What Young Founders Get Wrong About Startups | Articul8, Arun Subramaniyan

1. 0:00 – 2:24

   Intro

   1. ASArun Subramaniyan0:00

      So the biggest thing that is different, of course, being in a startup is that you don't have any safety net. You really need to have a hustle that goes way beyond anything you've seen in life. You don't have any time to sit and think. You just have to deal with it and keep rolling. I would say the biggest thing I'll do differently is to make sure that people who come to the company understand the fact that there's no safety net, and we've had our fair share of turnovers and even people who were in the early, early teams we've had to let go, partly because they may be perfect candidates, perfect employees in a large company, perfect candidates or outstanding candidates in a medium company, but a terrible misfit in a small company. Like I'll tell you a general conversation that would usually go. We ask for, uh, say, going and meeting with a customer or something we are expecting. A week goes by, you go ask them, "Hey, did this get done?" And they'll say, "No, I sent an email. We are still waiting for a response." Now in a large company, that's a perfectly fair statement to make. No problem, you'll get a response. And typically, say you're in Amazon or you're in Google or Microsoft, you send a response, people respond back. The same people, if you're sending an email from a startup, they don't respond most of the time. They don't have time to do that. But second, we don't have the time to wait. We send an email, then call the person, then text the person and text their wife if we have to to make sure we get a response. There have been cases where we would say, "Look, do you want me to go pick up your kids so that I can actually get 15 minutes with you?" It's that kind of hustle that you rarely almost ever need in any other job, but you need it here. And for that you also need humility because normally you would say, "Well, I am the CEO. I can't be going and doing something." It's exactly the opposite. In fact, you have to do everything, meaning I can work 18 hours a day, I can work seven days a week, I would still not get to even 30% of my tasks. If you're in an early stage startup, there is no such thing called work-life balance. Don't kid yourself. There is work, there is life, it's the same thing. The real definition of entrepreneurship is aiming to do something for which you don't have the resources. That's the definition of entrepreneurship. I'm Arun Subramaniyan, founder and CEO of Articul8. Articul8 is a domain specific GenAI platform that enables enterprises to get value from their deep domain expertise and data they have collected over decades. [upbeat music]

2. 2:24 – 6:19

   Principle 1: Make a Dent in the Universe

   1. ASArun Subramaniyan2:25

      I grew up in a family where technology was a given. Normal quintessentially Indian, uh, upbringing in the '80s and '90s assumed that you have to do well in school. That was the number one priority. I was fascinated by anything that flew even before I got to college, and very early on I wanted to be an aerospace engineer. Um, there are very few places you could go to study aerospace engineering at the time, and I was lucky enough to get into one of the top schools. I went to Anna University and there's a school called Madras Institute of Technology. My college education was just fun for me all the way through, so I finished undergrad there, went off to do my graduate studies at Purdue. Many people may not know this, it's called, uh, the birthplace or cradle of astronaut. It's a school where most astronauts in the US actually come from, and Neil Armstrong actually graduated from Purdue. There was a particular incident that deeply touched me. I had never thought about it that way. This was when I was in college. I was attending a seminar by somebody and he said something that I had never thought about. You need to feel ownership and responsibility to actually help. And what that means is he gave an example, which is think of the people who first designed dams and built dams, whoever they might be. They stopped the flow of rivers. At the time that they started building dams, it was all an act of God, wherever, whichever culture you were. They really wanted to make sure that floods didn't happen, that then people didn't die, they didn't suffer. They didn't sit and think, "Oh, this is an act of God. God wanted floods to come in. We can't do anything." They actually thought that I will help people not suffer and actually go build dams. When they first built it, it's an impossible act to be doing. Now it's a natural thing. Sure, engineering marvels, we build dams all over the place. But it's not for the first person to have thought about it. Think of the responsibility the person took to stop an act of God, right? And that's a massive responsibility. And not only did they thought about it that way, they went and built the dam. And if you actually think about it from the perspective of ownership and responsibility, you don't need to have anything to take responsibility. You can do your own small thing to make a massive impact in anybody's life. That made a very personal impact for me because it was mind-blowing to me as, uh, at that time probably I was still a teenager, to think about life like that. Until then, I just thought, like the world just happened around me. We didn't think we manifested something in the world, right? That's one thing. The second thing that affected me very deeply was the concept of paying it forward. So when I was in AWS, we ran the simulations, helped scale the simulations for running COVID predictions in terms of spread of COVID. And at the time, of course, COVID was just starting. The shutdowns had never happened anywhere else. No state had ever shut anything down. And we helped one of the state, uh, of California divisions scale their simulations to predict when the state of California is potentially going to run out of beds. So what we ended up doing was we helped them take their models and then scale them on massive amount of compute, 'cause that's what we are really good at doing. And it predicted that in five days or so the total number of beds in California would be exhausted. And, uh, that simulation, along with all the other data they had, was instrumental in the state of California announcing the first statewide shutdown. And that same simulation is being run by many countries today, and it was, uh, a deeply touching project to be working on because I didn't go to Amazon thinking that's what I would be doing. At the time we didn't realize it, but it had a huge impact on a lot of things in the world and it is truly humbling that, uh, the work we did helped in a small way in making the world a better place. In Steve Jobs' world it is like make a dent in the universe, but it's really around saying, look, whatever we find ourselves in, whatever little we do, make sure that we leave the place in a better world than we found it. The group of people that we have with us, I would say none of them need this job. None of them need to be here working God knows how many hours they're working daily. They're here because they believe in the mission. They believe in why we do what we do and how we do what we do.

