The part that astonishes me is that in the year of our common era two thousand twenty-six that it's not universally offensive and reviling to post an AI-generated response to another person.
If I'm reading something on the internet, I'm either reading it to learn, or I'm reading it to be persuaded. If I wanted the LLM to teach me (thank you, no), I would ask an LLM. I'm reading your website/newsletter/email because I want to hear from you.. If you can't be bothered to put your time into writing it and teaching me what you think, why should I be bothered to read it?
> The part that astonishes me is that in the year of our common era two thousand twenty-six that it's not universally offensive and reviling to post an AI-generated response to another person.
Because it wasn't pre-AI. It was normal for people to post links as arguments, counterarguments, etc. It annoyed me, and I didn't bother clicking most of them, and would occasionally tell them "If you can't bother articulating your thoughts, I can't be bothered with that link".
But I was always in the minority. If that behavior is acceptable to the masses, so is AI generated content.
(And, BTW, the "link as argument" bugs me a lot more than AI responses. If I know the person, I can assume the person has done some due diligence in reviewing the AI response before sending it to me.)
> If I wanted the LLM to teach me (thank you, no), I would ask an LLM. I'm reading your website/newsletter/email because I want to hear from you.
To play the devil's advocate: it's far from a given that had you asked the LLM it would have given you a comparable response to the one you got. You're precluding the possibility that the other party instructed the LLM to write what he intended to say.
It's like when you type a search in Google and get a wall of SEO spam.
I do feel like there is some middle ground where AI helps, but there's this one guy who keeps emailing everyone with walls of dumbass text and does not integrate or understand the feedback he gets when we are telling him what he needs to do. He just runs it though the LLM and replies and then forgets half of it in the next email engagement which functions as /clear on his end apparently. Like... dude I have ChatGPT and Claude, too. Actually read your goddamn emails.
I was going to say, the acceptance of bottom-of-the-barrel and subsequent capital investment in SEO as some industry-standard practice has pretty much lowered our standards for writing and comprehensibility across the board
it probably doesn't help that the US education system is so deeply broken with how rooted it is in segregation-era practices [0][1][2]. the average gets dragged down quite a bit when some districts receive so much money that they're flying their Spell Bowl teams to nationals and putting them up in hotels while another one a few miles away can't afford to pay for textbooks. average reading levels suffer and consequently so too does the effort that people put into writing well and reading critically
People are posting on this very website and commenting on Reddit using AI. I can't get myself into the headspace that would enable this behaviour. What exactly is the point of not engaging in conversation yourself and getting a bot to post it for you on an free platform. Crazy.
On reddit specifically, point of that would be karma farming. Compounding factor would be that vast majority doesn't care for either quality of the argument or for entire thing being sloppily dreamed up by a neural net.
Case in point: a repost of this AI-generated video:
There are comments from people engaging in earnest, with >15000 upvotes, and waaay, way down the comment tree, couple of people calling it out as blatant AI. With, like 5 upvotes.
I get the sense that people who spend all day interacting with software can start to see every interaction, especially in online text platforms, as a kind of API or user interface. You might learn to instrumentalize your interactions and relationships with people. Chatbots, including coding agents, only reinforce this kind of behavior, as they don't have the kind of limits of patience or of bodily or emotional needs that humans have.
I completely agree in principle, but to play devil's advocate, if an "author's" prompting technique is better than mine such that they generate a more useful article than what my own AI session might produce on average, then maybe there's value in some generated articles.
The above still implies some effort going into good prompting, however. I completely agree about the uselessness of "build me a castle; no bugs plz" style generated articles.
> that it's not universally offensive and reviling to post an AI-generated response to another person
There has even been an advert extoling the behaviour (I forget which phone OS brand it was for, which is a shame as I might like to try avoid buying anything from them): "if a friend asks a question and your phone can answer directly, shouldn't it?", to which my gut reaction is "absolutely fucking not, it shouldn't". My more considered reaction is pretty much exactly the same.
For a start I'd consider it rude and if I found out it was happening reduce my fucking my communication with that person, or call instead if messaging (unless it seems they have a fake them taking calls, no doubt that'll be a thing sooner rather than later). And quite frankly I will reply when I'm good and ready, thankyouverymuch, instant automated reactions plays far too much into the "always available" thing that I don't care for even without AI.
