Jake Aaron Villarreal: I'm Jake Aaron Villarreal, born and raised in Silicon Valley, and here to take you behind the scenes to share what it's like to be a startup founder, the journey they're on, the problems they face, and the products they build while they're transforming industries. I'm excited to have with us today Mike Palmer, who's the CEO of Sigma Computing, which recently closed a $200 million round in funding. Mike, welcome to the show.
Mike Palmer: It's great to be here. Thanks for reminding me of that, that it's finally over. But yes, we were able to close some funding.
Jake Aaron Villarreal: Great. Well, Mike is not the founder, but the CEO really driving innovation for Sigma, and excited to get into the story about not just where he came from, but also what he's doing there and where the company's headed. He has more than two decades of experience in the technology industry developing and delivering solutions for the enterprise and startups. As a former CMO, CPO, and GM across the enterprise technology landscape, Mike specializes in helping companies transform, grow, and scale innovation from idea to broad market success. There's a lot of value in Mike's experience and can't wait to tell you about it. Mike, before we get started here, where are you calling in from today?
Mike Palmer: We are in downtown San Francisco where we have almost an entire building, which is hard to imagine how fast that happened over these four years, on New Montgomery Street. Actually...
Jake Aaron Villarreal: Hundreds of AI startups are launching every month, battling to build their founding teams. As a leader, your job is to get results. When it comes to hiring, that's where it gets tough. So, you go out and you try a recruitment firm, but they don't understand your story. They're off target, and when they send you candidates, it's a waste of time. We believe you should never have your time wasted. That's why we launched Match Relevant, because your story is more than just an open role. It's your founder's journey, the problem you're solving, the product you're building, and why it matters. When we work with companies, we make sure we understand your whole story. So, we go out and do a search. We're on target, it's worth their time, they're interested, and more importantly, it's worth yours. And when it comes to hiring engineers, we work to make sure we get it right by deploying a team of seasoned CTOs that have built some of Silicon Valley's best companies. They can collaborate with you in the technical interviewing process. They can be a sounding board or they can run it for you. When it comes to building teams, there's no time to waste. Let's make it count. If you have a role that needs to be filled, book a time with a hiring guide at matchrelevant.com and learn how we do it.
Wow, that's great. I was just there yesterday on your street. I should have just called you. I didn't know that you were that close. I was there grabbing a cup of coffee with a company called Vouch, which uh big company right there on Montgomery. But um, anyway, thanks for um joining. Um before we talk about Sigma, give us a little bit more of a deep dive on your origin story and kind of how it all started. How did you get into technology and ultimately how did you end up at Sigma?
Mike Palmer: Wow. You know, it's funny when you uh when you've been in... when you work, when when working long enough, people start to ask you questions about how did you get there and what, you know, what advice do you have to get there? And I will uh be honest as I am with everybody else, which is I never had a plan. You know, I probably reacted reasonably well at times to some of the things that were changing around me. I worked really hard to get different experiences, as you kind of indicated when you introduced me. I've kind of run the gamut. I often consider myself a foreman. Uh if you're familiar with construction, you know, I've done a little electrical, done some plumbing, which is great because it gives you a perspective on kind of the challenges that everybody has in their jobs and maybe how to make them or help them work uh together a little bit better.
But I started off coming out of college, I'll give you a super brief history of time, how little I knew what I was going to be. I actually started working as a high school teacher for two years. I worked in Teach for America, if you're familiar with the program.
Jake Aaron Villarreal: Yeah.
Mike Palmer: I of all of my career experience, I tell folks that I probably learned the most in those two years. It's a very consolidated, high pressure way of learning how to present, learning how to get organized, learning how to show up on time. You know, kids are demanding. But ultimately, you know, started working in consulting at Andersen, went into the dot-com space way back when. We had one startup that went bankrupt, which was a big learning experience. Another one that I joined that we were able to to sell to Verizon. Spent a good 10 years at Verizon learning how to operate things at scale. Moved on to private equity software to growth software at Druva, which is still a great company going strong today, and ultimately landed here at Sigma four years ago, and time has really flown.
