LLM Inflation
68 comments
·August 6, 2025djoldman
Aransentin
The 4-paragraph business case was useful for creating friction, which meant that if you couldn't be bothered to write 4 paragraphs you very likely didn't need the computer upgrade in the first place.
This might have been a genuinely useful system, something which broke down with the existence of LLMs.
MontyCarloHall
The only definitively non-renewable resource is time. Time is often spent like a currency, whose monetary instrument is some tangible proxy of how much time elapsed. Verbosity was an excellent proxy, at least prior to the advent of generative AI. As you said, the reason Bob needs to write 4 paragraphs to get a new PC is to prove that he spent the requisite time for a computer, and is thus serious about the request. It’s the same reason management consultants and investment bankers spend 80+ hours a week working on enormous slide decks that only ever get skimmed by their clients: it proves to the clients that the firm spent time on them, and is thus serious about the case/deal. It’s also the same reason a concise thank-you note “thanks for the invite! we had a blast!” or a concise condolence note “very sorry for your loss” get a lot less well-received than a couple verbose paragraphs on how great the event was or how much the deceased will be missed, even if all that extra verbiage confers absolutely nothing beyond the core sentiment. (The very best notes, of course, use their extra words to convey something personally meaningful beyond “thanks” or “sorry.”)
Gen-AI completely negates meaningless verbosity as a proxy of time spent. It will be interesting to see what emerges as a new proxy, since time-as-currency is extremely engrained into the fabric of human social interactions.
handoflixue
The problem is, I'm a verbose writer and can trivially churn out 4 paragraphs - another person is going to struggle. The friction is targeting the wrong area: this is a 15 minute break for me, and an hour long nightmare for my dyslexic co-worker.
Social media will give you a good idea what sort of person enjoys writing 4 paragraphs when something goes wrong; do you really want to incentivize that?
hdgvhicv
The broken thing here is that Bob, costing $10k a week, is after a new computer costing $100 a week.
kelipso
This part I always found funny. Significantly increase productivity of the team for a fraction of the price of employing them? Absolutely not.
ToucanLoucan
> In fact, one could say that the LLM is optimizing given the system requirement: it's a lot easier to get around this bad framework.
Sure, as long as we completely disregard the water, power and silicon wasted to accomplish this goal.
danielbln
This image originally came out just around the time of ChatGPT release and captures it well: https://i.imgur.com/RHGD9Tk.png
reginald78
The important part is the GDP is now increased because of the cost of energy and additional hardware needed expand and then compress the original data. Think of the economic growth all these new hassles provide!
null
nathan_compton
The older I get the more concise I find myself (which is not to say I'm actually concise, as my comment history will demonstrate), but LLM's have really driven home just how much noise day to day communication involves. So much filler text.
It still surprises me when I see non-technical enthusiasts get excited about LLMs drafting almost useless copy or email or whatever. So much garbage text no one reads but has to be written for some reason. Its weird.
unglaublich
An LLM is effectively a compressed model of its input data.
Inference is then the decompression stage where it generates text from the input prompt and the compressed model.
Now that compressing and decompressing texts is trivial with LLMs, we humans should focus - in business at least - on communicating only the core of what we want to say.
If the argument to get a new keyboard is: "i like it", then this should suffice, for inflated versions of this argument can be trivially generated.
AIPedant
What I hate about this is that often a novel and interesting idea truly needs extra space to define and illustrate itself, and by virtue of its novelty LLMs will have substantially more difficulty summarizing it correctly. But it sounds like we are heading to a medium-term where people cynically assume any long email must be LLM-generated fluff, and hence nothing is lost by asking for an LLM summary.
What a horrible technology.
danielbln
Not to be overly snide, but I can imagine that almost every person who writes long, tedious emails that wax on and on thinks they have something novel and interesting that truly needs extra space. Also, most novel things are composed of pedestrian things, which LLMs have no issue summarizing sufficiently.
Maybe you can provide an example where this case would occur, and maybe some indication how often you think this would occur.
onlyrealcuzzo
> If the argument to get a new keyboard is: "i like it", then this should suffice
This seems like exactly what LLMs are supposed to be good at, according to you, so why don't they just near-losslessly compress the data first, and then train on that?
Also, if they're so good at this, then why are their answers often long-winded and require so much skimming to get what I want?
I'm skeptical LLMs are accurately described as "near lossless de/compression engines".
If you change the temperature settings, they can get quite creative.
They are their algorithm, run on their inputs, which can be roughly described as a form of compression, but it's unlike the main forms of compression we think of - and it at least appears to have emergent decompression properties we aren't used to.
