Finding Product-Market Fit After 3 Years of Failed Ideas

Welcome to the SaaS Podcast. I'm your host, O'Macan. AI has changed the playbook for building and growing SaaS. Every week I talk to founders who are writing the new one. My guest today is Girish Reddicar who built and sold his first SaaS, then grew his second to eight figures in ARR with over 3,000 customers. But the first time around he spent years building products that nobody wanted. He didn't even know how to code, so he taught himself when he was 28 years old because he couldn't afford to hire a developer. Then for his second company, he picked the most boring space he could find compliance. In this interview, Girish breaks down why he walked away from a profitable business that he bootstrapped for years and how AI is creating problems that didn't exist 18 months ago, which is driving a whole new wave of demand for better solutions. I talk to a lot of founders stuck in the same spot. They've got a clear vision. They just need the right team to build or scale it. 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Thanks for having me, all right? It's my pleasure. So for people who are familiar, tell us what is Sprint Odo, who's it for, and what's the main problem you're helping to solve? Sure. Sprint Odo is an autonomous trust platform and to explain what that does. Every business today depends on dozens or more of other businesses to operate themselves. Cloud providers, SaaS tools, payment systems, you name it. That creates a massive network of digital trade and that's growing as we speak, especially with AI. On top of the digital trade, you have now have growing security threats, regulations, privacy rules and so on and so forth. So companies need to prove that they are taking the right precautions to protect that data. They have the right safeguards in place. Sprint O's job fundamentally is to help companies build that trust with their stakeholders and drive confidence around their program, whether it's with customers, with partners, with regulators and to be able to do that autonomously. That's a goal we have set for ourselves. And give us a sense of the size of the business where in terms of revenue, customer size of team. So Sprint O's had about four and a half, five years under the sun. We are today, we saw more than 3,000 customers across 70 countries, about eight figures in ARR. So and we are about 250 people in all of them. Awesome. And I think you've raised about 30, 32 million so far. Yes. Great. So let's talk about your previous startup before you started Sprint O, which is called Recruiterbox. And this was a business that I think you got to several, several million in ARR and then sold it. But it was a bootstrap business. And also from what I understand, you and your your co-founder spent some time trying a whole bunch of different ideas that went nowhere before Recruiterbox took off. So maybe let's start there. Like what were what were some of the ideas that you were working on trying to get some traction with but not really seeing anything happen? Oh, that's a bit of a blast from the past. But honestly, when we started working on our first startup, my co-founder and I, we didn't know much about what it meant to build a software company, what it meant to be building any business of any sort. We really had no no background in any of that. I mean, among other things, we had to teach ourselves programming because we just couldn't hire programmers. So there was literally like, we had to teach ourselves doing that. And I think the first few products that we built, so the general idea was we were very interested in recruiting as a space. And we had seen some of those problems, ourselves as we were trying to recruit for our ARR and lawyers that we were working for before that. And I think the first idea that we tried was what we today have like indeed.com and basically like research engine for jobs. And we sort of felt like it was that we live in a world where if it doesn't exist on Google, you can safely assume it doesn't exist. But that's not that wasn't true for job related information. You could never be, you know, sure that you have done an exhaustive search of what kind of jobs exist out and what opportunities exist out there for me and be able to make sure that I've sort of applied and at least given a shock to each of them. I thought that was somewhat that was sort of deeply densit right with us in an age of information that's one of the most important decisions that you make as a person and not being able to be able to do that exhaustively was something that was a little, it was very laugh for us. And that was one of the first problems that we started working on. And it was during the course of running, doing that that we realized that hey, the fundamental problem is not about scraping technology and that you don't have like all the jobs in one place to make them searchable is that a lot of the jobs don't have a digital footprint at all. So they exist inside of some private communication, which is basically maybe like the company and it's a recruiter that just on an email on some private board somewhere which like a search engine will never be able to reach. So only about 30% of the jobs really have like a public digital footprint. The remaining 70% are just somewhere else. And we realized that hey, even if you could build the best technology to do this, it's more than going to be extremely useful. So then we tried a bunch of other things like I think one of the things that we built back in the day, which today's relatively trivial with AI was basically being able to match people and the resumes and the backgrounds to job descriptions as well. And it was done based on the state of art AI at that time of time, at that point of time, on machine learning. And that didn't go anywhere either as a business. I think the tech worked really well, but we didn't were able to do much of what it was business. And then we eventually basically built a recruiter box, which was quite simply a think