Jake Roeland

So how should I lead into it, Ann?

Yeah. So my name is Jake Rowland. I'm one of the founders and CTO at Emporia Research. At Emporia Research, we help companies conduct customer, competitor, and general market intelligence.

Yeah, at Emporia, we help companies conduct customer, competitor, and general market research. So what that typically looks like is helping companies run focus groups, in-depth interviews, expert calls on the financial services side, as well as large-scale surveys all through our platform.

Yeah. Yeah, so, D'Amporia, our target customer base is primarily large research agencies, but as well as client-side researchers at brands specifically.

We started in 2021, actually kind of as a different business, and then pivoted in 2022 on the back of a competitor who filed their S1 to go public and some opportunities we saw in the OpEx spin within that business to make a more programmatic expert network or research services business.

Yeah, it's really difficult for brands and agencies to find B2B experts for their research, so that's primarily the need or problem that we solve. So, if you're looking... If you're a sales force, right, and you're looking for 500 CRM decision-makers that you want to track quarter over quarter to see how they think about your brand versus HubSpot versus HubSpot versus Challenger CRM brands, connecting and finding those people or that data for your survey is really challenging, and that's really the hole in the market that we solve directly.

Oh, 100%. Especially, I think anyone who has any sort of service element to their business, I mean, it's crazy now what you can do with even in the last couple months, things like Claude Cowork. In the last even couple days, Claude now can manipulate your system directly, similar to what OpenClaw, I think, popularized in the last couple of months. But, yeah, we get a lot of inbound RFQs requests from clients that are saying, "Hey, can you get us any, again, N equals 500 IT decision-makers in Europe?" And what happens today is our team, or in the past, our team would actually process that RFQ, right? Go into our platform, look at feasibility, get back to our client with a quote, and now we have an agent that's actually just able to fully process that request, build the project on our platform. So it's this cool new, in my opinion,

paradigm shift where you're sort of seeing services become the new SaaS because you can create these agentic workflows that really basically can turn services portions of your business into things that look like software multiples or software scale.

Yeah, historically, it's been our access to data. So that was the original kind of moat that we went in with. If you've ever used companies like ZoomInfo or Apollo or Clay, we buy all the same data as those companies. So you can think like basically a proxy for LinkedIn. Our platform sits on top of 800 million professional and firmographic records. So you can come in and filter on things like job title, management level, location data, and find really the granular level of expert that you need for your research engagement. So historically, that's been our moat. But looking forward, I think it's just we're going to be really early on the adoption curve of AI. So kind of like I mentioned before, anything that looks like service, turning it into an agentic flow. And I think being smart with understanding that now software is fairly commoditized, right? In my opinion, a lot of, well, one, it's really easy to compete on software businesses, but a lot of businesses are actually going to roll into foundational models. So things like Cowork or OpenAI with OpenClaw and NemoClaw. I think being smart about where the future is headed and constructing your business in a way that agents in foundational labs can interact directly with your infrastructure is something that we're really focused on over the next two and a half years.

Yeah, I have two primary things when I think about engineering. One, and some of this comes from my background at Amazon, bias for action. You need to move fast, especially in the age of AI. You know, it's quick and cheap to build software, but there is a first mover advantage.

So we want engineers who will move quickly and won't get stuck in ambiguity. I'd say the second thing, this has just always been my principle from hiring even in past jobs, just don't hire assholes.

It's always worked well when I've gone against that principle and hired a talented engineer or seller, whoever it might be, that kind of, you know, wasn't a cultural fit. Might work out for six months, but eventually 18 months, two years down the line, that always comes back to bite you in the ass.

That's such a great question. For us, it's, are you adapting new tools? Are you thinking about the future? Like, we have a marketing role open right now that a year ago, the skills and requirements for it would have looked, even maybe two years ago, so different than it does today. Like, we're basically looking for a marketer who's like a vibe coder with a good sense of taste, right? And I think historically, it would be,

as you think about your marketing toolkit,

you know, like, I'm going into Figma and you're still doing some of that, don't get me wrong. And like, there's this whole, like, arduous traditional design process versus today, I'm like, are you asking Claude, like, how we should build this? Can you vibe code this, you know, in HTML into our website in like a way that looks cool? Are you thinking about next gen deliverables instead of like a PowerPoint deck or something? Like, how can we make something interactive with our data? Right? Like, that's the future of, you know, where I think leading companies are headed when they think about hiring. Its roles are changing with these technologies. Like, are the people, one, are they leaning in?

