is where I hired an HDR, and basically asked her to set up meetings, and I didn't give a lot of specifications. I didn't say that I need companies only of this size, or I need x percentage of this size companies. I just asked her, gave her a big list, and asked her to set up meetings. And then I also tried to incentivize people who were forthcoming with their time. So either a Starbucks card of 50 dollars or hundred dollars for the time they spent with me. And, and usually it was 50 dollars. The folks who did really well were generous with their time. I rewarded them with hundred dollars. So that's how we, we went about doing the interviews.

AI assessment note: “No, so this is where I hired an HDR, and basically asked her to set up meetings”

Q Any, any CEO that you admire the most?

A There are lots of people in my career that I've admired. I've said this before. One of my, one of the early people I admired a lot is a chap called Robert McNamara. Now, McNamara was the CEO of the Ford Motor Company. Okay, till President called, President Kennedy called him and said, now come and be my Secretary of Defense. And he was involved in the Vietnam War, a great guy. Then he went on to be the Chairman of the World Bank. So he's one of the few guys in the world who has worked in private sector, government, and public sector. That's rare, ok, non-profit when I say public, non-profit, ok. So, McNamara was outstanding that he was, when I used to read about him, when I was in college, starting my career, etc, almost everybody would say he would easily be the best prepared person in the room. He would read every single document said to him. That's a habit I ingrained from McNamara. Now, the other good habit of McNamara is, after he finished his stint, the Vietnam War, everybody got pasted. Everybody got egg on their face. He wrote a lovely book called In Retrospect, where he said, what went wrong? Why did we go wrong with the Vietnam War? That requires a lot of reflection, and a lot of humility to say, I was wrong. Yes. And McNamara says, the reason why we went into the Vietnam War was, we assumed that Vietnam will go the communist route. He said nobody sitting in President…

AI assessment note: “One of the early people I admired a lot is a chap called Robert McNamara.”

Q So how was your experience with Nokia was different from PepsiCo and Unilever? PepsiCo and Unilever were similar?

A Similar yet dissimilar, because the categories are very different, food and this thing. Nokia was easily the best company I've worked in. I have no shame in saying that. A wonderful bunch of people, great culture, ok. In Nokia, what mattered was, you did what's right for the company. Earlier you were talking about, you know, how do you ensure that people work for the institution, who can speak out. You know, in 2010, when Nokia had its reorganization, Ok, one engineer. We used to have 860 blogs in Nokia those days. Ok, not today. 15 years ago. One of the engineers of R&D wrote in a public blog, ok, saying, this reorganization is like reordering the chairs on the Titanic. Imagine. His boss, Nicholas Savender, who was the Chief Operating Officer, came to, you know, visit us in Delhi. I was running India then. So, in the car journey, I said, hey, Nicholas, this guy David has written this. You know what Nicholas said? Yes, Shiv, I need to tell him that, you know, it's good to have this thing, but, you know, just think about what you're posting.

AI assessment note: “Similar yet dissimilar, because the categories are very different... Nokia was easily the best”

Q And what happened like after the COVID years, like from then till the time you raised the massive round at five billion?

A Um, I think it was just keep on, keep your head down, and, and we, so, 20, 20, late, 20, 20 was, we, we made our first major acquisition also. We acquired a company called Slintel. Um, and that was also interesting. So we were in this thing where we always gave out company level information, right? We identify which companies are coming to your site, which companies you should be selling into, who should your sales team prioritize. The moment we started giving insights to salespeople and we started building a sales UI, the first question we got from salespeople was, okay, I know IBM is in market. Who at IBM should I talk to? IBM is so big. So we didn't have that data. We had their data from their CRM, but CRMs are so bad that they might still have your old job from 20 years ago in somebody's CRM, right? So we're like, okay, we can't do this thing. So we started working with other vendors and other partners who would bring that data. And we realized that this space, twenty-twenty now, Everybody's trying to enter each other's space. Money is like flowing through the system. Everybody wants to build every product. And so we like, okay, our partners are either going to get bought out by our competitors, or they will start entering our space. So we decided to go out and acquire a company. That's when we acquired Slintel, which was a sales data and a sales intelligence company. And s…

AI assessment note: “late, 20, 20 was, we, we made our first major acquisition also.”

Q But still it was a services company building web and mobile apps. So how did you differentiate?

A From, from mobile, how we differentiated was that we have a design team here in Silicon Valley. And design is such a thing. It's very hard to offshore because it's so cultural. Just imagine if, you know, someone has not experienced Disney, and they have not experienced how healthcare system works, or they have never bought an automobile insurance in their life, they can never connect with these companies. And these were our clients, some of the biggest ones. So what we realized, this is so cultural that we can offshore. And we built a 150 people design team here in Redwood City. And customers loved it, and where customers wanted to work with us for our design team, and they stuck around, you know, because our engineering team was good, and they were delivering at a cost-effective price, and it was sustainable, and we became almost like a startup within a, you know, a Fortune 500 company.

AI assessment note: “how we differentiated was that we have a design team here in Silicon Valley”

Q Um, so if you can share a little bit about how the tech ecosystem developed, which are the top three or five companies in tech that came out of Switzerland, right? And how are the exit ecosystem also in Switzerland?

A I mean, there are companies which are well known because they do B to C, right? And there's companies which are less known in B to B, right? And I think Switzerland was long term known for doing med tech and pharma things, right? A company like Octelion, for example, very well known, bringing new medication to the market, uh, ground breaking, right? Then we had a huge wave of crypto startups out there. For example, the foundation of Ethereum is in Switzerland, right? And then we had a lot of ICT startups, which also became unicorns. I mean, for example, we have two backup software companies, which originated here. We also have a fashion company called Onshoos, which a lot of people talk about nowadays as the competitor to Adidas and Nike. And it's so amazing that all of these different things came out of the same country, right? Now in tech, I mean, where I'm involved in, I mean, my history with tech, uh, basically after Google, I was working with companies that had to start from scratch. Just recently had an exit with one of the propoli companies of Sigtig, where I also was involved in, they were called Beekeeper, and they merged together with LumApps, and, uh, at, uh, at the end of the merger, they had a valuation of 1.1 billion dollars.

AI assessment note: “A company like Octelion, for example... foundation of Ethereum is in Switzerland”