[hellisothers]

Counterpoint: I forget where I originally read this thought but consider compilers. At one point coding was writing assembly and now it’s generally not, sometimes some people still do it but it is far from the norm. Now, usually, you “write code” in an abstraction (possibly of an abstraction) and magic takes care of the rest.

While I imagine “make an app that does X” won’t be as useful as “if … else” there is a middle ground where you’re relinquishing much of the control you currently are trying to retain.

[al_borland]

As complexity in a program increases, getting to the level of detail of defining the if...else becomes important. Using plain English to define the business logic, and allowing AI to fill in the gaps, will likely lead to a lot of logic errors that go uncaught until there is a big problem.

For the AI to avoid this, I'd imagine it would need to be directed not to assume anything, and instead ask for clarification on each and every thing, until there is no more ambiguity about what is required. This would be a very long and tedious back and forth, where someone will want to delegate the task to someone else, and at that point, the person might as well write their own logic in certain areas. I've found myself effectively giving sudocode to the LLM to try to properly explain the logic that is needed.

[rafterydj]

I mean that's basically all high level programming languages are, right?

I would argue that as an industry we love high level programming languages, because they allow you to understand what you are writing, much easier than looking at assembly code. Excellent for the vast majority of needs.

But then people go right on and build complicated frameworks and libraries with those languages, and very quickly the complexity (albeit presented much better for reading) comes back into a project.

[skydhash]

Sometines you need the complexity because they make the problem simpler to solve. Especially if you have a bunch of them. Take something like a task runner, or a crude framework, or numpy… just be aware of the lower abstraction level to detect when it conflicts with the main problem.