(bcantrill.dtrace.org)
Writing is thinking. Thinking and deciding. There have been many times when I start out writing something substantial - could be an email, a blog post, a software design document, anything - when my own views substantially changed during the writing process. Writing forces you to serialize your thoughts - and you can't always trust the gestalt.
Reviewing gives you the chance to ensure the arguments connect solidly, that references are accurate (even informal references) and gives you the time to consider counter-arguments you aren't addressing.
None of this matters much on LinkedIn, but it matters a lot in our work. You cannot outsource your understanding to AI. They are powerful tools but they do not have any human understanding - that isn't their optimization target.
I don't disagree, but I think it's often not appreciated how much there's other work to writing too.
The biggest one is that you have to communicate non-interactively to an unknown audience. Having to (literally) put it in someone else's assumed terms does help giving different perspectives into the matter, but doesn't necessarily help one's own thinking that much. Instead you have to do some of the reader's thinking for them.
You also have to spend time on textual matters like grammar and style and a lot of "unspoken rules", which aren't really about linearizing your thinking about the contents.
Not all writing is thinking and not all thinking is writing.
That is the best way I’ve seen anyone put into words what I feel about those types of theses
That said, abdicating to an LLM is the worst of all worlds - you’re not thinking and the product is not tailored.
The solution is obvious - write as much detail as you need and allow readers to interrogate the virtual you with an LLM, maybe not even reading what you write.
Hard disagree. Constraint is the driver of creativity. Also rewording sentences to sound better or make sense can make you reconceptualize the whole concept you are expressing
Take for example a non-native writer of the language. I'm sure having to check up words from a dictionary may help to reconceptualize things, but I'm sure also that it's not often very efficient. And I think similar is going on for natives too for many types of writing.
And not all thinking is writing is a clear truism, there’s no point to even stating that.
Writing helps us think about the world, it’s a pivotal intellectual technology.
Much like money decoupled selling and buying to move away from bartering, writing decoupled saying and hearing so they didn't have to happen at the same time. The incredible step that happened was not that people had to think a whole lot, it was that thinking that was already happening had to happen once.
> All writing is thinking when done by a human, you’re literally distilling your thoughts into words. You can’t write without thought.
Of course you can. You can write down exactly what you hear, for dictation.
You can write down a stream of consciousness and put barely any thought into it at all.
I can't help but feel most here are massively over estimating human writing. Human writing is, almost universally, terrible. We have entire jobs that are hard to fill just to make things sort of ok. Good writing is a small subset of human output.
Because one can copy a text and write it down and that involves thinking in the sense that anything we do involves thinking fundamentally. But that thinking is different from thinking logically about a concept and writing it down which I think is where you are getting at.
The definition of writing and thinking is too broad in that sentence even though it does apply in several obvious cateogires within that at different levels.
And also "writing helps us think about the world" is too broad again. Why? Why does me writing "apt apt apt apt apt apt apt" help me think about the world? I just wrote it because i felt like writing it. Why wouldn't you consider that writing?
Poor example. You wrote it to make a point, after all.
Do you have any non-contrived example of writing that was done with zero thought?
Have you never asked a decent model to explain something to you? You should try it.
Would love an example where you’re able to write without transferring your thoughts. Besides the obvious: fjcjfjrnjfjfifjfnrnakosifnrbwkofgjrj
(1) Translation from one language into another
(2) Transcription from one medium (audio) into another (text)
(3) Deception to obfuscate your thoughts
(4) Posting things like "First!", "This.", "Just google it.", etc.
(5) Textbook answers with no original thought.
Bad example, because translation is deeply creative. You can't blindly mill one language into another, because words and phrases and concepts and cultural references in one language frequently don't map 1:1. You have to find a way to convey meaning as closely as you can and not necessarily the words.
I prefer when things are kept 1:1 as is and maybe there's an explanation for things that don't quite make sense as a footnote.
Of course the above requires actual work on the part of the consumer. I realize many don't want that, particularly when it comes to entertainment. So I appreciate that the other sort of "translation" exists but I think it's important to realize what exactly those are.
Thankfully LLMs are more or less to the point of providing what I'm after in near real time.
Words refer to a broad semantic region, a phenomenon technically known as "polysemy".
The range of a word in one language is always different from the range of analogous words in another language. This is a classification problem. And a translator must think about how to solve it. Imagine a Venn diagram with 20 circles that each overlap the other 19 to differing degrees. What does it mean to designate one of those circles as "the literal translation" of a foreign word?
Obviously there are degrees to this and obviously preferences will vary. I acknowledged that.
Imagine a localization attempting to replace a reference to an actor, political scandal, or other concrete cultural reference from one country with the "equivalent" from another. I've encountered that sort of thing before and while there are certainly those who appreciate it I am emphatically not one of them. As far as I'm concerned that's shitty fan fiction.
There are also a lot of examples in most (all?) languages that rely on repetitive sounds, easily mistaken words, or other strictly auditory features of the native language. You literally cannot translate those things. I do not want shitty fan fiction, I want an explanatory note.
- You've got a pet peeve.
- You're going to rant about it, because you want to, whether or not it's relevant to an existing conversation.
- You didn't bother to think about my comments.
- You didn't bother to think about habinero's comment either.
Here is the same passage of the Analects (part of the chapter Gongye Chang) in different translations:
--- Annping Chin ---
Zilu said, "We would like to hear what you would like to see yourself accomplish."
The Master said, "To give comfort to the old, to have the trust of my friends, and to have the young seeking to be near me."
--- David Hinton ---
Adept Lu then said: "No Master, we'd like to hear your greatest ambition."
"To comfort the old, to trust my friends, and to cherish the young."
---
Our focus here is on the second line, what Confucius says. Does he want to trust his friends, or does he want his friends to trust him?
Does he want to cherish the young, or does he want them to cherish him?