of it as a CRM for hiring. It gives track of every all the activities that you need to do about hiring, make sure it's in one place. And in one of the other ways, like our goal with that was that if enough companies use this, there'll be a public footprint of all the jobs that they have, that's an outcome that happens. And that was one of the original problems we wanted to solve. So from what I understand, you spent two, three years trying different ideas before you landed on recruiter box. And they didn't really go anywhere. So I'm curious what kept you guys going and you know, continuously trying different things during that time. It was hard, you know, like both financially as well as just, you know, to just keep going mentally about it. And you know, depending on how things turn out, you could like one way to look at it is there was stubbornness, a certain degree of that. But if you come out right from it, then it looks like there was determination. Like I don't know how to characterize that, but you know, we always sort of felt like we were that one step away from what it actually means to do something that worked. And it was kind of good to have like a co-founder and you could sort of feed off each other's energy the time so somebody's low and the other person sort of tracks us through and you know, that was happening a little bit as well. It did help to have family support as well. I think that was extremely important as well. So yeah, I think all of these things came together to show us up for this couple of years, which really had nothing to show for it to be honest. Yeah, I think sometimes it's easy when people hear a story like this and say, oh, you know, "Garation is co-founders," they bootstrapped and they, you know, seven figures ARR and the sole this thing, to not really appreciate some of the struggles that you have to go through to get there when things aren't working, when you don't have, you know, all the funding, when you don't have enough money to hire people, then you have to learn how to, you know, break code yourself and all of these things that, you know, or sort of part of the journey. How long did it take? Well, once you landed on the idea of recruiter box, like how long did it take before you guys felt like, this is the one, this is the thing. And what were some of the signs that, you know, told you that? So I think the first version of recruiter box was basically pre-strike. It was a few months before stripe happened. And I remember that distinctly because we just didn't have like a way for us to collect payments. And it was happening that, you know, we were selling remotely. It was something that you could sign up for and then start using it. It was like a self-serve motion. And we realized that we basically cobbled together like this really, really caveman technology sort of thing where all you really did is as a customer, if you like, recruit robots, and you wanted to pay for it. We'd give you like a PayPal link. You go there, you swipe your card. Yeah. And depending on how much you paid there, we would add a sort of number of credits in recruit robots. And they would basically get, you know, deducted on like a daily basis. And eventually you ran out and then you basically had to go and swipe your card again in PayPal. And it was really bad. But what really surprised us was how many customers actually went ahead and did that. And that sort of told us that hey, we're doing this in such a bad manner. And yet people are taking that pain in order to actually go and do that. Now, means what we're building is, you know, it's valuable, at least for this, this set of customers, they appreciate what we're doing. And that means something. And then, you know, that was one of the early signs where how much just pain that our early customers went through just to be able to use us. And I think that was very encouraging for me personally that hey, you know, this is, you know, this has legs. It can go far. Yeah, I've heard that a few times. And I think this thing about, if your early customers are willing to jump through those kinds of hoops to get the task done, you're definitely onto something versus, you know, you're having to basically spoon feed them every step of the way and persuade them to even show any interest and so on. How far did you get the business? I mean, I know we said, you know, seven figures in ARR, but have you talked about publicly about the number? How much you've got two in terms of revenue when you saw the business? Yeah, that's unfortunately one number. I'm not at the luxury of sharing because there was part of my car track, but we were more than 2500 customers. So still single digit ARRs, but you know, like a large number of customers. And then we were going the time more than 100 customers a month. So it was a fast going business as such. So we'll just say it was somewhere between one and 10 million in ARR when you sold it just to keep it broad. The one thought I had was, you know, you went through that struggle, you built this business, you've got to the point where you've got some decent traction, some revenue, you don't have investor pressure. What drove you to sell the business versus saying, you know, let's keep working on this for a few more years. I think the simplest way to say that is it got a little too comfortable. And you know, the business was growing, it was doing well. We were trying to make the business grow a little grow faster, much faster than what it would like. We would have liked it to be, like we have a few thousands of customers, but remember the background that I gave, like we really wanted this to become like the de facto way of, you know, people hiring. And we didn't see a path from where we were to where we needed to be in order to be that. It was it was a great business in its own right, but it wasn't anywhere close to what our ambitions with that were. And at some point we had to ask ourselves like the hard question, maybe V as founders of the bottleneck to the business, not the other way