I look forward to future news stories where people with such features turned on suffer PII exfoliation or other hacks when someone finds a prompt injection hole, or just uses the feature as designed because the user has been too open with what they have given it access to and who it should respond to (perhaps by inaction, because the defaults will likely be wide open for "convenience" until there is uproar).
Me calling someone uncool would be rather hypocritical in afraid! I've done some interesting things, cool even, but that doesn't necessarily make conversation with me interesting/cool! I'll go with letting them know I find it dickish and perhaps even a tad offensive.
This is why even if I ask GPT or Claude or whatever to rewrite an email, I still rewrite it by hand with my own words, what I look for is, did the AI remove sentences where I repated myself or that were too wordy? Perfect, I'll ommit those details.
I went to a farm opening this weekend. A guy was there with fliers with about the barn renovation he completed, products they used, how the process went. 100% LLM output. How would you talk to your LLM about something like that? If he gave you that flier, would you scoff and trash it talking about how you can't be bothered to read it if he didn't write it? Or would you look it over?
> If he gave you that flier, would you scoff and trash it talking about how you can't be bothered to read it if he didn't write it? Or would you look it over?
Depends on his countenance and how good a mood I'm feeling in!
In any case I might well ask how much time went into at least reviewing the output. Or I say (rather than a flat AI;WR) "I'll scan that and have an AI summerise it for me later".
Yes, we get it. Laziness has always abounded in human endeavors. Despite the common social norms against it, there is a clear reason. Obviously, if you can get the same reward with less work it is a greater ROI. The incentive is pretty straightforward. In a mechanized world the incentives are even more aligned towards a kind of laziness given the capacity for automation to scale.
None of this is new. People who act like they were born yesterday at every instance in this parade of slop induced phenomena are more grating to me than the slop itself.
Just take your response. Reads as incredibly lazy to me. I've read pretty much the exact same sentence so many times by now. At a certain point, what distinguishes a mob of humans repeating each other from an LLM? Original, high quality commentary is exceedingly rare. Surely you must already know this. Of all the words written on the internet, most must be garbage. It was not LLMs that tipped this balance. In my experience, the average LLM actually speaks as a superior interlocutor to the average person online. It comes with the benefit that if you get a lame response, you probably deserve it for asking such a lame question.
Most humans are not worth reading. Sorry, but this should be obvious to anyone who has tried to research or investigate anything with significant rigor. People don't appreciate enough that many times when something comes up where the LLM is doing something "dumb" it is obviously because they are trained on a corpus authored by dumb humans. My favorite example of this is when people complained in a geopolitical simulation the LLM happily deployed a "tactical nuke" as if the phrase "tactical nuke" is not itself aptly described as a wholly human authored hallucination.
People are using LLMs at work or w/e to get back time from their corporate bosses that don't care about them. Not everyone has the luxury of being able to act like an enlightenment era university student. Most words published have to be akin to "we'd like to reach out to your about your car's extended warranty" anyway. Many blogs are more or less cover for the same, or at the very least indirectly subsidized by such commercial interests. If that is not offensive, frankly it's not clear why it would be more offensive to have an AI author it. It's mostly all pablum anyway.
No one who actually cares about a topic will use a LLM. The rest of them might as well, because it makes almost no difference. If you had a clearer model of this incentive structure you doubtlessly on the whole benefit from as a modern human typing on hackernews, instead of this knee-jerk reactive one ("universally offensive and reviling") you would learn to just move on and get over it. If you want more people to have the luxury of your enlightened discernment, you should probably celebrate LLMs automating away the majority of so-called "knowledge work" so that the economy, which has largely already solved for basic human needs, can achieve a state of hyper optimization, algorithmic foresight and UBI where none of us have to work and we can spend all our time in symposium with each other, given that is what you seem to desire for yourself and other humans. We will not get there if at every turn LLMs are demonized on these incessantly banal terms.
My coworkers continue to dump hundreds of lines of AI documentation in every PR and every other line of code has between one and ten lines of AI generated comments, talking about the real unlock and how things are byte for byte identical on the load bearing path or how the acceptance ladder is misleading.
Features are coming out and metrics are improving, but we’re basically in a post readability code base, with the occasional performative comment about a variable name.