3. 6:19 – 8:45

   Principle 2: Don't Put Yourself in a Box

   1. ASArun Subramaniyan6:21

      If you ask me how my career got built, is really being dumb enough not to say no. And the reason I use the word is whenever a problem was given to me, even very early days, I didn't know that other people would never touch that problem. It was given to me because I was silly enough not to ask, "Why would we do this?" We basically said, "Oh, it is an interesting problem. Let me go try solving it." I failed more often than I succeeded, but the times I succeeded, I succeeded in things that everybody else said cannot be done. The problems that were the highest value, the problems that were the most difficult to do, and failure was okay. So the way it started was I was at Intel. I was, uh, leading the Cloud and AI Strategy and Execution teams. My charter was to help Intel sell more AI hardware. But we knew that the largest workload was large language models. GenAI is going to happen. This is 2022, and this was six months before ChatGPT was launched. So we had built a- an AI supercomputer, and then we were trying to build a model for that one, and we actually worked with a very large company trying to get them to buy Intel hardware. And the project went all the way up to a final approval where everything broke loose. There was a misunderstanding in terms of who was going to fund what portions of it, which basically ended up being the project completely stopping, and it almost like the rocket analogy is the rocket blew up on the launchpad. That was a failure everything started with. But because we had already done the modeling, we then went to a customer and said, "Hey, we can do this for you. Would you want to do this?" They said, "Oh, okay, we can try this. Let's do a search model." We actually built a model for them. That model ended up being a software product. We built the software. We did all that to sell hardware. The customer comes back and says, "Maybe we'll buy your hardware at some point. Can I buy your software?" So in a sense, that was the second-biggest failure. We tried to sell hardware. We couldn't sell the hardware, but we could sell the software. And within a year we went from having a project that is almost in the bag that was al- already going to become the biggest project out there. That project failed. Then we went and got another project to sell hardware. That project also failed. Ended up being Articulate, the company. And if you think about if we had stopped at the first failure, we would have never gotten the second project. If we had stopped at the second failure, we would have never gotten Articulate. The perspective of looking at it from failed projects getting turned around, doesn't matter how many times we fall down, can we actually get up?

