I've been studying computer science for about two or three years and I'm currently doing a backend internship. Since AI tools are allowed at work, I've started depending on them for almost everything: I describe the task, accept the generated code, ask for explanations when I need to change something, and paste error messages back in for fixes. The work gets done, but I often don't understand the code deeply and wouldn't know how to begin if AI were unavailable.
I'm not opposed to using AI, but I want to rebuild my ability to reason through problems, read documentation, understand existing code, and write at least some programs independently. Should I return to the fundamentals, build small projects without AI, or focus on coding exercises? What's a good way to keep AI as a learning aid without letting it replace the learning process?
3 Answers
A project connected to a subject you want to understand can work better than doing random exercises. For example, implementing an emulator or another technically focused project forces you to read specifications, understand the underlying concepts, test your assumptions, and revise incorrect code. It will take longer, but you’ll retain much more.
Go back to books, language documentation, and basic theory, then apply each idea in a small program. When you get stuck, first form a hypothesis and try debugging it yourself. If you use AI afterward, ask a narrow conceptual question and make sure you can explain and reimplement the answer rather than merely accepting a patch.
The most direct fix is to spend regular time coding without AI. Pick a small project, start with a simple plan, and work through the design, implementation, bugs, and documentation yourself. It’s fine if the first attempts are slow or awkward—that struggle is where the skill develops.
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