I don’t really know how to address this situation or if it needs addressed. I certainly don’t read the long-winded AI comments or the AI documentation, but perhaps it’s useful for the AI on its next pass.
Have you considered talking about it? You're in a professional environment collectively working in a new way with a group of people. It's up to somebody to have opinions about what does and doesn't suck. If you silently go along and don't say anything you're dooming yourself and all of us to a lifetime of this garbage.
It's not the ocean, it's the poster's own team. A simple "AI comments suck" in a sprint retro would be trivially easy and would at least start the conversation.
I have five enforcement mechanisms: 1000 line max edit, PR comment character limits (get to the point of your description), ISO 24495 conformance check, and enforced code line citation that must exist, be a function declaration for the start of all paragraphs and inline commentary must be three lines or less and inline comments contribute max 10% of the PR. Fail any of these, automatic PR denial with no human intervention.
This sound pretty good, but every single attempt to put an actual character limit meets incredible resistance on my team. ISO 24495 looks interesting, how do you enforce that? Do you have some agent?
Prune the comments? Instruct the LLM to print less comments (this one is genuinely hard though). What's really happening is that you don't have a strong enough review process (or a code standards process) to offset this. The one issue I see with this is that your team is almost certainly _NOT_ doing any kind of code review (especially if they're leaving comments like that). The other problem is that excessive comments actually harm LLM output, I've done tons of A/B testing, and pruning comments actually helps LLMs spot bugs, among other things.
Honestly, if you saved a ton of hours with the model coding for you, at least give me 30 minutes of your own words, show me you know what you're shipping, if you can't do that, then I don't know if I want to approve the PR. My first job we always did peer review in a meeting room when a PR looked a little too much, you can't exactly bring in GPT into a meeting so its a good time to ask simple questions about the change to ensure you understand it just as much as they do.
It's actually insanely difficult to get LLMs not to produce comments. Even with explicit "NEVER LEAVE ANY COMMENTS WHATSOEVER", they still do, across basically all providers.
I really like the point I read somewhere the other day; instead of sending me the AI output, just send me the prompt you used to generate it. That is the only part that contains only the information you are trying to convey. The rest is just guesses flowery language added, and it confuses the actual message being sent.
I used to do that, but the person could be bad at prompting too (which is often why the LLM couldn't give a good answer in the first place).
So the polite version I use now is: "Hey, thanks for the <doc/code>, just to get a bit more context, what was the original problem you were trying to solve?".
That gets them to distill their own problem a bit further.
Yes, the original prompt is 10000% better than the AI output, because it shows me exactly how much the author (you?) cares about this topic and how much effort they're willing to put into communication, which is barely any at all.
Many people use many prompts and revisions or prompts or combinations or human and AI writing. Its not a simple as just making a single prompt and copying the output as the blog post.
That implies you think the output of an LLM is only a rewording of the prompt, and that it doesn't add anything from it's corpus of training data. That's obviously untrue.
> Look, I get it. It’s Q3 2026, and we should expect that everyone is utilizing AI at SOME point in their process (sourcing ideas, creating outlines, refining prose, etc.).
Sounds like this isn't everyone, but rather, it's people who have nothing to say, and -- even after they've "sourced ideas" -- they don't know how to reason about it, nor how to communicate it.
This isn't everyone. This is people engaged in generating noise, for the sake of noise.
One of the ways I think about this is to treat AI as if it were another person. If I want to give information to Bob but I think Alice might do a better job of writing something, I'm not going to ask Alice and then copy-paste her response to Bob. I'd either tell Bob to ask Alice, or loop Alice into the conversation. Me being the middleman between Alice and Bob can cause several issues including delayed communication, miscommunication, and obscured provenance.
Alice being AI or a real person doesn't change those factors much.
I think the main reason many people (including me), very often, lack the motivation to read content that is likely generated by AI is the suspicion that it comes from a place of intellectual laziness. Another reason, based on personal experience, is that AI content may suffer from too much verbosity, too much jargon and over-confidence, which makes the reading experience feel fake and border-line irritating. In many cases the content may have very little to no nuance, which is ultimately a waste of time.