Are they optimists about the technology? Can they understand and grok, like, where we're headed in the next three to five years? Because like we're on this crazy exponential growth curve. And are they leaning into the tools? And if they're not, I think they're getting left behind.

Yeah, it's a good question. I think we're still learning a bit. We're doing more like take home exercises, even for roles that are non-traditional engineering. So traditional engineering roles,

you know, you have a take home coding exercise, it's, you know, through Coder bite or whatever it might be. We're starting to adapt that more even for marketing for sellers. But for software engineering roles, I think it's changing as well. And it's something that we're adapting towards. It's like, yes, you want to have a foundational understanding of technology. But why shouldn't people be using, you know, AI coding assistance and interviews because that's what they're going to be doing on the job. It's like, can you use that effectively? I think that's a really important way of like reframing what the skill set is and what the hiring process looks like.

Yeah,

I think, again, it's move quickly,

optimize for culture, but then also be forward thinking. It's like this, the skills that helped you win five years ago aren't going to help you win five years in the future. So think about like what this role looks like in three to five years. And if it doesn't exist, that's also something to consider. Don't hire for a role that doesn't exist in three years, like, or maybe that's a temporary worker or something of that regard. But think about hire for what the role looks like in three years with the exponential growth curve that we're on.

Yeah, enterprise B2B. They're getting left behind. Like, I mean, if you look, it's almost like a joke. It's what's a running joke with like the kids. It's like, if you use OpenAI, you're a boomer now, right, instead of Claude. So it's just like, I think they saw that Anthropic was winning enterprise of B2B. And where revenue goes, growth goes. So it's like, if you think about your compute spend, probably 50% of it's on inference, 50% of it's on training. But if you don't have revenue, you know, catalyzing that, you can't train and build better models and you get left behind. So they're looking at revenue as a growth opportunity to build better models so that they don't get left behind. Or ideally, you reach a, you know, it's not just enterprise. You know, you have this data center of geniuses where we're solving some of the most challenging problems for humanity. But to fuel that, you got to have revenue and that's enterprise of B2B.

I think it's the moment in time that we're in, at least. It's not to say that that's getting left behind, but it what like what it's really good at, obviously, is like coding like coding. I'm less of an expert in like, I'd say like video gen and editing, etc. I think that's a big opportunity as well.

It's like where are the most dollars to be captured relative to like what is this good at today? And I think that's where it index is towards. And to start, that's that seems more like enterprise and B2B focus, which video I'd say like video editing, image generation, all that content creation falls within that. I think it's just a subset of it, probably less on the consumer creative side because there's just like less spin there, at least in this moment in time, it feels like.

I mean, they're just making room for different different capital expenditures. Like if you look at CapEx of all these companies, it's just massively growing and they have to allocate budget from elsewhere to put into that portion of CapEx that they're investing in AI. Like I've talked to friends that some of these even like Apple friends who are like, I can spend $500 plus a day on like Claude code. And you think about like the value of that. Now you're like, oh, shit, that's like up another person. So if you have another person operating tangentially to the one engineer that you've hired, like you've got to pull dollars from somewhere else. So I think one, they're just kind of restructuring around people that lean into what I said before, which is that are leaning into the tools and trying to cut roles that for better, for worse, you know, maybe there was an over hiring it post COVID. But like it fundamentally, they just had to pull dollars from somewhere and that's what they're doing.