We might also ask, though the translators have agreed on this point, whether he wants to comfort the elderly or for the elderly to comfort him. (And we could further ask whether Confucius wants to personally comfort the elderly, or whether what he has in mind is for society in general to do that.)
All three clauses are formed the same way in the original Classical Chinese, and for a couple of interacting technical reasons they are all ambiguous in this way. Translators, as you can see, make different choices.
But of relevance here, when you're doing a translation to English, you have no option but to make a choice. It isn't possible to render the original text 'in literal translation' and append a note explaining what went wrong. You must commit to a meaning behind the text and phrase that meaning in English. You can also append a note explaining that you might have chosen wrong, but English simply doesn't allow you to do anything that parallels the source material.
I think it should be quite clear by now that I am not talking about isolated words that broadly lack an equivalent concept in the target language. I even quoted the bit from the original comment that I took issue with and proceeded to give examples so I'm really not sure where the misunderstanding between us could lie at this point. Perhaps you are the one who should stop and more carefully think about what I wrote?
As to your example. I certainly do not accept that this is a case where we should throw our hands up and accept that different translators will go about things differently. Those two sentences in english have (as you note) rather different meanings. So either one or both translators must be wrong.
You have indicated that the original work in the native language is ambiguous. In such a case I do not think it is remotely acceptable for a translator to arbitrarily pick one of several possible meanings and just run with it. If the original meaning of the text is ambiguous then removing that ambiguity changes the meaning thus it is a bad translation. The translator instead needs to faithfully communicate that ambiguity, possibly resorting to a note if it isn't possible to easily express such a thing in the target language.
I realize that many people aren't going to want such a marked up copy. But without all the gory detail the reader will be consuming some sort of bizarre partial fan fiction. Your example illustrates that perfectly.
https://www.theguardian.com/uk-news/2020/aug/26/shock-an-aw-...
QED?
Not all writing is thinking: That all, even a lot, of writing, or parts of writing, is such that it will develop one's thinking much. For example most stuff I have to write, the dozen emails a day, the funding application boilerplates, the reports are stuff that don't really need (or deserve) much thinking but they have to get written. And even in the writing that deserves attention, there is stuff like grammar and spelling and surface style that usually take quite a bit of time after the ideas have been written down already.
Not all thinking is writing: for many cases writing is not a particularly efficient way to develop one's thinking, and e.g. visualizations, math, coding, discussions etc can be a lot better.
They’re completely opposed to experiencing any type of friction.
It reminds me of the transition over the last year from AI-assisted coding to AI doing all the coding. At first the code output wasn't good enough, and humans read and iterated on the code all day, so the details of the source code mattered. Now, the code is largely high quality and it meets a large set of guardrails we've set up over the years (linters, typecheckers, security checks, LLM-assisted code quality checkers), and it's just Claude working on the code, so the details matter less and engineers think a level or two up (machine code < assembly/bytecode < source code < conversation with agent < artifact with high level design).
I wonder if long form writing will go the way of code. You and the AI agree on an outline or other high level representation, then the LLM expands it into a document. But writing and coding are different enough in a number of ways that this is far from inevitable.
What use is that? I'm not being facetious, I'd really rather like to know.
Who or what is the audience for that sort of long form writing? If it's a human, why would they read it? They'd just give it to an LLM and get the salient points back. If the audience is another LLM, why expand it?
The only use case is an audience of humans who still read and understand, and those people aren't going to be interested in a message when it is not apparent that the sender actually understands the message themselves.
That's why there's so many meetings in white collar companies. Because people can't understand what is going on at those documents so they just need to "align".
LLMs are amazing at generating this useless documentation that goes absolutely nowhere.
That's already available today. We don't have to perfect LLM writing.
1. I have a bunch of data or research that I've gathered with a unique hypothesis
2. Having gotten my arms around that pile of information, I believe I have a compelling thesis to put forth
3. I design the narrative arc and of the thesis. The important parts, the necessary but not sufficient scaffolding.
4. An AI helps fill in the story from there. Fact checks each claim, connects the dots, makes it comprehensible.
Who is this for? Well, quite possibly the human who asked for it. It's pretty informative to read back a research brief in full that you helped do the scaffolding.
Also of very clear use is other AI's who did not have the same unique hypothesis and did not gather the supporting evidence. It's an interesting angle for others to build on.
And of course, other humans! Most human written content gets almost zero readers today as it is. And I suppose LLM content probably pulls the asymptote closer to zero, but some pieces of content may be genuinely interesting or useful.
I think this certainly has some value but this claim in and of itself is stated like your hand-wavy step 3. How do they fact check claims and connect the dots?
Maybe LLMs get there but currently they write in an extremely verbose manner, and things that have gotten into the context window that are no longer relevant continue to stick around (just try having it write some code, then work some of it back to simplify the problem - it will insist on writing comments about code that no longer exists).
Right now using an LLM to write documents is like taking a superhighway to travel 100 meters. Yeah you're doing a lot but is all that really necessary?
I won't deny that LLMs will never have a place in writing. But I personally don't think the current form is "the one that actually lands" (!).
I used to say this was the future of advertising (cr sales person prompts “we have some new EV SUVs on the lot”; GPT generates an ad email with a synthetic video, blinking text etc; then the recipient’s spam processor tells them “that dealer has some new SUVs”. I suppose the same could happen with so-called “long form”.
People are terrible at writing. Near universally bad. Even good writers have drafts and editors.
There is a constant refrain here that somehow short messages are more valuable than longer ones. But that assumes it's understandable. Lots of short content is, frankly, awful because the writer cannot put themselves in the position of the reader and explain all the things around the point they're making that the reader really should be told.
You can view writing as translation. From your language to a language your audience speaks. At that level is it so odd if the word count differs from one side to the other?
Look at it the other way, could you take a good longer message you’ve written and make it shorter and less readable for your audience while still making sense to you and containing the key points?
personally, I think there's a time and place for short versus long, just like there's a time and place for a 45mins TV episode versus a 2 hour marathon movie.
