There are still significant limitations, no amount of prompting will get current models to approach abstraction and architecture the way a person does. But I'm finding that these Gemini models are finally able to replace searches and stackoverflow for a lot of my day-to-day programming.
But I wonder when we'll be happy? Do we expect colleagues friends and family to be 100% laser-accurate 100% of the time? I'd wager we don't. Should we expect that from an artificial intelligence too?
You could say that when I use my spanner/wrench to tighten a nut it works 100% of the time, but as soon as I try to use a screwdriver it's terrible and full of problems and it can't even reliably so something as trivially easy as tighten a nut, even though a screwdriver works the same way by using torque to tighten a fastener.
Well that's because one tool is designed for one thing, and one is designed for another.
"AI"s are designed to be reliable; "AGI"s are designed to be intelligent; "LLM"s seem to be designed to make some qualities emerge.
> one tool is designed for one thing, and one is designed for another
The design of LLMs seems to be "let us see where the promise leads us". That is not really "design", i.e. "from need to solution".