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How to Raise VC Funding in India: Lessons from Stellaris
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Alok Goyal of Stellaris Venture Partners, the $600M fund behind Mamaearth, Whatfix, and Axtria, breaks down 13 years of lessons that every founder pitching VCs needs to hear.
Alok co-founded Stellaris Venture Partners after a 'Brownian motion' career: a failed startup, eighteen months unemployed after the 2001 NASDAQ crash, and a decade running SAP India before venture found him.
Today, the $600M fund backs Mamaearth, Whatfix, and Axtria, with over half of all cheques written before a founder has a single line of code. In this conversation with host Akshay Datt on Founder Thesis, Goyal reveals three anti-patterns that catch every VC at some point: market size estimates are almost always wrong; over-indexing on the market over the founder kills returns; and fearing Google or SAP will crush a startup is rarely justified, because incumbents have too much baggage to move. With agentic AI replacing entire job functions and a new US-India trade deal opening corridors for Indian software, this masterclass on early stage investing in India arrives at exactly the right moment.
👉Why Alok Goyal stopped writing cheques for an entire year in 2024, and what he concluded about the AI shift that rewrote the Stellaris investment thesis.
👉Why three predictable anti-patterns catch every VC at some point, from misjudging market size to fearing incumbents like Google will execute on obvious threats.
👉Why the shift from AI co-pilot to autonomous agent changes software pricing from per-seat to per-outcome, and what every Indian SaaS founder must understand.
👉What the Axtria story, where 22 employees used personal savings to buy out a top investor, reveals about the leadership quality Alok Goyal prizes above all else.
👉Why cold emails have never, in 13 years and over 4,000 companies seen, produced a single Stellaris Venture Partners investment, and what founders must do to access India VC funding instead.
Subscribe to Founder Thesis for weekly conversations with India's most consequential startup builders, and follow Akshay Datt on LinkedIn for daily insights on venture, AI, and the Indian startup ecosystem.
00:00 - Why Most VCs Hide This Truth
00:01:44 - From Broke Consultant to VC Founder
00:11:46 - How Helion's Split Shaped India VC
00:16:58 - The Dirty Secret of VC Returns
00:27:04 - How 400 Companies Yield One Cheque
00:36:09 - 40 Years of Software Evolution Explained
00:42:20 - AI Co-Pilot to Agent Shift
00:57:09 - Three Anti-Patterns Every VC Makes
01:14:37 - Cold Emails Never Work in VC
01:22:44 - The Leader You Follow to War
#AlokGoyal #StellarisVenturePartners #VentureCapital #IndiaStartups #AkshayDatt #FounderThesis #IndiaVC #IndiaVCFunding #EarlyStageInvesting #AgenticAI #AIAgentsIndia #StartupInvestingIndia #HowToGetVCFunding #Whatfix #SaaSIndia #FounderJourney #IndianStartupEcosystem #startuppodcast
Disclaimer: The views expressed are those of the speaker, not necessarily the channel
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Transcript
Introduction to Venture Capitalism
00:00:00
Speaker
What makes somebody qualified to be a VC? You don't need to have any specific qualification to be a VC. This is a business of formulating a gut. One of the dirty secrets of our business is that despite the high risk of this asset class, the median return is actually very good.
Common Mistakes in VC Decision-Making
00:00:16
Speaker
What are some of those anti-patterns you've discovered so far about your decision making? One lesson learned is don't anchor contacts. Alok Goyal is the founder of Stellaris Venture Partners, the $600 million dollars fund behind Mama Earth, Watfix and a bunch of massively successful companies. Alok shares 13 years of hard-won lessons on how VCs actually evaluate founders, what makes a great startup bet and the three mistakes that every VC ends up making. There are elements of gambling in this business. We don't believe that consensus is a great way to make venture calls. Almost always when I have over-indexed on large competition,
Qualities and Backgrounds of Successful VCs
00:00:51
Speaker
I've been wrong. how do you identify who's a great founder when they're not great yet
00:01:01
Speaker
alok you are one of the founders of stellar s venture partners a seasoned vc couple of very interesting bets in your portfolio welcome to the founder thesis podcast my first question to you is uh What makes somebody qualified to be a
Alok Goyal's Career Journey into VC
00:01:19
Speaker
VC?
00:01:19
Speaker
Actually, in many ways, Akshay, I would argue that you don't need to have any specific qualification to be a VC. I remember that when I joined the profession back in early 2013, somebody made me read this book called E-Boys, which was written on d on Benchmark as a firm.
00:01:40
Speaker
And it was the story of how they got created, were the backgrounds of the different partners that started. And it was fascinating to see as to what the variety of backgrounds of people were. Somebody was a recruiter, somebody was a lawyer, somebody was an investor as well. Somebody was an operator. So people came from wide variety of backgrounds.
00:02:00
Speaker
This is a business of formulating a gut on what the world may look like in the next eight to 10 years. And it's a business of judging people. um It's a different kind of a muscle.
00:02:13
Speaker
um And therefore, I'm not sure whether any particular background prepares you for it or whether any particular background also precludes you from the seat. Okay. Tell me about your journey. What what made you get into this world of venture investing?
00:02:26
Speaker
I think mine has been a very unplanned one, Akshay. It's been a Brownian motion. i started out thinking that I will be a professor and teach computer science. That's what I wanted to do.
00:02:39
Speaker
I sort of started with that. um but Where did you graduate from? and I did my undergrad in computer science from IT Delhi. Okay. And post that I went from my PhD to UT Austin.
00:02:51
Speaker
Okay. um Again, switched around in a few areas, but ultimately narrowed down to doing my PhD in the systems area, specifically in how video streams get transmitted over a network.
00:03:03
Speaker
And which year is this? This was 1992. Wow. Okay. Yeah. I'm a bit historical. Yes. i understand about that yeah i was in feelinging that yeah ah Yeah. So that's what I started with.
00:03:20
Speaker
ah Interestingly, midway through my PhD, I did a small stint at Microsoft in Redmond and the arrogant youth in me thought that I was very impressed by what Microsoft had built.
00:03:35
Speaker
was actually also very inspired by the Infosys IPO that happened in 1993. um And combination of just that youthful energy or stupidity, whichever way you can call it, I thought I want to be an entrepreneur.
00:03:51
Speaker
So I quit my PhD, came back to India with another friend, tried starting a company, didn't work out. And thereafter, my journey has been started. IT services business. That's right. I wanted to be product engineering services company.
00:04:05
Speaker
um which actually timing was not bad, um just that I was too naive um to be able to build anything at that point in time. So I did a short stint as a software developer, was writing software with which people design semiconductors, came to the conclusion coding is not what I want to do, switched to strategy consulting, initially in India, then in the US,
00:04:32
Speaker
um all put together six years, I actually enjoyed consulting. Okay. ah Which company? So initially with McKinsey in India and then a firm called McKenna Group in the Bay Area. McKenna Group was actually the first true blue consulting firm to be born in the Bay Area. It started when Intel and Apple started in the Valley.
00:04:53
Speaker
And it was a great journey. I loved it because most of my work was with startups formulating their product market strategies. until the downturn of 2001 and 2002 happened.
00:05:06
Speaker
And you know most people, I'm assuming our audience will not know what that downturn was, but I would like to believe that that has been the steepest downturn in the tech world ever.
00:05:21
Speaker
um NASDAQ dropped from 5,000 to 1,000 during that period. And my firm, which was only working with high-tech companies and product market strategies, basically from a storied firm, actually went down to nothing.
Formation and Growth of Stellaris Venture Partners
00:05:36
Speaker
And ah I thought I was a product person at that point, look for a job for a year and a half, couldn't get a single job, to be honest, went broke.
00:05:47
Speaker
I had done an MBA, my wife had done an MBA. So we were completely down to the barrel there. And eventually they got a Swiss. You must have taken on debt. Yeah. So I finally got a sales job.
00:06:02
Speaker
which I didn't want to be honest, but I took because I had to pay the bills. And I think I discovered that I enjoy sales. It's one of those things. It's like an experience good that until you try, you don't know whether you like something or not.
00:06:15
Speaker
I think just the kick of doing a deal, I really loved. And then I spent 10 years as a software salesperson and by and large, it was around large enterprise, large deal selling.
00:06:28
Speaker
I did that across a variety of roles. Initially for one year with a company called Siebel that itself went bust, and then for nine years with SAP. And across this time, initially in the US, then personal circumstances brought me back to India.
00:06:43
Speaker
And I ended up working for SAP in India, and eventually led the India P&L as the chief operating officer here. So that's sort of been my journey. i Why did I now? How did I come into venture?
00:06:57
Speaker
um I came to India because my mother had cancer and SAP was nice enough to allow me to be here. But once she passed away and once I had been running that P&L for three years, I was under pressure to move to different parts of SAP.
00:07:15
Speaker
Specifically, they were pushing me to go back to US or Germany. By that time, my wife had decided to be an entrepreneur. And she was not keen to quit. So I was trying to figure out what can I do with my life next?
