Man, these "hot takes" on the impact of AI are all becoming so tiring. I'm especially sick of all these "code was always the easy part" missives I see everywhere now, mostly because I think they're flat out wrong.
As another comment said, "easy can still be time consuming". I've seen plenty of projects that were well defined take months in implementation time (and then still sometimes fail for technical reasons). But most importantly, if "code were the easy part", why were top programmers receiving kingly wages for over 20 years? Because business people knew the difference between a successful tech company and an also-ran usually was, in huge part, due to the quality of their software engineers. If "code was the easy part", then you go write Google Maps in 2005, or Netflix streaming in 2007, or self driving cars in 2010, or, heck, ChatGPT in 2022.
Sure, good code for a bad product still fails, but this revisionist history trying to pretend coding was so easy, so LLM-assisted coding tools won't have a big impact, is nauseating.
Oh man, I was composing my own opinion, and I can see that Hacker News is brimming with opinions. But that’s perfectly fine, I believe. All the diverse perspectives that we engage in this intellectual sparring match is a positive thing, isn’t it? :)
Repeating this banality does not make it true. There were tons of tech companies over the past 30 years or so who, despite solving the same problems, lost out to competitors because they had worse programmers.
Easy can still be time consuming. I think trying to get an LLM to spit out the whole program is a flawed approach, but I understand why you'd want to be able to spitball 12 different data models quickly.
Man, these "hot takes" on the impact of AI are all becoming so tiring. I'm especially sick of all these "code was always the easy part" missives I see everywhere now, mostly because I think they're flat out wrong.
As another comment said, "easy can still be time consuming". I've seen plenty of projects that were well defined take months in implementation time (and then still sometimes fail for technical reasons). But most importantly, if "code were the easy part", why were top programmers receiving kingly wages for over 20 years? Because business people knew the difference between a successful tech company and an also-ran usually was, in huge part, due to the quality of their software engineers. If "code was the easy part", then you go write Google Maps in 2005, or Netflix streaming in 2007, or self driving cars in 2010, or, heck, ChatGPT in 2022.
Sure, good code for a bad product still fails, but this revisionist history trying to pretend coding was so easy, so LLM-assisted coding tools won't have a big impact, is nauseating.
Oh man, I was composing my own opinion, and I can see that Hacker News is brimming with opinions. But that’s perfectly fine, I believe. All the diverse perspectives that we engage in this intellectual sparring match is a positive thing, isn’t it? :)
But the code is the easy part. Solving the right problem is the hard part.
Repeating this banality does not make it true. There were tons of tech companies over the past 30 years or so who, despite solving the same problems, lost out to competitors because they had worse programmers.
Easy can still be time consuming. I think trying to get an LLM to spit out the whole program is a flawed approach, but I understand why you'd want to be able to spitball 12 different data models quickly.
https://notes.mtb.xyz/p/your-data-model-is-your-destiny