Introduction
In this insightful interview, we talk with Spiros, co-founder of Resolve, who has mastered the art of building successful companies. Having previously built and exited a company for nine figures, Spiros shares his journey of raising $35 million in seed funding within just one year of launching Resolve, an AI company building agents for software engineering on-call and incident management.
Founder Success Story QnA
Why are you building AI agents for software engineering instead of coding like everyone else?
Yeah. So I mean first of all uh it’s exciting that let’s say AI can create art or you know do creative work but you know for us what’s more exciting is if AI can uh actually do the work we don’t want to do as humans right and you know I most of us are engineers at resolve we have experienced what it means to actually build and maintain software at scale in my last role after my last company got acquired by Splunk I was the GM for Splunk observability it’s a big production system, right? Uh we had an a period over 6 months where 90% of our SR team resigned because of burnout. And you know cuz you know if you have incidents all the time and if it’s hard to keep systems up, you know, it’s a very difficult job, right? Like waking up in the middle of the night to solve a problem is something that nobody wants to do. And we felt like actually that although that problem was always known, we felt like now AI is at the point where with agents you can actually do this type of work and relieve humans from let’s say the the pain and the burden of on call and you know the challenge of maintaining production systems.
How do you differentiate between what is an agents company and what is just a chained series of workflows?
That’s a very good point. So I think that in a way uh people always try to automate you know tasks especially in this space right like you know some when something goes wrong even alerting itself right you know you fire an alert and you trigger a workflow in my opinion like the difference with agents is that they can actually u you know first of all learn and generalize from prior experience right a workflow automation usually is something that you know you execute within the bounds of you know some predetermined set of actions You know when this happens you know maybe these other three things follow and after that you know you take A or B with agents and first of all in like software systems at scale there are so many edge cases there is no way you can predict you know all the potential outcomes or corner cases. So agents especially how we’re building it they can actually learn and they can reason almost like humans and they can generalize right. So that makes them applicable to all sorts of problems that you know nobody has thought about it in advance.
You raised a seed round of $35 million and have 50 people on the team even though the company launched like a year ago. What was that process for you?
So you know first of all in our case u you know maybe starting with more basics like I’m a huge believer that the only way to build a company especially an enterprise company is to work with customers and I think if you do that well and if you’re honest with yourself I think you can get to the to the truth let’s say about what is the real problem and what is not the real problem very very quickly right so at resolve we’ve been working with design partners from day one before we had a product and the way this happened is we went in with let’s say 100 people before we started and tried to validate is this a big pain for them, right? Would they be interested in a new way of solving this problem, right? Like would they be interested in a kind of a way of automating all this, you know, software engineering toil if you wish? And many of them said yes. And in fact, they said we’re very interested to work with you, right? We’re like, okay, if you’re interested, let’s start working together from day one. So that gave us the ability to validate and iterate very very quickly. So we got to very high confidence of let’s say the problem market fit if you wish, you know, within like a matter of months. In fact, what happened is when we started the company, Mayang was my co-founder and I wanted to self-fund the company for a year and the reason for that is because we wanted ourselves to get to high confidence that this is an important problem and we can have a lot of impact and you know throughout this process I was explaining very quickly like in a matter of two three months we realized that you know the demand was more than we expected and you know our ability to deliver value very quickly was probably more likely than we thought. That’s what actually changed our perspective and we went to this what you call one shot approach where we raised $35 million. We actually did it with a lot of confidence that you know we were onto a big problem and we had like a good path of solving it well and also the market was big enough to support like a company that could raise $35 million and grow.
When you’re having these conversations with potential customers, what does the conversation look like? What are you actually asking them to figure out if they have this problem?
