The artist and the engineer
Why the future of GTME belongs to creative problem solvers
When Maria Kastani, an MBA student at the International University of Applied Sciences and a member of the Clay Club in Berlin, chose GTM Engineering as her MBA thesis topic, she unexpectedly produced what might be the first comprehensive academic study of the field.
Her 65-page thesis dives deep into GTM Engineering through 17 expert interviews, a real-world implementation at her company Parloa, and enough academic frameworks to make a business school professor smile. While most discussions about GTM Engineering happen in newsletters and LinkedIn posts, Maria did something completely different and brought rigorous, academic research methodology to the table. You can read Maria’s entire thesis below:
Read to the end for a short interview with Maria about the inspiration for her thesis where asked her about some of the challenges that come with researching an entirely new field and how she combined theoretical and practical analysis to create a first of its kind investigation into the world of GTME.
TL;DR
Creative thinking > tech stack: The best GTM Engineers aren't necessarily the most technical—creativity, systems thinking, and experimental mindset matter more than coding ability, especially as AI handles more technical heavy lifting.
Strategic function, not just tools: GTM Engineering isn't just "RevOps with better tools." GTMEs can “explore” new market approaches while RevOps "exploits" what works at scale.
Outbound didn't die, it just evolved: Traditional spray-and-pray outbound is dead, but targeted, context-aware outbound still works when matched to market size, company type, and channel saturation levels.
The skills debate: creativity over technical prowess
One of the most interesting findings from Maria's research pushes back on the assumption that GTM Engineers need to be deeply technical. Through her expert interviews, she discovered something exactly the opposite:
"13 out of 17 experts mentioned creativity as a core skill and highlighted the need to think out of the box in order to create innovative plays and improve processes."
What's particularly valuable about Maria's analysis is how she connects this to hiring strategy. She found that companies focusing on background and experience often miss candidates who have the right mindset but haven't followed traditional career paths. Maria identified what she calls the core skill triangle for potential GTMEs: creativity, continuous learning, and computational thinking. One expert told her about successful GTM Engineers "coming from completely different backgrounds, but they wanted to go into this space, they just sat down there, they started learning on mistakes, on successes... and they became successful."
This has real implications beyond just job descriptions. It suggests that the GTME talent pool is much larger than we might think, and includes people who haven't traditionally been in revenue roles but have the curiosity and systems thinking that can make a difference.
Patrick Spychalski from The Kiln put it bluntly in his interview: "the available tools are just catalysts for accelerating creative ideas but don't create creativity themselves."
We see this reflected in our experience. Tools like Clay are becoming more accessible, and AI is handling more of the technical heavy lifting. What separates good GTMEs from great ones isn't their ability to write complex formulas, but rather their ability to see systems, experiment quickly, and understand what actually motivates a potential customer.
Maria also found that traditional hiring approaches might actually be counterproductive for GTME teams. Alex Fine from Understory made that point in his interview that candidates with deep wells of experience can have unconscious biases about what motions they’re interested in exploring:
"Background can also end up being a hindrance. Because if you have all of these notions and concepts and ideas in your head about how things work and then you go into a role where it's completely experimental and you want to be trying new things, you might go into it with a bias."
This suggests that the best GTM Engineers might not be the ones with the most experience in sales or marketing; they might be the ones who can approach familiar problems with fresh eyes. That’s borne out by the interviews Maria did:
"Around half of the experts agree that a specific technical, sales or operational background is not necessary... most of our GTM Engineering team are actually not sales people or RevOps people."
Where does this role actually live?
It’s still an open question of where GTMEs should sit within an organization team. Maria's research found that there are several options that work, but there’s no single answer because GTMEs don’t operate in a silo.
"The dominant theme in this question was that the answer depends on the needs, size and structure of the company, and thus no universal solution exists."
Through her interviews, Maria found three main camps:
Most experts (9 out of 17) see GTME as living within RevOps, treating it as a specialized operations function. Others argue for placement in Growth teams, especially when the role is focused on pipeline generation. A smaller group advocates for standalone teams reporting directly to leadership.