Jake Aaron Villarreal: Wow, that's great. Um, I crossed paths a little bit with Druva a while back where you guys were really scaling up, and it was a lot of fun to see not just the company have an idea that that you brought to market, but also the growth part of that. When you were at Druva, what was your role there?
Mike Palmer: I was the Chief Product Officer. You will get a big theme in this podcast, but also in general for me, on the importance of having a great product, being able to build a product that's going and living in a big industry with a lot of open-ended possibilities. I really enjoy the product-market fit part of the job. So, yeah, I was a Chief Product Officer there. I was coming from another Chief Product Officer role at Veritas before that. So, you know, have kind of a history in products that I've really, really enjoyed.
Jake Aaron Villarreal: It really does start with what problem you're trying to solve in a business and also what product are you building that is valuable enough for a company to want to pay for it. What problem are you solving today? Let's just get straight into it with Sigma.
Mike Palmer: It's a great question. And by the way, before I answer that, I'm going to add a little point of view on what your last statement was. And it's not just whether you're solving a customer problem. It often has to even be more than that. It has to be, is there something happening that's even encouraging a customer to rethink the way they are doing things? If they're not in the sort of mental place where they're open to other possibilities, even if you're solving a problem, you're starting from further behind in the sales process. You're starting from further behind in the sort of brand and the marketing awareness. So I think sometimes you have to have a great product solving a real problem, but also having a market around you that's prompting a customer to be ready to hear you in the first place.
Uh, so Opera... Sigma is solving a big problem for customers in the right market. Let's start with the market. The market started 15 years ago when customers made the shift to cloud computing. They were rethinking all the silos they had in their data centers, their compute silos, their storage silos. They were migrating for flexibility, for scale. Interestingly, one of the side benefits that they got that really uh generated the environment in which Sigma could become something was the declining price of storage. AWS had been tracking pretty significantly you know, over four or five years in a row, and I stopped keeping track where a price of storing a terabyte of storage was like negative 65% CAGR. Law of economics will tell you, right? If it's cheaper, you'll have a broader market. And so data volumes really started to pile up.
And now data was... there was a mathematician in the UK that said that data is the new oil. But people really couldn't access it. Oil is a raw resource, you have to refine it. And this... this is where products like Snowflake and Databricks came along and helped customers organize that data. But again, still kind of an infrastructure product, not really getting to an end user. So Sigma came around as the interface to take this enormous amount of data that is a raw resource and try to get it to people who make decisions in their jobs every day and really improve the velocity of that process, improve the granularity of that process, improve collaboration around that process. And that's what we do today for customers from the Fortune 10 down to the startup on Montgomery Street. Maybe not that particular one, but others.
Jake Aaron Villarreal: Well, it's that's that's... thanks for presenting it that way. You know, when a company starts and it's founder-led, you you understand where it starts and kind of how it's projecting. Sometimes there's opportunities where you're not the founder and you come into a company and you understand where it's at, but really to make it grow and scale, you have to have a different perspective, maybe more experience in different ways. Maybe it's the product side, maybe it's the marketing side. Um, give us a little bit of the detail behind why Sigma made sense for you and when you got there, what was the state of the business, and walk us through that a little bit, and then we'll talk about kind of where it's at today.
Mike Palmer: Well, I think Sigma made sense for me for a little bit of the reason I described about the market changes. Like I had been coming from the infrastructure side. I could see what was going on with data. It made absolute sense that after making, you know, 20 years of investment in significant infrastructure change that eventually the question would be asked, "Where's the productivity benefit?" And I think it was pretty clear that data was the opportunity to actually make productivity improvements, change business models. We can talk a little about that later. That, you know, Sigma was kind of just, just about to get there. So for me the the conditions were amazing.
