Learning Lisp was a revelation. It opened my eyes to a way of thinking about code that was elegant, powerful, and fundamentally different from anything I’d encountered in my early computer science education. College taught me the theoretical underpinnings – data structures, algorithms, the abstract beauty of computation. Lisp took that abstract beauty and made it tangible, almost visceral. It felt like unlocking a secret level in programming, a deeper understanding of how software could be crafted. I dove deep, reveling in its macros, its homoiconicity, the sheer expressiveness that felt light years ahead of languages my peers were grappling with. I genuinely believed I had found the true path of a programmer. This, I thought, was real computer science.
The problem arose when I stepped out of the academic bubble and into the “real world” of software engineering. Suddenly, the theoretical purity and elegant abstractions that Lisp championed seemed… irrelevant. Enterprises weren’t clamoring for Lisp gurus to build their next web application or enterprise system. They needed engineers who understood Java, Python, JavaScript – languages optimized for industry workflows, ecosystems brimming with libraries and frameworks, and crucially, teams of developers already proficient in them. My deep dive into Lisp, while intellectually stimulating, had inadvertently steered me away from the practical skillset that the majority of the industry valued. Correctness, as emphasized in university, was still important, but now it was just one piece of a much larger puzzle. Testability, maintainability, deployability, monitorability – these were the new battlegrounds, and my Lisp-centric education hadn’t directly prepared me for them.
It wasn’t that my understanding of computer science fundamentals, honed by wrestling with Lisp’s concepts, was useless. Far from it. As the original article correctly points out, that foundational knowledge is incredibly valuable for long-term flexibility and adaptability. Picking up new languages and technologies became easier precisely because Lisp had forced me to think at a more fundamental level. However, the initial hurdle was significant. I was fluent in a language that, while respected in certain niches, was largely absent from the day-to-day realities of most software firms. The collaborative nature of industry projects, where code impacts not just grades but potentially thousands of other engineers and real-world economic consequences, was a stark contrast to the often-individualistic coding assignments in academia. My Lisp expertise, in isolation, felt like knowing advanced calculus when everyone else was focused on mastering spreadsheets.
Thankfully, like the author of the original piece, an internship became my saving grace. It forced me to confront the practical realities of software development, to learn the languages and tools that businesses actually used, and to appreciate the importance of those “-ilities” beyond just correctness. It was a humbling but ultimately transformative experience. Knowing Lisp hadn’t truly destroyed my career, but it had presented an unexpected detour. It highlighted the critical gap between the theoretical ideals of computer science and the pragmatic demands of the software industry. The deep understanding Lisp provided remains invaluable, a powerful tool in my mental toolbox. However, the journey taught me a crucial lesson: technical depth must be balanced with practical breadth, and sometimes, the most elegant path isn’t always the most employable one.
