Why Two IIT Engineers Turned Down $550K Jobs To Build A Startup

I was just panicked because I never prepared for anything. I mean I prepped so much for the interview that I chatted with a lot of XYZ interview founders etc. They all told me what's your idea what's your TAM and everything but HJ didn't ask about any of those things and I thought genuinely interview went like so horrible that we are not going to get in. Hajj told us you guys are really good engineers just pick something else and work on it. All right, we're so pumped to be here with Varun from Giga ML. Um, thank you all so much for coming. Varun, why don't you start by telling us a little bit about what GigaML actually is? Sure. We build AI agents for customer support. We work with some of the biggest companies in the world like Doash. We work with one of the biggest crypto exchanges in the world, top three telecom providers in the world. Yeah. And so what does it mean when you say AI agents for customer service? give an example of how someone is using your product maybe even how people here have used their your product and not even realized. The traditional way that support works is whenever is call the support it actually uh get to an IVR or a chart bot then goes to a human the deflection rates are closer to like 10 to 15% with AI it's just like you call it's entirely like humanlike experience closer to like 60 to 70% deflection rates we're aiming to get it closer to like 90 to 95% for top of the customers it's just like a better experience you have never need to be in hold again you can just call and get the issue resolved like really fast. Yeah. And why don't we start by rewinding the clock a little bit and hearing about the very early days of your company. So maybe even before you started a company why don't you just tell us a little bit about what was your upbringing like like how did you uh get introduced to technology in the first place? Yeah, of course. Uh my uh I was from this town in small town in uh Andhra Pradesh and my parents were both like government teachers. They of course wanted to be an engineer or like a doctor. So we were uh I grinded myself out to get into IIT which was a great experience. I I got into like IT corrector uh in electrical engineering and my first two years I did not like do much because it was like a covid year we're just like partying and like not much studying and uh during third year I started like uh doing my research in LLM in Stamford and that's when we started like uh seeing this is like a pre-sharg moment we're working on transformer models like bird etc and uh this was like when you were in college or still in high school. Okay. Yes. Yeah. This was when I was in college and I actually got like a pretty good job when one of our quant firms uh one of the leading quant firms in New York. I got offered like 550k at that point of time. It was like a big thing uh and I also got my PhD in Stamford uh to join and then charge launched uh this this uh around December is when I got in and then charge launched. We're like super excited. Uh the super exciting moment is it was able to write code and a lot of things. So we just wanted to build something on top of it and give getting into YC a shot because I was I was reading PG's essays launching like the 2014 YC startup school. It's a classic one and I just wanted to give it a shot and try to get into YC. So me and my co-founder, we both know each other from like freshman year and we just thought like what could go wrong? You can just apply and always see right. And it's so dramatical because I was supposed to join. We were supposed to like join in like 3 days. That's finally when we got in and the interview was also like so different than what we thought because we uh we were trying to build an edtech uh on using like LLM and we go to interview I clearly remember HJ asking me that hey this is edtech it's not going to work pick something else and it was never even about like the idea or anything we wanted. He was like you have like research experience in LMS pick something and etc. And and so so when you heard that did that increase your ambition or reduce it or how were you thinking about that? so much for the interview that I chat etc. They all told me what's your idea? What's your TAM and everything but HJ didn't ask about any of those things and I thought genuinely interview went like so horrible that we're not going to get in. And yeah, Hajj actually wanted us to join YC and he told us you guys are really good engineers. Just pick something else and work on it. That's how I mean we would you would not have existed without Hudge taking a bet. And so Okay. So I imagine then you went back to your roots a little bit as engineers. Tell me a little bit about what were your roots as engineers like like when you were in college. Were you like a by the book guy or were you more of a hacker? Like what was your kind of personality as an engineer? Yeah, it's it's very interesting because my co-founder was I think third ranked in entire IIT and he only got one B in his entire career. That two he really messed up actually. Uh there is uh he actually went to uh class and gave attendance for a wrong guy as a friend and he got penalized 10 marks. That's why instead of ex he got B or