Yeah. First of all, it depends on the stage, right? But I, you know, before we started the company, I would go and say, okay, you know, in our own experience, this has been a big problem. Is it the problem for you? Maybe that starts the conversation but then you have the right to ask oh what else is a big problem for you right now right is it something adjacent to what I’m describing or you know something completely different that you know bothers you and you know another thing that I I learned over the years is that you know users and customers whether it’s an interview like the one I’m describing or they are already using the product they’re very good maybe at they know their pain for sure right and usually they try to articulate a solution the solution is mostly wrong But if you actually can like you know dig deeper you can uncover a real pain for which people will pay money for right and you know obviously this is very iterative process that gets you to an answer if you do it well in my opinion and then the other thing by the way I encourage people right we did well is you know when you start before you even have a product right you should have like something that is demoable right something that maybe people can even use because that gives you a much better sense very quickly if what you’re building is the right thing right I I actually the the thing I tell my team internally oftentimes as a joke is you know you first sell then you design then you build but there’s truth to it right like the more you can you know make this uh circle faster the more likely it is that you’re going to build a useful product.
Tactically when you’re selling to these founders, are you telling them you don’t have a product built but you’ll build them a custom solution?
Not like that right the way I would do it like if I’m early on say if I’m starting again right the way I would do it is first of all I would probably have a thesis I wouldn’t be completely open-ended right like our thesis in our case was that you know like running and maintaining and troubleshooting these large software systems is very painful and very very heavy on humans because the tools we have you know are uh you know don’t provide any intelligence basically right and all falls back on humans so we have that thesis right and then you know I would go and ask the question right is this true do you agree what else do you see right is there something that has even more value and then you know but once you start having I would say a product then the way I would do it is I would say okay here’s a demo of product is it something you would use? How would you describe this back to me even right like you try to get like if people understand first of all what it does and you know I think what you what happens is if you’re solving something very real you see that people get excited and they start to maybe almost sell it back to you why this is important.
What stage in the product lifecycle were you at when you reached out to VCs for the $35 million round?
First of all, like I guess I mean the game is a little unfair in that sense, right? Like if you’re a multi-time founder and you know especially if you have an exit had to exit it is a lot easier right now. This is for good reasons in my opinion, right? Like obviously there is more confidence that you know what you’re doing and you know maybe more confidence that you can scale a team and all of that, right? But you know in our case what happened is um we actually didn’t want to raise money like what I told you earlier. We wanted to run the company and self-fund it for a year to get like to lots of proof that it works and high confidence ourselves. What happened is I would say there were a few maybe smart investors that kind of had the similar thesis at the same time we did right because we’re talking now maybe almost a year a year a year and a half ago right but it was not yet obvious that agents are going to be the thing right but I think people who have thought about this problem a lot probably had developed their own independent thesis and what happened is a few of them including Greylock and Sam who ended up investing came to us and said we believe this is a big big problem we believe that your team maybe is the best team to solve So we’re interested in working with you, right? So to us it was a very straightforward approach especially because you know to me investors u ideal is not just money right it’s somebody you can work with right if they join your board you can brainstorm right and you can debate and you know you can convince them and they can convince you back about something so we felt that we found somebody that was you know a great partner and you then it became a discussion of okay what is the amount of money you need and the valuation right if you can agree, we would do it. So, we didn’t actually go out to pitch many investors, right? We had we knew what we wanted and once we got it, we just did it. And of course, then we had also a lot of great amazing angel investors that joined around who also helped us with advice with credibility with connections.
Were you initially planning to raise a smaller amount or did you calculate that you wanted $35 million?
You know we our view was that this is a very big market and we have to move relatively quickly right so we felt that you know kind of a pre-seed type of round would not help us much especially you know as experienced founders that could do some of the funding ourselves so our goal was to go more to like a real seed or a depending on how you think about it right now the round ended up becoming a little bit bigger than you know what was our threshold but you know we also tried to keep it within bounds right like we said okay probably we need to raise more $20 million to like move quickly, but also we didn’t want to go to like, you know, 50, right? So, we ended up actually at 35, which in retrospect, I think it was a very good amount because it gave us the confidence to execute, move quickly, and, you know, we still have most of the money.
What was your allocation thought process for splitting the funding between product, sales, and marketing?