If you up the lossy-ness on a JPEG, you don't really end up with creative outputs. Maybe you do by coincidence, and maybe you only do with LLMs - but at much higher rates.
Whatever is happening does not seem to be what I think people typically associate with simple de/compression.
Theoretically, you can train an LLM on all of Physics, except a few things, and it could discover the missing pieces through reasoning.
Yeah, maybe a JPEG could, too, but the odds of that seem astronomically lower.
tomrod
The inverse of this is "AI Loopidity" where we burn cycles inflating then deflating information (in emails, say, or in AI code that blows up then gets reduced or summarized). This often also leads to weird comms outcomes, like saving a jpg at 85% a dozen times.
wood_spirit
And each cycle introducing error like a game of telephone
1980phipsi
Be more trivial
jdoliner
I saw an interesting argument recently that the reason you get this type of verbose language in corporate settings is that English lacks a formal tense. Apparently it's much less common in languages that have one. But in corporate English the verbosity is used as a signal that you took time to produce the text out of respect for the person you're communicating with.
This of course now gets weird with LLMs because I doubt it can last as a signal of respect for very long when it just means you fed some bullet points to ChatGPT.
adgjlsfhk1
Seems like an easy hypothesis to test: Do languages with a formal tense have short corporate language?
Ifkaluva
I’m a native Spanish speaker—all forms of written Spanish are more verbose than English, but the formal form is even more verbose. I remember notifications my school used to send my parents were hilariously wordy by English standards.
f1shy
I can speak 4 EU languages besides english. All 4 have special forms which are “formal” all 4 more verbose in the formal form. So if you ask me: “no”
jdoliner
This is what the argument I read claimed, I haven't verified it.
amelius
Perhaps we should judge the performance of an LLM by how well it can compress arbitrary information. A higher IQ would mean more compression, after all.
a_shovel
Which LLMs perform better or worse will be determined entirely by the scoring formula used and how it penalizes errors. It is not in the nature of an LLM to be capable of lossless compression.
optimalsolver
Lossily or losslessly?
amelius
Losslessly, because that's easier to test.
optimalsolver
When you're recalling a memory, do you remember the position of every blade of grass, or the exact angle of the Sun?
Humans, the only extant example of a general intelligence, don't do lossless compression at all.
I don't think you get to AGI by trying to compress noise.
santiagobasulto
> the load on my server is reduced
isn't this the opposite? Enabling compression will INCREASE the load on your server as you need more CPU to compress/decompress the data.
ltratt
As Koffiepoeder suggests, since the vast majority of content on my site is static, I only have to compress a file once when I build the site, no matter how many people later download it. [The small amount of dynamic content on my site isn't compressed, for the reason you suggest.]
have_faith
Depends on efficiency of compression I guess. If X bytes of data takes N time to transmit, and each slice of N takes Y CPU cycles during transmission, how many Y must your compression algorithm use, and how low must it lower N, in order to be more efficient from a CPU utilisation perspective? assumedly there's an inflection point from CPU use perspective, maybe a point that's impractical to achieve? I'm just vibe-thinking-out-loud.
Koffiepoeder
Or your server can cache the compressed content (since it is a static page anyway).
reactordev
It depends on where the bottleneck is. If it’s in network packet size, it would help serve more clients. At the expense of more CPU needed to decode/encode the data. If you’re serving large files and you have headroom in hardware it’s totally normal.
ModernMech
Not necessarily. For example you can pre-compress your files once, and then it'll be up to the clients to decompress on receipt.
roxolotl
My PM said they’d written a bunch of tickets for a project yesterday morning that we hadn’t fully scoped yet. I was pleasantly surprised because I can’t complain if they are going to get ahead of things and start scaffolding tickets.
Of course when I went to read them they were 100% slop. The funniest requirement were progress bars for actions that don’t have progress. The tickets were, even if you assume the requirements weren’t slop, at least 15 points a piece.
But ok maybe with all of these new tools we can respond by implementing these insane requirements. The real problem is what this article is discussing. Each ticket was also 500-700 words. Requirements that boil down to a single if statement were described in prose. While this is hilarious the problem is it makes them harder to understand.
I tried to explain this and they just said “ok fine rewrite them then”. Which I did in maybe 15min because there wasn’t actually much to write.
At this point I’m at a loss for how to even work with people that are so convinced these things will save time because they look at the volume of the output.
kasey_junk
Ask an llm for a project plan and they’ll happily throw dates around for each step, when they can’t possibly know how long it will take.
But project plan dates have always been fiction. Getting there faster is an efficiency win.