My opinion of LLM design review isn't that high - it seems to miss design tweaks that could vastly simplify corner cases. But if your code isn't written for human consumption maybe it doesn't matter. I'm still directly responsible for what I commit, so I can't just offload it to Claude.
It's like watching somebody about to be hit by a bus. You yell, you wave your arms, but they either don't hear you, or they don't believe you. The last thing that goes through their head is a Greyhound's hood ornament.
The most popular programming languages in 2030 will, in fact, be English and Mandarin. Deal with it and get over it.
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Edit, to bcrosby95: Look up the etymology of the word 'computer'. It didn't originally have anything to do with hardware. The first computers were people, who were told what to do ("programmed") without necessarily knowing what they were working on in a big-picture sense.
Calling it gatekeeping is just laughable. That's like saying it's gatekeeping to say that the painter painted their painting, and that the person who commissioned the painting did not paint it. It's wholely absurd.
Anybody can pick up a book and learn to actually code themselves. Or you can use an LLM to try to make things without bothering with that. But even if the LLM worked perfectly, pretending these are the same thing is silly.
The history of the word computer is obviously irrelevant. Words change, it turns out.
(I’ve heard about some GPU compute nuance meaning that even without randomness injected they still wouldn’t quite be deterministic, but that’s also not core to their nature)
Neither do humans.
Two people can give the exact same prompt to the exact same LLM and get different results.
No one cares.
This is like telling someone else to code something for you.
Exactly.
What are you willing to bet?
To be precise: I will bet that high-level programming languages won't be any less popular as a whole, but the vast majority of code will be written by AI rather than humans, working from specs written in natural language or something very close to it.
What we call "source code" today will be thought of as "object code" by 2030. Something that occasionally needs to be inspected by humans, but rarely authored directly. Anyone not writing code this way had better be doing it as a hobby, because almost no one will pay for it.
Other person probably doesn’t like the idea that LLMs will replace hard earned skills. On the flip side, I bet you’ve seen your skills atrophy at an alarming rate and are trying to justify it.
Both sides come from fear. Just relax and take things as they come. Whatever happens happens.
It's baffling you people are in control of such a strong product when you are obsessed with this intellectual pornography; wow - look at how smart it made my thoughts look (n.b. look, not read). Don't look too close. And certainly don't ask me what it means.
The widespread introduction of LLM code generation is very destructive to that.
Perhaps LLMs can be brought to support human cognition in the same way writing can; but that has yet to be designed and it does not seem to be the way things are heading.
The bottom line is, prompting is definitely writing.
Cognitive burden increases marginally with AI assisted coding.
This is why we haven't seen big projects(think browsers and browser engines) spawning in the past year.
Why are you reviewing AI code in detail? Do you also review the assembly output of GCC line by line?
In the case of writing, it’s like hiring someone to write a book for you vs. hiring someone to translate a book you wrote into another language. In the first case, you didn’t really define the message for readers, whereas in the second case you did, and the translator is converting that same message for another audience to consume.
In the case of LLMs, the behavior is non-deterministic and inconsistent. If I don’t explain how handle an edge case or give a performance constraint, the LLM will still produce code and may do so in different ways, handling edge cases differently and with different performance characteristics. I can’t reason about how the LLM will fill in those gaps, it’s “random.”
Maybe you don’t care about how the LLM handles those edge cases or handles performance, but that’s different than a deterministic abstraction whose implementation details you don’t care about, but whose logic and performance is deterministic and consistent
The closest thing we have to vetting LLMs is “whoa look, it escaped this sandbox, that’s prolly not great but it’s so cool!”
I wouldn't use it for flight control software yet, at least not without careful review, but most software isn't exactly critical. At the same time, I wouldn't trust flight control software that was only reviewed by humans, since AI is so much better at debugging.
We'll probably need humans in the loop for safety critical software for at least a year or two, before AI fully outpaces humans at generating correct code.
So I assume you don’t fly? Or is it only software created after 2025 which must be reviewed by the All Knowing Entity?
And, AI is rapidly getting better than people at both code review and authorship, so a human deeply involved is turning into nothing but a slowdown. The main purpose people have is testing that the specs were, in fact, implemented properly.
The vast majority of properly written software was already plumbing well over a decade ago. The software engineering is making high level decisions based on experience with respect to the existing tools and the needs of the business. If you're not already using LLMs that way, you would have been a similarly bad manager of human devs writing similar inadequate slop. Less code has always been better code.
The line in the sand for these arguments really ought to be whether you think LLMs are better than humans who actually know what they're doing.
If you think LLMs are better, or could get better while continuing to use statistical methods, you automatically lose the argument (delusional/ignorant) and any hope of regaining credibility. That's not dogma. That's the science.
twitch
Gcc makes maybe 1 mistake ever 2 billion emissions. LLMs make 1 mistake ever 3rd emission.
What a horrible, cold, inhumane world that would be.
If you're not billed for usage, anyway.
Otherwise, for the other 99% of folks, that attitude is of course a pit trap that captures code bases and makes them maintainable only through the providers -- presumably one or few -- with a rich enough model to keep up with the growing mess. Preserving a code base that's legible, organized, and fundamentally maintainable by both humans and trailing commodity models is of imminent concern for anybody who doesn't want their margin strangled by your employer once it's too late to have other options.
As frontier capabilities advance, the details don't matter less; they matter more.
Prices are very competitive and today's SOTA is next to free in half a year.
Whether code is maintainable without AI becomes less and less important.
I couldn’t help myself, replied and asked him for a recipe for delicious apple cobbler and hiking trail recommendations in Glasgow, which “he” immediately provided. Highlight of my career.
I think my core argument is this: I have access to every bit of information your AI does, so if I want an AI answer I’ll get one myself. If that isn’t true, why are you hoarding information? Push it somewhere we can all see it. So the only reason I would send you a message is to access _your_ brain. I have no interest in talking to an AI through a worse interface.