else he would have been like top of the campus. He's like a very book guy kind of a person. For me honestly I never my grades are bad. I never like really studied that good and I used to do a lot of Kaggle competitions primarily because you can make money if you win the competition. That's pretty much it. So I would say I'm more kind of like a hacker and he's more kind of like a book guy. But eventually we both turned out to be like a hacker kind of people. Yeah. Wait, can you Yeah. Can you tell everyone about your history with K competitions? Like how many of these did you do and like how much money did you make doing this? I did a lot of them. Uh I think I made like $50,000 or something. That's how I landed to like one of the one of the uh one of the high frequency trading jobs. I gamed it so much that they banned me. I Yeah, we we I gamed a lot of that thing. Yeah. So, okay. So, when you were in college, you're now spending a lot of your time doing Kaggle competitions. You're experimenting with machine learning models. Um you apply to YC eventually. Harge tells you, okay, this like edtech idea is dumb. Do something else. How do you now bridge those two worlds? Like what's kind of the next thing you decide, okay, let's try to give this a shot. Yeah, it's Hajj did a pretty great job. What he did was he made a shot with Corsera COO and a bunch of people who have like some of the most successful ed techs. All of them told it's a bad idea to do edtech. So we decided to pivot pretty much after a month into the batch and we were again we had like a pretty bad experience because both of our B1 Bas got rejected but this was the first time YC turned into in person we're just doing fully remote. We had experience on finetuning so we just uh I just read this uh research paper from one of the data bricks co-founders which is basically LLM uh caching LLMs to reduce the cost. At the time GB4 used to be super expensive. Instead of just caching, we thought that fine-tuning might be better using a smaller LM and everything. So that's how we got started with fine-tuning and we open sourced a bunch of models. We topped hugging face benchmarks. That's how we got like a lot of traction and a lot of people reaching out to us and we raised a $4 million seed round. So okay, so you did YC then you end up raising your seed round. You're you're working on this finetuning idea. That doesn't sound anything like customer service AI system. So how did that first thing become the second thing? What was that what was that story like in which you found the idea you're now working on? Yeah, the interesting part about fine-tuning is it's a really bad market for a bunch of reasons. The only reason you want to fine-tune is to reduce the cost and make it faster. Or else there is another use case which is if you are so secure it's very hard to sell to those uh big insurance companies or healthcare as an engineer because it's a sales process not engineered process. We have realized it after like a year or so and the interesting thing was the only two use cases on Gigab customers which are growing very well are customer support and coding. So we decided to customer support and so so you basically saw that from your customers, right? It wasn't like you just like looked and said, "Oh, this is a big market." You just you naturally discovered it from the thing you were building. Yeah, we saw it from customers and Aziz was just here and Zeppto was our first customer for that thing. We reached out to them and as they were scaling really fast and they tried us out and they turned out to be our first customer. So okay, I mean this is where I think things can be very counterintuitive, right? like when you chose to switch into customer service, there existed at least one or two other companies, some of which who have very famous founders who are very well capitalized, companies like Sierra, for example, that already existed uh at the point of you guys deciding to go all in on this. Why did you think that you could do it anyways and still win? Why did you think that it didn't matter or it was worth it for you to go after that market? Firstly, we don't know CR and Tech1 existed when we signed Z2. And so like there's a little bit of benefit to naive there. Yeah, that thing. And we didn't think of competition much. That's pretty much what I would say. We never I mean even right now our entire product is is if the is the are the customer willing to pay you? Can you deliver a lot of value to them just like D was like a pretty much a stronger mentality against competition. But again as you scale you need to do differentiate and everything. Then after Zepto the real competition happened between us and one of the leading companies that you were seeing at Dash. We have like eight people going against this 400% wellunded company and we won it against them and as you know Dash is one of the massive support logos. That's when we truly like us realized that there's a lot of arbitrage of actually building a great product rather than a sales team. So okay so that's kind of crazy right? You you won Door Dash's contract. you were only a team of eight people when you did that. Why was it that Door Dash, which is a huge company, was willing to trust you guys when you were only eight