You know, like I I actually tweeted this probably haven’t seen it like first time founders focus on uh product, second find second time founders focus on distribution, third time founders focus on memes. Oh, you know that’s a joke of course, but I think there’s some truth to that. you know if you have a great team right and you have a great product obviously distribution matters a lot but even awareness matters a lot right especially in AI like and I wouldn’t start there unless I I was very confident that what I’m building or what I have as a product is very valuable and useful but you know once you have that it honestly makes a difference if let’s say people are aware of what you’re building right and if the the company has a strong brand and the brand helps also you know to you know convince people to join you right So in in some sense maybe in AI everything is moving a lot faster and a lot of things that maybe came later in prior generations now come a little bit earlier. But if you do it right, you can you can you can achieve a lot more, right? Because if you spend two years building a product and then another year let’s say starting to sell it and then another year to build let’s say the you’ve market like in some sense in those four years or three years you spend a lot more money than you spend in a year and a half when you parallelize a lot of these things. Of course you have to time everything very well.
What was your go-to-market strategy after getting contracts with customers?
But by the way we we actually moved to production with customers before they were like paying us. We said like because our our goal and you know we’re honest with them was like listen we want to learn we want to provide more value back to you but also want to learn uh you know and as a founder I’ve done essentially you know I participated in every customer conversation almost right or every sale that has happened so far you know nothing that is unusual maybe from what you’ve seen elsewhere like very lots of founder sell founder sales but also the other thing maybe we did is once we got to confidence that you know this is an important problem and we can build a great product. We actually started adding people and go to market. Um you know I have a good friend his name is Jos we worked together in last company. Uh he has done sales and product. So we convinced him to join us a year ago way before we actually started selling.
What does the conversation look like when you’re trying to convince someone you’ve worked with before to join your new venture?
You know I think the hardest part of a startup in some sense is the first like six months to a year. Because you barely have a product. you maybe or maybe not don’t have money. uh you know it takes a lot of faith for people to jump in and do it and I think most people who are aspiring founders in my mind give up during that time and that’s what shows if you have what it takes right which is a lot of faith in yourself now if you have a lot of faith right this truly then you know it becomes like you know I had a lot of conviction right I could go to my friends and say I truly believe this is the best thing for you right it’s the best time for you to join and you know I didn’t do it to like just convince them I believed it it was the best thing for them and I actually try to to think that way right like when I’m trying to convince somebody to join us I try to think from their perspective right or I try to think from their side like am I truly doing the right thing for everyone else right and you know as a founder at the end of the day at some after you know a bunch of people have joined you and a bunch of customers decided to use your product the responsibility towards them is much bigger than you know kind of your own outcomes out of this so I think that way a lot.
Have you dealt with employees leaving to start their own companies after being inspired at your startup?
Not as much. Right. Like I would say yes in my first company we had folks who joined and left because maybe we didn’t have enough traction almost, right? Not so much because of inspiration. uh you know at Resolve in particular we’re now bit more than a year old we didn’t have to face that problem but also things have been going well right had a lot of traction team has been growing now you know maybe I’ll answer it in a different way I think that if you’re trying to build an enterprise company there is a lot of knowhow that you can gain if you work at the right company and even like a couple years of experience will probably make you a much better founder certainly in that space that doesn’t mean that you have to have it right many people became successful without that. But I just I think also that that helps a lot.
What’s your perspective on whether agents are going to replace software engineers?
So, you know, I’m as a four-time founder, I’m a I’m an optimist, of course. But you know I I first of all I think that you know in a way it’s true what people say that agents are obviously uh lowering the the bar or the floor and raising the ceiling. They allow us to do a lot more people to essentially participate maybe in technology and I think allow us to solve harder problems faster than we could in the past. My belief is that there is so much more technology and software that we can build to solve more problems that you know it’s not a question of is essentially software engineering as a profession going to go away because of agents. I think we’re going to have more people working in technology. It’s probably going to look very different than what it is today or what it was until recently. But I think the end result of this is I think us producing a lot more technology to the benefit of everybody, right? making problems that were very expensive or hard a lot cheaper or accessible to to the world and you know that’s going to benefit humanity in my opinion despite the trade-offs from here to there right like I think the end result is going to be much much better and our technology output is going to increase dramatically uh and you know I think that more people are going to work in technology right like being a software engineer is actually a great thing in my opinion right now it’s just that you have to adjust obviously how you do it.
