Quantitative finance went through a smaller version of this in the 2010s. The apprenticeship was building a Black-Scholes pricer from scratch, then a vol surface, then a calibration loop. Sweat problems that taught you what the math meant. Then libraries got good, platforms got good, and a junior could be productive without ever reeeeeally knowing how it worked. On some level yes the finer detailed knowledge is going to be lost because it gets locked in but in some ways we do get a "higher level api" to presumably solve more difficult problems.
I agree to some extent. I think that small aps, dashboards, service wrappers etc. you can vibe code.
But building software still requires domain knowledge, understanding data structures, architecture, which services to use. We probably have 2-5 years before thats fully automated.
Oh my god, I literally say this every day now. People think that just because its fast to generate a demo app using claude code that every production system can be built in a week. Generating code was never the bottleneck. It was deciding what to build. When you build an app using claude code, you are equal parts coder, designer, product owner, client, CEO of the universe. You make decisions lighting speed, iterate, and destroy anything you don't like at will. You can make strategic and tactical decisions at any frequency and point that you want to, without needing a bi-weekly board meeting to do it.
The bottleneck is always decision making and human review when multiple humans are involved. This is especially true when we are all trying to build agentic / llm based systems where the outcomes are highly varied and its impossible to write easy tests to automatically check quality or benchmark progress.
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