around. And you know, we eventually found a buyer who we believe could actually scale the business a lot better than than we could because they actually had done that a bunch of times with a bunch of other businesses like ours. So I tell that was, you know, at some point as much as we think of startups as our babies, it's important to sort of, you know, have its own life. And it's important to do what's right for the business rather than what's right for you individually. And I think it was a combination of two things. Like it was going great. It was relatively comfortable. We weren't quite challenging ourselves. The business wasn't going faster than what it, you know, it could and it should. So at that point we decided that hey, you know, it's best in someone else's hands who can actually grow it faster, do it right, do what's right by them. And we believe ourselves as well, but we had another startup in us. And then we wanted to actually do like a larger, faster growing business. And for whatever reason, Recruiter Box was a turning out to be that. So after you sold Recruiter Box, I think it was a year or a half after that that you found it sprinted up. Where did the idea come from? So this wasn't the only idea that we had on the table. They were the were a bunch of them. But one of the things that had happened during the course of growing Recruiter Box. And especially as we were trying to get, take it more and more up market to larger and larger customers, we kept getting asked for these things like a sock to certificate, so a sock to reporter, I so sort of a care bunch of security questionnaires. And again, as an engineer, this sort of fell into my lab, I had a front row seat to what these meant and why they were required. We did, you know, the usual thing that founders would do in that situation, which was kick the can down the road as much as we could at some point realize that we can't do that more. Then we hired a consultant to help us go through that process a few months and tens of thousands of dollars later. You know, we got what we wanted, but you know, it wasn't exactly what I'd call like a great experience. We were sort of grudgingly doing it. And that's not to say that that idea to do something about it came at that point of time, but you know, in that after we saw the company and we were thinking about what to do next, that was one of the experiences that stayed with us. And I was, I like this sort of this intersection of a van diagram where a problem is unsexy and boring that nobody wants to touch it with a 10 foot pole, but at the same time, it's available. And this sort of felt like that. But you know, to be honest, like this was one of the three or four problems that we had on the table. And I know we spoke a little bit earlier about this book called The Mom Test. And I came of all that book, by the way, during this break. And it kind of big influence on me, fundamentally because it was written by a person who was basically a software engineer and about, you know, how, how to go about really knowing whether what you're building is valuable and useful. And I told myself, and I make a founder, told ourselves that, hey, we're not going to write a line of code until we can validate what we're building is valuable. And, you know, and did the most uncomfortable thing that was for us to do, which was go talk to people, figure out and validate something that we didn't have yet. And you know, figure out whether it was worth building. So were you trying to validate multiple ideas at the same time? One at a time. Yeah, it was, it was one at a time, we should give it like a few weeks, you know, just build a few mockups for us to understand what it might look and feel like or maybe even tissue to other people, but more importantly, just have conversations around it. But it was, it was, we used to immerse ourselves into like an idea for a week or so, not necessarily make a decision about it, but, you know, spend some time on it, then we want to the next one, and then eventually make a decision. You know, I think it's really interesting that often I took to founders who start out and they have built something or they feel invested in a product or an MVP. So when they go and talk to customers, they're trying to get validation confirmation for what they've built. But once you don't do that and you go in very intentionally and say, I'm not going to build, I'm not going to write any code until we validated it. It's a little different because then you're like almost, it's almost like you're saying, can this person convince me that it's worth my time and effort to go and build something? And so when you start having these conversations, what did you start seeing? Like what told you that this is the thing that we should focus on? Again, I wish it was something that was like black and white and it was like, you know, like a clear sign that, hey, we know that this is absolutely important and useful to build. I think there's a certain degree of uncertainty still there. And as much as I'd like to claim that there was a, you know, there was like a wall of evidence to say that, "Hey, this would actually work." I think beyond the point it is intuition. Having said that, the process of actually just having talked to about 20 people and just hearing them how they describe the problem, etc. sort of crystallizes the thing in your head about what is it that you're really building? What part of it probably needs to be built first? And this is happening just implicitly. You don't necessarily have to think about it explicitly. What do they care about more than the other things? And why would they pay for it? And how urgent is that pain or how important is that pain? You start getting like a mental compass for some of these things. I wouldn't say that, you know, like for example, one of the ideas that the other ideas that we were pretty excited about that we eventually didn't end up building was basically a WordPress competitor. And I think one of the things that we realized