Maria also found that the placement decision should actually be driven by where the biggest revenue generation opportunities exist in a company. The GTME Engineer School founder Matteo Tittarelli put it this way in an interview with Maria "Where is the biggest generation of revenue?... [What is] the most time consuming or repetitive task within the biggest opportunity levers?" Only after answering those questions does it make sense on where to place GTMEs within your org—and even then the answers can shift as a company grows and changes.
The nuance here is in understanding that GTMEs are a strategic resource rather than just another role to plug into an org chart. If your biggest growth constraint is top-of-funnel generation, maybe GTM Engineering belongs in Growth. If it's process inefficiency across the entire revenue organization, RevOps makes more sense.
Maria's research connects organizational placement to compensation and success metrics. A GTME generating pipeline probably should have some variable compensation tied to results. One focused on systems optimization? Maybe they earn a higher base salary with efficiency-based bonuses.
The debate around compensation revealed an interesting tension in the field. Some experts argued for commission-based pay because GTM Engineers directly impact revenue. Others pushed back, arguing that since GTM Engineers can't control deal closure, variable compensation based on closed deals would be unfair. As Patrick Spychalski told Maria:
"If I was a GTM Engineer, I'd be pretty upset if, like, the AEs couldn't get the thing across the finish line, and ultimately, if an AE gets a deal and they don't close it, that's like pretty much exclusively on them."
This compensation debate actually reveals something deeper about how the field is maturing. We're moving from "this person uses Clay" to more sophisticated thinking about how GTMEs create value and how that value should be measured and rewarded. As Maria says: "The GTM Engineer does not merely contribute to optimized processes, but is a strategic factor for the growth of an organisation.”
The RevOps vs. GTM Engineering question
The theoretical core of Maria's thesis tackles the question that's been going around the industry: Is GTM Engineering just RevOps with better tools?
Her research found the field split on this, but the arguments on both sides are illuminating. Those who see GTME as distinct from RevOps pointed to fundamental differences in focus and approach. "RevOps may have been involved in orchestrating it, but go-to-market engineering really sits at a strategic data layer," Maria writes.
The key distinction many experts made was speed and external focus. RevOps tends to be internally focused, working with internal stakeholders to optimize existing processes. GTM Engineering, they argued, is externally focused because it actually touches the market and iterates based on external feedback.
As GTME expert Pawel Nical explained it: "go-to-market engineers go directly to markets, so they are closer to that external layer. RevOps is closer to the internal layer."
Maria found another perspective from some experts who see the roles as naturally complementary rather than competitive. Our own Yash Tekriwal described it as the difference between "keep the plane flying" (RevOps) and "how we are constantly innovating to stay ahead of the market" (GTM Engineering).
This maps to what Maria calls the "explore vs. exploit" framework from organizational theory. RevOps exploits existing capabilities and scales what works. GTM Engineering explores new opportunities and experiments with novel approaches. When something works in exploration, it gets handed off to RevOps for exploitation at scale.
What's smart about this perspective is that it positions both functions as necessary. You need the stability and scale that RevOps provides, and you need the innovation and agility that GTM Engineering offers. It's not about replacement—it's about organizational ambidexterity.
The Clay reality check
Maria’s research found that Clay was a consistent presence in conversations about GTME. "14 out of 17 experts mentioned Clay and its AI agent as their favourite tool," she wrote.
Maria acknowledges this might be a bit skewed as many of her interviewees have Clay partnerships. But she took it upon herself to ask why Clay is so popular.
The experts she interviewed pointed to data democratization (access to expensive data sources without enterprise licenses), workflow consolidation (doing in one tool what used to require many), and AI integration through Claygent as key differentiators. Patrick Spychalski went so far as to say, "I honestly think [Clay] is the reason this role exists... Most people hiring for GTM Engineer roles are just hiring people who are good at Clay."
Maria's research suggests there's probably some truth to Patrick’s statement. Clay has both enabled and furthered GTME as a discipline. What's particularly interesting is how Maria frames this in terms of data democratization. Previously, the kind of sophisticated data operations that GTMEs perform required expensive enterprise licenses for multiple data sources, plus the technical skill to integrate them. Clay made these capabilities accessible to smaller teams and less technical users.
