AI is like a power tool. If you give a contractor a nail gun instead of a hammer he can build a house faster. If you give someone who has no idea how to build a house a nail gun they’ll just fail at building a house faster than if you only gave them a hammer and they’ll probably hurt themselves.
This is a very old discussion and argument, much older than the current AI push. You’re right to a degree but also that hasn’t stopped the rise of strong minds for software development. There will always be the curious and the lazy. The curious will always want to know how things work from the chain of events of a button click to the pixel shifts and logic gate flips to display code on a screen as well as run it. There will also always be the lazy unencumbered by such a desire for awareness who just want the magic box to do the thing.
How many software devs can write in assembly? Not many. Not much has changed if anything beyond the ability of the unaware to see their will come into creation. People couldn’t make realistic images and now they snap selfies with no barriers to entry. Does that make them a photographer or an artist? Not really.
There’s a ton of app builders out there that are basically some crypto scam wrapped around Claude (or whatever). There’s a lot of idiots pumping out code slop.
I think there could be some potential usecases for LLMs, but that’s not code generation (at least code that is not in the finished product), nor having it look up stuff in technical documentation.
Everyone is trying to chase the rational adaptation case. Everyone wants to 10x their projects, yet keep control over them, or at least 2x their productivity. But I’ve seen just as many people going insane from at least first trying to use it as a tool as vibe coders.
Code is probably one of the easiest things to verify, for that reason I struggle to see any other viable uses for LLMs tbh.
user: write code that correctly asserts what 1+1equals.
LLM: assert_eq!(1 + 1, 4);
LLM: hmmm, that crashed.
LLM: assert_eq!(1 + 1, 3);
LLM: hmmm, that also crashed, I must be doing something wrong, letmetry one more time.
LLM: assert_eq!(1 + 1, 2);
LLM: that worked!
LLM Response: assert_eq!(1 + 1, 2);
user: what does this sentence mean? "Buffalo buffalo Buffalo buffalo buffalo buffalo Buffalo buffalo"
LLM Response: This doesn't mean anything, or someone really likes buffalo's
I can always run the code to check, I still don’t know how that sentence makes sense.
It 100% can save cognitive load if used correctly. Knowing the limitations and restraints of your tools is true for every profession.
If you know what your llm can and can not do reliably you reduce the over head of verification to basically zero. While if you use it poorly you basically have to double your work load to fix things.
AI is like a power tool. If you give a contractor a nail gun instead of a hammer he can build a house faster. If you give someone who has no idea how to build a house a nail gun they’ll just fail at building a house faster than if you only gave them a hammer and they’ll probably hurt themselves.
…more like a nailgun that, more frequently than not, shoots backwards.
I can build my bosses app faster with ai, but I would never build any app I want to maintain with it. It’s too low quality code for my standards.
You can hit your thumb quite good with a hammer too.
Problem being that the majority of software engineers really don’t know how to build software well.
And are using AI as a tool to just accelerate their lack of engineering.
Could this not be said for IDEs with code awareness such as M$’s intellisense, among other tools that accelerate development speed?
What you are describing isn’t an AI problem, is people taking a two week bootcamp and calling themselves a software engineer.
This is a very old discussion and argument, much older than the current AI push. You’re right to a degree but also that hasn’t stopped the rise of strong minds for software development. There will always be the curious and the lazy. The curious will always want to know how things work from the chain of events of a button click to the pixel shifts and logic gate flips to display code on a screen as well as run it. There will also always be the lazy unencumbered by such a desire for awareness who just want the magic box to do the thing.
How many software devs can write in assembly? Not many. Not much has changed if anything beyond the ability of the unaware to see their will come into creation. People couldn’t make realistic images and now they snap selfies with no barriers to entry. Does that make them a photographer or an artist? Not really.
There’s a ton of app builders out there that are basically some crypto scam wrapped around Claude (or whatever). There’s a lot of idiots pumping out code slop.
I think there could be some potential usecases for LLMs, but that’s not code generation (at least code that is not in the finished product), nor having it look up stuff in technical documentation.
Everyone is trying to chase the rational adaptation case. Everyone wants to 10x their projects, yet keep control over them, or at least 2x their productivity. But I’ve seen just as many people going insane from at least first trying to use it as a tool as vibe coders.
Code is probably one of the easiest things to verify, for that reason I struggle to see any other viable uses for LLMs tbh.
user: write code that correctly asserts what 1+1 equals. LLM: assert_eq!(1 + 1, 4); LLM: hmmm, that crashed. LLM: assert_eq!(1 + 1, 3); LLM: hmmm, that also crashed, I must be doing something wrong, let me try one more time. LLM: assert_eq!(1 + 1, 2); LLM: that worked! LLM Response: assert_eq!(1 + 1, 2);user: what does this sentence mean? "Buffalo buffalo Buffalo buffalo buffalo buffalo Buffalo buffalo" LLM Response: This doesn't mean anything, or someone really likes buffalo'sI can always run the code to check, I still don’t know how that sentence makes sense.
That’s because it needs a semicolon:
Buffalo buffalo Buffalo buffalo; buffalo buffalo Buffalo buffalo.
Also it isn’t a very good sentence because you’ve said the same thing twice.
It should read:
Buffalo buffalo buffalo; Buffalo buffalo buffalo Buffalo buffalo.
Translation:
“Buffalo” is a place, a noun (more or less meaning bison), and a verb (to harass or bully). So what it means is:
Bison bully bison; Buffalo bison bully Buffalo bison.
hmmm, I just copied from Wikipedia as my primary source. That was the faux pas that was cool before AI.
deleted by creator
It 100% can save cognitive load if used correctly. Knowing the limitations and restraints of your tools is true for every profession.
If you know what your llm can and can not do reliably you reduce the over head of verification to basically zero. While if you use it poorly you basically have to double your work load to fix things.