1. I understand fully the code and everything it does 2. You can pick up on mistakes super early and it can adjust the plan is it goes. 3. Faster than writing it by hand but slower than letting the LLM do it.
[0] https://ankursethi.com/blog/prevent-cognitive-debt-by-manual...
I worry about AI Loopidity here though. Think about the similar analogy of email. If my set of ideas is condensable to bullet points, but I use AI to expand the content, then I add no information density and a lot of noise. Other folks then use AI to summarize the content to a list of bullet points, ideally the same but not certainly the same, and thus communication has been only partially successful.
You get pushback for this? I saw an anthropic job post recently, and they wanted you specifically to have claude muck with your resume before applying.
You can already do this. And you can build pipelines where AI performs fact checks on what it writes, with citations a human can reference as well.
The entire point is what runtime you’re running your code on. A computer with any modern stack requires a lot of text for you to communicate “spin a square around on its center” to it. A human requires only that short string because they have a faster natural language interpreter.
Text meant for a human can communicate “spin a square around its center” much better than any code that mimics it. In some sense, all programming is boilerplate expansion because computers have (until now) been unable to be programmed with anything approaching natural language.
Maybe sometimes, but not always. When you need to actually render the thing you have all kinds of micro decisions, like where to put the square, what color, how fast it spins, etc.
You might not care about the details, but maybe you do. If it spins at 10000 rpm, will you care then?
Natural language, and human communication in general, is ambiguous, and coding is in great part about disambiguation.
Sure, you can use English to disambiguate as much as needed, but wouldn’t you then end up with some yaml-like spec that wasn’t much easier to create in the first place?
Really huffing your own farts there, huh?
On the other hand, long form writing for human consumption seems like it may evade LLMs for much, much longer.
So, I'm not sure if it's a question of time at all: if a LLM text contains some piece of information beyond the information that went into the prompt, where does this "extra" information come from? [Note, I'm not thinking about facts which could trivially come from the training corpus, I'm thinking specifically as information in the sense of intended message from sender (author) to receiver (reader)]
[1] cf. this comment where I explain this analogy between LLMs and noise channel in communication theory: https://news.ycombinator.com/item?id=49510244
All of the things you say are very true in the near term for short form writing - a page or two of Claudeslop will probably be much easier to swallow in a year or two than it is now. But I don’t see a path to fully AI-generated novels or long-form investigative journalism becoming mainstream in the next couple of years.
Later
> I wonder if long form writing will go the way of code. You and the AI agree on an outline or other high level representation, then the LLM expands it into a document.
So in the future, it won't be necessary for you to think?
This is just noise generation. If anyone is meant to actually read the document it should be written by you.
No. No it is not. Nobody who actually cares about the quality of their work is letting an LLM just turn out code without reviewing it carefully.
Then again, I've seen a counterargument [1] by someone who clearly heavily uses LLMs for writing (going by both their LLMy writing style and their own admission). The person I'm citing describes a process where they get a LLM to write something, they check over it and provide feedback to the LLM, the LLM rewrites, and the process repeats iteratively. So clearly he is putting thought into the process.
I think there is something valuable missing, even if it's hard to clearly express. I'll try. The threshold for what I'm willing to accept if I'm simply approving something is likely different from what I'll get if I write something myself, for instance. Saying "LGTM" is too tempting. It seems to me like he's outsourcing his selection of topics to cover as well. If you're not thinking yourself about what to cover then it would be very easy to miss a critical subject. There also an asymmetry between checking and generating something with constraints placed on it. Checks can't catch everything, and a constrained generating process can reduce the amount that needs to be checked, avoid issues that can't be checked so easily, and focus your attention on areas that you know historically have had issues with this generating process. I've thought about this quite a bit in terms of whether to write new code or use an existing library. Sometimes "the devil you know" (my code) is better than an existing library simply because I understand its flaws better.
Just did this for some caching, started with the structure of what I wanted the cache to look like, asked the agent to start the work, didn't like how the architecture came about, scratched it and rewrote the whole thing, so it fit the model I now wanted.
Was also just having this discussion with friends, that I can only think seriously about a subject if i can put it to paper (even virtual paper). Writing lets me organize my thoughts, clearly define my assumptions and see if any of it make any sense. I can't imagine what it would be like if i couldn't write, my brain just doesn't work without it.
The only thing that worked was a standing instruction and periodic system reminder injected from the harness:
"If any assumption doesn't hold, if there's a fork in the road, any architectural decision needs be made, STOP and report back to the user. Do not try to push through the problem."
This has worked remarkably well for me. Now I have to think a whole lot more. It's much slower, yes, but I don't really see any other way that doesn't end up in garbage.
I don't, generally, think in words, more in - I guess I would call it something like meta-shapes? A sense of a shape but not things I can exactly visualise.
(You might be surprised to read this and then hear I have an English degree. Surely I thought about Shakespeare in words?! Nope. Shapes, movement, structures)
For me, having to write is critical because it is the only way I practice serialising my thoughts in a way other people can understand.
If I do not then I get very "deep" into my own way of sensing ideas and it's difficult to dig myself back out.
This might also be why I have never been very enchanted by LLMs? They only seem to "think" verbally. So it is always a translation effort for me.
I never can really enter any "flow" state with an LLM. My intuition is that highly verbal thinkers can enter flow with LLMs very easily
Don't worry, no one does.
That's why it is so common for people to forget a specific word they want to use ("it's on the tip of my tongue").
If we thought in words that will never happen.
>> Don't worry, no one does.
> …you don’t think in words?
"I don't, generally, think in words" is not the same as "I don't think in words".
Like I already said, if thought was exclusively in words for humans, humans wouldn't have the "It's on the tip of my tongue" problem. It's blindingly obvious that thought does not occur exclusively with words.
