Emergent: How Six Months of Tinkering Led To A $100M ARR Company

If you look at like last 30 years like most of the economic gain in the world has come from software companies. If you remove all the software companies from you know NASDAQ and and S&P you'll see it's been just a flat line and and besides thinking okay what if we can bring this power to almost everybody in the world. Welcome super excited to be here. What a crowd. So, Mand um maybe not everybody knows what a merchant is and also like what a big deal it is. For those who don't know, a merchant is one of the fastest AI growing is the fastest growing AI companies in the world and really I would say one of the first truly AI native companies in India to get to real scale. Right. Right. Um and so you're going to get to hear from I really see you as like a pioneer of a next generation of startups coming out of India and you're going to get to hear how how he's done it. Um to start with maybe you can just tell everybody what emergent is. Yeah. So uh I mean uh thanks for inviting me. I'm super excited to be here. I can't imagine like so many people coming to the school and the whole energy in India about the whole YC trip has been amazing. I was at IT Delhi uh a couple days back uh same energy. Uh so super excited to be here. Um Emergent is a platform that allows anybody without any programming knowledge to be able to build software that you can actually ship uh that your users can use that you can monetize. Uh essentially we're riding on this whole wave of uh coding becoming easier with AI. Uh and uh when we started our journey we actually started off as a research lab building coding agents. Um became world number one on three bench which is the benchmark for all of the coding agent. Uh it was just a four people team which actually got us there and then we started thinking about like hey what would happen in the world if we can democratize coding for everybody. Um and me being a programmer Madav who's my co-founder who was my twin brother um he both of us have been programming since age 12 um and super super passionate about uh you know programming and um one of the things that we realized that if you look at like last 30 years like most of the economic gain in the world has come from software companies. If you the world like there are billion people with so many ideas so many ideas just die because you do not have an access to sort of bring them to life and and that was the mission that we started with uh today we have more than 8.5 million people uh who are using the platform more than 10 million apps have been built uh we recently crossed $100 million in annualized run Great. Uh, today one of the fastest growing startups in the world and and the reason is that we are able to allow people to actually really ship what they dream and it's as easy as just chatting with your agent and we take care of everything from hosting, deployment, maintenance of the product um, and truly unlocking the power of, you know, bringing an idea to life with just chatting with your agent. How long since you launched the current version of the product? Yeah, we launched about 9 months back. 9 months. Okay. So, keep in mind this is basically a 9-month-old company. tell us like about the scale that you're operating at just nine months in. Yeah, so we have uh close to about 8 and a half million users on the platform. Um and um we are we are well over 100 million in annualized uh revenue run rate. And again like I think the latent demand as a market is is really really high. people there are a lot of people who want to uh build software and and so far have not been able to have the access to these tools and platform like ours truly enables them to ship you know an idea that they have had in mind. A lot of our users are actually entrepreneurs who do not have a tech team and have been sort of handicapped by access to technology and and now are able to build. Who are your users and also where are your users? Yeah. So we uh have users all across the globe in 190 countries. Uh when I started when I actually like just to give you a little bit of background right when I came to India in 2014 I was before that I was in Google in in US and I've always had this uh thought that hey why is there no Google from India why is there no Facebook from India we have so much talent so much engineering talent. In fact, you look at the top leadership of uh all of these companies, you know, like Microsoft, Google, you know, there are sort of Indian folks who have sort of gone there, right? And I've always wondered why is there no sort of technology first global company from India, right? And so when I was after Tanzano when I was thinking what what to do next like one of the things that that I had in back of my mind was that I truly want to build a global company from India like just like Facebook and Google. And today we have people have been using us over 190 countries. Um and most of the uh like uh revenue comes from US and Europe. Uh India accounts for about 10% of our revenue. Um and uh but yeah, our audience is fully global. And I'm not sure that people know but before you started a merchant. You started another company that I'm sure they all know called Dunzo which is like a really big deal. You raised what like a half a billion dollars and it was like a it was a huge company. Yeah. Yeah. I'm sure in Bangalore I think a lot of people would know us. uh you know uh we were pretty popular in Bangalore. We like uh you know at a peak we were one of the most loved consumer brands in the country. Uh even today when people ship something they