Do you find yourself getting into philosophical debates with the team about AI’s impact?
I don’t no we do actually like we have like lunch and dinner every day and a lot of the conversations we have during those are less about business and more about like okay how does the future look like or you know something new and interesting that happened. um even even like our own perspective in some sense over the past year has changed, right? I think that obviously we believed we can solve this problem very well and we can do it in a way that we relieve humans from the toil and we can you know achieve better outcomes and create a lot of productivity but honestly uh I keep track of like things that surprise me over time and one of them is that I think we’re moving a lot faster and you know our agent is a lot more effective a lot more quickly than I even I expected.
Why do you think you’re making faster progress than expected with your AI agent?
I think that um you know in a way models improved quite fast like we’re kind of in an exponential curve of improvement right and maybe it’s hard to comprehend or visualize that when you’re in the earlier phases right or even today maybe it’s hard for us to predict what’s going to happen in 6 months but what I can tell you is looking back we made a lot more progress than what I expected a year ago.
Do you have a roadmap given how quickly things are changing in AI?
We don’t have a roadmap either what we do actually is that uh we do OKRs and we set like annual OKRs which are very like ambitious outcomes almost right it’s not like specific things we want to achieve it’s like you know how okay if we were to achieve like you know our most or solve the most difficult problems we’re facing right or you know scale a lot more how would it look like and that’s mostly for alignment and for you know setting up you know goals that everybody body can can kind of aim for. Then we do quarterly planning but even at the quarterly planning which is more realistic still we’re not trying to say okay let’s build this feature or let’s solve this particular problem. We’re saying okay what again great could could look like in a quarter and you know and what happens practically speaking is that you underestimate what you can do in a year and you always overestimate what you can do in a month or a quarter right but that’s healthy right because you always feel that you’re behind your goals for the quarter and then when you when you get to the end of the year and you look back at the goals you set you say wow like how did I do all of this so I think it’s it’s quite healthy.
How have you maintained your co-founder relationship through multiple companies and exits?
Uh first of all I completely agree with that right like sometimes as founders uh blame investors. You know it’s very rare that you’re going to see an investor doing something so disruptive to a company unless almost it’s absolutely necessary, right? It’s probably warranted if it happens. uh I think it’s founders themselves screwing up and it’s often times what you say right it’s founders you know disagreeing and not be not able to work with each other I think that’s much more common cause of like startup failure than it is investors so I know my young for 20 years actually we met in our first day in grad school so he grew up in India I grew up in Greece we show up in Illinois for at this international student orientation and somehow we sit next to each other so we met there now we didn’t start working together but you know I remember from like classes and he was my TA actually in computer architecture. I remember him being brilliant, right? So I ended up starting a company dropping out of my PhD to start a company with my adviser and two other students. Mayan was not one of them but I remembered how brilliant he was. So I tried many times to recruit him my first company and you know I never convinced him but after we got acquired that company got acquired by VMware in 2012 I think I finally was able to convince him maybe partially because didn’t feel as a huge risk but also partially I think his goal was to actually start a company right so he felt if you joined a group of people who have done this before maybe it’s the best place to be and then we worked together more or less since then and in 2018 we did omnition uh co-created with open telemetry which is a whole different thing an open source project that became quite successful and I think the reason for for the fact that we were able to work together and start now a second company is there’s a lot of trust there is a lot of trust in each other’s skills there is a lot of trust that both of us are aiming for the right thing um we have like a you know very strong alignment no we never go behind each other’s back for anything we always try to solve the problems it’s very very important you know even if we have some major disagreement it’s, you know, between the two of us to solve it and also we don’t step on each other, right? Like we trust that, you know, he’s the CTO, I’m the CEO. Obviously have opinions, but you know, we also, you know, we’re honest with ourselves that, you know, if you want to be the best CTO in the world, let’s say, and I want to be the best CEO, I can be for the company. And that helps quite a bit.
How has that co-founder dynamic changed through multiple companies and exits?