that, "Hey, this is a great idea and we should probably build it, but we are not the right people to build it." So it's not just about that as well. Like in the sense that we realized that building something like that would require a lot of developer evangelism. And we're not the best people to build something like that. So you realize some of those things as well. So you just start thinking a little bit deeper about the problem space. Then you would, if you just started building, which is what does it take to take this product to market? Are you the right, there's not just product market for it. There's a founder product for it as well, and that needs to happen. And you sort of live through the cycles in your head. Yeah, I can almost see that Venn diagram that you're talking about with this other circle now, which is this the right thing for us? Is this something that we're good at? And if not, then let's be honest about that because you don't want to spend five, 10 years on something that just doesn't feel like right to you. I know that, so how many of these interviews did you do before you kind of felt like, yeah, we can move to the next stage stage? For Sprinter, we did about somewhere between 15 and 20 interviews, conversations. And I think I read somewhere that you said that, you know, like the hardest part for Sprinter wasn't finding customers, it was like turning basically a consulting service into a product. And I know you guys spend a lot of time deconstructing that almost reverse engineering, this consulting service and breaking it down into his consistent parts and figuring out how to productize that. How long did you spend on that? And can you just kind of walk us through like how you did that? Because when I kind of came across that, I was like, that sounds like a lot of work that most people wouldn't be willing to do. And I think just kind of understanding why you did that and how you did that would be super helpful for a lot of founders. So there were a bunch of factors that led us to do that. Like the prevailing wisdom at the time is that, hey, you know, as when you know you're building, just build, put like a, you know, the MVP and like this, the smallest version of the product out there as soon as possible. And start getting customers for it. And, you know, I was born and raised in that school of thought. But there was something about a space where we made like a counter-interd of jump that we were going to go about it a little differently. And here was the fundamental issue that we had with the space at the time. We realized that us in recruiter box, when we had gone about this problem, the standard way to go about this, you basically hire like a consultant and it's like a services model of getting it done. And what we're fundamentally saying is that, hey, this can be product-less, right? And what we were very clear from the get-go is that we didn't want to build a services company. We really want to build a product company. And I thought one of the riskiest things for us was that if this turns out to be something that's product and part service and they know like sort of the service component is significant and really important. And you won't be able to productize it enough. And while it might be still a valuable offering, the company you're building is a very different one. And we wanted for our own sake to basically eliminate that risk. We were pretty sure that what we were building was valuable. Sure, to the extent that a founder can be before you take it to market. But you know, we were reasonably confident that this problem exists and people need this. What we weren't sure was that, whether it can actually be productized. And I remember at the time, you know, we had this mental model of the sort that, hey, if you're building a startup, you can think about it in two axes. You know, one is, are you solving basically, do you have a product risk or do you have a market risk over there? And what I mean by that is a product risk is a class of problems where the fundamental question you're asking is, can this be built? Not whether it can be available or can it be taken to market because if it can be built, you know, you're pretty sure you can you can market it. Like a good example of that in today's world would be something like a self-driving car. If somebody did build a self-driving car, you know, I think it's pretty it's it's it's pretty clear that you know, you can take it to market. So that's not where the risk lies. Or if you build like a machine that, you know, just transports people from one place to the other, if that were possible, that's a product problem. That's a large product risk over there. It's not a market risk over there. And I'm giving you extreme just to explain the the edges of the the the diagram. And there is another place where you have market risk in the sense that the product, building the product is relatively easy or simple. What you're really worrying about as a company is like questions about how do you take it to market? And you're packing yourself, you know, backing your skill at being able to do that. Like you're basically like a great GTM team that can take it to market. And most companies lie somewhere on this graph. And we realize what we were building was basically towards this line, which was there were higher product risk than market risk. And then we wanted to eliminate that. And so the thing that we did that was counterintuitive at the time is that we said that, hey, the most important stakeholder in this equation, who's not very clear yet, is an auditor eventually it's an auditor who has to give you the software report, the ISO certificate, etc. And we need to understand how they look at this. And what do they need in order to basically be able to productize this? And so our favorite past time of the time was we used to just go to auditors and say that, hey, we want to suck to report auditors. And they would do that. That's revenue for them. And we were building the product as we were sort of, you know, going