Extensively, I'd say maybe we're we're almost too early on the adoption curve to some in some degree for our customer base. Like I talked to conferences, I talked to customers who are still like, I don't know what Claude is. And we're like day one, Claude releases the ability to access your system. We're aware of it. So the only thing I ever get concerned with there is like,

you can be too early or too early for your customers. How do you build in a way that eases your customers into kind of where the future is going while still managing for this moment in time and how they adopt onto your platform before everything potentially rolls into some of the foundational models or into some new interface that we don't even understand today? I don't know if I totally answered your question, but.

Yes, I think a lot of people who don't come from a product and engineering background will understand what product market fit means. Right. Fundamentally, where you're like, I've got this idea. I like why if you have the, you know, the skills, let's back it up. You have the skills as an engineer. Like a lot of people, I think historically come to me like, why would you build this? Like you could just build this tomorrow and like, wouldn't you be doing that in all of your free time? And I think, yes, like historically, I have done that as a software engineer to some degree. But you do put time and effort into something and people don't want it.

I think a lot more people will learn that an idea doesn't have that much value. It only has as much value as you put on it in your head. It matters like will people adopt onto it? How do you execute across that idea? All that will still be important. I think it'll be a lot easier to test ideas, but you still need to lean in and execute. And we probably will end up with like a lot of just like wasted compute on like really bullshit things. I know I've done that, unfortunately.

Yeah, I think just I think yes. But then I think that that's maybe the, you know, 80% is going to probably be that I do think we have now more capacity for like the world's greatest founders because the the bar for software creation or for business creation is like way lower, at least from testing an idea. So I think that's gonna be challenging for I mean, you're seeing it in the market now with like SaaS companies. You can build Salesforce in two weeks and actually like a better version of it more customized for your business use case. So you're gonna have a lot more competition from the best and the brightest who are now like I am testing and moving quickly on ideas. And I'm not scared about this, the price of software because it's that's now cheap. So there's these all these like large incumbents who had this software moat that they built up over five, you know, 10, 20 years, you think about the dot com players that kind of emerged. And now that if I'm them, I'm scared. If you don't have a strong data mode or strong network mode, and you just have a software mode, people are going to come in and challenge and then just break things out vertically based on industry and build something more more competitive and fragmented and built to a use case of an industry.

I think what happens, like from a society standpoint, in the next 10 years is going to be really interesting. Like if you look at the AI companies by 2030, they're on track to spend trillions of dollars on compute. And if you look at the entire labor market, it's like 50 trillion, $50 trillion. So we're like an order of magnitude off from like what is being spent on AI from the entire labor market. So that they definitely believe that,

you know, these data centers of genius, like these data centers of geniuses are going to just replace the broader labor market and call it 10 years. So it's like what happens if we don't have systems in place that create a post labor society or have regulation that, you know, maybe forces employ. I don't know what it looks like, but, you know, when you have this kind of AI augmenting or replacing a lot of human labor, like what does society look like? And I think that that's like what scares me. Yeah.

Yeah, I think we can for the answer to separately for the company, we can build and test things a lot more cheaply. So things that you'd be like, this is a distraction. Or should we like we got to double down on our core business? Like, yes, we need to do that. But we can test new ideas,

kind of new marketplace or new product plays like pretty cheaply. So that that's cool.

I'd say broadly with AI and where things can go on the optimistic side, especially in like biotech, I think is really exciting.

I think we're going to cure a bunch of diseases in the next like 10 years, which is super exciting.

I'd say I'm definitely up to. And I think it's it's always I think it's good to be optimistic. So I say I'm optimistic about what AI can accomplish in the next five to 10 years. I'm definitely again, we're like day zero people on the adoption curve. It's important to balance. It's like if you're at Adobe or you're at a large company, like it's important to balance with where customers where customers are at. And we talk about this a lot where customers are at versus like where day zero is at where San Francisco is at something like that where the labs are at. But at the same time, you don't want to put your head in the sand and be like, this isn't coming. I'm fine. Let me just double down on what I do today because I think if you do that, you're going to be in a like a world of hurt in five years.

Yeah. Yeah. If you want to really get a good idea of how AI is going to impact your business and your customers at Emporia research, we can help you understand that through competitive analysis, through survey work, focus groups, in depth interviews, AI moderated interviews. So we'd love to talk to you.