Uh, actually it’s the same. Um, actually when we sold our last company, I thought I won’t start another startup. Yes. I mean I said this every time by the way but the the reason is the startups are very hard right and especially if you’re the CEO or the founder it is extra hard because there’s nobody else to go complain to but you know after and I had a very interesting role at Splunk who acquired us I was the GM for for a big business but then I realized that you know I was trying my best but I was feeling like at the large organization you know my efforts had minimal impact right maybe after a year of effort you you kind of moved the ship a little but you know I kind of I was very intentional about going back and starting a company again and what I told myself is I will either do it with Mayang or if he’s doesn’t want to do it or he’s not available I’ll just do it on my own because I tr I truly think there is huge risk in terms of like working with as co-founder if if the fit and the match is not there.
What made your previous company Omnition work so well, leading to a nine-figure exit in just 18 months?
100 year and a half. Uh I I’ll tell you like not different from what we did here like uh we found a problem that was very painful and what omnition did by the way was that you know in 2018 most people started building uh applications uh assuming they were on the cloud. So we use Kubernetes and containers and microservices. So a lot more complexity and velocity right and traditional tools for monitoring and APM as we call it did not work at all right because they were designed for monolithic apps and you know we kind of discovered this pain through our own experiences so we had like a lot of confidence that it’s an important problem and then we had a lot of confidence in this process of working very closely with customers to solve real problems and innovate that way right so what happened is that very very quickly we ended up getting like you know big customers customers like Straa uh Shopify, uh, Roku, who trusted us and why did they trust us? Because we’re solving this specific problem much better than anyone else, right? I would say so it’s this process of being very customer oriented, you know, maybe, you know, believing in your own process or believing in the process in some sense, right? That if you keep doing that, you’ll get to a great outcome. And, you know, that resulted in us, like I said, having strong traction. And you know many of the companies that were bigger in that at the time approached us for an acquisition. Now our goal was not to sell the company. In fact because we had a lot of traction our default was not to do it. We went through multiple rounds of kind of offers in the end. The reason the reason that made us sell that company was that it it wasn’t clear to us there was a path to a big company. were solving an important problem, but it wasn’t clear or you know it was it seemed unlikely for us to be able to build a big company from the problem we started.
How does having a large exit change the way you think about risk and approach your lifestyle?
I mean, obviously, if you you have an exit or something like that, it kind of I I I don’t think for most people I know, right, who did it, myself included, or Mayang, I don’t think it changes your lifestyle. I mean, you are who you are. First of all, if you’re a founder, there must be something wrong with you most likely. It’s not like you’re going to fix it because you you had an exit. So, but it does make things easier, right? Like you can take more risk. you can, you know, be more selective. You know, maybe you can take time off if you’re working on a problem. Like, you know, I resigned from Splunk before I knew exactly what I want to do with in between resolve and uh splang and resolve. It makes things easier, right? Um, and you know, I think that one thing I would say maybe that is contrarian is that, you know, there’s this belief that, you know, if founders, you know, take an exit or something like that, you know, they’re doing the wrong thing. Actually I I think it’s [__] and I think the best way to create wealth especially if you take risk is to actually consider something like this right like if an opportunity of this nature comes and if it if it works for everybody right you shouldn’t also focus just on yourself then you know I don’t think we should be judging anybody who does it now if there’s a path for a much bigger thing you should always you should you all to yourself also right to actually think about that but uh also to me this says that not Every startup should be VC funded. There are many problems out there that you can solve very well that you can be very successful and you can have an exit at some point uh and without essentially you know putting your back against the wall right without you know having the only outcome be like a huge outcome that might be unlikely for what you’re building.
It’s rare to find founders who admit their company might not become a billion-dollar outcome. What created that sentiment for you?