people? You could imagine they're like, "Oh, these guys are too small. They'll never, you know, they'll never trust me." Like, you know, 10 years ago, the assumption would have been that big enterprises would never buy software at that scale from a startup. It seems like that was no longer the case for you. Why do you think that is? I think u you got to have some unfair advantage, right? for us YC was that Gary introed me to uh Tony and it's a YC company and Doash has a basically a YC company so it's just like inherent trust to it and again it's I mean we piloted for like 3 months we never went down and all the metrics were good and Doash is a very meritocrative company and I really kudos to them and it's a company at that scale picking a small company would be hard and now a lot of companies pick us because of Doash and a lot of other big public companies users yeah so how is that what does the arc look like since then. So you got companies like Zeppto and Door Dash in the early days. What does your company look like now and how have you had to evolve what you're doing over the last uh few years? Yeah, last few years uh I would say we as I mentioned we work with the biggest crypto exchange in US and after getting like a customer at that scale we uh we are working with a lot of fortune 500s etc like trying to automate the support. Another big interesting thing that I have observed with AI agencies is it's fundamentally boiled downs to two things. This is for true for almost any agentic company. It's like a policies or the markdown file and how can you iterate the markdown file to affect a business KPI that is support for support is resolution rate or like seesat the all thing that matters is you let's say we start at like 30 to 40% resolution rate how to get to 90% how can you iteratively improve to get there the same fundamentals apply for compliance ITM ITSD and everything so we're seeing customers some of the biggest uh consumer companies in the uh US piloting us for internal support even compliance and etc. It's very interesting with a agents. It's fundamentally bogd down to markdown and like how can you iteratively improve markdown to move a KPI. Okay. So I want to change the change gears here a little bit and talk a little bit about the advice you would give for this people in this room. Right. So the people in this room are predominantly college students or young people recently out of college. you know, if you were rewinding back to your time as a college student, is there any advice you would give that's maybe different from the advice that they might be hearing from their peers or what is kind of the norm, you think? Yeah, I mean like a lot of people thought I was stupid when I rejected the job offer. I mean, like it was so insane because um they were like, "You're turning down this great offer from a quant firm. Like why would you do that?" Yeah, it's just for me and my co-founder, we just wanted to give it a shot. We thought like we just wanted to see how how how high we can go. That's pretty much like a thing and that's the reason that's the pretty much um the entire way that we build the company like yeah as scaling like even den uh acquisition office from some of the biggest companies in the world. That's how we pretty much like build entire company. We just wanted to reach to our potential and see is this the best we can do and push it. It's kind of more than me. It's my co-founder's mentality. He's fundamentally like a zero motivated by money person. So yeah, that's where it came from. And I read Paul Gram's essay on how to do wealth. It essentially boils down to doing a company and having or like doing equity in something big. That's pretty much it. Yeah. What did like your parents think about that in those early days? Like were they excited? You you said, you know, you grew up in a very modest upbringing. Presumably getting this highpaying job would have been life-changing for your family. Like how did how did that go? That conversation? you're like, I'm moving to SF. I'm going to start this crazy thing. My dad was super mad to be honest. And it's just uh I mean, it's a it's kind of like a big fight thing in home, but it's fine. I mean like they're like what can they really do? They can't like force a kid to do something. But it just was really like a hard conversation. I actually showed them what YCU is, showed them YC videos, and showed them these are the companies that they do. And I showed them like even if I don't succeed in a year or two, I can just go back to the job and do the thing again. When you come from like a middle-ass family or build a middle- class family, it's just like a lot of expectation to do things and especially when I got like a really good job offer and my parents were all happy about they I mean it's it's just not my parents even internally even I felt am I doing something wrong but again my entire philosophy has been like just take a shot and see if it works out or not. So when you think about now how college students or young people can put themselves in a position to find great startup ideas, what are some of the lessons from your experience that you think apply to the people in this audience? The biggest thing we made at least a mistake even after getting into YC is uh we