through these audits. So we were sort of the first audit was entirely manual. The second one we had some spreadsheets etc in place. The third one was, you know, we had some product in place. And then we was all happening behind the scenes. The auditors never got to see it. But by the time we were on a 10th audit or so, we had it bad down. Like we knew what we were building. So that had that because now by the time we actually went to our first beta customer, we had a lot of confidence. Just say that, hey, you know, we know exactly what auditors look for because we have done that many times before. So when I when I initially thought about you productizing this, I imagined it as you going out interviewing people, seeing how they were doing the job and then figuring out how to build a product. But you were actually paying auditors to come and have you audited over and over and over again until you felt like we understand this well enough and we have enough pieces of the product in place to be able to sell it. Yes. You must really love audits. Like I said, the boring and sexy problems that nobody wants to touch, you know, because that was like the, that's basically where the rubber hits the road. It's not fun. Everybody hates it. But that's that's basically the trial by fire, right? Like you need to get that piece right. And the sort of the mental concept we had as well. If everything that we are doing is print ways of black box and the only thing that comes out of it is what an audit receives. How much of that black box is automated underneath? That's really our test. The auditors just need what they need and they are not going to change themselves just because, you know, you're doing it in a product this manner or you're doing it in the services business. They don't care. Now, as I understand with Recruitbox, it took, it took a long time to get traction there. But with Sprinto, you landed what 30, 40 customers, very quickly within months of launching. And you know, some big names like I think HP was one of one of your customers. What did you do differently that helped you get that type of traction that quickly with Sprinto? So I basically have a mental model now of how to take products to market. And I think, you know, there's a like I have an engineer's view of this. This is not necessarily like a savvy marketer or a GT in person's view. And I feel like they're fundamentally two categories of product when it comes to GTM. One is where you are what I call what you're really doing is harvesting demand. So you sort of, in a space where the demand for what you're building already exists. And your job is to be able to harvest it, so which means that you need to be at the places where people look for something whenever they have this problem. So most products we know sort of fall into that category. Sometimes, increasingly with AI, you have sort of categories of product where people are not explicitly looking for it. But if you weren't in front of them and they realized that, hey, there was a way of actually doing this, they'd be willing to try it. But they're not going out looking for an answer to, hey, how can I entertain myself better with short form videos? Let's say, that's not a question anybody asked. But if I came across it, I tried it, I loved it, let that look square, or anything up there. So there's a category of problems of things on along that axis. So I think fundamentally, it's important for us to start to realize which of these two things do you rely on. And we were squarely on a place where there was demand for this. People were talking about this in founder groups. They were asking this to the investors. They were reaching out to some consultants. They were googling for this. And all sorts of things were happening. And we realized that, okay, there was a problem. People faced this problem. They they went about asking certain people or systems like Google and that's what they would basically do. So our job became then to be present at the places where people looked for answers about this. Right? So the standard answers, we actually made ourselves present on a bunch of these founder networks, communication, the Slack groups, the WhatsApp groups, there are various kinds of places where founders hang out, ask questions about what I was going on in the, okay, do you know this vendor? You know, what do you do about, I need some legal help on this contract. Everything else, and compliance is to come up once in a while over there. So we make sure we got us injected over there. They are straff the VCs. So what we did was we got us injected into the Perks program of a bunch of VCs and we started giving discounts to startups if they were affiliated with the VC and you know that that helped us get some of our OD customers as well. Google helped. The fact is if you're a CT on a young startup and you get like a security questionnaire on your desk and say you need to answer this or you know, today you would change your pt. But the time you would basically go to Google and say, hey, what the hell, what do I do about this software? What do I do about that? So so being present on Google, either by ads as well as later as in terms of SEO was an important channel for us. So that you know, so it sort of started from the fact that find where people go today in order to solve this problem and then try and be present on those places. That's what worked for us. When you and I were talking earlier before we started recording, I asked you about how you got to the first million in in ARR and why you identified these three or four channels that help you get there, you also mentioned, hey, we tried 20 other things that didn't work and then eventually we figured this out. And I think there's a really valuable lesson there because sometimes you know, founders who are struggling to cut a quiet customer's might hear this and say, oh, you know, Gyrish did XYZ. So I should go into XYZ. But I think it's more about the process you went through of trial and error and figuring out what