00:07:28
Speaker
What can I do for the next 20, 25 years? And I worked with a coach. um And one of the hypotheses that came out was early stage tech investing. And I thought, why not give it a try?
00:07:41
Speaker
And that's what led me to to venture. And you joined Helion. That's right. You know, ah the bizarre thing is I didn't know anything about any startup. I just barely heard of Flipkart.
00:07:56
Speaker
I did not know any venture funds either at that point in time. But um as I was talking to different people, one of my friends put me in touch with Helion.
00:08:08
Speaker
It was more an informational discussion. I wanted to understand what this profession is like. But one thing led to another. And I found myself inside Helion. This was the end of 2012. And I joined them in January 2013.
00:08:21
Speaker
And when did Stellaris start? So early 2016 is when two of my partners and I left Helion. um That was a time when a few funds in India had been created in the mid 2000s.
00:08:37
Speaker
The same cohort of funds had continued. And we were the first set of people to break away to start a new fund after nearly a decade in in India.
00:08:49
Speaker
So 2016 was a fundraiser for us, but January 2017 onwards, we started investing from our first fund. So we have now been around for just over nine years.
00:09:01
Speaker
Okay. um You know, you probably must be constantly wanting to avoid the fate of Helion. Today, Stellaris is much bigger than Helion. What were your learnings? Like, like why why didn't why isn't Helion one of the big funds in India today?
00:09:21
Speaker
So, um first of all, I'll say, Akshay, that I have never worked with a smarter set of people than I did at Helion.
00:09:33
Speaker
And my, now that I am at the age that I'm at, my assumption is I will never again work with that quality of people. um The founders of Helion, all of them had um absolutely outstanding backgrounds.
00:09:49
Speaker
And I think they built a firm which was certainly one of the best, if not the best at that point in time. So India's first venture-backed IPO, which was MakeMyTrip,
00:10:00
Speaker
actually came out of Helion as well.
Venture vs. Public Markets
00:10:02
Speaker
right And while I'm giving you one isolated example, actually, there are a battery of outstanding outcomes that came out of Helion. um But venture is a funny profession, Akshay, that you hire people.
00:10:16
Speaker
They eventually become partners in the firm. um And unlike regular corporates, which have a classical pyramid in the hierarchy,
00:10:27
Speaker
um venture is sort of like an individual business as well. Every partner defines their own agenda, have their own investment styles, have a different view of how a fund needs to be run.
00:10:40
Speaker
Sometimes those ideas match with each other. Sometimes those ideas do not match with each other. And this is not a, this is not a, what should I say?
00:10:51
Speaker
um This is not a comment on Helion, but the fact that different people within the partnership had different ideas. And we felt at that point in time that we would be better off coming out and building a firm in a way that we believed in.
00:11:08
Speaker
Right. But we learned a lot of things at Helion. I think it was one of those unique firms where just the bar for intellectual honesty was very high. the bar for founder empathy was very high.
00:11:22
Speaker
Also, I think they were amongst the first ones to say that, look, as the entrepreneurial ecosystem is evolving and getting larger and larger, it's not just that we are making a bet on the founder.
00:11:36
Speaker
The founder is equally making a bet on us. They need to see something in us because of which they choose us. And that, what do they see, is largely going to be our expertise in those
Strategies in Venture Investing
00:11:47
Speaker
segments.
00:11:47
Speaker
And it's very hard to build that expertise unless you have depth, and depth doesn't come without focus. So we took a call in Helion to be very sectorally oriented, and which is why actually I was hired, for example, I was hired to build the enterprise software and services vertical.
00:12:03
Speaker
um Similarly, my colleague Rahul, he was looking at consumer products. So we we were very sectorally oriented and those are things that we learned and that's what we have continued from our Helion days.
00:12:16
Speaker
Why didn't it survive the exit of three partners? See, that's a hard one, Akshay. As I said, different people have very different views.
00:12:29
Speaker
um Helion was started by three founders, one of whom had actually left even before we did. And that has been a very successful fund that he has created post that, which is Fireside.
00:12:42
Speaker
He came from a consumer goods background, used to be at Unilever. um And I believe that he has created a pole position in that particular segment and built an outstanding firm in Fireside.
00:12:56
Speaker
um And so essentially, there were quite a few people that eventually left um and beyond which it was difficult. But the good news for the ecosystem is that four new funds actually came out of Hylion.
00:13:09
Speaker
So Firesight came out of it, Stellaris came out of it, one of our colleagues created Arkham, and one of the original GPs actually also created a fund called Fundamentum.
00:13:22
Speaker
So while Hylion does not survive on its own, but there are four new funds that got created out of it. And I think overall for the ecosystem, that's not such a bad thing.
00:13:32
Speaker
That's amazing. I was not aware there was like a Helion Mafia. Yeah, so there is a Helion Cubs or Helion Mafia, whatever you may want to call it. Right, right, right. Okay, amazing, amazing. Okay. um How is, ah ah you know, for somebody who has money to invest, how ah How should that person think about investing in private markets through a VC fund versus investing in public markets? What's the difference and you know ah what is the right lens to look at this asset class of venture investing?
00:14:09
Speaker
It's a great question. And I'll tell you what I tell my friends Aksha first. ah Many of whom have money. um Some of them think about this asset class. So first of all, why does the asset class exist in the first place?
00:14:25
Speaker
See, when it comes to public market, those stocks are available on a stock exchange. Everybody has access to them. You can buy one share of a company. You can buy a million shares of a company.
00:14:37
Speaker
um You can sell a week later. You can sell 10 years later. Whatever you feel like you can do, right? Number two is that all information about that company by regulation has to be equally available to everyone.
00:14:53
Speaker
um And that's something that the regulator ensures is the case. And there is also very constant disclosure. There are quarterly disclosures, annual disclosures that happen. So there is lesser information asymmetry in that market.
00:15:08
Speaker
Private markets are very different. Number one, you start a company today, Akshar, It's your call whether some part of your company should be given to someone else or not.
00:15:19
Speaker
Even if I want and even if have money, I can't necessarily have access to. access is one big component component of it. The second part of this is that it is there is no information available in this business.
00:15:33
Speaker
Information only comes from founders or comes from your proprietary research, but there are no information disclosure norms in private markets. So that creates, in fact, a lot of information asymmetry in this market. And the last part that one has to understand is just the concept of risk.
00:15:53
Speaker
It is a highly, highly risky asset class. And I don't know what a good parallel should take, Akshay, but if you see a two year old kid and you have to figure out whether this kid is going to become a Sachin Tendulkar or a Taylor Swift.
00:16:11
Speaker
and you are trying to see some very early signals, Oh, this kid started speaking when they were nine months old or started running when they were 15 months old. And therefore there'll be a great athlete or a great singer. They're trying to clutch on those straws to be able to analyze those risks and those indicators of success or future success.
00:16:31
Speaker
But, uh, there is very thin information and therefore there is very high risk. Also, the longer the duration it takes to get to the success, the higher the number of points of risk, higher the number of unknowns, and therefore very few things work out in our business. So now to go back to answer your question, I think if one is investing in this asset class, one has to recognize that even before we think of the very high rewards is that it is very high risk.
00:17:03
Speaker
By and large, I tell my friends that use your play money for investing in this business and not your investing money to invest in this business.
00:17:14
Speaker
Because whatever you put, there is a fairly high likelihood that it may actually go down to zero. You know, one of the dirty secrets of our business is that despite the high risk of this asset class, the median return is actually very low.
00:17:31
Speaker
Now, why do people still invest? People invest because the ones that succeed the returns on those can be absolutely humongous. And there are some massive outliers in our business.
00:17:45
Speaker
And those outliers create a lot of difference between the average and the median. And people want to catch those outliers. ah I don't want to sort of go too far with this parallel, but there are elements of gambling in this business that if you are lucky,
00:18:04
Speaker
then you may truly actually get to a jackpot. I would like to believe that it's more than just being pure dumb luck. um But there are elements of, right? And then like with everything else, Akshay, like I'll take an example, even though I'm a private market investor, I actually do not invest in public markets in picking stocks directly.
00:18:30
Speaker
I believe that movement of markets is governed by institutions and not by individuals. And there are people who spend their days, day in day out in evaluating a Reliance stock or an HDFC stock or a Mahindra and Mahindra stock.
00:18:46
Speaker
And just my cursory glances at those charts and finding one information from my friend, I don't have the ability to create any alpha in those markets.
00:18:57
Speaker
So I would rather leave it to professionals who do this day in, day out. And that is by and large my advice to my friends as well, that even if you do want to take exposure to this asset class, you are actually better off trusting professionals who have access, who gain at least some level of muscle because they're not talking to two founders or five founders.
00:19:17
Speaker
They're talking to hundreds of founders every year. And they see more patterns of success and failure. And despite all those advantages that professional investors have, it is still a highly risky class, asset class. So be prepared to fully use your money when you invest even in a fund.
00:19:34
Speaker
Okay. I want to recap a little bit of my interpretation of your answer. Um, If you are looking for great deals, and by a deal, it means like a mispriced asset, like a company which could become a massive success, but like say a reliance, it could become a reliance one day, but today is available cheaply.