As an anecdote, someone posted a blogpost on Linkedin on using agents to implement a driver to access PCIe devices over TCP/IP. I was intrigued because that's not an easy task for several reasons, like handling PCIe interrupts and DMA. For exmaple, how does the remote machine map the device's PCIe BARs? And when it issues I/O to the devices registers, how are these reads and writes transferred to the remote device. In the end, this is just some virtual memory. In a local machine, this is either directly mapped to the PCIe physical addresses or some IOMMU virtual address space which is then translated by the hardware upon CPU/device/VM access.
After reading the long verbose promising article, in the end, the guy (with the help of the agent) only managed to implement access to the PCIe config space so that lspci on the remote machine works and shows the remote PCIe device, but that's all. It never addressed the issues above nor even mentioned them. The code was AI generated. The article was AI-written. The article never made a reference to DMA, interrupts, MSIX-X, IOMMU, IOTLB, virtual memory, etc, but it made big claims on next-gen datacenter disaggregated architecture, boosting GPU utilization, reducing large scale inference costs, etc.
Anyway, you get my point: big long beautiful words, but zero nuance.
If some text is AI written as a response to a much shorter prompt, then the prompt and/or sources used to make the text should be published instead (or at the very least together with the text).
I had to do this with my boss. He sent an email saying he asked AI about an assignment he gave us, then sent us the reply from the LLM. It was verbose and lacked any and all awareness of the constraints we have within the company. The assignment was poorly defined from the outset, and I asked for the prompt he used, because I thought that would be far more useful to understand what he was looking for rather than what AI decided to spit back.
It turned out his prompt was equally uninspired... 1 or 2 sentences. That was the thought he put into it, which then had us spending hours trying to figure out the AI reply. He could have saved the whole team a full day by just sending the prompt... or nothing at all.
Funnily enough, for me AI writing is usually the summarizer rather than expander. I would usually give Claude 2-3x the amount of data in notes, context, braindump etc; when doing person-to-person communication, using AI to _expand_ the context rather than shrink it is doing everyone a disservice.
The infinite monkey theorem[1] can be applied to show that AI is not incapable of producing quality output. However, expecting your audience to sort through the output from a very large quantity of monkeys is not respectful. I think the best approach would be:
"Here is the prompt and model I used, here is the portion of the output that stuck out to me as relevant and useful, and here, in my own words, is why I think that is so."
i.e. Highlight the good part of the output for me and, preferably, explain why you think it's good. Otherwise it's the same thing as posting slop, only with extra steps. You thought it was worth posting and I thought that made it worth looking at, but now I'm sorting through a bunch of monkey garbage looking for what made you think that. Being a different person, I may not find that hidden gem and I may become quite frustrated with you.
I wish I could do a "right-click -> view page source"-like "right click -> view prompt" or like the dark mode toggle (prompt <-> ai slop (expanded)), depending on my mood (although almost everything is in constant dark mode, so I believe I'd look mostly at the prompts)
I think of a prompt more like a tweet. The medium does matter. If someone was only willing or able to put an abbreviated amount of thought and effort into something, it's not worth a disproportionate amount my time or attention.
Exactly. And I think the information theory matters here: it's worth putting in information proportional to the human-supplied input, not proportional to the AI-expanded output.
"please walk our observability stacks, our IaC code and config, our cloud account, and our application codebases to gather an RCA for for any errored out request responses we've been producing this week. include a tabulated breakdown."
~actual prompt i sent in to claude last week. doing what you propose would be basically impossible / nonsensical, and further undo the entire exercise, sending all the money spent on the tokens down the toilet.
put differently, if you use agents in any actually useful manner, the principle you describe erases whatever value they did end up providing. though since the whole underlying premise is that ai never provides any value, maybe that's the intended result and is as expected. in which case, i'd argue such a desire is more than a bit demagogue.
It's an ego issue for most people. For one, part of it comes from genuine intimidation or fear, the notion that a machine can be smarter than you, or at least produce answers that are more knowledgeable than you could. But I think the more striking issue is what LLMs do to the perceived value of expertise. Especially in engineering there's this weird pecking order hierarchy, where someone should be listened to just "because they have the YOE/Experience/Other meaningless metrics" under their belt. Now all of a sudden, someone with relatively little (or no) background in a given subject is capable of just entering a prompt and within seconds obtaining an answer that is expert or near expert level. (You can see the results of this with engineers just hopping between different fields with ease)
The implication is that expertise is being devalued in real time, and in a sense it really is, but I think that most people really do need to face the reality of their emotions and where it comes from. For myself personally, I have no qualms about reading or even engaging with AI content, as long as the content itself is of quality and truthful.
