Why a liberal arts background belongs in technology
Sannie Lee, a Lead Consultant Business Analyst at Thoughtworks with more than ten years of product management experience, has noticed a troubling pattern. Students and interns aiming for tech careers are increasingly choosing hyper-specialized tracks like “agile software development” or “software engineering management.” She argues this focus is misguided. Her own degree in international studies, with concentrations in film and German, had nothing ostensibly to do with technology — yet it prepared her for product management better than any narrow technical major could have.
Lee believes that the decline in liberal arts enrollment is a problem for the tech industry specifically. As generative AI accelerates changes in how we work, the adaptable, human-centered skills developed through a liberal arts education are becoming more valuable, not less.
Critical thinking grounded in evidence
Across history and literature courses, Lee learned one consistent lesson: never take information at face value. Analyzing Fritz Lang’s film M, for instance, required looking beyond the surface narrative of a serial killer to see its commentary on Nazism and the lingering trauma of World War I. The discipline of weighing primary sources against secondary ones, and corroborating facts, transferred directly to her product work.
Lee avoids relying solely on internal stakeholders who “think they know best.” She goes directly to users to understand their problems. In one case, user research revealed that people couldn’t interpret a graph her team was developing. When internal stakeholders praised the design, she checked the analytics and found supporting data that validated user complaints. The team scrapped the graph, saving development effort by not simply implementing what key stakeholders wanted.
With generative AI, this kind of scrutiny matters more than ever. Lee asks: Where is the AI getting its input? Can I trust the output? What data set is it based on, and could biases skew the answers? For developers using AI to write code, the same principle applies — you still have to assess whether the output is valid.
Communication equals influence
Expressing thoughts clearly is the natural counterpart to thinking critically. Lee sharpened her writing through countless university papers, culminating in bachelor’s and master’s theses. In tech, that ability to write concisely and persuasively is essential for aligning people who don’t share your depth of knowledge — whether they’re developers, designers, or stakeholders.
Speaking skills were equally honed through debate, presentations, and rapid-fire classroom discussion. Lee describes her daily work as the same exercise, only with “students” replaced by “stakeholders.”
Clear communication has two specific implications for generative AI. First, the quality of AI output depends entirely on how precisely you can ask for what you need. Second, strong writing skills help you evaluate the AI’s response — is it clear, understandable, and to the point?
Synthesizing across disciplines
A liberal arts education forces you to draw from history, politics, language, the arts, and literature into a cohesive whole. Lee understood film, her focus area, through the lens of each of those disciplines. Product management works the same way: it sits at the intersection of technology, business, and users, and requires bringing often-disparate concerns together into a unified strategy.
Understanding how business constraints impact technology, and vice versa, is a form of connecting dots that applies to software developers too. They must see how new technologies and current problems fit together, and how the direction of the software shapes the solution.
Adaptability over specialization
Lee is quick to acknowledge that a university degree isn’t the only path into product management or tech. But the trend toward extremely narrow majors worries her. Technologies and methodologies are transient — agility is popular now, but what comes next? Generative AI is already forcing teams to rethink how they work. Skills that can be adapted to new problems, rather than tied to a specific framework or role, are what sustain long-term success.
The liberal arts have weathered centuries of change for a reason. They produce people who can adapt to their times, a quality the tech industry cannot afford to overlook.