say hey tons of it and and almost became a verb in the country. At peak we were doing about 10 million monthly orders. Uh we were one of the first people to start the trend of quick commerce in the country. Um the 10-minute delivery trend you know it was it was a pretty different journey like I was solving problems which were very operational in nature. Um also like last mile logistics you know how do you sort of set the dark darkstone network um and uh the lesson that u you know like u I would say was applicable there and is applicable here as well is we picked up to solve the hard problems uh when we started Dunano there were about um 87 companies which were doing exactly the same thing right because we had it was very simple you could just WhatsApp us and and we would you know we were kind of like a concage on WhatsApp so it was super easy to get started but I think The hard part was the last mile like how do you sort of really make sure the the end consumer actually gets the product the product is delivered in the right state. Um and and we chose to sort of do that. You know we were actually doing deliveries ourselves early on. Like I had you know a bike and a car and I would just in the night get an order. I would I would jump on a bike myself and and go and deliver. And I think early days just doing things yourself and and this is one of the YC mantra doing things that don't scale right really really helps you get close to the customer understand the real pain point whether there's a value or not. Um, and I think like uh just just you know being a customer yourself or doing things for the customer really really helps. Can can we actually go back in time a bit and talk a little bit about your personal background? I learned just a couple of days ago that Emerant is actually not just your second company but your fifth startup. This guy's actually started five startups. Um tell us like yeah um maybe tell us a bit about your early career where you grew up and went to school coming to the US and just sort of like getting started. Yeah. So I actually like grew up in a very uh I would say middle class upper middle class family. My dad is an engineer. Um and um obviously like uh got into engineering college. um did my engineering um always had this uh idea that I want to do something of my own. I actually very early on saw a lot of videos of Steve Jobs and was like really really inspired. Um I mean I I saw him him launching the first iPhone in 2007 and that was the moment like you know I thought oh I want to bring something to the world uh you know in in similar fashion and in fact I went to uh Spain for an internship in 2008 bought an iPhone. I mean it didn't work in India but I just bought it because I liked it so much. Just brought it as a souvenir for myself. Uh tried to hack it to make it work. Uh and then 2009 is when I went to US to do my PhD. Um and um then did an internship at Google. I liked it so much and I whatever research I was going to do, Google had actually done that research already two years back. So I thought there was no point. So I dropped out of the PhD program, joined Google, was in the search ranking team. There was a 50 people team that controlled all of Google search ranking. uh I was the youngest person in that team uh so I got a lot of liberty to sort of you know question a lot of things because I was um you know young person who could just just challenge the system and at that time Google was very anti-machine learning like they didn't want to like have machine learning in search and I was a machine learning engineer so so I I I got a lot of um you know uh leeway in terms of asking a lot of questions saying hey like why are we not using machine learning here eventually like got to push some of the biggest changes in search ranking when I was there for for a couple of years um then got bitten by the um startup bug. Uh left that uh Google started a company which was uh trying to build a group education platform where you can actually uh you know bring a group group class together. Uh raised a bunch of money. Um eventually like we pivoted into a P2P software company and realized that my passion was not that I really wanted to sort of solve education built wanted to build something consumer first. Uh so returned the money shut down that startup started another company into uh sort of habit creation. how do you sort of help people form better habits same time got married my wife didn't want to move to US so I moved back to India and I thought I could do startup from anywhere uh and I had an engineering team in New York I was I was working from India but uh realized the hard way it's really hard to coordinate uh you know without at that time so gave that up um and um one of the things that sort of has stuck with me like since the beginning has been that um and which I sort of you know like over time I've sort of realized to uh you know like do more of is just trust my intuition Uh and um and um so even with Tanzo like I started with this personal problem that when I moved to Bangalore like there were too many things to be done like I had a car to be serviced I had you know electricity uh to be set up gas all of those things and I thought there must be an easier way to do this and I just you know um started a WhatsApp group and gave that number to a lot of my friends saying that hey if you need anything just bring me on this group we'll we'll help you uh get that done. So started with a personal pain pain point that hey like we wanted to sort of you know make life more convenient in urban cities. Um and I think that has sort of stuck