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The AI Slopologists strike again. More garbage by garbage people.
It will save people time reading the 5-10 other identical vacuous comments
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Yeah I kinda agree. The AI boosters have been super annoying for a while. I’m not anywhere close to an AI booster but I find value in it. I think we should think of it less like some intelligent being or “agent” and more as a code generation tool. It would both be more productive and healthier.
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It’s worthwhile to me under specific conditions, mainly that the codebase has existing patterns and abstractions that the LLM utilizes, and they’re actually good. It’s not a common case but I’m lucky that one of the codebases I’m in is one I built myself mostly by hand, and LLMs are really effective in it at the moment. My main concern is making sure the generated code maintains the high standard, but it’s definitely…
I’ve reached a similar conclusion, but there’s a part that worries me: the expertise that allows us to judge AI’s output was itself built by doing the work we’re now delegating. So there’s a risk that our judgement will decay over time. I’ve been thinking about the problem as choosing where we can afford to “borrow” comprehension, versus where we need to keep exercising it, and how to “claim back” the critical compre…
Also, somewhat amusingly, the “founder” consistently being at the top of the use curve might just have something to do with everyone else also using it, but that more implies people are using it because the chief at the top wants them to use it… not because it’s actually useful. A pattern that’s typical of bad AI deployments.
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That plus if you’ve ever stared at your code and then searched StackOverflow to see if you could find a better way of doing it, it’s like having that running continuously.
Yeah it’s great for prompting for improvements, granted you can actually judge the suggestions for yourself. They’re often slightly or majorly bad.
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In my experience? It used to be that one person had one to three codebases they knew intensely at my company. If you needed a bug in codebase X fixed, person Y was the one to do it and if they aren't available, person Z can do it, just not as quickly. Now every person on my team has to handle tickets for every single codebase. There are about two dozen different large codebases involved here. It's a ludicrous antipat…
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Writing code directly takes longer to warm up. Usually, I'd keep tens of thousands of lines in my head. In the past, I spent a lot of time designing error propagation and execution contexts. (Talented people might figure it out right away, but unfortunately I don't have that kind of talent.) So I'd have to think about things like Result and how far to propagate errors—and worry about whether my approach would conflic…
> But these days, AI just generates code following the existing patterns of the codebase Is this sarcasm?
The AI Slopologists strike again. More garbage by garbage people.
I might build a Chrome extension that looks for “AI” in HN submission titles and shows a fake comment at the start saying “AI is all slop garbage that’s total slop and I hate it. AI sucks and it’s slop!” It will save people time reading the 5-10 other identical vacuous comments
This looks like measuring what is easy to do, rather than what really matters. PR open counts, issues created , ceos/founders spending more time on linear don't automatically lead to better outcomes (in my experience they are often negatively correlated:-) )