actually worked and what didn't work. So tell us a little bit about that. Like what were some of the things that you tried that didn't work and how did you kind of go through that and navigate through that and to find the channels that did? Yeah, thanks for bringing that up. Like, yeah, this by no means meant that I had a theory and it meant that here, this other three places we should try and that's what worked for us. We tried 20 things, 17 of them didn't work, three did. The fact is still like for example, something that you could intuitively think that could work and I for a long time thought that it should be an important channel for us, especially with the young startups was, you know, going to partners who are like advisory firms who start us would go to and try and see if we can sort of co-sell with them. And for whatever reason, like on paper, it makes a lot of sense, but it didn't work for us as well, at least in the early days. We started working for us a little later, but it didn't work for us in the early days. So there's a ton of such things that even by the by the principles that I just described seem like they are the right things to do, don't work. So I think it's there is still a, this is by no means a sure short way of getting an answer, but at least just a way of knowing that hey, these are some of the kind of things that you could try. So I remember like doing a bunch of startup conferences earlier, which again you would imagine should work, but it didn't, at least at the time. It started working for us again later in a different context, and you know, maybe some of these things require you to already have a certain degree of brand or some Refinisibility before it works. So they may not necessarily work for you in the pseudo to one journey, but they work for you in the one to ten journey. And honestly, there is no playbook for that. You just have to try a few things, and you know, you only make the shorts that you take. So you have to take about 20 shots to make two or three of them to work. When you tried something, how long would you spend on it typically before you decided to move on? Again, I wish there was a formula to that. Honestly, there is a bit of intuition about, you know, when it doesn't work, does it completely fall flat, or do you see that it's not working because of the way you are doing it right now, and maybe if you tweak a few things it might work. So I don't think it's as much of a science, at least not to me, at least I'm not able to sort of pull it down to say the head. This is the extent to which we should try it, and then we should sort of give up on it. But in other places, you see that the more you put in, the more you get out of it. So, and a lot of those things to be honest is not even about it didn't work. It's like, you know, as a startup, you've got to pick your battles to fight, and it just so happens when something else starts working. You know, the start of sort of starts gravitating towards that and spends more time and energy over that. So some of the other things don't get as much time and energy on them as well. So, you know, to be perfectly honest, it was possible that some of those things could have worked if we spent more energy on them. But so happened that we just, you know, got pulled in some direction, that started working. So we just sort of double down on it, and then we had to sort of hire people to try and some of these other things later. So again, there's at least to me there is there's not a lot of science that says that hey, this is a lot of time you should spend on it and then you should move on or something like that. Yeah, I mean, it would be great if there was, right? But unfortunately, there isn't. And I think that's part of the challenge is when it's so messy at those stages, when you're going through like trying to figure this out, it's like the question is, is this the right channel for me? Am I maybe you're not super clear about your ICP at this point? So is it, am I talking to the right potential customer? Do I have the right messaging or positioning that's going to land with these people? Am I talking about the right problem? And then as you said, it could also be a timing thing that yeah, I've got all those things right. But the timing in terms of where I am right now with the business isn't there, but maybe in a year's time, this will work really well for us, right? And so it's a really difficult, messy thing to work out. And you know, one of the things that at least I didn't think deeply enough about the other time is that different channels have different sort of majority periods, like ad words, if that works for you, it's kind of like opening a tap and things start flowing. So you can experiment very quickly with it or something like partnerships. It takes months and months of investment before something comes out at the end of the pipe. You know, and you basically have to keep investing and it for a while before you get something out of it. So if you as a start of have like a goal of getting to somewhere in three months or six months, that's not an answer. But at the same time, that is not the same thing that you can't start on that tomorrow. In the sense, you can't wait to start until that six months later. You have to start on it today so that you can actually layer that in maybe nine months down the line. But there's a bunch of things that are going to give you immediate benefit, or as some of those other things will have a certain gestation period before they can actually start reaping rewards for you. And I didn't quite understand that as well early on that, you know, hey, different channels just have have different majority periods. So yes, they are important to work on, but I can't count any benefit from them in my immediate goals right now. So there's that math happening as well. Yeah, yeah, so it's very interesting. Let's let's talk a little bit about AI. You know, we're hearing a lot these days about, you know, sass is dead. You can vibe code everything. I'd like to