with me throughout you know that where whenever I'm I've been able to sort of you know um solve a personal pain point like the feedback loop is stronger um you relate with the problem more deeply you relate with the customer more deeply and and even with the version same thing happened like you know me and Maddie both of us are like idea guys like we have like thousands of ideas all the time and we wanted to sort of you know like automate and get more of these ideas out in the life and and and that's why we sort of started automating uh programming and and got started on the journey Dunzo was a huge deal. I mean, you scaled a massive company. Maybe you can remember some of the some of the stats about how big it got. How many? Yeah. Yeah. So, Dunanzo like we had almost a million riders on the ground. Uh, and we were doing 10 million monthly orders, almost like 5,000 stores overall. Uh, so pretty uh large scale. Yeah. Do you have like lessons that you took away from that experience? either things you think you know you did right in order to scale something so large or maybe even things that you would do differently a second time. I mean I think Danzo like even though like you know like it is a bitterswe sweet ending like for us like the um takeaway was was like for me were like two two three things. one was like solving the hard problem, right? We actually as I said there were like 87 companies doing the same thing and we really really uh cared about the consumer a lot. Like I remember you know earlier back then there was no AI. So so all the chatting had to be manual and every evening there would be a spike in traffic and every single engineer would drop what they were working on get back on uh you know on the chat screen talk to our customers and very early on we had this you know like um culture where we really deeply cared about the customer. Like there there was a customer who wanted to ship something to a different city and we actually put a driver the one of the riders on a plane uh to send that packet. So we would go that extra mile for every single customer and that's how sort of we we created this genuine love from all the customers. Uh second thing I think like one of the things that I learned from like us not being able to sort of scale eventually was I think like focus is really important like I think for us like Dark Store was really working and working really well but at that point we were doing like 10 other things like we were doing a marketplace model we were doing pick up and drop we were doing you know like bunch of those things. Um so I think like us like knowing that hey this is working let's double down on this model would have really really helped. Uh but eventually I think like I I just see this as a series of you know like me being a builder you know um you know just just as a stepping stone to to do something bigger. Yeah. Okay. So you worked on Duno for a bunch of years. You scaled it to this really huge company. It must have been a very intense experience running a you know like Adams based business where all kinds of things go wrong every day. I'm sure very very very hard like I mean yeah I mean we we had a team called watchtowwer which would watch over every single order and um it it almost like a war room you're in a war room continuously because everything operational things break pretty pretty often yeah and lot of that is sort of I borrowed here so the way we sort of run emergent as well is we monitor all the all the all the all the tasks that are that are getting built all the software that is getting built and and if some things are breaking we flag that so lot operational rigor I've been able to borrow from um you know Danzo to emergent as well. Yes. So in 2023 you've been doing this for a number of years and you left Duno. Um tell us the story of like leaving Danzo and then what what emergent like came out of Yeah. I think 2023 like um at one point we thought like Danzo was too big to fail. Um and you know we had raised $100 million in a recent round and I actually told my co-founder that hey I think now we are too big to fail uh right and and of course like the story didn't end end end that way. Um so when I got out in September 23 I was actually pretty depressed uh like didn't didn't want to do anything in my life. Um and for like first 6 months I was just you know um reflecting on hey what could have be done better. Luckily like AI was happening at that time so you know like chip was just taking off. um GP4 had just come out. Uh so I think it was it was a little bit easy for us to sort of build thing and and sort of building and coding became sort of my escape from from all the you know the noise that was there. So I would actually spend like 10 12 hours just sitting on my computer tinkering with um all all of the things that was coming out. The new voice models were coming out you know people were there were new open source models coming out at that point. So I actually got this luxury of 6 months of like just pure tinkering on things that I really liked with no sort of objective in mind. Um I I built this like um an assistant on my Mac where it could actually talk to me and I I could sort of something very similar to open cloud but very early version of that and I I was just following you know like whatever was exciting to me at that point and uh it became very clear to me very early on that like coding as a space is going to be one that that's going to get disrupted very quickly. Um and I spent a bunch of time in the US with my friends with with people at the labs. Um but I think it was just pure joy of tinkering, pure