Learning Programming in an Age of LLMs
A developer discusses the challenges of learning programming in the era of LLMs, noting that AI can help build complex systems that exceed the user's actual understanding. The piece explores the tension between using AI for productivity and the need for deep, foundational knowledge to maintain production-level software.
Why it matters
It addresses a growing concern in the software industry regarding the 'competence gap' created by over-reliance on AI-assisted coding tools.
A reader recently wrote me a long letter with lots of questions about learning programming in this age of LLMs. After a bit of back-and-forth, I got permission to quote extensively from the letter in order to attempt some answers in public.
None of my answers I consider particularly rigorous; the situation is so uncertain that I can only answer to the best of my abilities, but I don't claim them to hold any kind of immutable truth.
"I'm trying to understand how people who deeply understand software think about learning and competence in the age of AI. I'm approaching it almost as a historian would: asking people directly how they make sense of a technological transition while actually living through it.
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