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399 points nomdep | 1 comments | | HN request time: 0.211s | source
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waprin ◴[] No.44295040[source]
To some degree, traditional coding and AI coding are not the same thing, so it's not surprising that some people are better at one than the other. The author is basically saying that he's much better at coding than AI coding.

But it's important to realize that AI coding is itself a skill that you can develop. It's not just , pick the best tool and let it go. Managing prompts and managing context has a much higher skill ceiling than many people realize. You might prefer manual coding, but you might just be bad at AI coding and you might prefer it if you improved at it.

With that said, I'm still very skeptical of letting the AI drive the majority of the software work, despite meeting people who swear it works. I personally am currently preferring "let the AI do most of the grunt work but get good at managing it and shepherding the high level software design".

It's a tiny bit like drawing vs photography and if you look through that lens it's obvious that many drawers might not like photography.

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notnullorvoid ◴[] No.44295759[source]
Is it a skill worth learning though? How much does the output quality improve? How transferable is it across models and tools of today, and of the future?

From what I see of AI programming tools today, I highly doubt the skills developed are going to transfer to tools we'll see even a year from now.

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npilk ◴[] No.44298338[source]
Maybe this is yet another application of the bitter lesson. It's not worth learning complex processes for partnering with AI models, because any productivity gains will pale in comparison to the performance improvement from future generations.
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1. notnullorvoid ◴[] No.44299910[source]
Perhaps... Even if I'm being optimistic though there is a ceiling for just how much productivity can be gained. Natural language is much more lossy compared to programming languages, so you'll still need a lot of natural language input to get the desired output.