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183 points WolfOliver | 1 comments | | HN request time: 0.001s | source
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MorehouseJ09 ◴[] No.45067492[source]
“If it takes longer to explain to the system all the things you want to do and all the details of what you want to do, then all you have is just programming by another name,”

I think this is going to make the difference between junior and senior engineers even more drastic than it is today. It's really hard to know what/how to even describe real problems to these tools, and the people who invest the most in their tooling now, are going to be most successful. It's hard for someone who hasn't designed a large codebase already to do this in an ai native way where they don't have the experience of abstracting at the right level and things like that.

Today's equivalent, I've often found some of the best engineers I know have insane setups with nvim or emacs. They invest in their tool chain, and are now bringing AI into.

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roxolotl ◴[] No.45067904[source]
That quote really perfectly encapsulates the challenge with these tools. There is an assumption that inherently code is hard to write and so if you could code in natural language it would save time. But code isn’t actually that hard to write. Sure some people are genuinely bad at it just like I’m genuinely bad at drawing but a bit of practice and most people can be perfectly competent at it.

The hard part is the engineering. Understanding and breaking down the problem, and then actually solving it. If all we gain out of these tools is that we don’t have to write code by hand anymore they are moderately useful but they won’t really be a step change in software development speed.

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1. elcritch ◴[] No.45069751[source]
It's not too different in my opinion from the skills need to build complicated machinery like Boeing 747s despite how much Wallstreet and PHBs want to believe it's fungible. Having competent experienced engineers on the ground level watching these processes and constantly revising and adapting to everything from personnel, material, or vendor changes is so far irreplaceable.

Maybe if we get super AGI one day. Even then I suspect that from a thermodynamics perspective that might not be cost effective as you often need localized on site intelligence.

It's an interesting question but I bet humans combined with AI tooling will remain cost competitive for a long time barring leaps in say quantum compute. After all organic brains operate at the atomic level already and were honed in an extremely competitive environment for billions of years. The calories and resources required to create highly efficient massively powerful neural compute had incredibly thin resource "margins" with huge advantages for species to utilize.