Maria also found that Clay's flexibility—what Pawel Nical compared to "LEGO blocks"—allows for the kind of creative experimentation that defines good GTM Engineering: "From LEGO blocks, you can build a rocket, can build a ship, you can build a plane. It does not predefine what you can do with it," Pawel told Maria.
Maria’s analysis of common workflows bears this out: automated CRM enrichment, LinkedIn engagement tracking, job scraping for market signals, automated commenting systems that improve connection request acceptance rates by 35-40%. These are processes that were either all done manually before tools like Clay existed.
The Clay dominance also reveals something about the maturity of the GTM Engineering field. When one tool is so central to a professional function, it suggests the field is still in its early stages. As the space matures, we'd expect to see more tool diversity and specialization.
Matteo Tittarelli made a point that connects to broader technology adoption cycles: "there's always like a curve of adoption and that leads more to saturation. But then eventually there is always a new innovation that reignites [it]." This suggests that we're in a natural evolution cycle. The current tools and approaches will become saturated, leading to new innovations and approaches. GTMEs, with their experimental mindset, are positioned to identify and capitalize on these cycles.
The outbound evolution: not dead, just different
Maria's thesis digs into a hot debate in GTM about whether traditional outbound is dead. Her research found unanimous agreement among experts that outbound isn't dead, but it has fundamentally changed. "The experts share a unanimous agreement that traditional outbound is not obsolete but has fundamentally changed to a few years ago and that poorly targeted approaches do not work anymore," she writes
GTM strategist and founder of Blueprint Jordan Crawford summed it up well: "What they really mean is you can't do yesterday's playbook today and expect the same results." Maria's research identified the specific factors that determine outbound effectiveness. It's about market context as well as personalization and volume, and merging them can create a huge difference for GTM teams.
Here are three other strategies Maria highlighted in her thesis:
Total Addressable Market size matters. If you have a large enough TAM, mass outbound can still work. If your TAM is small, you need surgical precision.
Company type matters. Generic personalization might work for small businesses but falls flat with Fortune 500 companies that get thousands of similar messages.
Channel saturation is real. The democratization of outbound tools has led to oversaturation, but this creates opportunities for those who can cut through the noise.
Looking forward: strategy over technical skills
Towards the end of her thesis, Maria looks at where GTME is headed. Her research suggests we're shifting toward a world where strategic thinking matters more than technical chops, something we hinted at earlier in this post. "Several experts suggested that as the available technology becomes more widespread and easier to use, the emphasis will shift into critical thinking and strategic skills," she wrote.
This tracks with what we see in other technology adoption cycles. As tools become more powerful and accessible, the competitive advantage shifts from having access to the technology to knowing how to apply it strategically. One expert told Maria: "The ultimate skill that will drive more return or more revenue to your company is not technical skill. It's 100% creative on your know-how."
But Maria's analysis identifies a particularly interesting prediction about the return of relationship-building. "As AI-driven outreach becomes indistinguishable from human outreach, sales is going to transform into a connection-based field, since no one is writing a $100,000 check without having a conversation with a person," she wrote.
This connects to what Maria calls the "High Tech/High Touch" theory, the idea that as technology becomes more prevalent, people increasingly value human experiences and relationships. The implication for GTMEs is significant. The current focus on automation and AI-driven processes might be a transitional phase. As these capabilities become commoditized, the competitive advantage will shift to those who can combine technological leverage with genuine relationship-building.
Maria also identifies an acceleration trend that has implications for how GTM Engineering roles will evolve: "companies that will be late in this will need to pay the price for that, for not being competitive." The speed of innovation and adoption is increasing, meaning GTM Engineers need to be able to experiment, learn, and adapt faster than ever.