I described a problem to a new hire. Symptoms, how to reproduce, etc. and asked him to go investigate it, pin down the problem and solve it. It was a non-trivial and hard to reproduce bug.
Instead of doing any of that, he sent back very quickly a wall of text. Generic advice. Nothing relevant. Along with this he sent a PR that would have broken prod.
It was useless, and basically amounted to throwing the assignment back in my face. Since I, like literally everyone else, already have Claude Code, having an expensive person use it for me (slowly and badly) is worthless. In fact, it's negative value, and a huge waste of time. ChatGPT would have given me the same wall of text for pennies.
In the end I got rid of him.
I'm sure he thought I was "intimidated", and had "ego" issues. But he's actually just redundant.
No, that’s not it. Its easy as competent engineers for us to forget how terrible most people are at prompting AI, or reviewing and correcting AI output. Raw output from typical prompts is garbage. If I start reading something that no one even bothered to edit well enough to tone down the AI speak, odds are its garbage and I don't need to spend more time engaging with it than the author did.
But the point is that it's garbage because of the low quality of the information, and not necessarily because an LLM made it. I do agree that most people don't know how to prompt.
Right, and I’m not going to spend the time trying to gauge the information quality when I already know the person who sent it didn’t think it was important enough to edit - or isn’t capable of it.
Admittedly a controversial take, but I think some of the AI skepticism I see is driven by status anxiety, alongside the perfectly legitimate complaints about verbosity, low-effort output, lack of a human voice, etc.
The bar for what counts as expertise is shifting. If someone with relatively little background can use an LLM to get to a reasonably informed answer much faster than before, then experience and credentials alone carry a bit less signalling power than they used to. That obviously doesn't mean the inexperienced person suddenly has the judgement, context or intuition of an actual expert, but I do think some of the hostility toward AI comes from discomfort with that change.
AI is still wrong, goes in weird circular loops, and doesn't solve the fundamental human problems around judgement, organization, learning curves, accountability, etc. But it does seem to be raising the baseline expectation for what a competent knowledge worker should produce, and I feel that shift is genuinely uncomfortable for a lot of people who based their identities around being rigorous abstract problem solvers.
Reading a copy-pasted AI response feel the same to me as reading a massive wall of text with no punctuation. It may contain valuable information, but it's harder to extract the signal out from among all the noise, and the writing style is correlated with a lack of valuable information, so I generally give up and decide to spend my time reading something else.
If a coworker sends me an AI generated report to help on my task, I am more likely to ask them to just send me the prompt and model they used. Let me own the session and steer it however I want.
I believe I have better context data in my session than someone simply prompting based on hearsay of what they think they know about the task I have at hand.
Also, I may have already started looking into it, but now this other person just wasted money.
I left a comment on some of my interns, clearly AI generated code and response asking for him to please not respond with AI generated output — the response was talking about things I had known he was unfamiliar with because I had worked with him. The response itself had some particular formatting/content decisions that were generally a very odd way for anyone to write, but certainly not an intern. He responded that he did write this himself and that he was upset I would accuse him, etc.
I, of course, had no choice but to apologize. I hope I was right, but clearly there is some chance I was wrong.
Anyone else have coworkers responding to your human PR review comments with AI? I feel like I'm taking crazy pills, how can anyone find this socially acceptable?
I have been feeling the same way for the past few months. I just want to say I will never read a paragraph that has signs of AI, because most of the time, the people didn't put much effort in it. I don't care if it is factually correct or not.
We have a junior research student who does this on slack.
Before I think he was using AI and other tools to translate his messages since english isn't his first language. His own words, then AI translated it. Sounded kinda clunky, but I could sense the human behind the words and I gave grace since I can only imagine how hard it is to properly communicate your ideas when English isn't your first language.
But now it's gotten to a point where I can tell he's not using it for just translation. I'm gonna need to chat with him.
Redacted example below
```Hey @PERSON_WHO_ASKED_QUESTION Both good, and the retrieval one isn't written down anywhere. In order.
One corpus or four. My lean is one. Same chunks and embeddings tables, source_type column to tell them apart.