That said I’ve found that llms are good as interrogators. If used to guide a conversation, research background information and then be explicitly told to tersely outline the steps in something I’ve had very good results.
danielbln
The date/week estimations in plans are especially funny when you work with an agent and it spits that out. "Week 1, setting up the structure" - uh, no, we're going to do this in 10 minutes.
waynenilsen
The software requirements phase is becoming increasingly critical to the development lifecycle and that trend will continue. I have started writing very short tickets and having claude code inflate them, then I polish those. I often include negative prompts at this point so claude may have included "add a progress bar for xyz" and i simply add "do not" in front of those things that do not make sense. The results have been excellent.
dimitri-vs
The only acceptable response to obvious AI slop - unless it's it's clear it's been heavily reviewed and updated - is to put it back into the AI and ask it for a 1 paragraph summary and work off of that.
boxed
> Brevity is the soul of wit
Now that pachinko machines can create lots of prose, maybe it's time to finally learn this lesson.
thimabi
One of the things that makes me hopeful for the future of LLMs is precisely this: humans are needlessly verbose, and LLMs can cut through the crap.
I expect smaller models to become incrementally better at compressing what truly matters in terms of information. Books, reports, blog posts… all kinds of long-form content can be synthesized in just a few words or pages. It’s no wonder that even small LLMs can provide accurate results for many queries.
tharne
> humans are needlessly verbose
What a depressing belief. Human communication is about a whole lot more than just getting your point across as quickly and efficiently as possible.
thimabi
Oh, no, I do understand the value of long-form and deep human communication. I’m an avid book reader, for instance, and I actually prefer longer narratives.
What I don’t agree with is being needlessly verbose in circumstances in which the opposite is more valuable. Unfortunately, humans have a tendency to use flowery language even when that comes at the expense of message clarity.
Think, for example, of the countless self-help books that can be converted to short blog posts. Or think about legal or academic writing, which often stands in the way of readers actually understanding what is being said.
There’s so much writing like this out there that even LLMs were notorious for taking this over-elaborate language to a whole new level. And in my opinion that’s the kind of thing that we can (and should) avoid.
wood_spirit
You mean that language is a form or bureaucracy and gate keeping?
mapmeld
People are not reading and absorbing the longer pieces of writing. I worked at a company which would create information-dense, wordy PowerPoint slides for client updates, and at some point you see it has no point besides trying to impress. If we actually needed something in an email, they told us to put it in the first sentence.
I've also noticed it when people post LLM writing on Reddit. Something may give me pause, and then re-reading the content any given paragraph was way off. I had even glossed over the bolded conclusion "it’s a coaching-wheels moment" (?) because as you read it your brain thinks of a way it could make sense.
procaryote
Pretty often it should be about getting your point across as efficiently as possibly though, but people add fluff out of tradition or cultural norms.
nathan_compton
There are many, many, contexts where humans just pile text up for no real reason than to fill space.
tossandthrow
Where I work, I do the opposite: I let my colleagues know that they should write much mess and much more concise.
I actually straight up reject it when text is too inflated, and I remind people that LLMs are available to expand on request.
lelanthran
> Where I work, I do the opposite: I let my colleagues know that they should write much mess
Sounds like a fun place :-)
(yes, yes, I know it's a typo, I could not resist)
dspillett
This type of verbiage inflation was happening in business all the time anyway. LLMs are just being used as a method for doing it faster.
tovej
Was it? I don't remember ever running into anyone preferring long documents. Also, anything added by the LLM is pure noise with the possibility of a hallucination or two. If, for some reason, you might even add some relevant information at times, and you're not going to start making things up.
And if an LLM is also used at the other endpoint to parse the longer text, that creates a broken telephone. Congrats, your communication channel is now unreliable.
> Bob needs a new computer for his job.... In order to obtain a new work computer he has to create a 4 paragraph business case explaining why the new computer will improve his productivity.
> Bob’s manager receives 4 paragraphs of dense prose and realises from the first line that he’s going to have to read the whole thing carefully to work out what he’s being asked for and why. Instead, he copies the email into the LLM.... The 4 paragraphs are summarised as “The sender needs a new computer as his current one is old and slow and makes him unproductive.” The manager approves the request.
"LLM inflation" as a "bad" thing often reflects a "bad" system.
In the case described, the bad system is the expectation that one has to write, or is more likely to obtain a favorable result from writing, a 4 paragraph business case. Since Bob inflates his words to fill 4 paragraphs and the manager deflates them to summarise, it's clear that the 4 paragraph expectation/incentive is the "bad" thing here.
This phenomenon of assigning the cause of "bad" things to LLMs is pretty rife.
In fact, one could say that the LLM is optimizing given the system requirement: it's a lot easier to get around this bad framework.