And by the way, I'll just add on to the fact that we have two incredible co-founders in Rob Woollen and Jason Frantz who, from a deep technology basis to a platform development basis, which I think is an important emphasis here. Platforms ultimately are open-ended and create huge markets. To a set of board members who are legendary at this point, and in Sutter Hill. So Rob and Jason incubated Sigma alongside Snowflake, uh and Brad Gerstner at Altimeter, John McMahon having been a four-time CRO at major software companies, Scott Dietzen who was the CEO of Pure Storage... and like, it was a great learning opportunity in a great set of market conditions, uh, a product that had the right ideas, but just wasn't quite there yet.
And I think that was, when I joined Sigma, we were, we were looking at the right idea, but having to make some significant changes to the product itself. And in fact, two months after I joined, Rob, Jason, and I agreed, we just going to have to do a total rewrite. Which I think if you've been in the business as Rob and Jason had been for at that time six years, and you're going to burn it all down, which we did, and it's going to take a year to burn it all down and start from scratch with a new product in the market, it's really hard to do. But on the other hand, muddling along with incremental gains instead of doing the right thing and getting things to the point where you could have rapid growth based on a product that you rethink from scratch... That's a courageous but rewarding thing to do and and that's ultimately what's put us in the position that we're in today.
Jake Aaron Villarreal: Yeah, it's uh, it takes a lot of courage to do that and you place some bets, you hope you get it right. What was the product like before you made the change and what's it doing today that made... that was the breakthrough that unlocked the growth?
Mike Palmer: Great question. You know, if you're going to... Rob and Jason set out to not build a technology product for technologists. If you think about Silicon Valley's big winners over time, most of them have done just that. And they really wanted to reach out to, let's just say, just the average person, right? Wanted to build a product that was easy to use, that made a difference in their jobs, made their lives easier. And if you're going to do that, the number one thing you have to focus on is UX. It has to be simple. Has to be something that is commonly understood. And what they focused on was a spreadsheet, because there are a billion people that use spreadsheets in the world today. It's a very commonly accessible skill, right? I tell, I... if I ever want to have a layup question, I just ask, "Is there a spreadsheet on your laptop?" It's a 100% yes.
Jake Aaron Villarreal: Yeah.
Mike Palmer: So they got that right. Now. But where the product was on the other hand at that time was in effect three separate products. We had a dashboard. We had worksheets, and we had data sets. And you really had to stitch these things together in order to do something productive. And we knew that that was not going to get to the average user. We had to make something that was singular. We had to make something that was intuitive. And that was the basis that drove the decision to really uh press pause, no longer work on the former product, take all the learnings, roll it into something, and get simplicity right. And the breakthrough number one was really taking three separate components or modules, making them work seamlessly as one.
The second big thing that we did that still no one does today is fundamentally different than any other product in our category, which is on top of being able to read data, and we do this better than anyone because we do it at very, very large scale, hundreds of billions of records. We allow customers to write data into enterprise systems like Snowflake. And that was a second major, major breakthrough because it unlocked a whole set of new workflows for customers that they hadn't even thought of when they compared us to, let's say, legacy BI or analytics tools. So those were the two real big bets that we made that I think have paid off.
Jake Aaron Villarreal: When you talk about the customers that you're working with today, what are some of the brand consumer brand companies that the listeners would know about?
Mike Palmer: You know, you name the vertical, but we could... oil and gas companies like ExxonMobil, financial services companies like JP Morgan Chase, Bank of New York, Morgan Stanley. Manufacturing companies like Caterpillar, but you could also look at see... the ones that, you know, we really love working with at the at the other end of the spectrum. You know, the, you have the DoorDashes, the Lovepops, you know the, you know, we have 20-person startups as much as we have companies like ExxonMobil. And I think it's magical to have a product that resonates in terms of its usability, its scale, security, as much with a Fortune 10 company as it does with a 10-person company. So we we pride ourselves in the fact that we don't have a target vertical, that we don't have a target segment. You know, we really built a product for the average person who raises their hand when they say, when I ask, "Do you have a spreadsheet on your laptop?" Because that is how the vast majority of people get their work done today.
