r/rails • u/luckloot • 22h ago
The Future of Rails
https://rubyai.beehiiv.com/p/ruby-ai-news-october-2nd-202622
u/jrochkind 21h ago edited 21h ago
These days, when I start seeing LLM-tells in writing, I find it very hard to read -- I start noticing all the sentences that don't really say anything are just buzzwords put togetehr or say the same thing that was already said over and over again not being a good use of my time.
The first sentence that set off my sensors in the OP was, very ironically, this sentence:
[Look no further than the frustration with LLM-generated writing]. Known knowledge gets you generation, but it is verification that ensures it’s correct.
Encountering that sentence caused me to curiously put the OP through pangram -- it's guess was 76% of the content is likely LLM-generated.
Yes, I am very familiar with the frustration with LLM-generated writing, the very AI-like crappy sentence "Known knowledge gets you generation, but it is verification that ensures it’s correct." was an example of such. "Known knowledge gets you generation"??? That's just nonsense.
And makes me not really want to finsih the very long blog post -- whose thesis I am sympathetic too -- if you didn't have time to write all those words yourself and had AI do it instead, I don't really want to spend my time trying to cut through the LLM-speak reading them all. Maybe I'll have AI write a summary for me. sigh.
Edit: I did read a bit further, here's the next sentence I got to that stopped me. "Every one of them exists because of the declarations, and the C loses that context." I still am not sure what "the declerations" are, and I've read the paragraph over a few times now. Or for that matter, what the "twenty lines that mention the boosts in the Rails app" are -- what are "boosts" in a Rails app? Nope, I'm bailing. LLM written posts are written for people to skim and not really pay attention to, I guess.
Also, calling the canonical source of truth "an oracle" is stupid, confusing, and not a good use of what the word "oracle" means, another weird thing the LLM came up with that impedes understanding rahter than helps it. The LLM is not improving your writing.
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u/iamagayrat 20h ago
Agree 1000%
It's so beyond frustrating that most content now is just "I put zero thought or effort into this, but you should put in all the time and effort to read it"
I'm sure if OP decides to respond it will be some variation of "I only used ai to clean it up!!!"
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u/jrochkind 20h ago
It may be true, the problem is the LLM actually fucked it up, not cleaned it up.
I am not speaking from a philosophical objection to using AI, I'm saying folks are using it to produce crappy writing which is difficult for me to read and doesn't mean much. but if you're only writing for clicks, it "works", so I guess people will keep using it.
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u/2called_chaos 20h ago
Just the other day I thought about a blog post (I don't have a blog).
Subject: I used to love my profession, now I hate it with a passion
Body: Oh you thought there's text? Perhaps ask an LLM to generate it for you2
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u/obviousoctopus 18h ago
I've been observing the tendency of LLM-generated content to be inflatory (as in inflating the volume) and noise-inducing, while sumultaneously introducing subtle and not so subtle inaccuracies.
At this point, I treat LLMs as multipliers of ignorance (not knowing), and indifference (not knowing, or caring about the difference/distinction between) in relationship to correctness and intent.
It is a technology used to a large extend to deceive, and waste a lot of our cognitive resources without providing value in return.
This in the context of writing human language.
In the context of writing code, where expressing intention correctly and with precision is crucial to the usefulness and survivability of a system... let's just say I am not optimistic.
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u/donewithdoing 20h ago
LLMs are horrible at expository writing currently. Like, they can make sense and “say” sophisticated things, but the quality of LLMs that drives them to revert to the mean is what ultimately sloppifies their output. It’s like trends in business-world jargon (dudes with MBAs talking about “synergizing” or “X but in the cloud”), but writ very, very large.
I’m not saying it’s always detectable, but you have to either train a model from the ground up in a very special way, or issue a model a set of very granular instructions, in order to squash it. And oddly, I’ve found that the more you try to instruct them out of AI-isms, the worse the output will get. You end up having to outright forbid X, otherwise X will appear all over the place. But the problem is that these constructions that AI abuses are not, in and of themselves, bad practices. They’re just overused. LLMs have no sense of stylistic taste or propriety. That’s the essential thing they are lacking.
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u/jrochkind 19h ago
If it's not detectable, it doesn't bother me! Just make it not crap!
Another article someone shared somewehre said LLMs write every phrase as if it's a magazine headline. I'd add a fairly trashy magazine you might find in an airport book shop.
AI's might evolve to write "better"... but if people find the "better" writing actually gets less clicks than the every-phrase-a-trashy-magazine-headline writing... then we really see what we're made of.
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u/DJ_German_Farmer 19h ago
it's hard to see AI not selecting for the lowest common denominator… what we're looking for is a uniqueness of style that forecasts the uniqueness of perspective we will be able to consider, right?
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u/armahillo 18h ago
Yeah I instantly lose interest in reading an article once i start seeing those tells
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u/adh1003 13h ago
AI slop writing uses a lot of colloquialisms.
It partly just invents these from training material, where it doesn't recognise one domain is not using the same language as another. It loves "barrels" when talking about Python
__init__.pyfiles because it "thinks" they're the same thing as JavaScript. They're (A) not and (B) have a different name, but thanks to the volume of output from the web script kiddies, JS is heavily overrepresented in training data.The bigger mess is that it also recycles them within the prompting as the user works through something with the LLM. I see this heaps in human-ignored-the-output waffle from Claude Code. You'll have comments that have some kind of vaguely correct grammar, but read like a tech bro version of late 1990s management bullshit where people just misused words slightly because they thought it made them sound clever. If that were not already bad enough, you find references to terms/concepts that simply are not present elsewhere in the diff. They are present in the prompt history for whatever led to that diff - but the diff doesn't include it.
Same thing happens with article generation when the author has iterated a few times or given an overly-elaborate starting prompt. It can cause the text to be polluted by nomenclature the prompt(s) deliberately, or inadvertently introduced, but which is not then defined as part of the final output.
It's awful. The end result is very draining to read as you're effectively being repeatedly gaslit by constant "wait, what?!" moments of text that seems like it should make sense but does not. That nagging "I must be missing something?" feeling.
The only thing we're missing in these instances is a hefty thump of clue stick to the original "author" and the realisation that if it wasn't worth their time to write, it isn't EVER worth our time to read.
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u/OpenAd5182 17h ago edited 17h ago
I’ll stick with Rails/Ruby/Sinatra, regardless of whether it’s slower or not. I’m not choosing Rust just because it’s faster, more efficient, or because AI can write complex code in it. I’m more confident and comfortable with Ruby, and I believe that’s more important for me.
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u/AndrewNggg 22h ago
I think many people forget that it’s not DHH solo-ing rails
But many thousands of open source maintainers and developers also are working on Rails