00:19:58
Speaker
you are unlikely to find those in public markets because there is equal information. Everyone can analyze books. There's a lot of public disccoure disclosure norms, et cetera. So the chances of finding great deals in public market is low, which is what makes private investing appealing, that you can find these...
00:20:16
Speaker
uh next flip cards or whatever next alliance or so on so so that is to find those next great companies is only possible in private not only possible but chances are much higher if you're investing in private market therefore the appeal of investing in private market But these very features of ah the unequal access to information and access and being part of the deal is what makes it so risky that you may end up missing the best deals or your your information ah
00:20:49
Speaker
is based on secondary research, whatever you could be wrong. There's a lot of gut involved in that decision making. And therefore that makes it equally risky. And the best way to invest in this asset class is through a portfolio approach. Like is instead of picking a a Zomato or a Reliant stock, it's better to just invest in a index fund. Same way, the equivalent of an index fund investing to some extent would be like to invest in a VC fund.
00:21:15
Speaker
So, Akshay, some parts I do agree with. Some parts maybe I'll i'll make some small modification. I think even in public markets, people generate alpha. They bring their unique insights.
00:21:28
Speaker
up All I was commenting on was that information availability is more democratic there. But that doesn't mean that people can't create an alpha there. And at least my biases for someone like me, and that's just my choice, even there I would trust professionals to do it than my own therefore.
00:21:45
Speaker
despite that democratization of information. But I think you can make a lot of money in public markets as well and people do. So there are great funds, hedge funds who will actually up create a lot of alpha.
00:21:57
Speaker
In private markets, the risk is even higher than public markets. I think the one thing and maybe I will go ah go to the next level on this one is that I think index fund equivalent in private markets is actually a bad idea.
00:22:13
Speaker
Index fund is basically taking exposure to the market overall. Like in, let's say you are investing in let's say you're taking exposure to Nifty 50 or Nifty 500, then you're taking exposure to the broad market. The broad market exposure or average or median in venture is actually not worthwhile at all.
00:22:34
Speaker
And so here, when you are investing, you are basically investing behind the investment judgment of the people who are picking inside of those funds.
00:22:46
Speaker
And the alpha here comes not because they make a large number of bets. Alpha comes because they make a smaller number of bets and pick those judiciously. So as you are constructing a fund and for the sake of example, actually, let's say somebody has a hundred million dollars to invest.
00:23:05
Speaker
See, there are three variables that you are toying with. You have to decide the number of companies that you're investing. You have to figure out how much ownership do you take in each of those, right?
00:23:18
Speaker
You could put all your money in a single company or you could invest in 50 companies with relatively small ownership. You also have to decide how much money do you put in the first checks versus how much money do you put in follow on checks, right?
00:23:32
Speaker
And the reason you make those distinctions, the third one is because you learn a lot more about the risk parameters as you spend more time in those companies. So you might say I'll put a half a million in a company today, but as I learned more about the founders and the space, and if I like it, like the trajectory, I will actually put another million behind it tomorrow.
00:23:53
Speaker
But I'm not going to expose all the money upfront when I have a lesser understanding of that risk or reward for that matter. Right? So those three variables is what you are toying with. And there is a judgment call to be made on each of these.
00:24:06
Speaker
The challenge with our business is that hardly anything works. the number of points of failure are so many that by and large, the odds are against you in every single bet you take.
00:24:20
Speaker
Right. And therefore, one of the questions you're asking always is not that what can go wrong, but you're also saying if everything goes right, can it be such a big outcome that it can make up for all my other failures as well?
00:24:37
Speaker
And for some For that to happen, not only do you need to be part of that company, but you also need to have a substantial ownership of that company. If a company becomes a billion dollar and you own 1% of it, at the time of exit, you only make 10 million and in a 100 million fund, you will need 30 of those for you to get to 300 million as an outcome.
00:25:01
Speaker
And you can't make 30 great outcomes. That's not possible. You likely will have two or three at best. So ownership in what succeeds is also important. That's why the upfront ownership you take, what do you put in reserve ratio? How many bets you take?
00:25:17
Speaker
There is an inverse correlation between the number of companies and the ownership you get in companies. But those are the judgment calls that fund managers are making day in, day out. Okay. Amazing. Amazing. It's a very good understanding of the incentives and motivations of fund managers in terms of how they think about when to invest.
00:25:38
Speaker
Businesses which i like, say, operationally heavy business, like, say, an India Mart would be and ah very operationally heavy business. They take some decisions every quarter, but it is more important to execute those decisions well. It seems to me like running a venture fund is not so much about operational excellence as much as it is about decision-making excellence.
00:26:02
Speaker
I think at a broad level, that is correct. Um, While there are operations in any business and ours has as well, if I were to compare my life as an operator versus what I do today, that operational intensity in venture is far lesser than what it is in a regular company.
00:26:21
Speaker
I remember that in the year that I quit SAP, I think we had we had closed about 2,000 deals in that year, which means that we worked on 5,000 to 6,000 deals in a year um There is a large army of sales, pre-sales, industry experts, value engineers, a finance team. Just you feel like you're on a railway platform where trains are coming, going, tickets are being checked all the time. right that's the Venture that way is very different.
00:26:54
Speaker
Every individual defines their own agenda. They are constantly thinking where the world is going to move. They define their investment thesis. They meet people that they want to meet. and they diligence what they want to do and eventually try and get to judgment calls. There is some operational aspect of our business too.
00:27:13
Speaker
In particular sourcing, i think in early stage, it's a needle in a haystack business. Our ratio is that out of every 400 companies we see, we invest in one. But you have to get to those 400 companies first.
00:27:26
Speaker
Our job is to figure out who is going to start a company literally at the time they're thinking about starting a company. and being in front of them before other people do. And that does create a certain operational component also, but in the grand scheme of things, our operational complexity is nowhere close to what a classical company is.
00:27:46
Speaker
So as ah founder of a VC fund, is your biggest role to pick the right people then who can take good decisions because ah you want to optimize the quality of decisions? Well, ah you know,
00:28:02
Speaker
The answer is yes, but I'll give a caveat to that as well, which is unlike other professions, Akshay, in venture, there is very little of a pyramid.
00:28:16
Speaker
It's not as if my role or my other co-founders role is to find people who can make the right decisions. I have to be making those decisions directly on those companies.
00:28:29
Speaker
Right? So venture winter is actually like a jungle. Every person need to hunt for themselves. So doesn't matter whether I started the firm or I joined the firm later, every person, they need to source their own deals.
00:28:47
Speaker
They need to filter. They need to evaluate. They need to make investments. They need to sit on boards and they need to get these companies to
Technology Waves Impacting VC Investments
00:28:54
Speaker
exit. So in that sense, there is much lesser leverage in this indies in these professions.
00:29:00
Speaker
And as I said, there is much less a pyramid therefore in these professions as well. So, but at the same time, yes, we understand that to constantly evolve as a firm, new people need to come on board.
00:29:15
Speaker
They bring fresh ideas on investing and they need to make their own mistakes to become better eventually. And that's how a firm grows.
00:29:27
Speaker
How have you improved your own decision making? Well, there is an assumption there that I have improved. Akshay, you know, the difficult part of our business is that I'll go back to my earlier math.
00:29:41
Speaker
We invest in one company out of every 400.
00:29:46
Speaker
And out of every 10 bets that we make, one or two work. Now look at the math. I have met 4,000 companies.
00:30:00
Speaker
I invested in 10, one or two work out effect. There are 3,990 that I did not invest in. As good as I think I am, many of those companies become great companies, right?
00:30:16
Speaker
Every day I sit and think, what was I thinking at the time I evaluated those companies? The second part is that out of the 10 I bet on, The one that succeeds, it takes eight to 10 years for that company to succeed.
00:30:30
Speaker
And until I have truly exited, I don't think I'll fully know whether it has worked or not work. Right. In the meantime, some of those companies are beginning to fail. So in the early years, all you see is failures. You don't actually see success in this business.
00:30:48
Speaker
And so all I see a share at all points in time is anti-patterns. What did I do wrong is what I see. What I did right, it actually takes a lot more time for me to figure out. right And I think both one of the fun and one of the drawbacks of this profession is that the feedback loops are veryja are very long.
00:31:14
Speaker
Not very wrong, very long. um What also makes it harder is that sometimes when a company does not work, it may not be because you made a bad choice. It may be because the market's completely changed, right?
00:31:28
Speaker
um One of my colleagues backed the company, for example, in very short rides from Metro stations within a short radius. Great founder, and at least I thought was a great concept, COVID happened.
00:31:43
Speaker
Two years, company could not survive, right? Now, was it a bad judgment call? Should I iterate on my decision-making framework? Or is it just plain bad luck? Sometimes it's also also actually plain bad luck as well.
00:31:58
Speaker
right So we also have to figure out what to learn from and what not to learn from. And despite all the failures we see, I mean, we still have to wake up every morning and be super optimistic and be willing to back our own conviction.