worked on a lot of stupid ideas which didn't make any revenue or doing anything. Uh for a long time I mean like people just want have like a lot of ideas. I can just go into charged and get like 10 ideas on what to do right. Uh it's never about the idea. It's about if somebody is willing to pay you money for it and is I mean I don't even think about you need to care about market to be honest. is somebody willing to pay real money if you solve the problem for the value that you delivered. That's the strongest approach we took and I made a lot of it took me a lot longer to realize right now even for our new products that we build we make sure that the customer can actually pay and we predict like this is the amount you're going to pay and get a commitment from the customer and then go and build it. And why is it that you know charging for a product so early is useful. You know, I think a lot of people in the audience might think, "Oh, I'm just a college student. No one's ever going to pay me for something I make right now. I should I should just get started for free or something like that." Why does that not tend to work in your mind? If it's an important enough problem, people would pay either with money or with time. I would say, I mean, social media networks are just time. They don't charge you any money. But in general, for any single B2B company, if the problem is important enough, people should be willing to pay money for it. I was like you're just solving a fake problem. So you are also part of a new generation of Indian origin founders who is building your company both here and in SF. How do you think about that? I mean do you think about that or is there uh any any particular framework you have for how to expand your company and take advantage of your background from India? I think that you should just stay close to customers wherever you are. But if you're doing anything closer to like genai and very like research based things, I strongly think SF is a place because the amount of access and you know with the researchers and etc you get is insane because almost all the innovation in this geni field is getting drive on Bay Area alone compared to India. But again if your customer is primarily based out of uh India it should be here. What do you think when it when you look forward to the future and you think about, you know, all of the pivots your company has gone through to get to where it's at now? How do you think what do you think the next few years look like for your company? Like, do you see yourself now? Do you feel like you found the thing that's going to become really big or do you see yourself continuing to evolve? And and how are you evolving yourself? Yeah, I think I think we're I'm very confident that we are moving in a great direction. The biggest bottleneck of every single enterprise a deployment regardless of support or any automation that they want is this concept called forward deployed engineer. You need to have them u bunch of them coming and sitting with the customers and configuring it. We're trying to build an AI forward deployed engineer. We're going to launch it soon. Yeah, and that is where I would say that I'm very competent on because whenever you want to make these policy changes whenever you want to like just spin up a new dashboard for me or how can I go from like 40 to 60%. Our aforemention is going to join is on slack is going to join Google meets and take all the nodes and do the changes automatically. So I'm very confident on the direction that we are moving on uh how we are going to tackle uh AI adoption in enterprises because the biggest bottleneck right now is forward deploy engineer and we're going to take it over. Could you tell us a little bit about how your company actually runs internally using AI also like you me obviously your product is very AIdriven but in terms of the company itself like what are the tools that your engineers and salespeople and whatnot are using what does that actually look like? It's funny because we have a one of our values is automate, automate, automate. So we force people to like use as much automation as possible and the in general the boral mission of the company is to automate all of the world's work. We are intentionally like moving into that direction of generic automation builder able to automate anything on top of us. Some of the examples were you don't need to have a personal assistant just add it open cloud runs and schedules the meets for you to actually like uh sales people use it very interesting. They pull transcripts from Kong to do analysis of what are the biggest things that work working against a specific competitor across like a multiple things. So yeah, everybody's u that's the one thing I love about cloud code. It turned a lot of people into builders and people are using it innovatively to drive specific insights that would have like taken like humans go through a lot of things and doing it. Yeah. I mean, if coding agents didn't exist, how many engineers do you think would be at your company versus what it currently is? Like, how much what would the company look like without all of that? I think they should be at least like six to seven times more compared to now. We're relatively like a very small engineering team. It's like