Values I'd propose, flat rather than nested: paper, dataset_description, dataset_readme, dataset_contributors, dataset_records, dataset_files. Description and readme split because their units already differ, one row versus one row per paragraph. A discriminator that can't separate those isn't doing much. The existing 440 rows would need backfilling to paper.
Chunk id in the same spirit: dataset doi, source type, ord. So EXAMPLE_DOI.
Worth checking before any of this matters: does chunks.doi carry a foreign key to papers.doi in 0001_init.sql? If it does, a metadata chunk with a dataset doi can't go in that table at all, and separate storage stops being a choice. Ten second read, I haven't done it. Shout if you get there first.
Retrieval is the one that's bigger than it looks. Search once across everything and nothing guarantees a paper chunk and a metadata chunk both land in the top k. The facts we want relate the two, and the generator can only write those if it sees both sides in the same window. So if one type systematically wins the ranking, that class of fact doesn't get worse. It becomes impossible.
Which way it goes I don't know. Two mechanisms pull opposite ways. Metadata chunks are short, tens of tokens against roughly 450 for a paper chunk, so they may just lose. But we embed context header plus text, and on a short chunk the header is most of the vector. The header is the dataset name, which is also most of the query. That points the other way.
Cheaper to measure than argue. Load one dataset's metadata, run a normal dataset level query, record the rank of the first chunk of each source type. Runnable as soon as any one of our four subtasks lands.
After that it's one pool, per source with quotas, or one pool with a floor per source type. I'd rather not pick before there's a measurement.
```
"Look, I get it. It’s Q3 2026, and we should expect that everyone is utilizing AI at SOME point in their process (sourcing ideas, creating outlines, refining prose, etc.)."
Hell no. Sourcing ideas? From AI? Are you kidding? Essentially guaranteeing they won't be original? Refining prose? Making it much more likely it'll be generic as hell. Call me old fashioned, but while I can certainly understand asking LLMs concrete questions - how do I fix this, where can I unsubscribe from that - using AI to help communicate seems bass-ackwards. LLMs have no idea what you're talking about - they're free associating probabilistic sentences! What on earth value could that have in communicating. They self contradict, hallucinate, speak most frequently in a weird smug corporatese. How is this an attractive use case of the technology?
I personally don't care whether a piece of writing was AI-generated as long as it's useful or insightful.
However there's only 10% of AI-generated writing that is worth reading. If some articles convince me that there's somebody behind it contributing valuable understanding, I'm willing to overlook the telltale AI mannerisms. It's understandable that some domain experts aren't very proficient in English.
That said, statistically speaking 90% AI-generated pieces are a waste of readers' time. It's a good strategy to simply skip them.
I know this looks like a bot comment. It's not. It's a much older style of writing known as Chinglish. That's why as a non-native English speaker, I can totally understand why someone would want to use AI to help with their writing.
I thought the exact same. There is also a growing problem with people using AI to summarize everything instead of reading the actual text. I thought this addressed that issue by having a section for the AI to help summarize or something similar.
I am pro AI, and also deeply share this sentiment.
I think sometimes people have a big long thread with Claude where they feel enthusiastic about the back and forth being very productive -- and then they genuinely want to share the summary of the conversation with their colleagues so that they can feel it too. It's not just typing a short prompt and copy/pasting the response.
But, Claude, especially Opus is so unnecessarily flowery, and smug -- and it's so identifiably characteristic.
It somehow rubs salt in the wound: "I didn't take the time to write this out in my own words, so now you get to listen to this petulant asshole mansplain it to you".
If it would get to the point, and with some humility, it would be a much different proposition.
There is a light at the end of the tunnel for all the minds burned out by AI slop.
I already saw someone getting fired for only producing AI text as part of their entire output, after being unable to explain what they “wrote” in multiple situations.
And recently my company enacted a mandate that text made for humans should not be AI generated.
Sooner or later every company will start realizing that this is just people too lazy to actually work and coasting on a paycheck, at the expense of every other worker.
This makes me happy to hear that someone got fired for that, but I just cannot picture that happening at my organization. Perhaps standards are too low. What sort of thing did they get fired for? Was there some warning etc?
Product Manager using Jira AI to hallucinate tickets, epics, metrics and roadmap. Even the numbers were completely made up.