joy of just building something without any pressure. Um that sort of led us to sort of think of this idea led us to sort of you know um build emergent uh in some way because all the insights that we got while tinkering we were able to apply while we were building the product. Um and and uh you know that really helped and I think just having this um sense of curiosity and sense of um you know like when you're you're building things just for the pure joy of it just for the um you know because because you want to solve a problem right I think I think that allows you to go really really deep into the problem and bring insights that is otherwise very hard to get. I I like I kind of love this picture of you. You'd like you just had the super intense experience. You build one of the top companies in India. You're burnt out. You're basically just like recuperating. And in your spare time, cuz you have some time, Ben, you're just like tinkering with the latest model. You're just seeing, oh, maybe we could get like chat GPT to write some code. I don't know. Yeah. I mean, it was practically like just, you know, like um me I mean, just going back to like in the old times when I was a kid, you know, like I would just pick something new and and play with it. And it just felt like the same thing that I was just playing with this new technology and and uh the pace at which uh you know models were sort of accelerating it was it was really really fascinating for us to see that and for us to build a lot of deep insight into like how elements are going to progress for example like when we started emergent most of the companies were building uh co-pilots that that was the fashion that was that was what what every VC uh bought to here we in fact went and pitched to like 10 12 VCs got rejected from most of them uh and this is you know tons of founder was had a big company coming out getting rejected from most VCs because we told them hey we're going to automate software engineering and they thought it was crazy like that you know it was the AI is not there yet and but we could see we could see the model are capable like you know if if you just project it out a little bit um you know that the steps that they are failing like could be easily trained back um so we we took this very massive view that AI progress is going to be exponential and we will always build in the direction of AI and and that sort of led us to um sort of think from a problem perspective that hey let's automate all of software engineering versus piece by piece. Uh thinking of that. So I I I think having that downtime and just that tinkering energy like really really helped uh uh us find the way. Yeah. I I just want to like pull on a thread from this because I think this is really good general advice for everyone in the room. Like what what Mukun was doing we we we have a name for this at WCOM. We call it living at the edge. It's like the models weren't good at writing code yet and when you like pitched to VCs they were like the models like aren't going to be able to do this and like they weren't quite able to do it yet but you could tell that they were that like if you if you projected out you could see the sparks. Yes. Right. And like that is where a lot of the best startup ideas come from. It's the things that aren't quite possible yet. That's maybe a good segue to talk about some of the technical details of Emer like um if you just go to Emerion maybe you don't realize the sort of like deep technical foundations that it's built on. Can you talk about that? Yeah. So I mean we actually uh you know like when we started our journey like most people were building copilots. We thought we'll build autonomous agents that could do agents was not even a word then now it's obviously everywhere but like we built this multi- aent orchestrated system where you have uh different agents who which will come in different point of time uh and and perform different um action like for example we have an automated testing agent which will test your app. We have a design agent that will design your app. Um all of this is coordinated you know through a large memory system that we have built which are sort of self-learns every time a new app gets built on emergent like you know our agents actually extract from that what are the learnable aspects and sort of store it in memory so every every new app actually getting built on the emergent makes the platform even better um and a lot of the energy has gone into us into collecting a lot of the data that we have now we do a lot of RL on top of that uh we do some amount of finetuning and and but a lot of the things that we have built essentially is all of the infrastructure that we have built ourselves So we have built all of the coding agent. We have built um all of the infrastructure. For example, we when we started there was nobody building um deep container technology. So we had to invent a lot of the container technology ourselves. Like for example uh we wanted to preserve state so that you could have multiple panel agents running on the same same snapshot. So we had to invent disk snapshotting, memory snapshotting, all of those things. uh and I think one of the things that you as you said like you know living on the edge you actually discover these problems much early on before you know like other others other ecosystem discovers it and often time you'll have to go solve it them yourself like for example today like we have um multiple different sort of parallel agents that can sort of swarm together and and complete a task which we think is going to be like like like the future