The maturation of a field
As GTME matures from experimental practice to established function, we need more thinking like this. Maria's thesis provides a framework for understanding not just what GTMEs do, but why they matter and where the field is headed. It's rare to see academic rigor applied to an emerging field in business. Maria's work gives us something we didn't have before: a structured way to think about GTM Engineering that goes beyond tool tutorials and growth hacks.
Her research suggests that we're at an inflection point. The early adopters who jumped into GTM Engineering because they were excited about new tools are being joined by more strategic thinkers who see it as a competitive advantage. The field is developing its own body of knowledge, best practices, and experimental frameworks.
This evolution from craft to profession is natural and necessary. Maria's thesis provides a roadmap for that development.
Q&A with Maria Kastani
Clay: You wrote your master's thesis on GTM engineering and Clay specifically. How did that idea come about?
Maria: It started first as curiosity. I work in lead management in the growth team at Parloa, doing lead generation, data enrichment, prospecting, creating campaigns—all these tasks around the area. We were using manual processes that were time consuming, basically eating up resources and time that could be devoted to more important tasks.
Back in January, our VP of RevOps at the time was looking into GTM engineering and Clay. He gave me the idea and I decided to do my thesis on it to combine my university and work focus and provide some actionable value. The idea of looking into a new undiscovered field is much more interesting and rewarding than going over some traditional topic that has been discussed over and over again.
What were the unique challenges of researching such a new field?
You start with no proper academic peer-reviewed literature to reference. This exists for the more long-standing topic of go-to-market strategy and core principles, but not for GTM engineering. So the main source of knowledge has been industry articles, blogs, newsletters, and then the interviews that I did with GTM engineering experts, which was a core method of getting the most up-to-date insights, since those are the people that are shaping the field right now.
There's obviously no proper academic research on GTM engineering so far, which brought some obstacles. But I think this is also what makes the area more suitable for academic exploration, because it provides this opportunity to gain insights at an early stage while the field is growing so fast.
Did anything surprise you during your expert interviews?
From what I had read before, people were praising tech savviness a lot—writing that you have to code, you have to know Python and JavaScript and all these things. So framing the role as super technical and only accessible to people from backgrounds like computer science or data analysis.
But the majority of the experts framed it differently. They said the most important characteristics are systems thinking, creativity, this experimental mindset—and the technical skills you can learn. It's like tools, you can learn them. And coding, right now, is being replaced by all those AI coding tools. So it doesn't seem to be as important as I thought or as I read in the beginning.
What was the reaction to your thesis?
There was a great reaction to it. I got the best grade I could get. That was surprising, but I mean, it was a lot of work, and I really tried to put everything in it.
I had university professors with PhDs thanking me for my contribution, telling me how much they learned from me, how important it is that this field is now explored academically as a first step towards more research and discussion around it.
And then I decided to share it with the industry, and that also blew up. A lot of comments, appreciation, people asking to read it, opportunities opening up.
Were you expecting that level of response?
No, not at this level, but it's great.
Where do you see GTM engineering heading, and what's next for your research?
I identified a lot of areas for further research in the thesis. There could be a broader analysis across more organizations. My research was a mixed method approach, both qualitative and quantitative, but the quantitative practical part was a single case study based on my employer.
Further research could focus across different company sizes or industries and see how GTM engineering provides efficiency in different contexts and organizational structures. It would be super cool to have more long-term studies that track the evolution of the role over time and actually determine the impact over the years.
This is what will show GTM engineering isn't just data enrichment or outbound, but show the strategic value it brings and how Clay enables all the GTM teams to constantly innovate, break boundaries, and explore new possibilities again and again.
Maria’s full thesis includes detailed expert interviews, implementation frameworks, and extensive analysis. Her work represents the kind of structured thinking that will help GTM Engineering evolve from experimental practice to established discipline. We want to thank her for her time and for her incredible work exploring GTM engineering with an academic lens.
Agree - you don't have to originate from a technical background. Especially in our new world of AI. Historically, I've been a seller at high-growth companies and used Clay (in a couple of simple forms) at 2 companies. Then dove in deeper once I joined Clay as one of the first GTM Engineers.
Brilliant 👏 work and research, thanks to thought leadership.of clay team