There were too many incidents of “this doesn’t look right” in the same week, so when their boss did a thorough check a couple days after, it was all fake, everything. Eventually they admitted and got canned.
I guess I'm in the minority. I don't mind an AI response if it's informative, concise and well-crafted.
The problem is that those kinds of responses are rare in the tech world. But when you have someone competent at the helm, it's much better than reading human slop.
> But if you’re my colleague and we’re in a Slack discussion and you post a wall of Claude output, then I’m afraid I received a different message than you intended.
i have what ill call a "condition" where i fear assuming someone did something stupid is insulting. i try not to patronize people because i also assume that would be insulting. this leads to issues where sometimes people really want to be lead to water rather than make an implied connection themselves
this is a roundabout way of saying, is there a genuinely polite way to tell colleagues posting ai copypasta makes them seem ignorant? i dont think ai:dr is workplace appropriate. id like to tell people gently and avoid patronizing if possible
TL;DR works because I can see the length at a glance
And you cannot tell all AI. Only mainstream crap like ChatGPT and Gemini which is full of cached tropes and boilerplate formats so it all sounds the same.
My custom invoicing software automates notes based on years of my previous notes and tasks I did - looks nothing like AI.
Use a real library and local model, mess with settings, there is a lot more to this than the mainstream consumer apps.
A similar metaphor (I think I came up with but can't remember) is the slop sandwich. You can deliver slop to me but only when wrapped in a thick layer of human intervention (which usually also means removing 50% of the slop)
By the way, just want to say, AI can be good for some bedtime stories while trying to fall asleep lol
After you've exhausted your favorite audiobooks, I mean
Like, I love The Wind in the Willows, but I wish the part where Toad and the gang go on the road in the cart lasted for longer. I asked ChatGPT to invent some fill-in chapters matching the same style and speak it out loud, and it kinda did OK actually.
This hurts particularly much when it comes to software changelogs/release notes, most recently for me was the solidjs 2 beta, reading the announcement post was painful, even the headers are LLM:isms.
There's been a few. The last one was 2007 when the iPhone changed the internet from a place you went because you wanted to be there and had a reason to engage, into an app meant to entertain you for 5min at a time between text messages and flushing.
> Yes, there are certain situations in which we should expect 100% AI-generated copy. Customer support would be a perfect example. We’re not looking for artisanal “did you make sure to reset your phone” style dialogue.
No, no, no, no - the whole point of customer support is that I am having a problem that requires attention from a representative of the business I am dealing with. Businesses really don't like doing this; they call it a cost center to have to talk to their own customers, so they staff their call centers with increasingly useless script-readers designed specifically to shield the people with knowledge of the matter you're facing against customers like you. This is a great solution for dealing with technically illiterate people who don't do basic troubleshooting and terrible for literally anyone else who actually tries to be a good customer.
> TL;DR (too long; didn’t read) was the solution for social media.
> AI;DR (AI; didn’t read) is the solution for AI slop.
Maybe I'm the odd one out here and didn't plumb the worse-depths of social media, but I feel I need to defend good old TLDR as a slightly different, and less-hostile animal.
It can be a moral condemnation of the poster, where they're disrespecting everyone else's time by posting something big and vague... But it usually isn't. At least half the time TLDR is someone providing a summary because they think it'd be useful (even of it's sometimes a hostile interpretation.)
tl;dr as the sole reply to someone IS a condemnation of what they wrote. tl;dr at the front of your message with a short summary, is an admission that the long version may not be for everyone and there's a core point for quick consumption.
I'd say that sounds about the same for ai;dr. I could see myself posting a prompt like that in front of the generated report.
The purpose of writing is to communicate. The person communicating is an important part of the message.
Consider the sentence "I'm waiting for you at home." It really matters if it's said by your loving wife or an evil clown. You can extrapolate from this.
So how much time do you deem a minimum amount for someone to spend on some unit of work before you're willing to read it? And what technologies are allowed -- are word processors allowed or does it have to be done with a writing instrument like a pencil? What about spell check? Do you care if they had done their research with a Wikipedia or do you prefer card catalog for the really important work?
