Comment by unnouinceput
13 hours ago
No, it didn't. Or rather it did for run of the mill coder camp wanna be programmer. Like you sound you are one. For me it's the opposite. That's because I don't do run of the mill web pages, my work instead is very specific and the so called "AI" (which is actually just googling with extra spice on top, I don't think I'll see true AI in my lifetime) is too stupid to do it. So I have to break it down into several sessions giving only partial details (divide and conquer) otherwise will confabulate stupid code.
Before this "AI" I had to do the mundane tasks of boilerplate. Now I don't. That's a win for me. The grand thinking and the whole picture of the projects is still mine, and I keep trying to give it to "AI" from time to time, except each time it spits BS. Also it helps that as a freelancer my stuff gets used by my client directly in production (no manager above, that has a group leader, that has a CEO, that has client's IT department, that finally has the client as final user). That's another good feeling. Corporations with layers above layers are the soul sucking of programming joy. Freelancing allowed me to avoid that.
I'm curious: could you give me an example of code that AI can't help with?
I ask because I've worked across different domains: V8 bytecode optimizations, HPC at Sandia (differential equations on 50k nodes, adaptive mesh refinement heuristics), resource allocation and admission control for CI systems, custom network UDP network stack for mobile apps https://neumob.com/. In every case in my memory, the AI coding tools of today would have been useful.
You say your work is "very specific" and AI is "too stupid" for it. This just makes me very curious what does that look like concretely? What programming task exists that can't be decomposed into smaller problems?
My experience as an engineer is that I'm already just applying known solutions that researchers figured out. That's the job. Every problem I've encountered in my professional life was solvable - you decompose it, you research up an algorithm (or an approximation), you implement it. Sometimes the textbook says the math is "graduate-level" but you just... read it and it's tractable. You linearize, you approximate, you use penalty barrier methods. Not an theoretically optimal solution, but it gets the job done.
I don't see a structural difference between "turning JSON into pretty HTML" and using OR-tools to schedule workers for a department store. Both are decomposable problems. Both are solvable. The latter just has more domain jargon.
So I'm asking: what's the concrete example? What code would you write that's supposedly beyond this?
I frequently see this kind of comment in AI threads that there is more sophisticated kinds of AI proof programming out there.
Let me try to clarify another way. Are you claiming that say 50% of the total economic activity is beyond AI? or is some sort of niche role that only contributes 3% to GDP? Because its very different if this "difficult" job is everywhere or only in a few small locations.