see somebody vibe code a compliance platform like your building, because I think there's a little bit more to it than just that. But when you're sort of looking at, you know, what's going on right now, let's start with like what's the biggest impact AI? has had to your business so far. - I think we are in a very interesting space in the fact that AI has impacts our business from three directions. And that I feel is really fascinating and strange. Like if I were to explain one way that, one of the ways that AI has impact on us is the fact that, you know, we obviously are an AI first company now. So we want to make sure that our product itself is more autonomous and do things that otherwise require humans to do. And, you know, my mental model is that for a very long time software is this thing where, you know, it just humans feeding software. You're filling boxes inside of a software. You just, you know, you're giving data, that that software just faithfully stores for you and then gives it back to you in a nice report if you will. So for a long time software has been like that. And we took a jump from that to making more automated software. But AI is actually going to get to a point where finally, finally software will work for you rather than the other way around. And I find that very interesting as an idea and we want to be at the absolute frontier of it. There are some very interesting things that we're doing at Springtown in order to basically enable that. So that's one aspect of how AI affects our business. The other aspect of how AI affects our business is our customers, you know, they are internally becoming AI first. So the folks that we sell to, like a product is becoming AI first, but our customers themselves are also becoming AI first internally, like they're actually having a bunch of their internal business processes run on top of AI now. And that has implications on how you run your GRC program or how you go and run your governance risk and compliance program. And trick implications to what Springtown has to work. So there was a time where we were just managing entities and software and systems and people and servers. But now you need to basically think about agents and other things that you are trying to manage. So I think that's an interesting piece that our customers and our ICP cares about. Like the Chief Information Security Office are now increasingly cares about how to make sure that the AI that they're building in DERLOT is safe and sound and secure in Governdt well. So that's the second way that you sort of AI affects us as a business. And the third way that AI affects our businesses basically we are squarely in the security and privacy space. And there are tricks from security in a privacy manner that are actually happening from the outside to a business. So there's AI in our product. And there's AI in our host business, are the our customers. And there is AI outside of that business that this business is trying to protect itself from. Which is there's just so much more social engineering fishing AI based attacks, very sophisticated attacks that are happening now. That need to protect themselves from and a governance risk and compliance programs. One of the jobs is to basically be able to do that. Right. So I think it's just like a very compounding trifecta of factors that are coming together with respect to AI. And we often think about AI in only one of these three modes. But all three of these are happening together and just just leading to like an extremely exponential change in the way the software this category is going to emerge. Because that's not just happening uniquely to us. It's basically going to happen to pretty much everyone in the category. And I for one I'm excited about it. Like it poses newer challenges to our space that were never posed before. And if for one that if that means that basically we need to evolve faster as a space that I am all for it. Yeah, that's a really, really great way of framing that because it's an incredibly, there's so many dynamics I play here. Now one thing about being AI first and in the compliance space. And if the AI fails, your customers potentially fail audits. I'm curious like how do you ensure that you have the guard rails in place for that not to happen? Right. So I think the wavy look at this is relatively-- I won't say it's easy, but we have a simple way of thinking about this. Everything that eventually needs to get audited needs to be deterministic in the sense that, hey, did you actually encrypt a state of this or not? You can't have AI answer that. That's a deterministic thing. It was either yes or no. Did you make sure that you off-boarded this user from this account or you revoke their access from this account when they left the company or not and when did it happen? There's no-- there are no two ways about it. Respective of who does it like this. This was a timestamp at which they left the company. This is a timestamp at which you revoke their access. Your SLA says that this can't be more than 48 hours is that true or not. That's yes or no. So I think those are the places that will continue to remain deterministic software. What AI does do for you is just everything that happens in between a lot of plumbing that needs to happen that happens in between. It can make that better and better. So I'll give you an example. Traditionally, software and our space has been great at telling you that, hey, you're trying to meet software requirements. Here's a list of requirements. Here's how you meet them. Quick. What software has not traditionally been good at in our space is to say that, hey, by the way, you has a company assigning contracts as well. And somewhere in that large dense contract, there's a clause that says that you're going to have a certain SLA on your product. Who's reading that and making sure it becomes a part of your program? That's a great use case for AI. You were not doing that before. It was just manually impossible for you to be able to do that before. But the fact