00:32:15
Speaker
with all those failures behind us, if we are not optimistic, we'll not be able to take a leap of faith that we do. How do you still have conviction after seeing so much failure? like like Like, it just sounds like a... I would imagine being in your shoes, would have probably lost my conviction in my judgment if I had seen so many failures ah the way you're describing it.
00:32:38
Speaker
I think there are times... So I think, first of all, you have to be an inherently optimistic individual. i If you are not an optimistic individual, I think it's very hard to be in this profession.
00:32:53
Speaker
um I also think that you have to be a bit bold in the sense that you have to be willing to stick out your neck despite all the failures behind you. When you like a company, you need to have the confidence that there must be some good reason why I like the company and be willing to back your conviction, be willing to bring that company to the investment committee.
00:33:16
Speaker
And despite the failures, sort of sound confident as to why you think this one is going to succeed. Right? So I think that inherent optimism is required, but there are times in your career you do go through those cycles. I remember that when I backed my first company, within six months, I knew Akshay that this is not working out.
00:33:38
Speaker
And I think I took a real beating. Personally, my colleagues didn't give me a hard time, but I gave myself a hard time. I think in general, I think we are the harshest critics of ourselves, not others.
00:33:51
Speaker
And there was an almost, actually there was a period of, there was a period of 14 months where I did not write a single check after my first check.
00:34:03
Speaker
I took it so harshly at that point in time. And, you know, theoretically, I knew the math that one or two out of 10 work. So even if the first one did not work, not a big deal. But that's not how the brain thinks.
00:34:16
Speaker
I also remember that when Gen.ai started, and I'm going back to, see, November 22 is when OpenAI anyway got announced to the world.
00:34:29
Speaker
In 2023, I remember I was, I did take some bets, but I also did not, anticipate the evolution to be what it was um this time around.
00:34:44
Speaker
Again, I could argue I've seen many evolutions in the past. I've seen cloud, I've seen mobile, I've seen internet actually from the ground up as well. And I think certain past assumptions actually are a baggage in your head.
00:34:58
Speaker
I completely misunderstood the pace of evolution this time around. And I post 2023, actually took a break first. I did not write a single check in 2024. There was like a 12 month period.
00:35:13
Speaker
And it is not a lack of conviction actually. But I thought, let me understand where this train is headed before I begin to plonk, before I begin to buy tickets um on this train.
00:35:27
Speaker
um And there are times in your career where you do take a step back and you just reflect and you think. But as I said, again, you still have to be a fundamentally optimistic individual.
00:35:38
Speaker
and be willing to take bets on yourself and your judgment. You know, I used to say that to be an entrepreneur, you have to be irrationally optimistic. It seems like to be a VC, you have to be maybe two times as irrationally optimistic as an entrepreneur is.
00:35:55
Speaker
Yeah, I don't think that you have to be irrationally optimistic for this profession. So you ah spoke of how you saw the evolution of the software industry, internet, cloud, mobile, and now AI. um Can you like take me through the VC lens of this evolution? What opportunities did each of these waves create? And that one year break you took before investing in AI, what thesis did you form in that one year? How do you see AI, um the AI wave playing out? What kind of bets do you think makes sense? See, fundamentally, if you go back to the history of software, software was actually very hard to code.
00:36:38
Speaker
It was even harder to customize. It was very hard to integrate with other things that existed inside of a company. The data that sit inside software was very hard to migrate.
00:36:51
Speaker
And given all the resources that it required, i would argue that software, therefore, started as a domain of the large enterprises. There is a reason why IBM was the first large successful software company.
00:37:03
Speaker
They were the ones who had access to enterprises. They were the ones making those mainframes. And they had the armies of people that could actually work, understand your customer's requirement, write, build those software, deploy those, and do the change management required for that software to truly work.
00:37:22
Speaker
And for a long time, that was the domain. So if you trace the history of software over the last 40 to 60 years, I think that one of the big themes is that the software that the center of gravity of software has been gradually dropping.
00:37:39
Speaker
what was largely a large enterprise domain has actually consistently dropped. And I will draw on that at several points as I as i talk about it. um The world went through mainframes. It came to minis.
00:37:57
Speaker
It came to what then began to be called client server. And those things lowered the barrier at which these things could be adopted. right But I think the big shift that happened was the internet first.
00:38:09
Speaker
And this was the early 90s. And that basically de-layered the software in the sense that what stored data was the database layer, the application contained the logic, and then there was a presentation layer, which basically became the browser or what came to be known as a browser. right That was a massive structural shift in software.
00:38:36
Speaker
And the previous generation clients or companies actually took time to migrate to that. And whenever incumbents take time to migrate and there is a new paradigm that when lots of companies get created, I was fortunate to be able to witness that era. This was the mid to late nineties and
00:38:58
Speaker
companies were getting created by the hundreds at that point in time. Right. I was part of one of them eventually, which was Siebel. But if you trace back just the history of CRM, there were hundreds of companies even in CRM.
00:39:12
Speaker
right Very few, of course, succeeded in that way. But I think that was the first wave that happened. But that did lower the center of gravity. of So even a mid-sized company could actually begin to work with software that they could not.
00:39:24
Speaker
So Salesforce is like in ah like a baby of this era? No, it is not. It is not. Siebel is a baby of this, actually. Salesforce started with the legacy approach of being on-prem?
00:39:38
Speaker
No, so I will come to Salesforce. So if you look at companies like iTOO, look at PeopleSoft, look at Sebel, lots of these companies, which eventually got acquired by either SAP or Oracle, frankly, but a lot of them actually came out during this era.
00:39:54
Speaker
The next wave that came was the cloud. And why was cloud? See, even in the three-tier architecture, you still had to deploy your servers. And you had to have an IT staff, ah server room, data center, all those things to be able to deploy and use software.
00:40:11
Speaker
But cloud was magical. Cloud is basically saying, Akshay, you don't need to put any server inside of your company. I will write the software. I will have a single instance running from my data center.
00:40:24
Speaker
You just need to log in and begin to use. And guess what? You don't need to make a perpetual payment for the license. You pay as you use every year. So what was a capex became an opex.
00:40:35
Speaker
And that was the big revolution of SaaS as we know it. And Salesforce was born in that era. there were There were actually two companies that come to my mind. I'm sure there were a few more, but Salesforce for CRM and SuccessFactors for And...
00:40:52
Speaker
and We saw when I was talking about the lowering the center of gravity of software, it is not just the fact that from ah large companies, we are coming down to smaller companies.
00:41:05
Speaker
It is also that we are coming down from power users to common users. So it's not just an HR admin in the company that's using software. actually a typical individual business user is using HR software or a particular or an individual salesperson is beginning to use CRM. That was also a shift towards that lowering of center of gravity.
00:41:28
Speaker
And I remember that Salesforce started by selling to companies with five salespeople, 10 salespeople. That's not what Siebel was selling to. And they truly got to those SMBs that were earlier totally unserviceable malware.
00:41:43
Speaker
And that was a big shift that happened. You did not need to customize software. It can just be configured to companies. And that created the next level of inclusion within software.
00:41:58
Speaker
If you sort of were to take this movie forward, I think we are seeing the next stage of that revolution happen with ai And that is what actually took some adjustment to do.
00:42:13
Speaker
See, still in the world of software,
00:42:19
Speaker
software was there to make a human's life easier, to make them perform better. I think what's fundamentally changing today is the fact that software today can do the work and its job is not to make a human do the work better.
00:42:42
Speaker
And I think that's a fundamental shift we are seeing. And the reason I took a pause at the time I did is that at least it took me some time to understand that shift.
00:42:54
Speaker
This is saying co-pilot to agent. This is a co-pilot to an agent. Indeed. That's the fundamental shift that we are making in software. I was still thinking of software to be a co-pilot at that point in time. I was still thinking of my old mental models um of software.
00:43:10
Speaker
A human was still at the center of my imagination of software where actually I don't think I think work is at the center today. It is not necessarily the human. Right. And ah that is what's shifting completely. The burden of the outcome is now lying with software and not with the customer.
00:43:31
Speaker
ah That just changes the pricing models as well. Because earlier I was making a human better. I was charging per human. Today when I'm delivering work, I'm actually charging for work. being delivered, right? I mean, I'll give an example. we have a founder in our portfolio that I really like.
00:43:48
Speaker
It's a company called Pebit. ah This individual started by building a company that was making software for insurance companies that are doing commercial insurances. Did that for some time.
00:44:00
Speaker
Was actually pretty successful doing what he did. But as the Gen AI wave came, he realized that I can actually do a lot of the work that needs to be done by insurance underwriters or underwriter assistants.
00:44:21
Speaker
And I will deliver that work. I will not just give them software. And while I'm giving an isolated example, those are there everywhere. Earlier software will pop up a window on a call center agent's desktop saying that this is a product that you can position to a customer.
00:44:39
Speaker
Or if there is a pushback, this is how you can answer it. Or if they have a problem in your product and this is the question, this is the answer you give. Well, today you don't need to help that human. You can just do the call itself. right And therefore therefore, the mental models of how we have thought about software are fundamentally changing um today. right So that's the shift that we are making in the way we think about software.