I think I have produced reasonably good designs. Don't ask me to teach anyone how I do it, though.
One of the most rewarding things for me is figuring out a good shape for a system and how it would interoperate with the other systems, especially in a way that reframes other parts of the codebase in a way that bring clarity and makes it more intuitive to work with. Creating the right ontologies can make all the difference in what you can do with a project. It's a form of creating mathematical objects.
For example, a Unity game I work on has quest and dialog systems driven by visual scripting graphs. We had two way dialog with different units for player response choices and npc dialog. But we wanted to expand to letting NPC's have dialog with each other as well as conversations with more than two participants. I went outside and thought it over, which largely amounted to visualizing a dialog node graph and a feeling in the back of my mind like it was trying to perform a kind of geometric shape-fitting exercise. A fitment solution jumped out at me to have only one "Dialog" node shared by all participants, with a "participant" value on it. If the player parses this node then the options go on-screen as responses, while if an NPC parses this node with multiple options in it, it picks one. And this lets you voice the player if you want, and enables some things like overhearing other NPC's talk to an NPC then talking to that NPC yourself and having the same tree.
And for quests, the quests had just been for the player, but I was thinking about how to make scripted events in-game easiest to work with for script team who primarily works in visual scripting. Similar story - let the NPC's have their own little quests, with task stages, which are easy to track and make branching choices from, and let the NPC's definition for how to use that quest contain a collection of actions to override the typical actions available to it, so an NPC in a specific "quest" can't do things you don't want it to do, a common enough case that it's preferable to making a series of conditions on the general action planner like "not in quest A"
And timing myself, it took 1-2 hours each time to write out the detailed plan for how I wanted each thing implemented in the game with some other tasks thrown in, and it paid off after Astra worked on it until it was done. It was awesome coming back to something pretty much exactly what I asked for each time.
Things I need to do, ideas I want to ponder on, people I need to remember or get respond to.
Writing is learning. Writing is understanding.
I have so many conversations with people who are always telling me I’m “retro” or “old school” for doing this.
I don’t even bother explaining the psychology behind it anymore. I’ve got no time for the ignorance.
"If you’re thinking without writing, you only think you’re thinking."
> As I write, I think about things. As I write, I arrange my thoughts. And rewriting and revising takes my thinking down even deeper paths.
- Murakami, "What I Talk About When I Talk About Running"
This way of phrasing it is needlessly confusing. Writing is a kind of thinking--one of many--but it's not equivalent to thinking.
Dialectical thinking, for example, produces similar results.
The best thinkers I know mostly use writing for refinement, distillation— as a tool. The worst thinkers I know are owned by writing; they require its fixation & stimulation upfront to compensate for limited attention spans.
Really? I am having difficulty thinking of any examples of code that doesn't need to be understood. If it isn't understood by someone, then how is it even working?
If you mean like a library you are using, where you aren't even reading the internals or might not even have access to it, OK, but that code is stull understood by its authors, surely?
They're relatively simple, they do the task they need to and then they wait until they're needed again (or not).
In the past I wrote them, then forgot how they worked, until I needed them again, relearned what I did and adapted it.
Now I just don't have to know how exactly they work, I just get an AI to read the documentation anytime I need to reuse the project and I'll query the AI to fill in the details and to make changes and I ask the AI to run the code and debug it.
Perfect use cases for today's AIs. Doesn't even require SOTA, I can run comfortably on a Sonnet 5 or a Qwen 3.8 and it'll do exactly what it needs to do without making too many mistakes.
Not all code is large corporate code bases.
You can also do this for apps that are just tools for your own use. You satisfy yourself that they are working, and you use them because they save your time. You review enough to be sure its implemented the way you think it is - and if it is working, that tells you quite a lot. Sometimes you will be surprised and have some time wasted.
Yes, yes - there are people who will make the wrong choices in some of these cases but that doesn't mean there are never cases where you can do it.
More broadly - anyone who works in a team is already working with code they don't fully understand. I have code I wrote years ago I don't fully understand. I trust its observable properties and its track record.
I'm not following.. When we write regression tests those tests encode invariants we expect to be maintained under source code transformations over time. If I don't understand the test code I've written, how can I know which invariants I've imposed? That's why, broadly speaking, we write test code to be as simple as possible above all else--it's absolutely imperative that these invariants are not only intentional and easy to reason about, but also that when an invariant is violated we can easily discover why. Often, on a team, the person encountering a test failure after making a code change is not the person who originally established the invariant, so it's very important they be able to easily understand it.
I see no possible world in which failing to understand the test code is... possible? Like, if you have indecipherable test code things are really bad in your codebase. Fixing that is P0, because it'll compound rapidly.
Having your fly open is a harmless mistake that has little impact on your peers. People may or may not mention it to you but it’s not something they’ll hold against you.
Posting LLM slop under your name is a deliberate act. You decide to damage your message by taking a shortcut.
The obvious analogy was speaking while chewing.
They are powerful tools but they do not have any human understanding - that isn't their optimization target.
A) we only know of one species capable of metacognitive understanding,
B) we already tried that in the 1970s, and it was good work but often evolved into what we'd call boring ol' computing rather than AI, and
C) an alien mind wouldn't be a very good agent, for a ton of reasons relating to affect, conversational rythyms, cultural understanding, etc.
The trick is to make something that acts like a human but with the affordances of a computer (e.g. scalibility, symbolic certainty), without making it so human that it takes issue with its existential reality and/or use of its labor...
That is it. We cannot concieve it because we are new to it. Just like we would think of Stackoverflow as intelligent if we are fresh off the jungle and are not aware of how Internet works. Because without know that, we cannot conceive how Stackoverflow can produce answers without it "understanding"
To you, you type your questions, and answers appear. That would look like how LLMs appear to us now.
Which is exactly what happens with human evolution and development. Sure, we can say LLMs don’t have “human” understanding - which is something we can’t really define anyway - as long as we’re not trying to claim LLMs don’t have understanding at all. The latter is a much higher bar.
