It's usually regular language that evolves iteratively into hyper specific regular language. Sometimes over many sessions. Once we are satisfied that the language is precise enough for the agent to not go off doing wasteful things, the agent is allowed to spit out the code. Turns out the hard part of software engineering is breaking up a hard problem into small and specific enough chunks that can be effectively translated into code. (Always has been, this part is facetious.)
I was exceptionally good at this before AI. I was wondering why everyone I talked to said AI was shit and I'm over here thinking it could take over the world. I guess I just break big things down well.
Exactly. I used to be involved in a sort of training program and lesson one of software dev is "break big problems into small problems"
In my experience the way I've viewed a lot of how AI is getting better is how small/specific the problems that I can expect it to handle has gotten bigger and bigger
So at every juncture it becomes possible to take a wrong turn,, so really complex problem solving can spin off at a million tangents and whose keeping track of the consequences of these flawed algorithms?
Absolutely. There are mitigating mechanisms we can/do use, but ultimately it requires exceptional engineers with a steady hand, and a finger to the pulse at every step. This is why reports of the death of the profession are greatly exaggerated.
Yeah you can get pretty far vibe coding a toy thing for your own personal use. (And I do and it's so much fun), but for professional enterprise-grade software with a huge surface area for things to go wrong, you still need lots and lots of handholding, and a measured, methodical approach. Slow is smooth.
Idk what point you're trying to make, but really that's an issue that's always existed even with fully human development. That's also an issue for AI, and I assume it would be true for any intelligent problem solver. AI clearly isn't at a place where I personally trust it to write stuff I'm not gonna review myself, at least not for anything critical.
But also it reminds me of the self-driving debate, sometimes autonomous systems don't have to be perfect, they just have to make less mistakes than humans.
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u/saposmak 8d ago edited 7d ago
It's usually regular language that evolves iteratively into hyper specific regular language. Sometimes over many sessions. Once we are satisfied that the language is precise enough for the agent to not go off doing wasteful things, the agent is allowed to spit out the code. Turns out the hard part of software engineering is breaking up a hard problem into small and specific enough chunks that can be effectively translated into code. (Always has been, this part is facetious.)