You know I mean I don’t know if like I could put a number to to the outcome but in our case what happened is the problem we were solving at the time required basically if you go if you know approach if you explain technically it required us or required let’s say users to go and instrument their code for distributed tracing right that you know had a lot of friction in how a new user could be on boarded once you did it there was a lot of value but the pace at which you could move was limited by how fast people could do that So we felt that that would limit our growth and our ability to create you know a big company quickly and in the meantime there were other folks who were approaching let’s say observability differently that maybe allowed them to to create a bigger company much more quickly. So it’s not like it was an absolute no you not build a big company. It was more like the amount of risk and the amount of friction it exists made us think that you know there was a price for which you know it made more sense to to join a bigger company and do it there.
What AI tools are you using at Resolve that you didn’t have when building Omnition?
I mean everything right you know somebody was asking me CTO of a company was asking me you have metrics of productivity. I said we don’t have metrics of productivity but I can tell you this if we take the AI tools everybody will resign. So um you know obviously we we use resolve a lot like you know we use it for any type of task or question we have around production. We use it for every alert and incident even if it doesn’t fully work like for something we actually go and try to understand what what happened right so we’re the first users and we use it to improve the the product a lot and actually it’s very satisfying because me as a user of the product I can see how it gets better every week right so it’s it’s a it’s a it’s a great way to to assess of course we use coding tools uh and we used all of them right I think cursor wins here yeah lately um you know uh clo code is very popular in the we created did some one of our engines created like a a memory file that you know helps a lot but yeah some people use curs some people use copilot or combination of copilot and clot code um but we use AI everywhere else right like you know whether it’s something as generic as such or gemini or like specific tools we use in marketing or sales or anywhere else anywhere else.
How are you using AI with marketing and sales beyond just writing email copy?
So the I mean we we review contracts Don’t let your legal team hear that. You know like uh uh actually I do that right every time I receive a contract whether it’s a customer or a vendor. I’m not saying that’s the only thing we do but you know like okay what should I pay attention to here right but you know we we try to do you know obviously other things right like I I first of all I do believe that in sales and marketing especially like you know there is a lot of value in actually you know a human in the loop and a personal touch right so I don’t we’re not trying to go all the way to the other end right but you know we use it a lot to do research to understand maybe which customers could benefit more from our product because they use the tools that the agent knows how to use we use it to help our own team let’s say do their job faster and help them you know whether it’s content or whether it’s understanding who is the profile of a user uh but you know we don’t also I think there is a risk of becoming too impersonal also right.
With your background, how do you approach talent acquisition and hiring at Resolve?
I mean actually at a startup it’s always hard to recruit right and I think many founders say that they prioritize talent but you know I’ve been spending probably 70% of my time on this right and that’s the only way to do it now especially in this in AI right where things are moving so fast and where you’re dealing with very very hard problems like we do in AI for software engineering you know you need to have both a bit deep problem of the domain or the problem you’re solving but also pretty deep understanding of let’s say how models work and you how ai actually can be effective. So it takes like deep deep expertise in both to do it well. And you know what I observed is that we were able to recruit folks who come let’s say from research labs and from like deep research experience. And you know these folks would never work in an enterprise company before and I think the reason for that is you know AI is changing like how we work right like it’s not just a tool now that an engineer is going to use it’s actually something that you know does the work and that’s very interesting as a problem and it’s very impactful right so you see for the first time you know people who would in the past only work at the lab let’s say or at a consumer company joining maybe an enterprise company because the impact you can have is maybe even bigger than the consumer world Right? You know, obviously Chad GPT or similar tools are amazing, but you know, in the enterprise space, you can actually build something that does the work of a human or the 70% of it, right? And that’s hugely impactful and can happen today. And that also, first of all, to do that, you need amazing talent, but also amazing talent is interested in participating in something like this.
What does the onboarding process look like at Resolve?
You know another thing we did is that we spend a lot of time thinking about recruiting and thinking about you know the experience of people who join us. So because we’re still early, you know, we have obviously try to have documentation and tools and all of that. But the other thing we do that works very well, we usually assign a body to somebody and you know, we have like an onboarding plan for a week basically, right? Where each of the day they have kind of some sort of a goal and you know they have their body, they can ask any question, anything that blocks them to unblock, right? And I think the sooner you get to some win or you know understanding how everything works, the more confident you become and the easier the next few steps also become.