a very strong talent and very small engineering team. That's crazy, right? Like 7x the number of engineers you would need if you didn't have one tool, which probably costs you much less than seven times your engineering team. It's it's a it's more than cost. It's just it's better w without context switching. It's better for you to own the thing and build the entire thing rather than having like a lot of people working on it. You can just ship much faster and the context transfer actually kills a lot of things and slows down things. So given that I imagine the kinds of people you look to hire on your team also are very different from the average SAS company 10 years ago or at least in some ways different. I'm curious how you would describe that. Are there things that you guys look for that are maybe different than what like a big tech company who doesn't use that many that much coding agents yet uh might look for? Our interview process specifically designed we ask people to wipe code and remove AI and ask them to like change the code. So we you actually have them vibe coding in your interview process. We ask them to wipe code and then remove access to the tool and ask them to change the code without AI. It's intentional because we want people to understand the code as well on how it works etc. So we are I mean again this is also keeps evolving as AI models keep getting on better and better do we really know to know how the code works even if cloud does the entire thing but that's how that's where we landed on generally the things which we look are some sort of like extraordinary ability and spikiness that we can like relate into for me and my co-founder that for us was me having the highest uh one of the highest offer jobs my co-founder was third in the entire and um he also got the I think the highest paying job offer in India in a in a quant firm and we're trying to look like a very spiky things on which is the.1% of people would do and that's how like we're generally going at So, you know, I think a lot of people might look at themselves and say like I'm a technical person, I'm an engineer, but like what do I know about business, right? Like I don't have a business background necessarily. How did you guys think about that? Right? You and your co-founder are both computer scientists. I assume you did no business before you started this company. What has been your experience on whether that's that that preexposure matters whether if you just kind of learn it as you go? I mean there are a lot of people who will buy your product without business background. You just got to find the right buyer. I mean like Zipa is one of those companies they didn't care. You have like a bigger salespeople. Doash doesn't care about sales people. You just got to find your ICP. But I guess I mean more for you guys as founders like in your own founder ability. Do you feel like it would have benefited you or do you feel like your technical abilities allowed you to get somewhere in itself and then you know that's what kind of gave you the opportunities? I I personally like bias a lot towards builders and sellers because uh this is the mistake I made while starting the company. Me and my co-ound had this huge debate because I thought sales was the most important thing in the company. I was so wrong in like so many ways. If you take a look at all the successful AA companies is product none of them are succeeding. I mean nobody uses anthropic for the best sales team. I don't think that pay I mean anthropic and open air doesn't even pay sales people commissions. That's how they don't care about like a sales and I think with AI product is the most important thing. How how how good is your product at delivering a lot of value to the customer at short amount of time. If you can prove that everything else should follow through. Yeah. Okay. We're almost at time here. I'm curious if you have any parting final thoughts or reflections. you know, you've now been at this for 2 or 3 years. You're no longer in school. You've been spending your time split between San Francisco and Bangalore. Are there things that you now realize about how the world works um that maybe weren't obvious to you when you were getting started and you can leave people with some parting advice. Yeah, the biggest thing is just getting started and trying to sell the thing is just getting started and jumping the thing and burning the boards is a good thing to start. it it is only like really valuable and things get really real if you burn the boats. That's when I really felt because we know that when the company was not working, me and my co-founder were thinking, "Oh my god, we rejected all these job offers. What are we going to do?" It actually forces you to make things. And I think it's not like really really burning boards per se. If you have a job, you can get a job. It's not going to go anywhere. But in general just like going at it and like doing things has like a lot stronger value. Especially with AI it's just yeah the cost of building things is so low. Uh people should just build things and try to like uh deliver as much value as they can to very small set of customers and see if they can pay their money. Awesome. Thanks so much for coming Varun. Really appreciate it. Thank you.