I'm not sure. Another way to think about it: how _little_ time is someone able to spend on something where you will still be interested in reading it? If someone tells their unattended LLM agent to create a blog, write whatever content will maximize banner ad revenue, and then share each post on Hacker News, would you read it? What if the content is actually interesting in your opinion?
1. I can't effectively engage in follow-up conversation with the "author." I can't do it with the human (principal) because they didn't write it and can't explain it--and, in fact, they may not even personally agree with all if it!
2. It shifts the cognitive burden from writer to reader. What makes writing hard, and valuable, is the effort put into translating one's raw, unfiltered thoughts into writing that is easy to comprehend, and the writer's own unique personality that is expressed in it. As ambient prose, AI-generated writing is often not only more difficult to read than human-drafted prose, but it also has this "sameness" quality that makes every "author" have the same personality.
In one case, I could tell because the tone of the piece sounded exactly like the kind of stuff I would read after prompting an LLM and I had never heard of the author before, but I knew that they were like an intern or a new college grad and for some reason their piece was trying to persuade employees in a certain field about how they had to use AI itself. It just rubbed me the wrong way because if they did use AI, then they didn't even bother to rewrite the repetitive instances of "it's not X; it's y", and also "This isn't X".
Imagine a future where 99% of text is written by 1 unpassionate person. Reading the same patterns, the same tropes, the same flow across paragraphs, over and over, would be unpleasant. It already is unpleasant.
The problem is that some people think all AI-assisted writing is prompting "write me a post about X", so they see LLM prose and assume there has been no thought or effort put into it.
Wow, peak ableism. It is a post about how I use an LLM as an accessibility aid for reading and writing. We're not all out here faking creative writing you know...
>If you’re not bothered enough to review and edit it...
>...then I’m not going to bother reading it.
Just playing Devil's Advocate here, but we've had copywriters and editors for generations now. Not reading something because AI did the post-writing work feels kinda weak. Skip stuff started from AI, fine, but this is just because it's AI, not because the author didn't do the task. And I do get the point is that if an AI did /most/ of the work, ok to that, too, but not post-write processing alone.
I think the main reason many people (including me), very often, lack the motivation to read content that is likely generated by AI is the suspicion that it comes from a place of intellectual laziness. Another reason, based on personal experience, is that AI content may suffer from too much verbosity, too much jargon and over-confidence, which makes the reading experience feel fake and border-line irritating. In many cases the content may have very little to no nuance, which is ultimately a waste of time.
As an anecdote, someone posted a blogpost on Linkedin on using agents to implement a driver to access PCIe devices over TCP/IP. I was intrigued because that's not an easy task for several reasons, like handling PCIe interrupts and DMA. For exmaple, how does the remote machine map the device's PCIe BARs? And when it issues I/O to the devices registers, how are these reads and writes transferred to the remote device. In the end, this is just some virtual memory. In a local machine, this is either directly mapped to the PCIe physical addresses or some IOMMU virtual address space which is then translated by the hardware upon CPU/device/VM access.
After reading the long verbose promising article, in the end, the guy (with the help of the agent) only managed to implement access to the PCIe config space so that lspci on the remote machine works and shows the remote PCIe device, but that's all. It never addressed the issues above nor even mentioned them. The code was AI generated. The article was AI-written. The article never made a reference to DMA, interrupts, MSIX-X, IOMMU, IOTLB, virtual memory, etc, but it made big claims on next-gen datacenter disaggregated architecture, boosting GPU utilization, reducing large scale inference costs, etc.
Anyway, you get my point: big long beautiful words, but zero nuance.
The problem with copywriters is that they wrote "copy" - which turns out to be writing that I don't want to read. And the problem with AI is that much of what it trained on is copy, so it trained to write stuff that I don't want to read.
So in the end, I don't care if a human wrote it or an AI, I don't want to read it either way.
What's wrong with copyrighters? They write like corporations, not like humans (see the Cluetrain Manifesto for more on this). They sound like nobody - literally inhuman. I don't want to read that. I want to hear a human voice. If I can't hear that in your writing, I don't need to read it.
If I'm reading something on the internet, I'm either reading it to learn, or I'm reading it to be persuaded. If I wanted the LLM to teach me (thank you, no), I would ask an LLM. I'm reading your website/newsletter/email because I want to hear from you.. If you can't be bothered to put your time into writing it and teaching me what you think, why should I be bothered to read it?