By Sharon Cheng, Student in the M.S. Technology Management program
During my first semester, Professor Allan Chochinov's Practices in Design and Innovation course began with an unusual assignment: identify a personal pain point and generate one hundred solutions. The first ten came easily, but the more creative insights didn't emerge until around solution forty, when I had exhausted the obvious and had no choice but to think differently. That exercise became a blueprint for Columbia's M.S. in Technology Management program itself. Instead of rewarding speed or immediate answers, the multidisciplinary curriculum forced us to slow down. Classroom discussions often began with questions of feasibility until a professor redirected us to harder questions about what we were choosing to build—and why.
Before Columbia, I knew how to solve problems quickly but rarely questioned whether I was solving the right ones. After four years working in agencies and startups, momentum felt essential, and pausing felt like a luxury I couldn't afford. A problem worth solving was one with clarity, alignment, and a clear execution path. Through courses like Law for Technology, AI/ML for Technology Leaders, and Block Chain, Crypto and Web 3.0, I began questioning not only solutions but also the assumptions beneath them. Who benefits from this technology, and who bears the risk? What happens when efficiency comes at the cost of transparency?
But questioning assumptions in isolation only goes so far. Classroom discourse, peer feedback, and shared experimentation created space to test ideas openly. Site visits to Newlab and Google NYC, program residencies, and guest lectures grounded our discussions in real-world decision-making. Hearing founders, operators, and engineers speak candidly about uncertainty and failure reframed what it means to lead with curiosity and courage.
I carried that mindset into my Entrepreneurship Capstone. I interviewed twenty growth managers at early-stage SaaS companies and kept hearing the same frustration: they had hundreds of customer conversations but no efficient way to extract insights from them. Rather than treating that variation as confusion, I saw it as a signal worth understanding. I built Pulse, an AI platform that synthesizes customer feedback in minutes instead of weeks, turning what I'd learned about listening closely into a working tool.
Capstone sessions became working sessions in which my cohort challenged my framing, and Professor Katja Schroeder pushed me to clarify my business case. On demo day, we pitched to venture capitalists who didn't hold back. Watching my peers present solutions they had built from personal experience showed me what the program is truly about. The capstone evaluated not just our prototypes, but how we identified problems worth solving and reasoned our way toward solutions.
I'm leaving Columbia with the discipline to slow down, the curiosity to ask better questions, and the confidence to act with intention. Just as valuable is the cohort I leave with—people who challenged my thinking, celebrated my wins, and will continue solving problems alongside me. The work I do now starts with listening closely, collaborating thoughtfully, and taking responsibility for the systems I help shape.
About the Program
The Master of Science in Technology Management at Columbia University prepares graduates to lead digital transformation, and align technology and business strategy with an ethical lens. Through experiential learning, industry partnerships, and Columbia-supported research, students gain fluency in digital platforms and emerging technologies, and learn to design human-centered solutions that drive innovation and sustainable impact.
The program is available for part-time or full-time enrollment online or on campus in NYC. Learn more about the program here.