How do you convince AI research talent to join Resolve instead of places like OpenAI or Anthropic?
Yeah. So, first of all, it’s very hard because obviously you know all these are companies with a lot of interesting problems. They pay very well. But I think uh they’re also already bigger companies in some sense, right? So the amount of freedom and flexibility and work you’re going to do there is not necessarily at the same level as as a smaller startup like we are right you can have a lot more impact you can bet a lot more in yourself even right open AI is probably going to be successful despite any individual at this point right where somebody joining us can actually make a difference between you know the company making it or not and I think that’s very impactful and it’s very very kind of satisfying now it doesn’t mean everybody wants to do that but I think the types people who can go work at OpenAI have this ability, right? And maybe betting on themselves is very powerful. So I would say, you know, what convinces somebody to join us versus there’s bigger lab is that you know you can do potentially more interesting work, you move a lot faster and you can have a lot more impact.
Do you work with recruiters or how do you find potential candidates?
A lot of it is referrals from people recruited. uh and you know what I observed is obviously you know great people have great colleagues they worked with and you know that’s a strong signal but also the more you add like amazing people to the company the easier it becomes to also reach out to somebody they will look up who’s in the company and you know becomes a little easier we we have in-house recruiters and you know one of our first hires was a recruiter actually I I’m a huge believer in in doing that early I think many founders actually do it too late and then you know we trade it a lot in figuring out what is the right model and the right approach and the right experience for candidates and we’re way better today. I probably argue way better than most big companies actually and how we do it in both like the how to find the people who are great and how to ensure that you know they understand the impact they can have when they join us. We worked also with external recruiters but very very selectively.
Do you have a system for employee referrals or does it happen organically?
It happens organically. I think that it’s you know honestly the best way for that to happen is people join the company and they have fun and they feel like they it’s they made the right decision and it you know I I see that you know you don’t even have to do anything right. People really want their friends to join them because they feel like this is the right thing and they have a lot of fun.
What is your company culture like at Resolve?
Yeah. So, we’re in person where, you know, and that was a decision we made like before it was cool. It has become very cool in the last year. 100%. Uh, and for us, we made that decision because we ourselves felt like during COVID, you know, it wasn’t fun and, you know, we’re not productive, right? So, we wanted to go back to first of all, it was a very hard problem. So to us it meant that you know we have to have like high velocity and lots of context and you know easy collaboration right that these were the decisions uh it was definitely the right decision I think it is sometimes a bit polarizing about people some people want to work remotely but also maybe it helps right because there is another set of people that actually want to work in person certainly so we you know we don’t have specific hours right most people show up between let’s say 8 and 10 you know some people maybe go home people who have families go home let’s say at 600 people who you know a lot of people stay have dinner at the office it’s you know I I stay for dinner many days because it’s a good time also to have like just discussions right about not about work it’s intense but AI is intense in general because things change often there’s when you have a lot of traction you know there are many many problems you’re trying to solve in parallel um but also I think we try hard to let’s say not take ourselves too seriously right to also have fun and you know enjoy being in the I actually I enjoy it a lot, right? The huristic I use for myself is when I wake up in the morning, do I look forward to going to the office? And you know the answer here has always been yes.
When was the last time you didn’t look forward to going to work?
Not at resolve. But it was it was true before for sure.
From your experience, what is the main reason startups struggle or fail?
Okay, there are many reasons but if I approach this from a product perspective, I think often times uh people are almost not honest to themselves and maybe they try to do too many things at once like resolve is a very ambitious company right we’re building AI for software engineering and want to solve many of the problems that humans face in doing their job in that area right starting with a lot of the things that have toil but also we’re certain that the only way to do that and the only way to gain the right to actually do more things is are solving one problem very very well right and in our case we started by solving let’s say the problem of incidents and production issues that wake up people in the middle of the night we want to do a very good job of solving that well and relieving humans from the from the pain and but at the same time I think we’re building a platform if you wish that understands software end to end and can help with many other things but I think it’s also a trap if you think that or if you prematurely try to go into many other directions before you have solved one problem So that’s how we approach it and often times see let’s say companies that have some success to maybe broaden the scope too quickly and then you know not do anything great.