Jake Aaron Villarreal: Yeah, DoorDash is a company I love. I use it all the time and I know that they've had a great run during COVID and post-COVID and lots of data, lots of analysis of that data. I'm sure everyone has a spreadsheet there. But for the, you, for the listeners that are hearing this, if you're at DoorDash and you have a spreadsheet and say you're running sales or marketing or any type of group within the organization, what's your system going to do for them that have that spreadsheet, that have the data and how is it going to benefit them?
Mike Palmer: It's a great question. I think it actually starts with what DoorDash intended to do culturally when we started working with them. You know, what DoorDash does? We all love it. We all use it. Um what's interesting about DoorDash a few years ago was they really are strong believers in individuals controlling their destiny around data access. And what that meant for me at the time was regardless of your job, you needed to know how to write SQL. Problem with that is, first of all, SQL is relatively complicated for the everybody. Secondly, when you're working in a utility compute environment, which means you're paying for all of the compute that you're generating, that the less the efficient your SQL is, the longer it takes to run and the more it costs you. So, you have problems that start with hiring all the way through cost management.
And so, what DoorDash wanted to do was not relax when it comes to having the the every person at DoorDash have direct access to the data they need to do their jobs. They didn't want to have a heavy service overlay and that's a skills question, but they also wanted to have something that was going to reduce their costs over time and allow them to scale globally, which they have done since we started working with them through acquisition and otherwise. So, if you were to go to DoorDash today, whether you're in the marketing team or you in customer success and service, you're working with Sigma. If you are a, an entity that gets data from DoorDash, you get that data through Sigma. Uh, and we've created in effect the most, the level playing field. You don't have proprietary skills. You have the ability to access that data to make changes to the way that you view it with, you know, without a lot of overhead. And so I think we fit very neatly into a cultural directive they had before we were around. And frankly, working with them over these past few years is we've learned a ton and how to continue to perpetuate that culture as well.
Jake Aaron Villarreal: That's great. You know, when you have a product and you do a pivot and you're getting into different markets, it might be the same markets you're getting into just with a different message. Who is most interested in hearing your message when you go to market or you run a campaign or you're have a sales team that's out there pitching? Everyone's got spreadsheets. Who are you pitching to?
Mike Palmer: Great question. And it, and the message does... the message doesn't change, but the emphasis in the message may change depending on who the listener is. So, for example, if you're working in financial services, I say that all financial services businesses are data arbitrage businesses. That's 100% of what they do. They're trying to figure out, you know, "where where is something less that could be more, right?" And "I want to own that thing, whether it's interest rates or it's stock performance." And of course, within this context, you also have a very heavily regulated environment. So the two things that really help financial services customers are, can you give me really fast access to really granular data and can you do that by improving my security and governance posture?
And what Sigma does in terms of never extracting data from these core databases. We don't have caching. We don't have to pull anything into our proprietary layer. Means they have absolutely seamless adoption of their current audit, current permissions rules, their current RBAC schemes, everything. At the same time, we're allowing them to, because of skills, whether those skills are spreadsheet skills by the way, but they're Python skills, they could be SQL. We give them this multi-modal access. We allow them to be able to give access to to their employees, for example, to hundreds of billions of records and allow them to get to a single row in seconds. So their ability to go from the big picture to the needle in the haystack finding is very unique, unparalleled with another product. And for them this, you know, security and governance, large data sets down to really granular views is something that is super, super attractive.
But if you walk to a different company like a SaaS company, for example, what they're going to talk to you about is building a data product. What they want to do is share data that they have with external entities. So they look a lot at like, how do I build a data product in an embed and how do I make that the best possible experience? And again, Sigma not only allows customers to extend all of that, like, user flexibility—they're able to build analysis, they're able to manipulate it, they can build their own visualizations, they can do all the things that usually you had to go to an administer, an administrator for—we also allow them to collect data from that customer, which again is super unique. So in that world, what's resonating is interactivity with customers outside the four walls of their business. So, Sigma... and I could keep going, but you know, data is what you need it to be. Sigma is a platform that allows you to take advantage of how you want to get access to and share that data.