4. 8:45 – 10:14

   Principle 3: Why 95% of AI Projects Never Reach Production

   1. ASArun Subramaniyan8:45

      Say principles we go by in the company, which is we typically do not do POCs. POCs meaning proofs of concepts. We only do production pilots. You may ask, what's the difference? The difference is a POC is something that anybody can do. Honestly, even a high school student with a good enough knowledge of some of these tools can build a POC with a few tens of documents. The difference between a POC and a pilot is pilot is production scale. You have to go after your most complex use cases. In fact, we go into a customer and say, "Give us your messiest of dataset. Give us your most complex problem, and let's actually show you how to actually take that to production." Right? That's what we mean by a production pilot. And the other big difference between a production pilot and a POC is once you're done with your production pilot, turning on the production is just a matter of a contract signing. All the technical work is already done. And the third thing you might ask is, "Okay, that means this should take a long time to do." We actually cap production pilots to be between four to eight weeks long, no more than that. Even the most complex of use cases that we do is entirely done within eight weeks. So it's very important because when a customer hears this statement, which is like, "Give me a nice clean dataset, and it's nicely curated. Give me a small problem for me to show you that it actually works." After you make the POC, to get to production, it ends up taking six months or a year. And most of the projects, if you see the latest MIT study that said 95% of GenAI projects don't go to production is because of that, because people do POCs and it never moves forward, right? It's a very different, uh, uh, philosophy.

5. 10:14 – 13:05

   Principle 4: Stop Chasing Low Hanging Fruit

   1. ASArun Subramaniyan10:16

      Last count a few months ago, there were 28,600 startups in the world that claimed to be GenAI startups. I'm sure the number has more than doubled since. The reason for that is everybody, I believe, believes that they are solving an important problem. I don't think anybody goes out and starts a startup or works so hard to solve a problem they don't believe is important. However, what they're solving for, for is in different domains, and they... what they're solving for is in domains that they think is hot. Now, there's two ways to solve a problem, two ways to tackle a problem. The first way is, of course, go after where things are hot. That's the red ocean theory. Or go after things that are the blue ocean theory, where there's nobody there. Now, a path less traveled is less traveled for a reason. It's hard, and it's filled with more failures than the path more traveled with. But it really depends on what you have stomach for and what you're actually going and solving and what you have resources for that you can go do that. I don't think there is any one right or wrong answer. It is just about what is personal for you. Now, do I believe that these companies are going to make an impact? Absolutely. They already are. They've changed the way the world in so many fundamental ways that it's no longer going to be the same. Same thing that OpenAI did. OpenAI was a small startup when they started. They have fundamentally changed the world, and I think that's going to continue growing. That we believe that the low-hanging fruit is first and foremost the most crowded market out there. Every company is a GenAI company, and every large company is trying to do something with GenAI. Where do they go? They usually go to marketing. They go to finance. They go to HR, partly because it's the lowest hanging fruit. Because you have use cases, but if you make a mistake, not much is going to change. It's not a, a company-threatening event. However, if you look at what is the most important thing that the company is doing, it's mostly not related to any of these things. A manufacturing company does manufacturing. Uh, an aerospace company will do design or manufacturing or, uh, maintenance. We go after use cases in those particular segments, and we actually go after what makes a big difference for the company's top line. And the reason for that is if a company can actually find new business, find new ways to make money out of AI, that is something that will be longer lasting Whereas productivity use cases typically go after the bottom line, which everybody's going to do. Whether you like it or not today, you're doing it or not, every company is going to use some productivity tool to get their AI use case to reduce their burden for what they're doing. That's not going to give differentiation for any company. So we believe that we work on things that give a company differentiation that gives you longer lasting value. And we also have a philosophy that we are fundamentally grounded on saying, "Look, we build our business based on the fact that we added value to your business." So we can share in the value. That's how our business grows. Our business is not necessarily growing by making you more efficient.