AI's Influence on India's SaaS Landscape
00:45:09
Speaker
I will do argue from a flip side of it as well. Now let's think about therefore how the evolution is happening. In general, when a massive wave comes, it's very hard to create any impact or any value before you have the infrastructure to be able to build those applications.
00:45:29
Speaker
that same by the way argument goes for That same argument goes for the internet wave as well. If you go back and go to the pre-downturn phase of 2001, 2002.
00:45:43
Speaker
Some people might recollect that the most valuable company on earth at that point was Cisco. Why was Cisco the most valuable company? Because Cisco was doing the plumbing for the internet.
00:45:55
Speaker
For packets of information to move from from one point on earth to other point on earth, you needed a whole array of routers and switches. Where were those coming from? They were actually coming from Cisco or the telco companies are making money.
00:46:10
Speaker
So selling shovels in a gold rush. Yeah, absolutely. Telcos were making the money because they were laying the fibers. And initially it was a browser companies that were coming up because that provided the user level infrastructure for anything on the internet to be accessed.
00:46:27
Speaker
That's what came up first. Thereafter came the user level adoption. And what was that adoption? That was search. Unsurprisingly, by What is the most used gen AI application today? Actually, I would argue it is searched today as well again, right? Me asking a question and getting an answer.
00:46:46
Speaker
Today, OpenAI has about 800 million monthly active users, and which basically but is about 10% of humanity already in what, three years, if I'm not mistaken.
00:47:00
Speaker
ah But that shows that that's where the adoption has started first. And you will notice in this process, Akshay, that in the earlier model of software, which is where IBM was the player and maybe a Procter & Gamble was amongst the first adopters.
00:47:23
Speaker
Actually today, the large enterprises, they're all making noises. They're all doing and experiments. But real deployments are actually very slow, right? Just an auto complete with an email or a thread of conversation being summarized by a bot.
00:47:42
Speaker
I don't think of that as true use cases just yet. um And we are seeing therefore a bit of a bottoms up thing here that in fact, we are finding that use cases and SMBs are coming up faster.
00:47:55
Speaker
They have lower legacy to deal with. They have lower risk, even when something goes wrong. And therefore we see faster adoption in SMBs. And I think eventually we'll move towards the enterprise. By this you mean an SMB would be more willing to have a sales agent do their sales rather than a legacy company. Indeed. i mean, you know, we have a company that is working with an automotive dealership or they work with automotive dealerships, I'm sorry.
00:48:25
Speaker
And they are building voice agents for them. um Now, if you were to go to a very large company, and tell them that a voice agent is going to field a call on their behalf? The answer will be no, because the perception of risk will be very high. You'll have to go through seven layers in the chain of decision making.
00:48:42
Speaker
ah ah By the time you see the light of the day, six months would have moved for sure. So they work with individual small dealerships. And the first use case is that people also call these dealerships after 6 p.m.
00:48:55
Speaker
There's nobody to field those calls. Those calls and those leads were being lost anyway. So we might as well try. There is very little risk. They see those working. Then they begin to take even during the day.
00:49:07
Speaker
Then initially it was a call being taken and a call was being set up with a human thereafter. Now they're saying, Maybe just the voice agent can do the call itself um altogether, but they are moving very rapidly as they see value.
00:49:23
Speaker
As I said, there's lesser legacy to deal with. There are lesser layers of decision making to deal with. There are lesser points of integration within those landscapes today. And that's what makes it easier for to adopt.
00:49:36
Speaker
SaaS for India as a theme has never been a popular theme, right? It is generally believed that India does not pay for software. What is the biggest SaaS company in India? Something like a tally, which again is not very big compared to companies which are selling outside India. ah Is that changing because of AI?
00:49:57
Speaker
So um two parts to your question, Akshay. Number one is that it's not that India does not need software. In fact, India uses a lot of software. um I was part of SAP, but similarly, I had friends in Microsoft, IBM,
00:50:17
Speaker
um lots Oracle, lots of different companies. If you look at, and I'm now going a bit historical, I'm actually going 10 to 15 years back. The P&Ls in India of these companies were somewhere between half a billion to billion anywhere even at that time. And I'm sure they have grown much larger. The aggregated software spend in India is actually also pretty high.
00:50:40
Speaker
I think what is different is that when a startup is created, they are bringing a new concept to market. And in general, with any technology, you first need early adopters.
00:50:52
Speaker
And early adopters either happen because someone is a technology buff, they just use it for the heck of it, or they need to see an insane amount of value, a very critical pain being solved that was not solvable earlier.
00:51:09
Speaker
And usually in software, Akshay, we have seen that human productivity goes up with software, and therefore the value is proportional to the cost of that human time.
00:51:23
Speaker
And in countries like India, it's not just about India, but I think it's for Asia at large or Africa as well, the cost of those humans is lower. And therefore, the pain is lesser. And therefore, the value also is lesser. And there's a reason why more software was initially created with countries which have much higher GDP per capita because the cost base is much higher.
00:51:42
Speaker
I mean, I'll give a different example. One of my colleagues and I have visited China recently. China is at the forefront of robotics today. And they're saying that the bulk of the market they're targeting is not China. They're actually targeting Europe.
00:51:57
Speaker
Because cost of humans, even though China is five times India's GDP per capita, it is still not expensive enough. right So I think we have the same issue that we see in India.
00:52:07
Speaker
Now, that does not mean that there is no software company that can be successful. There can be pockets where that success is possible. But by and large, the odds are against you. But does this change when you stop selling software as a service and you start selling service as a software?
00:52:24
Speaker
It's a great question, Akshay. And I think we are, ah you're right, we are also taking a bit of a relook at that. um We recently funded a company which is making voice agents in the banking and insurance sector in India.
00:52:41
Speaker
And I'll tell you the use case. If you look at it, I don't know whether that happens to you actually or not, but I get at least 10 calls every day. Somebody selling me a loan, somebody selling me an insurance, sometimes somebody selling me a car.
00:52:54
Speaker
um ah So, and as you can imagine, India has, I'm forgetting, but probably somewhere around two to 400 million accounts today in the banks.
00:53:08
Speaker
And Through human calling, only so many people can be reached out to. um These humans are not the most highly paid humans. They're not the most educated humans either.
00:53:21
Speaker
They are limited in their own capabilities. They can only customize those calls as much. They follow up pretty much a script. Today with voice bots, you can scale them infinitely.
00:53:34
Speaker
you don't You're not limited by making 100 calls a day. You can actually make a million calls a day. All you are scaling is the infrastructure compute infrastructure at the back end. You can customize every single call. right um you can If you are talking to a 70-year-old woman in Begol, you can talk in Bengali. You can talk at a slower pace.
00:53:59
Speaker
Whereas if you are talking to a 23-year-old in Gujarat, you can speak in a different language, and you can speak at a faster pace. the So many things can be customized and can be can be different.
00:54:10
Speaker
So we do believe that India will also be a massive adopter when work begins to be delivered by software and not just software being delivered to humans. Right. So to that extent, that's true.
00:54:21
Speaker
What I think is different is that the value of that work in India will still be lesser.
00:54:30
Speaker
So when I sell a loan in India, I might be selling a 30,000 rupee loan. On that as a bank, I can make X amount. And my alternative cost to achieve that call was Y. I'm comparing against that. Whereas if I'm selling it in the US, I might be selling a $40,000 car loan.
00:54:48
Speaker
And that happens to be 100 times the amount that I just talked about. right And ah the cost of a human call there is different. So to give you a comparison, the payment on a per call or a per minute basis in India versus US is actually dramatically different.
00:55:06
Speaker
So I think margin structures might be different, but I do think that the need for scalability is very similar in both the countries. As a fund, you would still first want to back companies which are building agentic solutions for the global market rather than India focused because the margin structures are much better scalability.
00:55:29
Speaker
for the same service so actually i will give you an alok goel answer i will not give you a stellaris answer because as i said ours is a business where every individual in the team formulate their own thesis and we now have got six people even within our software and ai team and different people have very different beliefs uh convictions and everybody will take but yes at least i do carry the bias that the most scalable as well as the most early adopter market still happens to be US.
00:56:07
Speaker
I still believe that to build a exitable software company, there is no way to build one unless you're successful in the US. And lastly, I believe that it's much easier to build for the ground up in the US then be successful somewhere and then move to US.
VC Experience and Anti-Patterns
00:56:26
Speaker
And a combination of those three beliefs, I anchor very heavily on the US market from the get go. Okay. Okay. Interesting. You know, you told me that most of your learning is anti patterns.
00:56:39
Speaker
um And because you just mentioned that you have this very strong bias here, What are some of those anti-patterns you've discovered so far about your decision making over the past decade plus that you've been an investor, things where you ended up being on the wrong side?
00:56:59
Speaker
i would say three um anti-patterns, Akshay, and those are all hard lessons. um Number one is that every time i have worried too much about market size,
00:57:17
Speaker
I've been wrong. And again, as I said, we evaluate the founders and those markets when they are just emerging. We evaluate them at a stage when they are in their zero to one journey.
