alt Hacker NewsIt seems the author has misunderstood the point of the common narrative and has torn apart what’s essentially a strawman.
The degrees, the books, that’s not the supposedly easy part. That’s the HARD PART, and it’s actually the “what you build” thing. What you build is the code architecture, knowing how to conjure objects, methods, modules, lambdas out of thin air in a way that faithfully represents a real-world problem. Literally the shape of the resulting code. It’s not product or CS.
The easy part is supposed to be actually typing out the code, putting the methods together, remembering method names and syntax quirks.
I think a lot of the discourse around AI is imprecise, but you’ve done a good job of clarifying. AI is also changing the definition of some terms, so debates are happening where people use the same words, but mean very different things.
Some people say “coding” to mean the process of converting a well-defined plan (requirements, architecture, everything) into executable code. Others use “coding” to also include all the small decisions you make when writing code, like the abstractions you build and how you handle ambiguous requirements.
AI has decoupled “typing the code” from “making the decisions about what to type” because AI can generate code from very ambiguous prompts. So “coding was always the easy part” is meant to use the second definition and emphasize that you may be able to generate code, but having good decisions embedded in the code is still a difficult, unsolved problem with AI.
There are also different definitions of “what to build” with some people meaning the technical details, as you’ve called out, and others (I think especially more business/product roles) meaning the functional requirements of the system.