Jake Aaron Villarreal: Really interesting. So, if I understood that right, you're helping companies internally use their data and be able to use it as they want to and do analysis with it with an easy user interface, but also be able to take data from their customers if they have agreements and take that data and make that valuable data that they potentially then could launch new services, data services for, as well. So you're actually giving them not just a product they can internally use, but one they can actually build new revenue streams with.
Mike Palmer: That is exactly right. This was going to come back to the statement that we started the meeting with, which is if data was the new oil, but it was unrefined, right? I couldn't, I can't pull oil out of the ground and put it into my gas tank, right? Someone has to refine it for me and make it usable. Companies have done that internally with us. But what they've increasingly realized is their data is a unique view on the world. Someone else will get benefit from that. They just need to refine it. They need to present it. They need to give them secure access. They need to give them the ability to manipulate it so it's truly usable for the the the user on the other side. Uh and through Sigma, we're giving them that combination of interface, of security, of governance, but at the same time flexibility for that end user and even interactivity.
Jake Aaron Villarreal: God, that's, that's amazing. I ask you a question. You may have already touched on this a little bit, um, but I'm going to ask anyway. You know, as you look at data, um, and doing, you know, data democratization appears to be a cornerstone of your business uh philosophy and aiming to put data analytics into the hands of every employee, which I think is phenomenal. Um, how do you envision this democratization changing the way organizations operate, particularly in data-heavy industries like retail and healthcare?
Mike Palmer: I love this question because I do think that companies aren't even being as insightful, if you will, about what they should be doing in the future as as they could be today just given their access to data through Sigma. And so I'll start with this. I am a very firm believer that when you're building a company or growing a company, which hopefully every company in the world is focused on, velocity is the most important thing. And everywhere that you look in your business and you do not have maximum velocity is lack of growth. That's the result. And if you think about the cadence of like your normal job, you're showing up to a meeting. Someone's putting up a slide. The slide's got some static stuff in it. You have four questions. Can't ask the question of the slide. Someone takes an action item, they walk away, and then you have a meeting two weeks later. You know, culturally just turning that entire asynchronous process into a synchronous process of "I've come here without slides. I'm showing you data. If you have a question, I'm going to drill into it right here. I'm going to answer all the questions you have. We're going to come to a decision and we're going to execute leaving this meeting." A very simple change in terms of idea, but so powerful for getting companies to move at velocity.
Secondly is granularity. If you have that lab... you raised your hand earlier, that spreadsheet, you have a million row limitation on it. Our companies, our customers have tens of billions, if not hundreds of billions of records. So for you to use your spreadsheet, someone had to aggregate and aggregate and aggregate that data for you. It's lost all of its nuance. You're getting summaries of summaries and yet the magic is in the granularity. So the second thing to be thinking about is are we really creating the best decisions that we could based on the best possible data? And the answer in a, in a non-Sigma, non-large scale warehouse world is no way. You're just getting generic stuff. So I could keep going, but there are many areas, you know, in which every business being a data-driven business is making suboptimal decisions at suboptimal speeds.
Jake Aaron Villarreal: Yeah, fascinating. Um, you know, looking at the broader picture, including macroeconomics and tech predictions, how do you see the role of cloud analytics and tools like Sigma evolving to meet the needs of diverse VC audiences, especially when analyzing markets and performing due diligence?
Mike Palmer: That's funny that you say the due diligence part actually, because we started um, you started the meeting by mentioning our our D round and we presented all of our data to investors in Sigma. So they had to log in and we not only provided them all of our data, which just came out of our system. So we had very little work to do in order to produce a data room, but every update that we made was live. It sent an automated notification. So every investor could come into the product and they could actually build their own models in Sigma too. Which, by the way, as the provider of that data, it was a lot of fun because we have telemetry on everything they were doing. So, a very symbiotic benefit.