00:57:35
Speaker
And we are making an extrapolation for what they will be at step 10 or step 100. And by and large, most market size assumptions are wrong.
00:57:45
Speaker
And um
00:57:51
Speaker
One of the companies I evaluated was Postman. And I've been a coder before. it's I understand what APIs are. But I did not imagine how just the world of APIs will evolve and how developers or what developers would need as tool sets to be able to build and test APIs.
00:58:14
Speaker
and In the past, really no large developer tool companies had been had become really big. Very few exceptions to it. And those mental models hurt.
00:58:25
Speaker
I actually find that great founders, they're constantly able to evolve the definition of who they are, expand that definition, and therefore grow the time that they're going after.
00:58:36
Speaker
So in general, at least for me, one lesson learned is don't anchor on temps. That's number one. Number two is that
00:58:47
Speaker
See, in general, we are evaluating both markets and founders, but particularly in, see sometimes the definition of markets is very clear.
00:58:59
Speaker
I am doing last mile deliveries, right? The technology I may use for that may evolve or change. And there might be some adjacent markets that I can extrapolate that this can go into, but still those markets are relatively a bit more defined.
00:59:15
Speaker
But there are markets and technology which are very, very undefined.
00:59:21
Speaker
And I think I have gone wrong often because I have over indexed on the market and not as much over index on the founder.
00:59:34
Speaker
And again, saying this is easy, but putting this into practice is very hard because it's very easy to say a great founder being a great founder once they've become great. But it's much harder to realize that they are great when you are meeting them in the zero to one journey.
00:59:52
Speaker
But building that muscle to be able to identify greatness when they truly are not great um and anchoring on that as opposed to markets has been the second big mistake um ah that I've often done.
01:00:06
Speaker
And the third one is that, see in our business also this question always comes up. I mean, since I come from a software background, at one point I used to question, why can't SAP and Oracle do this?
01:00:18
Speaker
Today in many businesses we say, oh, why can't Google do this? Now we ask, oh why can't open and cloud do this? right we We always ask these questions. right We always believe that the large people will gobble up your space ah before you sort of realize who you are.
01:00:33
Speaker
And actually, I think that I have over...
01:00:38
Speaker
Almost always, when I have over-indexed on large competition, I've been wrong.
01:00:45
Speaker
And I have left companies which I thought will be eaten up by Google, by Adobe, by SAP, and by so many others. Almost always, it has never happened, actually.
01:00:59
Speaker
And why does it not happen? Because large companies... I think they have so much baggage, weight, friction, number of battles they're fighting, ah low decision-making speeds, hierarchies to deal with that even though the answers might be obvious in terms of what they need to do, but it never really happens.
01:01:25
Speaker
And I think if the team is good, if the market is there, Um, and if you can find people who can move with very high velocity, um, I think it's okay to take a leap of faith on the competition.
01:01:43
Speaker
And I've been wrong, not just in judgment calls I've made on my own deals. I've actually mostly been wrong on judgment calls I've made on my colleagues deals as well, actually.
01:01:54
Speaker
And, um, so that's the third anti pattern, but again, these are three broad anti patterns. What happens when you disagree with your colleague's decision or ah proposal that that there's a proposal presented by one of your co-founders to invest in a company and you don't agree with it? How is that resolved?
01:02:13
Speaker
Happens every day. And happens every day now for multiple reasons. Number one is that when we are trying to imagine the world eight to 10 years from now, chances that all of us around the table have the same view of that world, very, very hard for that to happen.
01:02:29
Speaker
And we think that that disagreement is a feature, not a bug. That disagreement is healthy because the deal teams also
01:02:40
Speaker
get different ideas or angles of exploration of both risk and reward on those deals. And ah so we treat those disagreements actually as a as ah as a feature.
01:02:54
Speaker
In our decision making though, Akshar, we anchor very heavily on the conviction of the DLT. We don't believe that consensus is a great way to make venture calls.
01:03:06
Speaker
And if we do use consensus as a mechanism, we will end up doing the safest deals. And we will therefore end up doing the deals which have the lowest reward as well.
01:03:16
Speaker
ah This need to do safe deals, ah does this increase with the size of your fund? Now, your your most recent fund, I believe, is a $300 million dollars fund.
01:03:28
Speaker
ah The first one was an $80 million dollars fund. At $300 million, dollars does the pressure to follow what is trending increase, ah you know, to to really make contrarian bets? Does it seem more risky? How does how does your mindset change when when you're running such a large fund?
01:03:49
Speaker
Actually, it is just the opposite. When it's a smaller fund, you could actually make reasonable outcomes even with safer bets. because the outcome sizes you need are smaller.
01:04:00
Speaker
Again, I go back to my math. So let's say we invested in a company and we own 20%. By the time we exit, we got diluted, we own 10%. do For that percent to be meaningful the outcome of a small fund, that exit size can be smaller.
01:04:16
Speaker
But for a larger fund, that exit size needs to be even larger. And therefore, it needs to be an even more nonlinear bet for ah for an outcome to be meaningful to you and therefore your risk taking capability needs to actually go higher and actually not lower.
01:04:35
Speaker
yeah okay I think you can make safer bets only if the return expectations from your funders are lower. So if I'm if I believe that for the risk that people take in our fund, they need to get an X percent IRR.
01:04:56
Speaker
If I were to lower that X percent IRR to let's say X by two IRR, then i could make safer investments. But as long as the return expectation is same and the fund sizes are larger, actually we need to be able to take even higher risk.
01:05:11
Speaker
How do you build risk appetite in people? Do you hire for risk appetite or ah do you hire for like deep domain expertise and build risk appetite? I think part of risk appetite, Akshay, is just inherent.
01:05:28
Speaker
As I said earlier, we have to be people who are optimistic. That's one. And the other word that you use is foolish, which is that despite all our mistakes, we still need to be willing to back ourselves.
01:05:41
Speaker
um It's like you have lost 100 rounds of poker, but you still come to the 101st because you believe this game you're going to win. right So that, I think, risk-taking ability to a certain extent is inherent.
01:05:56
Speaker
Part of it is also cultural. How would you evaluate risk-taking ability in somebody that you're interviewing? Or does it happen over a longer period of time, not just an interview?
01:06:08
Speaker
I think it depends. Actually, we have over anchored on hiring people who have been actually either entrepreneurs in the past or been at startups in the past.
01:06:21
Speaker
And by the way, this statement is not to say that people who have worked in more traditional organizations cannot become good investors. That's not the point I'm making. But if you have demonstrated risk taking in the past,
01:06:38
Speaker
then that actually always helps. It actually also adds to another dimension, which is that if you have taken risks yourself, if you have done zero to one journeys in the past yourself, you have actually can understand that persona also better. So your lens of evaluation also changes.
01:06:55
Speaker
So we have over anchored, I think I keep forgetting, but half of our team members were actually ex entrepreneurs and the other half have been ex operators.
01:07:06
Speaker
And so we over anchor on that persona. So I think that's, that's one part of it, but I think a lot of risk taking is about culture. When people are discussing their deals, you can either beat them down on how stupid they are because they did not think of these five risks, or you can encourage them by saying that, look, these could be two of the reasons why this could be
Risk-Taking and Deal Sourcing in VC
01:07:29
Speaker
successful.
01:07:31
Speaker
Right. And that's a bit of a cultural element or coaching of letting people make their own mistakes, which I think is a very important part of building a venture fund as well.
01:07:42
Speaker
It must pain you to let people make their own mistakes, right? Because there's money on the line. and No, that's true. And what makes it makes it even harder is that it's not your own money, it's somebody else's money that you're accountable for, right?
01:07:55
Speaker
If I was writing an angel check, I'm not answerable to anyone. And even if I make a mistake, I make a mistake. But if I'm putting somebody else's capital to work,
01:08:06
Speaker
I'm actually answerable for that capital. You would describe Stellaris as an early stage investor or a growth stage investor? early We are very classical early stage investor. Akshay, more than half of our deals are at inception stage, which means there is nothing. There's not and even a line of code.
01:08:22
Speaker
There is barely a PowerPoint at the stage that we come in at. And so we prefer to come right at the early onset of these companies when pretty much all questions are unanswered.
01:08:36
Speaker
How do you build that deal sourcing muscle? The ability to see 4,000 deals of which you invest in 10. How do you build that kind of a funnel that you, a deep enough high quality funnel because your investments then depend on the quality and quantity of the funnel, right?
01:08:55
Speaker
Absolutely. I think, you know, while we pride ourselves on our decision making, on the role that we play on the board, et cetera, I think the single biggest thing of our business is access and therefore source it.
01:09:07
Speaker
Were we in front of that founder at the right time or not, matters so much. um Again, different people have very different methodologies actually there also.
01:09:19
Speaker
We are finding that in our business, there are very few templates that apply to all the people in the firm or frankly, even across firms or whatever.
01:09:32
Speaker
So different people have figured out different playbooks to build their own, um to build their own muscle on this front. Some people try to, try to constantly build a brand through thought leadership.
01:09:49
Speaker
They will write articles, they will put out blogs, um and they want to be seen as the expert in their sector. And therefore they might have very ah they might be very active on that front.