6. 13:05 – 19:26

   No Safety Net in Startups, Just Move

   1. ASArun Subramaniyan13:07

      So the biggest thing that is different, of course, being in a startup, is that you don't have any safety net. Like any other job I've had, there's always somebody who I could go to for help, but ultimately the responsibility lies with me, meaning the buck stops with me, which is a huge change when it comes to it. I took a little bit of time to adjust, but the nice thing about being in a startup like this is you don't have any time to sit and think. You just have to deal with it and keep rolling, right? So that's a good thing because you don't have the time to freak out. Uh, I would say the biggest thing I'll do differently is to make sure that people who come to the company understand the fact that there's no safety net. And we've had our fair share of turnovers and even people who were in the early, early teams we've had to let go, partly because they may be perfect candidates, perfect employees in a large company, perfect candidates or outstanding candidates in a medium company, but a terrible misfit in a small company. And the reason for that is you really need to have a hustle that goes way beyond anything you've seen in life. Like I'll tell you a general conversation that would usually go, we ask for, uh, say, going and meeting with a customer or something we are expecting. A week goes by. You go ask them, "Hey, did this get done?" And they'll say, "No, I sent an email. We are still waiting for a response." Now, in a large company, that's a perfectly fair statement to make. No problem, you'll get a response. And typically, say you're in Amazon or you're in Google or Microsoft, you send a response, people respond back. The same people, if you're sending an email from a startup, they don't respond most of the time. They don't have time to do that. But second, we don't have the time to wait. We send an email, then call the person, then text the person and text their wife if we have to, to make sure we get a response. There have been cases where we would say, "Look, do you want me to go pick up your kids so that I can actually get 15 minutes with you?" It's that kind of hustle that you rarely almost ever need in any other job, but you need it here. And for that you also need humility because normally you would say, "Well, I am the CEO. I can't be going and doing something." It's exactly the opposite. In fact, you have to do everything, meaning I can work 18 hours a day, I can work seven days a week, I would still not get to even 30% of my tasks. If you're an early stage startup, there is no such thing called work-life balance. Don't kid yourself. There is work, there is life. It's the same thing. It's what it is. It's just that the people's mindset has to be very different. I don't think twice before clearing out all the coffee cups in the office, if that's what I have to do. If I see something and I have the time, I have no problem doing it. If I have to be the one going and talking to the, the biggest investor out there raising money, I will do that too. So there is no such thing called a job is beneath you and there's also no such thing called you can just delegate and walk away. You cannot delegate responsibility. Some of the people have asked me a question like, "Have you always wanted to start a startup?" The answer's no. I was happy being a researcher. I trained to be a researcher and I ended up becoming one. I was more than happy. The business side was entirely accidental. I didn't go to business school. Everything I learned about business is what I learned in the job. Uh, for me, it's a kid in a candy store moment all over again because you're solving problems that very few people would solve. Why is democratization of technology important for me? Partly because it's a universal equalizer, and the reason for that is think about science and math and even, say, philosophy in general is universal. It's deeply liberating. There is no inequality irrespective of where they are. And if you actually allow people to use that more easily, that's the most equitable thing you can do back to the society. And, uh, that's really what's been driving. And also if you look at it, that also comes from how I grew up. Like I grew up in a world where things were not easily available. Like there was no cable TV when I was growing up until I was in high school. There was no internet. Uh, and as crazy as it seems to think about it today, going from there to sitting in any coffee shop accessing anything in the world happened in less than a lifetime, right? The unlock it gives is massive. Think of the child who may not necessarily have the resources, may not have the backing, being able to actually improve their life because of this. That's really what drives us. And the reason why I like the word democratization is it's the most equitable thing you can do. You are enabling people to pick themselves up from whatever situation they find themselves in. Some of us have been super fortunate to, to have had the education, to have had, uh, to be in places where we could actually see these things and learn from that. A lot of the people are not as fortunate. By the 10 years, we would have become the platform of choice for domain specific applications anywhere in the world, in any domain you have, and that's really the mission that we are after. And to become the platform of choice, we also have to be giving disproportionate value back to all of those outcomes, right? That's the one thing. And the way we would change the world really is to make sure that we enable every single person working in every single company to have their own digital twins multiple times a day and be able to make meaningful outcomes for themselves as well as their company. Meta announced in their super intelligence lab they're doing, that's what they announced that they're gonna do for personal life for people outside. We are saying we'll do that for the enterprise. Nine out of 10 startups fail, and even the 1%, one startup that succeeds doesn't become a Meta or a Google. But the pain you endure is so massive that you really need to have an inner guiding principle to actually get you past that. It is, I guess, rooted on the belief that we can actually make a small difference, not because we think we are smarter than anybody else. It's because we have perseverance. So what I keep telling my team and I keep telling myself as well is, "We can lose, but we can't be beat." Well, I would say my greatest source of strength has been my wife. She's somebody who's brought balance in my life because I'm a deeply, I would say, imbalanced person, meaning if I get passionate about something, I'll forget everything and just dive in. And so bringing a semblance of balance is something that she taught me, and it's also something where I've been enabled by a lot of people, but I don't think I've been enabled as much by anybody else other than her. [outro music]

Episode duration: 19:26