What Studying Computing Taught Me About Thinking

I studied Computing and IT at The Open University. I finished with a First. And the most important thing I learned had nothing to do with code.

Abstraction Is a Superpower

The central skill of computing is abstraction — the ability to take a complex, messy reality and model it at the right level of simplicity to reason about it. A good data structure is not just a technical construct; it is an argument about what matters in a system and what can be safely ignored.

I use this constantly outside of software. When I am thinking through a business problem, I find myself asking: what is the simplest model that captures the essential dynamics here? What can I safely abstract away?

Algorithms Are Just Recipes for Thinking

An algorithm is a precise, finite, unambiguous set of instructions for solving a class of problem. The discipline of writing algorithms — truly precise, edge-case-considered, failure-mode-anticipated — trained me to think about problems in a way I never had before.

Now when I approach any complex situation, I find myself decomposing it. What is the input? What is the desired output? What are the steps? Where can this fail? What are the edge cases?

This is not a computer science thing. It is a clear thinking thing.

What I Wish I Had Known

The Open University route is not the traditional path, and when I started, I had doubts. Was this real? Would employers respect it?

The answer is yes — unambiguously. But more than that: the self-directed nature of distance learning taught me something that campus students often miss. No one is going to make you learn. Learning is a choice you make every day.

That lesson turned out to be more valuable than anything in the curriculum.