01:10:06
Speaker
um Some people do it through personal networks, one-on-one networks. um So every individual that we have evaluated in the past, even though we don't necessarily invest, that becomes part of our network, right?
01:10:22
Speaker
And ability to create that massive ah unorganized fragmented network of where the flow is coming from day in day out. That's a massive source.
01:10:33
Speaker
Some people build brands on Twitter, on LinkedIn, other kinds of sources. ah Very often it comes from as you, as your tenure in this profession grows, just your own network coming from the founders you have backed in the past app also changes.
01:10:52
Speaker
I think what also changes is that usually Younger people in the firm might be better equipped to get to younger founders. Some of the older ones might be able to get to second time, third time founders better.
01:11:07
Speaker
um And therefore different people need to contribute to sourcing of a firm. Therefore differently as well. As long as collectively we figure out that we are in front of the best founders before others are, then we have done yeah justice to ourselves. Which of these strategies is working well for you?
01:11:23
Speaker
Actually pretty much all of it. But different people do different things. And by the way, we have people. So we also use technology. We are actually also using technology to figure out who might be becoming an entrepreneur soon.
01:11:36
Speaker
Strange as it may sound, today you can use data science to be able to figure that out. We will reach out to them via LinkedIn. And we'll try and set up a conversation with them.
01:11:48
Speaker
Very often we are wrong. They're not looking to be entrepreneurs today. But we track many of these people as well over a period of time. So there's a lot of outbound in this. And going back to your earlier question on operations in our business, this is part of the operations of our business.
01:12:05
Speaker
It may not appear so. It appears like we are a buy side business, but actually we are actually a sell side business. Like say Swiggy has gotten an IPO and you know, a lot of people, they would have made their wealth through the ESOPs being monetized and some of them would now want to move out. And like, that's how you would identify people who could be looking at a ah venture and have the chops to pull it off.
01:12:30
Speaker
You're bang on. One of the companies I funded last year was someone who was coming out from Swiggy. And even though I know it's an isolated example, I'll be surprised if as a team, we have not reached out to a few hundred people from Sugi already.
01:12:51
Speaker
um And that will apply to every good startup that has been created in the country. You feel that it it is more important to hunt for good founders or is it more important to...
01:13:04
Speaker
Have a process. Because I've... As an outsider, to me, it seems like early stage investors must be fielding a lot of inbound pitches.
01:13:16
Speaker
um And maybe as an outsider, I might feel that you have ah so much choice in front of you. Maybe what you need to do is ah build a strong signal engine or something which tells you, okay, out of these 100 pitches I received today, I should look at these two more carefully and that should solve the problem. Is that the case? Yeah, in fact, Akshay, if there is any founder listening to this call, one of the things I would like to emphasize is that
01:13:46
Speaker
Influencing someone is a complex process. This is like B2B sale on both sides. And by and large, if somebody sends us a cold email, which by the way, we get hundreds of every day.
01:13:58
Speaker
I'm sure. Yes. ah For at least days, I'm sure that would happen. yeah I can't recollect at least me having done any deal in last 13 years, which was an inbound email in my inbox.
01:14:10
Speaker
In fact, I will take my statement to a next level.
01:14:15
Speaker
I don't ever remember doing even diligence on a company, which was a cold email outreach to me. Okay. That's fascinating. um See, one of the things we are judging is that if you are sitting in founder's shoes, you're also thinking, what's a way for me to be noticed and influence positively, right? Because there are no hard, this is not a math problem.
01:14:40
Speaker
um So by and large, all deals, that we do have usually come from within our network from someone that we trust or people that we knew for a while and we have had built a relationship with them for some time.
01:14:59
Speaker
And therefore, those are the deals that matter. So even though we get a lot of deal flow, there is a large part of the deal flow that we do. And see, when you're getting, as I said, see, today we do ah about eight to 10 deals a year.
01:15:16
Speaker
So give or take again, we go back to the 4,000 numbers, 4,000 number in a year. If we start spending time equally on those 4,000 deals, we'll be dead. right So one of the first calls we make is which one to even do a call with, which one to do a second meeting with, which one to do a proper evaluation of or diligence, right which one to bring into IC.
01:15:37
Speaker
So there is that funnel in our business as well. And um it's a pretty sharp funnel. in terms of where we decide to really spend our time on. And if it is coming from a trustable source, that matters a lot.
01:15:52
Speaker
Do you have data on opportunities you may have missed because they came in through a cold email? Is it possible that you ah got great opportunities which because it was a cold email, therefore did not get evaluated?
01:16:08
Speaker
You know, i was i have a spreadsheet open on my on my other screen. right now where I have listed all the companies that have done well in my sector and I did not invest in.
01:16:27
Speaker
Actually, I can't recollect a single one of those that came as a cold email to it.
01:16:34
Speaker
And maybe the data is skewed for me, Aksha, because i look at the software sector and usually the average age in software tends to be slightly higher than let's say consumer spaces.
01:16:48
Speaker
And it's possible that younger consumer founders may be reaching out via cold inbound lead as well. And therefore, I'm not arguing that we would not have missed through cold as well. So there will be some of those examples too.
01:17:01
Speaker
But all I'm trying to point out is that that's a bit of a rare thing. That is such a strong insight for founders that cold email is not going to help you get in the door. You have to you have to do sales. And I guess that is proof of your ability to sell as well, if you're able to absent reach an investor through a trusted source of that investor. So figure out who is a trusted source, reach them first, and then get them to introduce you.
01:17:27
Speaker
Okay. Very, very strong insight. um You said that the ah the three anti-patterns which you spoke about, ah you know, largely the the common theme throughout all three was ah find great founders and invest in them.
01:17:43
Speaker
ah Don't worry about time. Don't worry about the market that they are, as it is currently defined by them.
Identifying Great Founders
01:17:49
Speaker
and Don't worry about a large company wiping them out. Yeah. How do you identify who's a great founder when they're not great yet?
01:18:01
Speaker
And that's like the million dollar question. I know. The most difficult question you have asked me, Paksha. And um I wish I knew the answer well on this one.
01:18:15
Speaker
Right. Again, I'll still attempt an answer. ah But this is one of those things we're all constantly trying to learn. how to, how to do this. And as you can imagine, there is science to it, but I think there's a lot of art to it as well.
01:18:31
Speaker
Our business therefore is also a craft in that sense. Um, see, there are some basics.
01:18:41
Speaker
If you do, I mean, every startup that is being built, if that space eventually is worthwhile, you should assume that number one, you're not competing in a sprint, you're competing in a marathon.
01:18:55
Speaker
Number two, there are not 10 runners, 15 runners, there thousands of runners in that lane that you are running. You have to have both velocity, stamina to survive that distance.
01:19:12
Speaker
So therefore, there are first of all, lots of basics that come to mind. So you need to have the basic smarts. You need to, and again, some of those are actually relatively easier to judge, i would argue.
01:19:24
Speaker
um You also need to have an insane amount of learning agility. Basics means what, like say communication skills, storytelling. So I first went smarts in the sense, can they can they problem solve?
01:19:36
Speaker
Building any company means that you will constantly be be bombarded with new problems. Can you think about what's the root cause of that problem? Can you think about what are the four options with which you could solve that problem?
01:19:50
Speaker
Can you figure out how to make experiments? ah Can you make judgment call on what constitutes success for those experiments? All that is classical problem solving skills, right? um So
01:20:05
Speaker
problem solving skills, just learning agility. um In general, I always comment that founders actually grow in dog years. ah What a classical person takes seven years to learn, a founder learns actually in a single year, right?
01:20:23
Speaker
They have to go from absolute scratch zero to building these multi-billion dollar companies in eight to 10 years. That journey that they take, they need to evolve themselves very rapidly and therefore very high learning agility is required.
01:20:41
Speaker
um If I go back into my companies, they did not know what sales was. They did not know how to interview a salesperson. Tomorrow they might be managing a sales team of 500 people of a thousand people, right? That evolution they have to take just in a few years.
01:20:59
Speaker
um Unlike managers who become from a senior director to a VP in four years, that luxury doesn't exist with founders. So I think so i think
01:21:13
Speaker
Some of those are basics. Integrity is a basic. Then there are some, our basic lens Akshay is that there is no perfect human being. There is no unique recipe to be a great founder.
01:21:27
Speaker
Everybody needs to possess one or two superpowers, one or two spikes, and they better be so off the charts that those spikes make up for all the deficiencies that they have.
01:21:39
Speaker
So we are not trying to go through a checklist while talking to people. and say, do you have this? Do you have this? Or whatever, even in the way we ask questions. We just spend a lot of time with them to figure out, is there any spike or are they just good?
01:21:53
Speaker
So just being good is not good enough. They need to have some massive spike that makes up for a lot of different faults. Can you give me some case studies for this? I'll give you one example that comes to my mind and actually has been also one of my better investments in the end.
01:22:11
Speaker
um And I hope this gentleman is listening to it as well, um eventually. But I met this guy called Jassi Chadda. He had built a company called MarketRx, sold it to Cognizant and had started another company called Axtria, A-X-T-R-I-A.