But you know, if I, if I'm sitting in the VC audience, I'm thinking a few things. You know, first of all, time to value. Cloud-based products are simple to deploy. If they're not, I'd question whether they're really cloud-based. But if I'm deploying a Snowflake or a Databricks or, you know, a competitor product and I'm putting Sigma on the top, I should be realizing benefit in hours. I should be doing that because architecturally it's simple to deploy and maybe far more importantly from a skills point of view, it's easy to adopt for for the people on the team. If I'm funding that company, I should be thinking I don't need as many overly serviced people because a lot of that work is now self-service-oriented. So we have less and less going into the support backend and more and more being done faster by the by the team on the ground. Those are just very simple changes.
But if you think further, I would be funding companies and if I'm building a company, I'm thinking constantly about where is my data valuable? Am I building a data product that is extending the reach of my service? That I think is something that almost all of the younger companies that we deal with are leaned in. And increasingly, even up to the Fortune 10 companies, are thinking about how do I expose that data for value externally? And sometimes it's to directly monetize. Sometimes it's just a better supplier relationship where for example in a supply chain, I can uh see what inventory is available more readily than I could if you sent me a spreadsheet. So I think some of those things are just ideas that are going to change the way and the pace and the cost at which businesses are run.
Jake Aaron Villarreal: Yeah, that's great. I'm going to ask you a question. Feel free not to answer it, but when you started, where was revenue? And three, three and a half years later, where is revenue?
Mike Palmer: When I started, it was less than a million dollars and we'll finish the year around 100 million.
Jake Aaron Villarreal: Wow, that's fascinating. It's also a testament to when you make a change, you never know where it's going to go, but it sounds like you guys are hitting on all cylinders when it comes to growth. Um, what's the biggest challenge you're facing today as you halfway through 2024 looking at 2025?
Mike Palmer: The biggest change that we're facing, I I'll be honest like I I I consider us extremely fortunate. I mentioned earlier I think the market matters as much as the product and I I actually think that we are really supported by tailwinds in terms of accelerating cloud deployments, accelerating cloud-based database deployments. I think the world wants more self-service. I think the, want the world wants more usage of data. We will continue to lean into that.
I think where we are trying to break out, if you will, of kind of the the analytics category and tack on a whole new TAM is in workflow. The interesting thing about analytics is that in of itself is an asynchronous process. I look for insights so I can do something, but the "do" is always somewhere else. And if you want to again focus on velocity, then you want to bring the analysis together with the action. And so our biggest changes in this coming year are a combination of a) finding faster insights, which of course at at some levels AI-driven, and then executing actions at the time the conditions change right inside of Sigma, and then Sigma interacting with the necessary external systems, which is a a category we call data apps. So we think that this closing of the loop of historical trends to forecast to conditions to actions is really the magic to generate productivity. That's where you're going to see Sigma evolving toward.
Jake Aaron Villarreal: Yeah, really cool. You know, you look at AI and it's impacting almost every industry, co-pilots for every sector, and there's this just flow of capital being invested into startups. I heard the number is something like 67,000 AI startups launched globally and have been in business and number is growing weekly. What's your play with AI? Is it already embedded in your technology? What's uh AI look like for you?
Mike Palmer: It's a great question. Actually, I'm going to change your question though to say what does AI look like to a customer, because I think that's ultimately what matters the most. So, we think about AI in two ways. Number one is back to that theme. How do I get better access to data and how do I draw the most accurate, trusted conclusions from that data? And we think AI has a big role to play there. So in terms of used in our product itself, we use AI to help customers understand complex visualizations and data sets. We do offer the ability, as a modality as I like to call it, you know, which is a natural language interface to ask questions when your question is a question answer style format. So we want to make sure that AI is there for an end user to be able to work within Sigma the most seamless way possible.
At the same time we need to think about AI in the same way metaphorically that we once should have thought of mobile phones you know, which is we like to tell the story inside of Sigma. If you were around at a time when the mobile phone came out and and really being adopted in let's call it the mid-1990s. It was magical. You did not have to be at home to make a phone call. This was fantastic. Right. And I I I have two daughters and if I call someone today, my daughters tell me I'm rude and I'm like some form of Luddite, right? Why don't I text them? You know, I was on the phone today. Uh water department showed up at my house and couldn't get in to to change the meter. I opened my garage through my phone. Everyone knows this story, right? We started off with a value proposition in wireless to replace a wired phone, and we ended up in a very different place because the technology itself was a platform to do things.