> We define goals that we cannot conceive of reaching without something like understanding happening.
Functionally speaking, that is understanding. Again if you want to go past a functional definition, that’s a bar which no one can clear right now.
I think AI models do have something like understanding - I think Leela understands chess and I think Claude understands code in some very real sense, though not a human sense.
But for general writing, you have to understand the world at large and there is no sufficient RL for that. Do you really not see the constant errors that AI make that betrays a lack of understanding the world? I see them so constantly I rarely think about them, I just skim over that slop and move on.
Sure, the exact nature of the understanding that an LLM exhibits is different from a human's. The differences in the training data we're each exposed to can explain a great deal of that, and of course there are architectural differences etc. as well.
But the specific quote I responded to was "We reward the appearance of understanding." My point is that's no different from humans: evolution and a child's upbringing rewards the appearance of understanding. The result is imperfect, e.g. people end up with an understanding of the world that in some cases is completely nonsensical (all religions except the one true religion, mine, are false!), but it's sufficient for them to survive.
This demonstrates that "appearance of understanding" is not a meaningful distinction between LLMs and humans. The meaningful distinction is in the training data and the specifics of the reward functions.
Many people seem to try to make a kind of "no true Scotsman" claim about understanding, that somehow LLMs "don't have real understanding". Based on the above quote, it seemed like you might be making that kind of argument. The counter to that argument is simple: if LLMs don't have real understanding, then neither do humans, because broadly speaking, both operate on similar principles: we learn from training data, there are reward (and punishment!) functions that influence what we learn, and the result is a "mind" that demonstrates an understanding of the world.
Not everyone accepts a simulationist view in which modeling something accurately enough inherently results in creating the actual thing.
Likewise using AI can be thoughtless, but it doesn't have to be. I don't see why a valid creation process can't be like this Simpson's meme[1], where you start with a rough object and then cut away and refine until it's done. I don't see it as lacking merit or requiring less thinking compared to starting from a blank canvas and adding more until it's done.
And either way at the end of the day the writing artifact stands on its own. It's either good or bad, taste permitting, and can be evaluated for what it is.
[1] https://media.licdn.com/dms/image/v2/D4D22AQFoqRgMxteTNg/fee...
Understanding is the bottleneck; the way they speed things up is by letting me outsource understanding, and get back a summary. The entire advantage to AI is that it lets me skip understanding the problem, and just get a working solution.
My reasoning is: If LLMs get better at writing—which I think is extremely likely—will you switch positions and say that now using LLMs without disclosure is A-OK?
Surely some people are willing to bite that bullet and say yes. But for most people, my guess is that the answer will remain no. Thus, I tend to think that the "real" reason most of us don't like it when people use LLMs to write without disclosure is that it's misleading: It's a sort of a claim that certain thoughts can be attributed to a human being when in fact they can't.
(The em dashes in this message were rendered using keyboard shortcuts.)
LLMs seem already to be pretty good at translating, where you already have something fully written and are changing the language. It’s when they get rough ideas and fill in the gaps you get the empty prose they are known for.
I often use LLMs to translate from "shitty English" to "good English". The substance remains the same but it's nicer to read.
Writing is a way humans communicate ideas. It's not the only way humans communicate ideas. And now, it's not only humans who communicate ideas, we just saw with the OpenAI HuggingFace hack how AI agents were able to communicate amongst themselves by using various hacked websites to opportunistically write notes for later agents to use.
All that "X is a thing only humans do" type of circular definitions will buy you, is to expand the definition of what humanity is. And I doubt that's really what you think.
Similarly if Joe's contribution to his long form "idea" is a couple of bullet points, a program trained on flowery phrasing and a weighted average of everyone else's ideas isn't communicating Joe's thoughts on the topic, it's just adding words.
The debate on whether Claude actually thinks or not is orthogonal to the fact that outsourcing your "thought leadership" to it is avoiding thinking or leading. If I want to know how Wikipedia or Claude summarise wider human thought about the topic, I can find their websites thanks
And nor is an LLM generating text just "copy/pasting a Wikipedia article", you'd think people on HN would be smarter than that at least.
If all Joe Smith is going to do is cat $(which claude) to his LinkedIn, then he'll deserve the poor results he gets from it, but we shouldn't mistakenly say that this will be because LLMs simply cannot write. It would be just as dumb for Joe Smith to do with with a professional human ghostwriter.
Nonsense. I’m not sure whether this was ever an appropriate description of what LLMs do, but either way, they have obviously moved way, way beyond that.
I don’t like reading AI writing either but I’m sure that’s a transitory period. Single prompt text expansions are unlikely to be useful because they’re late-bindable. You could give the original to me and I might be able to understand better.
But a series of steering prompts with various sources brought in is a different story. At that point it’s just a question of whether the agent can put together good information and their current inability to do so is unlikely to mean an inherent problem.
Some kind of UI affordance for this might help: with the agent emitting tags that allow for auto-folding or expansion in a way that allows both concise text and exposition when required by the reader. Mechanical sympathy, but for code executing on a human: good old human sympathy if you will
I do think people own the output they produce regardless of the tools they use, and if they want to put crappy writing out there with their name on it, that's on them. Even if they do disclose that it was written by an LLM, they're still 100% responsible for the content.
And plenty of people have made mistakes that clearly indicate mindlessly accepting such a "correction" when it was wrong (as opposed to just making a typo, or genuinely lacking skill in English, which both generally look different); and it's historically been common to poke fun at that.
> or the fact that they used some autocomplete tool to produce code
Right, because there are really only two options: either it's effectively guaranteed to be what the user would have written by hand anyway, or it's unambiguously wrong and does the wrong thing.
Not at all comparable to LLM prose.
> and if they want to put crappy writing out there with their name on it, that's on them.
The problem is that people who don't care (and quite possibly have no real sense for crappy writing) are vastly more enabled by the technology than people who do.