01:22:30
Speaker
And this was a company in the pharma analytics space, very boring. It's not a consumer company. A classical B2B company is helping sales and marketing organizations in large pharma companies.
01:22:41
Speaker
manage their operations. um This was a services company. And Jussie is from IT Delhi. He had built one company, been pretty successful in selling that company as well. And therefore, strong smarts.
01:22:58
Speaker
um
01:23:01
Speaker
But when I was talking to Jussie, one of the things I learned, and I spent a lot of time with Jussie, and I was lucky that I got to spend that time without seven other people breathing down my neck and having a three day trigger on the deal.
01:23:19
Speaker
But one of the things I learned about Jussie is that when he started the company, he started in the insurance space first. He got money from a very high quality investor.
01:23:34
Speaker
And for the first year and a half, He had zero revenue to show. There was no product market fit. Things were just not working. And there was a lot of pressure from the investor as well.
01:23:45
Speaker
And at one point he said that, look, I don't want to take this pressure. I'm losing my freedom in what I want to build. And I want to recapitalize the company.
01:23:57
Speaker
There were 22 people in the company. All 22 people put their personal money to recapitalize the company and give the money back to the original investor. Now imagine there is zero revenue to show for a year and a half.
01:24:13
Speaker
And it's one of the most reputed investors on earth. You are giving back their capital and recapitalizing the company. How insane a belief people those 22 people would have had on the founder.
01:24:28
Speaker
And by the way, those 22 people came from the company that he built in the past as well. They all quit their jobs to to to start with this new company as well.
01:24:39
Speaker
And at least while this founder has got many, many qualities, but the thing that stood out for me was his just leadership. He is a guy that you follow to war while knowing that you will die.
01:24:54
Speaker
Oh, wow. Right? And that's the kind of leader he is. I think he's a kind of leader that you work for once and you cannot actually work with anybody else. And that was the prime part of my investment thesis.
01:25:09
Speaker
Even though he was building a services company, classically, you would expect internal accruals, margins, et cetera. They were nowhere to be seen. So it it was in many ways an antithesis of how a services company is being built.
01:25:22
Speaker
But it was just a belief on Jesse that led me to write that check. And how is it doing now, Xtria? It's doing, it's a fabulous company.
01:25:34
Speaker
They are in multiples, multiples of hundreds of millions of dollars today in revenue. it's um It's now a market leader in its category.
01:25:48
Speaker
um They have, of course, they had the team that they have, but they've hired outstanding talent, built a great company since then. um So, yeah, it's been one of the better investments for me. what What would be like your top three or top two investments? Oh boy, this is now an even more difficult question. It's like asking a parent who's your favorite child. No, I'll tell you what makes this question very difficult to answer.
01:26:16
Speaker
Is that all the checks that I've written in the last five to six years, there I cannot declare them as success because it takes a while to get to success in our business.
01:26:28
Speaker
So it's only my relatively older checks that actually just by design ah by definition will be more successful and therefore the patterns of failure or success.
01:26:43
Speaker
But if I look at therefore my older investments, um Clearly, X-Ray is one of them. The other one that has worked well for me has been Watfix. um ah Amazed with the trajectory that those I backed them when there were only two founders.
01:27:00
Speaker
And again, what did you see there? When I wrote my first check, incidentally, I wrote my first check when I was at Helion. Two Watfix only. For me, it was actually two things that came to my mind when I wrote the check.
01:27:11
Speaker
One, I had worked with SAP before and I saw how hard... software is to use. I know it's ironical, but they built a software to use software.
01:27:24
Speaker
And I was amazed at how simple and insightful their observation was in what they built. It was only two founders. One built the software, the other sold.
01:27:37
Speaker
So one part was that. But the other thing therefore that amazed me is that even with two people at that point in time, they had seven customers. at the time. One of them, by the way, was India's largest private sector bank at that point.
01:27:53
Speaker
And one of them was the largest consumer packaged goods company that exists on planet earth. And having sold software in the past and being used to a bus that's available to you, an army available to you to sell and months, these guys had done it. We're just in a two people company, those two. So I i thought that they bring something unique.
01:28:16
Speaker
um And I think on both on product and go to market, those founders have turned out to be completely exceptional in their journey.
Founder Characteristics for Success
01:28:23
Speaker
So this is proof of velocity. You you mentioned velocity a bunch of times. This is actually a proof of learning agility.
01:28:29
Speaker
Okay. And I think one of the things that I have learned from the WhatFix founders is their ability to constantly figure out that, see, a company doesn't usually go like this.
01:28:44
Speaker
I think a company grows in step functions. And before you are able to take that step, you figure out what is the biggest bottleneck that is unlocking my next layer of growth.
01:28:56
Speaker
Even that's a skill. Problem identification is a very in so is an act of insight. So that's step number one. Step number two is to solve that problem.
01:29:07
Speaker
Who are the right people to speak to? Right? Maybe if it's a sales problem, I can speak to Alok, but maybe it's a product problem, I should speak to Ritesh. That's also a judgment call that you're making as a founder. And who to listen to for this. So ability to identify the right people to take inputs from,
01:29:26
Speaker
Apply your judgment on top of those inputs to figure out what's the root of the problem. Brainstorm what's the solution to that problem. Do the experiments. As I said earlier, define what's successful criteria for those experiments and have the courage to kill the experiments that do not work and have even more courage to scale the experiments that worked.
01:29:51
Speaker
I think this playbook I have learned from WhatFix founders like nobody else. Why does velocity matter? You spoke of how Akshira had zero revenue for the first year. It does not seem like they had velocity on their side and still you back them. so I think you can, this is very simplistic, Akshay, you can break the journey of a company into two halves.
01:30:10
Speaker
And this is a bit logarithmic in my approach that I'm taking. I think figuring out product market fit is the first half, but once you have figured out the product market fit, scaling it's the second half.
01:30:26
Speaker
Figuring out product market fit actually has very little recipe to it. It can take you three months. It can take you three years or you may never get to it also.
01:30:39
Speaker
There is, and even the best of founders sometimes go wrong, right? I mean, you might recollect that in the early nineties, Steve Jobs, which is clearly one of the most iconic founders we have all witnessed in our lifetime or even beyond our lifetime.
01:30:56
Speaker
went wrong with Next as a computer, went wrong with Newton as a as a a notebook that he released in the early 90s. So you can go wrong in your product market fit, and it can take whatever time it takes.
01:31:10
Speaker
And I think there, it's not the velocity necessarily. It's the thoughtfulness ah that that matters, experimentation that that matters, learning agility that that matters.
01:31:23
Speaker
Once you do find product market fit, I think it is velocity that matters. And ability to think that what should my team look like when I'm 10 times my size.
01:31:34
Speaker
And by the way, that 10 times is not going to happen 10 years later. That 10 times is actually going to happen 18 or 24 months later at best. And if I don't hire the team and ram them up for them to be able to handle the 10x scale, I'm not going to get there. What are the new distribution channels am I going to need for that?
01:31:51
Speaker
What will my unit economics look like? um So ah will I need to go to larger customers? And if so, how will my sales motion change by that time? So there are so many things that you are constantly thinking ahead and implementing.
01:32:05
Speaker
If you don't think with that velocity all the time, you're not going to make it. Because if you don't, I believe there is no IP pretty much in most companies.
01:32:16
Speaker
It is about execution. And if you are not running with that speed, somebody else is actually going to run with that speed. and They'll overtake you and you'll miss the bus. Okay. ah I want to point out a discrepancy. So you said you are looking at...
01:32:35
Speaker
US first ah for ah software slash AI businesses, because that's where the margins are, that's where the market is. And yet at the same time, all your learning so far has been founder first.
01:32:49
Speaker
So I'm just wondering, like it sounds like a bit of a contradiction where your thesis for your AI investments is more about the market.
01:33:00
Speaker
Akshay, you truly are insightful. And you're right that I have made that mistake. And there are founders who began with India, started building something and either completely pivoted to a different product altogether of different problem, completely pivoted to a different market outside India.
01:33:24
Speaker
And because of my biases, I have not been able to back those founders. And every day I do try to question those biases. And sometimes when I'm meeting founders, I'm also trying to ask myself that for a minute, let's assume that this was not the business.
01:33:41
Speaker
Would I still like those founders? But as easy as it is for me to say that both our asset is our experience and our liability is also our experience. And that experience creates those biases too.
01:33:56
Speaker
And even even when we use the word learnings, that learning is nothing but a bias. Yeah, so true. Tomorrow there can be patterned against that learning too. right And therefore all learnings are biases by definition.
01:34:09
Speaker
So they they are your strength, but they're also your weaknesses. And I don't know how to how to always just use them as strengths and not use them as my weaknesses, but I feel there so many times.
01:34:23
Speaker
Amazing. Thank you so much for your time, Alok. I really enjoyed this conversation. Super insightful. Thank you so much, Akshar. I really loved it as well. um Gave me a lot of food to think. Your last question in particular, by the way, has has made has made me think a lot now. So thank you so much.