AI is the same. We are not going to be living in a world of co-pilots. Co-pilots were just a very quick and simple way to try to take this new thing called AI and apply it. Five years from now, that's not what we're going to be using AI for. And so where Sigma positions itself is we're an infrastructure interface between the inevitable changes in the back end. So for example, are we all going to be using ChatGPT? Probably not. Are we going to be using 20 LLMs that we might replace on a regular basis? Probably yes. How are we going to allow flexibility on the back end to swap out those models without disrupting our front end, which is our user? We don't want to have to introduce them to new tools. We don't want to have 70 different companies in our software portfolio. You know, we want the capability, but we don't want the disruption. We don't want the cost. We want the security. We want the integration. So, if you think about Sigma as an interface to your users, helping trust, uh providing them access points, collaboration, while you're getting flexibility on the the back end, this is where Sigma is going to add value to our enterprise customers adopting AI over the long term.
Jake Aaron Villarreal: Yeah. Well, well said. Yeah. We we're hearing a lot of different stories. One, one story we're hearing a lot of and you being in the in the position of a CEO is CEOs going to their team saying, "AI's here. What's our strategy? Who's going to lead it? Who's going to benefit by what we build and how long is it going to take to do it? Is it going to be profitable?" Every founder and every CEO of Fortune 500 companies are asking that to their engineering teams. So really the question is, if you have a strategy and you start to deploy it or you start working on it, you have to have the right people that are building it too. There's this idea about having a Chief AI leader in the company. What's your view on that?
Mike Palmer: I do have an an allergy, by the way, to to thinking that if you're going to do something new, you have to give it a Chief title. It's it's an easy answer for an executive to say "I'm doing something. I hired an executive to lead it." We started here, first of all, trialing AI to see if it would even benefit us. So, you know, we're doing that in our programming team actually using another portfolio company's product called Augment to to see if uh code completion, for example, was something that would work out and and create productivity for us. We started to put some value propositions into our product to see what would resonate with customers without trying to build a fancy AI organization.
And then, you know, we we like to say that in product you starve things into existence. You know, you you provide the minimum amount of resource, not the maximum, the minimum. And if someone likes it, if someone starts to use it, then you feed it. And I think where we are right now is we starved it and starved it through one of our co-founders and a and a couple of, coalition of the willing engineers. We learned some things. We failed at a bunch of things actually. And now we're feeding it. And I think whether we feed it and ultimately drive a much larger organization is something that we're still determining.
What I can tell you is anything that we do is not going to be focused on technology. It's going to be focused on product and it's going to be focused on customers. So we're always looking for that magic combination of what's possible in tech, but what's benefiting a customer, and you have to bring those two things together. So, I'm not uh overly concerned about demonstrating to anyone that I'm more leaned into AI than the, than the next company. I am very concerned about building something that changes our customers' lives tomorrow and then every day after that. And where AI plays a role, we're going to be invested in it.
Jake Aaron Villarreal: Yeah, I like that. Well, I really uh appreciate you taking the time here, Mike, and and and sharing the story about Sigma, but also your story and what you're building. I think the growth story tells itself, where you're headed, and the adoption rate is clearly there. So, excited to check in with you down the road and see how things continue to heat up and grow uh with your product and your company and just in general, the industry. Um, if anybody wants to find you or find your company, where do they go?
Mike Palmer: Go to sigmacomputing.com where we have a refreshed website. Hopefully they will like it. We have a lot of information there, but of course, you know, you can find us on our social platforms as well.
Jake Aaron Villarreal: Very cool. Well, my name is Jake Aaron Villarreal. I'm the host of the show and excited to uh continue this storytelling. Um can't wait to catch up with you all on the next episode. Signing off for now. Until then, take care. If you like what we're doing, don't forget to subscribe, leave a review on Apple Podcast or wherever you listen, and follow us on YouTube where we go behind the scenes to learn what it takes to be a startup founder.
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