that now you can know all your commitments in world place, whether they come from a contract, whether they come from a cybersecurity insurer, whether they come from your risk or your policy or your framework, it doesn't matter. If you can have them in world place, and AI can solve that for you. We used to stop at saying that, hey, this database isn't encrypted, and you need to encrypt it. But the best in class at the time was basically saying that here's some documentation on how you can actually go and encrypt it. And people are reading that and going and doing that exception. That's painful. You can actually have AI now sort of go and do that for you while you are actually on the screen. We have basically a fixed-to-t agent. So you as an engineer are supervising it, but you're actually doing the job for you and making sure that the thing gets encrypted. But it's making your life easier, and it's going over and beyond what was possible before. But I think the basics of our business don't change. I don't think there are certain things which are sanctimonious in an audit of any kind, not just security and privacy audits, but even in financial audit. Did you pay this or not? Is in fact, in debt can't be blurred. And I think that will continue to remain like a system of record. But there's a bunch of stuff that happens around it that can still become faster, more autonomous, faster, yeah. It's intriguing. You're making compliance sound interesting to me. That were possible. Yeah. Yeah, I know. This isn't everybody's cup of tea, but we do geek out over it over here at Sprintah. Love it. If you're building an AI agent, a SaaS product, or stuck trying to scale, check out Gear Heart. They can act as your fractional CTO and technical team, bringing AI expertise from projects for meta and Google, plus strong Silicon Valley connections with founders and VCs. And since they're a Ukrainian born company, you get senior engineers with an offshore pricing model with offices in San Francisco and London and a distributed team of 40 experts. They've helped build over 70 successful products. That's gearheart.io. All right, we should wrap up. So let's get on to the lightning round. I've got seven quick five questions for you. You ready? Yeah. What is common startup advice that founders get that you disagree with? I disagree with most advice, honestly. And I think it's because all advice has some context behind it. So we take the advice, but we'll lose the context. So I think all advice needs some context behind it. Like you do anything, which is like launch early, and that could turn around and bite you in the back. So the context is important. What book would you recommend to our audience and why? We talked about it overwhelmingly and wholeheartedly recommend the mom test. If you're a builder, go read that because building is becoming cheaper. The thing that's important is basically, are you building the right thing? What is something that you're good at now as a founder that you were terrible at in the first year? I think this is like a philosophical thing, but like people say that you can't control others' behaviors. You can control your response to it. And I think I'm realizing the importance and the performance of something like that. I think I'm generally better at that today than I was 15 years ago. What's your favorite personal productivity tool or habit? I'm not much around productivity. It goes like the only thing that works really work for me is uh. and deliberately blocking some time for deep work every day. So I just don't let anything go in that. - That's a good strategy. What's a new, crazy business idea you'd love to pursue if you had the time and money? - Maybe after all of this is said, and then one of the things that I really curious about is personalized education. And I mean, really personalized, not just adaptive quizzes. Every kid learns differently. As a father, I'm seeing my young one grow and we've known it forever, but a classroom of 30-page students and one teacher is never going to deliver on that. And I think, finally, AI can change the economics of that. And I feel like at some point, it's not just for kids for adults as well. Most professional learning is still terrible. And it'll be great to be able to work on something that makes humans learn better. - I love that, I love that. What's an interesting or fun fact about you that most people don't know? - Well, something we mentioned on this conversation passingly. I had to teach myself programming with Minnesota Refers Company. I did not know that. I was, yeah, I think the first line of course that I've really written ever is when I was 28 and I can't imagine living without that now. - I was surprised about that when you told me that. I just imagine that you're a strong development background. I've been coding forever. And finally, what's one of your most important passions outside of your work? - It's a bit of a cheat answer because it's not really outside of work, but I, from a long time I've been thinking about applying mass production techniques to software. And increasing with AI, I'm increasingly curious about the question of how software, I don't mean code, like how software changes and how the job of creating software changes. And I think AI is finally making that possible, but we're still all figuring out exactly how. So one of my favorite pastimes is to sort of, I have this side quest where I try to cobble together something and try to refine my understanding of that. - Love it. - Love it. - It's awesome. I appreciate you so much, which you want to me to speak to pleasure. If folks want to learn more about Sprint0, they can go to Sprint0.com. And if they want to get in touch with you, what's the best way for them to do that? - It's my first time, Gary, share Sprint0.com. - Awesome. Thank you so much. I appreciate you taking the time and sharing your story and lessons. And I wish you and the team the best of success. - Thank you so much, Omar. I really enjoy being here. - My pleasure. - Cheers.