Blog post written by current fellow Matthew Roxas, Class of 2026
What if a company completely ignored technical skills when hiring?
No coding assessments. No technical interviews. No requirement that you’ve studied marketing, finance, sales, engineering, etc.
Instead, when interviewing, they ask:
Can this person lead?
Can this person communicate?
Are they curious?
Are they humble?
Are they hungry?
Are they good with people?
For most companies, this would be an absolutely terrible hiring strategy. But what happens when technical skills become dramatically cheaper to acquire and apply?
Before answering that, I should probably explain why I’ve been thinking about this in the first place.
My bio goes into the winding version of how I got here, but the TL;DR is that I entered Purdue as a Computer Engineer, where I was able to build a strong technical foundation, doing everything from building a Convolutional Neural Network using only NumPy to implementing the game show Who Wants to Be a Millionaire? on an STM32 Nucleo board. Despite all of that, the most fulfilling experiences I had were those that involved applying that foundation through people, leadership, and consulting.
Currently, I work in Marketing Operations, which is definitely not the conventional engineering job where I expected my CompE degree to take me. Despite this, I’ve found myself regularly using the engineering principles I learned, whether translating user needs into technical requirements or designing a system for implementation. My engineering background hasn’t become irrelevant. Rather, it shapes how I approach and solve problems.
I originally thought this was just a personal epiphany as I finally figured out what kind of work I enjoyed. However, as I’ve watched AI become increasingly capable of helping me perform the technical work I spent years learning to do, I’ve started wondering whether there’s something broader happening here.
Since I started work at Valve+Meter Performance Marketing a couple of months ago, the two people I’ve learned from most have shown me even more extreme examples of the phenomenon I’ve experienced myself. My boss, Robert Calhoon, took a nontraditional path without a college degree and has worked his way up into a VP position. The other person is Tyler Lonergan, the Senior Data Analyst from whom I have received the most technical training. He comes from an undergraduate education in French and Francophone Studies, and carries aspects of that liberal-arts background into how he approaches storytelling with data. For all of us, our educational backgrounds have shaped how we think without confining us to the disciplines in which we learned to think.
The other commonality between us is that we extensively use AI to extend our technical capabilities beyond the areas in which we were formally trained. In the past, it was not uncommon for professionals to cross these disciplinary boundaries, but AI is dramatically lowering the barrier to doing so. Someone who doesn’t know SQL can now produce SQL. Someone who isn’t a software engineer can prototype software. Someone who isn’t a designer can create a passable design. Someone who isn’t a data analyst can interrogate a dataset. This does not, however, suddenly make them experts in those disciplines.
Historically, a lot of professional value came from the fact that “I know how to do something that you don’t know how to do.” AI increasingly shifts this toward: “We can both access the ability to do this. The question is whether I know when, why, and how it should be done.” This shift.is where “soft skills” begin to enter the picture. At the individual level, this places greater value on the ability to frame problems, navigate ambiguity, communicate across audiences, and exercise judgment. At the team level, it places greater value on understanding each other’s strengths and weaknesses and knowing how to bring different perspectives together.
All of this allows me to return to my original question with a slightly different framing: what if you selected people primarily for the qualities that aren’t captured by their technical credentials?
That’s essentially what the Orr Fellowship did with me, in addition to a lot of my peers. I had no idea how I was going to make the pivot from a traditional engineering path into the kind of interdisciplinary, people-oriented work I knew I wanted to pursue post-grad. By emphasizing the person beyond their accolades and technical prowess in the recruiting process, the fellowship is able to select for and create a community of hungry, humble, and people-smart young professionals. This allows partner companies to hire for potential beyond a candidate’s existing technical background, while giving new graduates access to fields their degree alone might never have led them toward.
The big draw for me when choosing to join Orr was the community. At Purdue, I was primarily surrounded by people with similar technical backgrounds but wildly different personalities. Orr has almost completely inverted that. We’re selected around a shared set of interpersonal and leadership characteristics, but come from wildly different technical backgrounds.
In a world where AI increasingly allows us to reach into one another’s technical disciplines, having that diversity of backgrounds becomes incredibly valuable. I’ve had some of my most interesting conversations in years with my fellow Fellows, and I’ve also been more productive with personal projects by utilizing the Orr community to both keep me accountable and learn new perspectives.
Communities like Orr become particularly interesting in the age of AI. While AI gives individuals greater abilities to cross technical boundaries, these communities provide direct access to the humans on the other side of those boundaries. The engineer can use AI to understand marketing, but also has a marketer in their community. The marketer can prototype something technical, but also knows engineers. Someone can explore entrepreneurship, design, finance, operations, whatever, while surrounded by people who actually inhabit those disciplines. AI provides access to capabilities and information. Community provides lived perspectives, judgment, accountability, relationships, and context.
Orr happened to become this community for me, and as much as the recruiting team probably wants me to, I’m not explicitly saying that everyone needs to move to Indianapolis and join Orr. My viewpoint is that as AI makes it easier to get work done across different domains, intentionally surrounding yourself with people whose backgrounds differ from your own becomes increasingly important.
That said, if you’re a graduating student interested in Indianapolis or Evansville, I could not recommend Orr more, and all it takes is your resume to apply here. If you’re not, I urge you to find your version of Orr, whether it’s another fellowship, interdisciplinary organization, professional community, or even just getting back together with old high school friends.
So, what if a company only hired for soft skills? I’m still not entirely convinced that I’d recommend it. But what if a community did?