and and what we are observing is that every time a new model comes comes out like for example a new class of model for example opus is a new class of model like you have to actually delete whatever you have learned so far and sort of reimagined the world from the lens of this new model. Uh so so far like you know in nine months we have already rewritten our system three times um and and just just when when a new model comes out we have to sort of start rethinking that okay what are the new possibility that's going to open up and what what where this model is going to be in 6 months um and um and one of one of the things I was telling you before that you know like that like when we started emerging like one of the biggest challenge was actually that models could not do a good JSON output and like there were like at least 20 or 30 YC companies that were solving the exact same problem JSON parsing right And we took this view that hey like you know like the next model will be able to solve this. So let's say we just completely skip that problem let's start building the agent and and sort of you know went on the journey. So I think living on the edge and just trying to imagine what is possible in the next six months is really important as you sort of progress through your startup journey. Um can you talk about beating the benchmark is that's a that's like a core core part core part of the founding story here. Yeah. So um so one one of the things that like happened when we went to IC was that uh and this happens with a lot of IC founders that that you know like you you come in with a different idea you sort of you know stumble upon a different idea when we actually went to YC we were building testing agents initially right and um and and and when when sort of we were coming coming from India like we drew this on a whiteboard that hey like very soon you'll be able to build build web apps mobile apps um you know through AI and we had this diagram that hey like we'll be able to build web apps mobile apps on on on this thing. We day one we went to our YC partner told him that hey we want to build a consumer app building company and they said okay this this you know like maybe you should think about enterprise this this seems too ambitious. Um and for the first like it's a three-month program so for for for 3 months every week we would have a new idea on the board. Okay, idea of the week is you know let's say AI Zapier and and we'll spend a week sort of you know building that or or tinkering with that. Um and eventually like you know every every week we'll have a new idea. We were pivoting like crazy and um and team was getting frustrated. Hey like you have a new idea every week. What are we going to do? Uh so almost just to distract them I actually picked this benchmark free bench which was the hardest benchmark at that time and I told them hey like while I figure out what what are we going to pin let's just attack this benchmark because you know it'll allow us to solve harder problems and and so almost send them in that direction. It took us 3 months to sort of crack that benchmark became world number one on that benchmark. But that's really set us the foundation for emergent where we were able to build world's best coding agent. uh all of the innovation that we sort of have in emergent right now whether it's it's paralyzed test time compute um all of the memory agent to agent communication all of those things we were able to discover when when we were on this benchmark and I think like like even today I think like um attaching yourself to a number which which can sort of show you progress is really really good way to sort of you know attack a goal or or go go towards a building a company because that sort of focuses you into right direction it gives you like a really good feedback in terms of what's happening yeah yeah it's super super impressive what you guys did beating beating that benchmark before you even really had a startup idea like for what to do around it. Um a recurring theme of the talks today has been um this concept of second mover advantage. Um you know like Zeppto wasn't the first grocery delivery company and Giga wasn't the first AI customer support thing. Emerion was also not the first AI website builder to launch. when you launched a version, there were already a couple of like pretty big players and probably a whole bunch of small ones. Um, much like I guess your story of starting Dunzo when there were already 80 80 similar companies. What what what gave you the confidence to launch this anyway even though you weren't the first to the market and how have you been able to carve out such a such a big space for yourself? Yeah, I mean for us um when we looked at uh the problem space, we realized that like most of the other platforms that were out there like they were mostly focused on front end and building demoare, right? And and that's what like where a lot of these were finding product market fit, right? But what we realized was that like users are actually going to want real software to be shipped. Um and you know the problem is far from solved, right? Like and we saw that the the expectation that user have versus you know and I'm sure the same thing is with giga as well right like the expectation that user has like hey my queries get solved same expectation our users have that my software should actually work right when I when I'm prompting something and most of the solution out there like even though they they were like good at getting started right they were like really bad at finishing like you you will not get a working software out of