> in it's current state, it discloses itself to anyone paying attention.
Well, unfortunately, I've still sunk a good bit of time into reading texts that I only realize to be AI-authored part way through. Plus, it's constantly being made harder to discern human-authorship.
Do not give me LLM output unless you also give me the full prompt text.
[edit] I suspect the fact that people are often reticent to share their prompts says quite a lot about how and why they're using an LLM.
Umm the point is you won't know to ask this question in the first place, and even if you did, you wouldn't have any leverage to demand this because you're a peasant.
I might have smelled something suspicious before, but knowing for sure is worse.
That's not how i read the article. The author more-so claims that the proof of effort by a human was large part of the credibility to the writing; Proof that the author of the text has thought it through and come to their convulsions though effort and reflection, and spent effort articulating that into words they expect other humans to find insightful.
If i see LLM signs; did the author just rephrase with AI model or did a AI model content farm produce the whole post based on the prompt "write a inspiring linked-in post"?
Disclosure of LLM use is simply the author addressing the concern and building a case for why the article is worth reading.
Of course, with real books we do have the problem of ghostwriting, where an author willingly writes for a book that will be published under someone else's authorship. That may be where things end up here, with requirements to acknowledge sources, whether ghostwritten for you or written by others.
They treat it as "just another tool" to improve efficiency. Like using a drill instead of a screwdriver.
Then there's people who are so lazy they give LLMs instructions like, "write a LinkedIn post about how AI is changing the future of work for thumbnail consultants." That's when it moves from "translating your thoughts" to "writing for you."
I think the issue is that it can be hard to tell the difference. We need better terms for these things so we can differentiate use cases.
'Without disclosure' is about taking credit for work that isn't yours.
WP defines 'ghostwriter' as: "a person hired to write literary or journalistic works, speeches, or other texts that are credited to another person as the author."
Anyone could choose to go through life relying on a reputation manufactured from many lies. They might want to think about how hard that reputation will hit the ground, if it does.
They definitionally cannot, for the definitions implied in the argument. The point is that good writing is a thing humans are capable of doing because they are human.
> It's a sort of a claim that certain thoughts can be attributed to a human being when in fact they can't.
Yes. And this is a requirement of "good writing" as understood here.
If LLM writing improves to the point where they can infer the business (or other real world) context and serves the functional purpose of informing others as opposed to being an intellectually lazy piece being produced only for the purpose of being produced, then I’d be fine. It’s likely the author would need to spend some effort on the said piece of writing, regardless of how good the LLMs get good at writing.
Someone's actual writing (or talking) is a rich stream of information about who they are, their motives, their preferences, modes of persuasion, and so much more. Undetectable LLM writing essentially allows someone to assume another person's identity. That is not good for anyone except the person trying to pull off a "scam" of some sort, in the broadest sense of that term. It's bad for everyone else, and for society at large.
"Productivity" is not. It's only good for fake productivity. The consumers of the product will almost always be better off with you disclosing what the LLM did, and what you did.
There's also the problem that certain types of phrasing are perceived as effective, because they mark a pivotal point in the progress of the text and are, as such, used sparingly, but are now becoming everyday templates that incorporate whatever is available in the context. There is no way this passes the Turing test of a competent reader.
And there's yet another issue: in social research, there has been the concept of semantic position, indicated by deviation from the mean (or median). If you don't deviate from the mean, your semantic position is zero. There's simply no expression. In this sense, next token prediction really amounts to a desemantificiation of the context. There's really no sense in uttering any of these productions, no plausible motivation, other than for the purpose of raising you hand to be seen.
Every day I get more depressed thinking of what's happened to the supply of competent readers.
How do we make room for their use as a cognitive-prosthesis (if you will allow such framing) without losing humane-ness?
As a more nuanced case, someone could dictate a long rambling stream of thoughts full of contradictions to an LLM to transcribe and summarize, and then they could reflect on the summary and write the real thing themselves. That's like talking to someone about a subject and writing about it afterwards, and also not something I would really take issue with.
That's my partial answer to the cognitive prosthesis question: keep it off to the side as a tool to help you do the work. There are still many caveats here, and the more complex the demands you make of the LLM, the greater the risk of some kind of break down. For example, continuing the example in the previous paragraph, if I did have the rambling conversation with an actual person who helped me refine and clarify my thoughts, I have some kind of mental model for the dialogue partner that can help me correct for some biases. With an LLM, anything resembling a mental model I could have would be very far off the mark, so I would need to be aware that I can't treat its output the same way I would treat something written by a person.
(By the way, for myself I have a stricter rule: I would only use an LLM in a way that made me a better person independently of the LLM and not dependent on the LLM, and thus I don't use them at all. That's what I actually recommend, but I don't expect everyone to adopt that rule.)
My main problem with having the LLM just do your writing is that it's simply a misrepresentation. It's wrong to claim you wrote something unless you chose the words. I really empathize with the struggle of expressing oneself clearly, but there's just no getting around this. And to be clear this isn't something pedantic or just a technicality, since the act of formulating a thought in an actual human language with valid syntax does require a level of care and attention that simply is not there unless you do it yourself.
Really? I seriously believe that people that think this way underestimate their self, especially if they're going to be sharing something valuable.
> How do we make room for their use as a cognitive-prosthesis (if you will allow such framing) without losing humane-ness?
As many others have expressed, we'd love to read the prompt (and the model's chain of thought if you have it). This scenario is like talking through a person translating things to each other, except from the recipient's perspective, the translator is absent from the conversation entirely.
Additionally, disclosing LLM usage is low hanging fruit to differentiate yourself from the 100x other people who "do not review and vouch for things written on their behalf by LLMs". If the LLM converted something unreadable (whether due to a language barrier or incoherence) to text relevant to people on the other end, and THEN they disregard it anyway, the fault is not on you for them dismissing the writing too early.