What would you want to accomplish in the next year to consider it a success?
Okay first I’ll start with uh that I would like to wake up every morning and you know be happy to go to work and then you know as a product and as a business. I hope that by then we would have solved you know this one problem we started with very very well would have a lot of happy users who I guess feel their life is better as a result and hopefully by then resolve would have expanded to solve additional problems and help you know engineers in in in more ways than what we started with.
Spiros Business Stats
Spiros has demonstrated exceptional success in building successful companies, with his latest venture Resolve raising an impressive $35 million in seed funding within just one year of operation. His previous company, Omnition, achieved a nine-figure exit in only 18 months, showcasing his ability to rapidly scale and sell companies. Resolve now employs 50 people and has already secured major customers including Stripe, Shopify, and Roku, demonstrating strong product-market fit in the competitive AI space.
- Raised $35 million in seed funding within first year
- Grew team to 50 employees in just 12 months
- Previous company (Omnition) achieved nine-figure exit in 18 months
- Secured major enterprise customers: Stripe, Shopify, Roku
- Four-time founder with multiple successful exits
| Metric | Value |
|---|---|
| Seed Funding Raised | $35,000,000 |
| Team Size | 50 employees |
| Previous Exit Value | Nine figures |
| Time to Previous Exit | 18 months |
| Major Customers | Stripe, Shopify, Roku |
Spiros Method
Spiros has developed a proven method for building successful companies that focuses on solving real problems for customers before building the full product. His approach emphasizes rapid validation through customer partnerships, maintaining strong co-founder relationships, and balancing ambitious vision with focused execution on solving one critical problem exceptionally well.
- Validate problems with potential customers before building
- Work with design partners from day one, even without a product
- Maintain strong trust and clear role boundaries with co-founders
- Focus on solving one problem exceptionally well before expanding
- Build awareness and brand early, especially in fast-moving markets like AI
Spiros Tools
At Resolve, Spiros leverages cutting-edge AI tools across all aspects of the business to accelerate development and improve productivity. He believes in using AI not just for coding but throughout the organization, from contract review to customer research, while maintaining a balance between automation and human touch.
- Resolve – Their own AI agent for incident management and production issues
- Cursor – Primary coding tool for development team
- Claude Code – Alternative coding assistant used by some team members
- Github Copilot – Used in combination with other AI coding tools
- ChatGPT & Gemini – General AI assistance across various departments
Key Notes
Throughout his entrepreneurial journey, Spiros has identified several critical factors that contribute to building successful companies. His experiences across multiple ventures have revealed patterns that separate thriving startups from those that struggle, providing valuable insights for aspiring entrepreneurs.
- Customer validation before product development significantly increases success odds
- Strong co-founder relationships built on trust and clear boundaries are essential
- Solving one problem exceptionally well is better than addressing many poorly
- Experienced founders can raise larger rounds faster due to established credibility
- Not every startup needs to pursue a billion-dollar outcome; strategic exits can be optimal
Get Started in Just 5 Steps
Building a successful company like Resolve doesn’t happen by accident. Based on Spiros’ proven track record, here are five essential steps any entrepreneur can follow to increase their chances of building and selling a successful company.
- Identify a painful problem through personal experience or extensive customer interviews
- Create a demo or prototype before writing significant code to validate interest
- Secure design partners who will work with you from day one, even without a finished product
- Focus intensely on solving one core problem exceptionally well before expanding
- Raise strategic funding based on proven traction and clear market opportunity
Conclusion
Spiros’ journey in building successful companies demonstrates the power of customer-focused development, strategic fundraising, and maintaining strong co-founder relationships. His ability to raise $35 million for Resolve within a year, following a nine-figure exit from his previous company, showcases a repeatable method for entrepreneurial success. By focusing on solving real problems for customers before building complete products and maintaining a balance between ambitious vision and focused execution, Spiros has developed a blueprint for building and selling companies that aspiring entrepreneurs can learn from and adapt to their own ventures.