that you will not get a you will not have a real back end you will not have a real databases attached and and so we came to this from from a very different angle saying that hey if you were to automate all of software engineering, how would you approach the problem? We almost built everything ground up. Um, and we could see like in practice when we sort of ran prompts on all all the platform and asked like we were massively outperforming everybody else in the market, right? So that allowed us to sort of really really attack attack the market in a big way. But I think again like we we came to this from a very sort of consumer insight that consumers are actually going to want real software that is working and not just prototype and demos and and nobody in the market was solving that. Um and there were no good solution that actually could could take you to the finish line and that's why sort of we we attacked that and once we had the product like we had to think through GTM how do we market it uh we looked at like which companies are growing really fast what what what they have done um and uh sort of almost converted our growth into a maths problem saying that hey how many social views do we need how many like you know um impression do we need how many clicks will we get how many users will we get and at that point we knew okay like influencer is a good strategy for us to sort of really launch because we knew the priority is really good, working really well. We just need to get in front of as many users as possible and that's sort of been the growth engine for us. Where is the emerging team based and how do you think about building an AI native company that targets a global audience um here? Yeah, so most of the team is actually in Bangalore. Uh we have 95% of our team in Bangalore. Uh pretty much built out of India completely. We have a very small team in SF. We have recently opened a new office in SF. So small team is there. And by the way, we are hiring. So if people want to you know uh apply and and work at a strong AI native company please write to me mukunemergin.s happy to take a look at that. And I think like one of the things that I' I've realized uh you know like and we generally like hire for like learning slope people who are like really really passionate about you know solving a problem people who get excited about uh you know solving some of these problems and what we have seen is that I think like one of the things that separates us right now from from the company is that everybody in the company generally enjoys solving and working with AI right I think there's this added of course the growth is great and and you know we get to solve real user problems but I think just the um you know the the complexity of the problem and the possibility ities are so much that we tally enjoy like day-to-day problem solving with AI right now. So that's amazing. You've had a chance to build two very different companies. You built Danzo in the sort of like first wave of great Indian startups that were building things like Zeppto, a lot of like local stuff. Um and now you're building emergent which is like the part of this like second wave of AI native companies postGBT. I'm curious first, what are what are some of your your takeaways from building those two kinds of companies? And then second, what would your advice be to folks in the audience who are thinking about where to look for startup ideas and what kind of things to build? Yeah, I mean I think I mean my realization after building the two companies is that like building a company for for India, a local company versus building a global company is actually exactly same effort. You know, it's it's equally hard to build a company in India versus building a global company. And so my advice to a lot of people right now is just think global from day one because I mean it's going to be equally hard to build both the startups. I mean and and it's kind of like a like a prevalent wisdom that actually starting a harder idea is easier because you can inspire a lot more people to go after a harder problem, right? And you can sort of you know uh inspire yourself to to go after these. So so I would I would I would recommend that like think global from day one because like now you have the reach the access internet is with everyone. Technology is a big leveling u you know for for everyone. everybody has the same access to the same technology and um and you can actually just reach global customer from days you zero from from India today. Um the other thing I would say is that one I think um just following your intuition is is really really uh I mean you'll get a lot of advice but I think following as a founder following your intuition uh is actually much better because you know like you probably have a better sense of general you know what your customer wants uh what your customer needs um and also I think um just thinking big and ambitious I think whatever you're thinking right now just 10x that 100x that because I think the next you know with AI I think lot of lot of things are changing and and it's it's not a time to sort of attack the floor. It's the time to attack the ceiling and think really big and the bigger you think the the the I would say the higher probability that you'll get to success. That's an amazing piece of advice for us to end on. Muk, you're an inspiration to us. Thank you so much. Thank you. Thank you so much for having me here and and the energy is electric here and I'm looking forward to load of Giz and Emer coming out of India over the next year or so and looking forward to this people here. Cheers.