GoKawiilOpen answers to a reader's letter.
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. "About a year ago I became fascinated by AI-assisted programming. Despite having no formal CS background, with LLMs I managed to build a fairly large TypeScript/JavaScript system involving APIs, PostgreSQL, LLM pipelines, research automation and multi-model workflows. At first it felt almost magical: AI seemed to collapse the distance between having an idea and being able to build it. "But now I'm trying to turn that system into a real production product, and I'm struggling. I fix one error with AI, then another appears, then another part behaves in a way I don't fully understand. After months of refactoring I had an uncomfortable realization: I may have built a system that is above my own level of understanding. When everything works, that gap is almost invisible. When it doesn't, it becomes very real. "Sometimes I genuinely don't know what to do next without asking another model. That made me wonder whether I spent a year building a product, or partly building the appearance of one: something sophisticated enough to work, but which I don't yet understand deeply enough to truly own. "I'm not anti-AI at all. I'm fascinated by these systems and want to work with them professionally. But I'm unsure what the right relationship with them should be."
Indeed, I'm not sure either, but before proceeding, I find it most transparent to reveal my position. I haven't yet decided on AI, but I lean toward disliking it, knowing full well that it may be unstoppable.
I do work and experiment with it, and it often impresses me. At other times, it frustrates me. It's usually when it impresses me the most that I resent it maximally.
When it's bad, it can be frustrating, but then at least I can absorb an ember of warmth in the illusion that what I've spent more than thirty years learning is still relevant. When it's at its best, I sometimes think: Where do I sign up for the Butlerian jihad?
My position on LLMs is only partly based on my own socio-economic status. I'm old enough, and have had enough success already, that all other things being equal, I can survive unemployment. I'm not sure, on the other hand, than any knowledge-based society can.
It may be that LLMs will take programmer jobs before they take other white-collar jobs. After all, programming may be a discipline where verification is easier than, say, insurance claims management. Still, if we reach a point of mass unemployment among knowledge workers, I'm not sure society as we know it will survive.
I usually don't talk much about my background as an economist, but in this context I find it relevant to mention. As an economist, I can't imagine that mass unemployment of 30-40% will not have a significant impact on the economy.
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