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rudolph9 | 4 months ago
I use AI on a day-to-day basis, and by my best estimates, I’m doing the work of three to four people as a result of AI — not because I necessarily write code faster, but because I cover more breadth (front end, back end, DevOps, security) and make better engineering decisions with a smaller team. I think the true value of AI, at least in the immediate future, lies in helping us solve common problems faster. Though it’s not yet independently doing much, the most relevant expression I can think of is: “Those who cannot do, teach.” And AI is definitely good at relaying existing knowledge.
spaceman_2020|4 months ago
At present rate, there is a good argument to be made that the economic value is teetering towards negative
A comment on a post or an article on the internet has value ONLY if there are real people at the other end of the screen reading it and getting influenced by it
But if you flood the internet with AI slop comments and articles, can you be 100% sure that all the current users of your app will stick around?
If there are no people to read your articles, your article has zero economic value
gnepon|4 months ago
Automation over teaching sounds terrible in the long run, but I could see why learning languages and skills could improve productivity. The "issue" might be here that there's more to gain in developing nations with poor education standards, and so while capital concentrates more to the US because they own the tech, geographical differences in labour productivity reduces.
rudolph9|4 months ago
buellerbueller|4 months ago
tclancy|4 months ago
osn9363739|4 months ago
rudolph9|4 months ago
Little things that historically would get me stuck as I switch between database work, front-end, and infrastructure are no longer impeding me, because the AI tools are so good at conveying the existing knowledge of each discipline. So now, with a flat org, things just get done — there’s no need for sprint masters, knowledge-sharing sessions, or waiting on PR reviews. More people means more coordination, which ultimately takes time. In some situations that’s unavoidable, but in software engineering, most of the patterns, tools, and practices are well established; it’s just a matter of using them effectively without making your head explode.
I think this relay of knowledge is especially evident when I can’t tell an AI comment from a human one in a technical discussion — a kind of modern Turing Test, or Imitation Game.