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.
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.
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.
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.
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.
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.
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.
I think there is a middle ground where you can absolutely build apps faster with the help of ai and still get maintainable code.
Just don’t let AI write a whole app in one shot. Or even whole features.
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.
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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.