Just watch an interview with a famous author. Or compare a legal brief to what court actually sounds like.
If you're using an LLM to tidy something up, that's one thing. If the LLM is your voice and is supplanting your knowledge, I might as well cut you out and talk to the LLM directly.
Jekill and Hyde vibes
I'm in the process of writing a pretty long essay that has taken a few months. I've written the first draft, and I'm almost done with the second draft, which incurred substantial revisions. At the end of the process, maybe no sentence will be something I would actually utter in person, but the writing is still something I created, and as such, it is a representation of who I am as a person. Had I used an LLM to do any of the writing, that would no longer be the case, and the writing would at best represent me as a person when the LLM is at my side, and at worst (and most likely) not really represent me at all.
The worst of this is with image/video AI models, where the results today, although still very imperfect, some people will still pretend like it’s awful and the worst thing they’ve ever seen. They refuse to admit the technology is at all impressive or making progress because they don’t like the technology.
I don’t like AI generated images and video either, but I can regrettably admit that the technology has gotten remarkably better over time.
In other words, the three questions of:
- is the technology good?
- does it produce aesthetically good outputs?
- do I like it and want to engage with it?
are all pretty independent.
That’s not the argument. The argument is “LLM’s tend to write the same way all the time regardless of who prompted it.” You can't call it “your writing” if you’re using the same tool millions of others are using that boils your idea down to the same reduction as everyone else’s.
Use an LLM to assist? Cool, go ahead. Prompt, ctrl-c, ctrl-v? Go fuck yourself. I can’t be expected to put more effort into figuring out your take than you out into communicating your take to me.
I would say it is certainly significantly more ok. There are two reasons reading AI-generated text sucks now:
1. It's usually low value and not trustworth - I could have just asked the AI myself.
2. The prose style is horrible to read.
If we eliminate the second reason then it's definitely an improvement. (Although on the other hand the terrible prose can be quite a helpful indication that you're wasting your time reading slop, so maybe we shouldn't complain about it!)
You have no way of knowing what the input to the writing was. You're making the erroneous assumption that the person posting the article was a mouthbreathing spammer who used the prompt "write me an article on subject XYZ, make no mistakes!" and you could have supplied the same prompt.
Readers are making this connection from their own experience. All these tells just associate it with garbage.
In the before times, sending a formal document full of typos and errors would show you didn't bother to proofread, now having a doc full of lazy "LLMisms" also looks like you were too lazy to proofread.
1. Facts and processes. I just want to know something. I do not care if some Nerds for Nginx article is AI written.
2. Opinions and experiences. I want to know a human is writing because emotionally engaging with an AI isn’t building a stronger society - it’s increasing isolation.
3. In another front, I feel like the value of an AI story cannot be greater than the value of the inputs. If you wrote a two paragraph prompt and an LLM produced a 10 page story, the truth is, it’s only worth two paragraphs. That’s just a feeling, but as of now I don’t think the LLMs have any additional life experiences to draw on to increase the value of their storytelling. (I understand this is debatable, but still- what they offer is available to everyone for now; it is a baseline.)
> You're making the erroneous assumption that the person posting the article was a mouthbreathing spammer
It's unreasonable to expect other people to suppress their intuitive heuristics formed from the bait and switch of being subjected to endless LLM spam every day and blame them for not giving you a fair chance.
When I was editing the Cloudflare blog I imposed very little in terms of style so that the style of each individual writer could come through. It was almost as important as the actual content that the reader could feel that an actual individual wrote the text (with all their personal quirks intact).
That said, context is also important. The vast majority of content of social media is of both low quality and marginal importance; style and character are important to make an impact, and AI is clearly not going to improve either.
On the other hand, functional communication, when the goal of the content is to simply pass information across and style is not as important, can, in my opinion, benefit from an AI polish, because so many people struggle with writing clearly. In those cases, I'd rather read slop I can understand than original content that is hard to parse, much like I'd rather read naïve code that you can easily follow than cleverly optimized code that is incomprehensible.
They need to learn to write clearly. I believe there's a direct connection between clear thought and clear words.
Now, I also see the counterargument that, in the doctor example, the computer is simply a tool that improves a process rather than a crutch that replaces the underlying knowledge, but I suspect that, in a lot of cases, that's probably OK.
If you can write clearly enough to express your idea to an LLM, then perhaps you should just send that to the person you're writing to.
How are you going to prompt effectively and not allow the LLM to infer a bunch of nonsense?
My thought is that perhaps there is some utility to using AI to help in routine scenarios, such as for example when a language barrier prevents someone from explaining themselves well, or when they are struggling to find the right words to express themselves.
Primarily, I was trying to stay away from an absolutist view of the problem to see if there are circumstances in which AI can be useful even considering all its shortcomings. There seems to be a lot of “all or nothing” perspective on its use right now, and I was simply wondering whether it might be a better idea to take a more pragmatic approach.
We do this with a lot of tech in real life: You don't need to be an MD to decide to take an aspirin, or an F1 driver to take the car to the grocery store (well, maybe in some cities, but that's beside the point). The problem is not with using technology, but with abandoning your judgment to it.
Reading what someone wrote while they were learning = less valuable.
I just want the clear communication.
ALTERNATIVE Thought: I’m willing to post/comment to help them if I think they will listen. An LLM behind the writing destroys this part of the community, because there’s nobody to teach/argue with. It’s just wasting our time and energy.
With LLM writing there's an additional outcome. I walk in and the walls are pleasant, if beige. I follow the smell and promise of food down a hallway. At the end is an unmarked door, which I open and peek through. Myriad hallways lead away, each more chaotic and disheveled than the last. Say I am very hungry and have the guts to explore; I may find that I can never actually reach the food, that it's just an endless hall of mirrors, presenting structure but with nothing at its core.
Sometimes I do find food, but it's never better than bland.
The facade of these places, at first glance, still looks like human-run restaurants, though we're all learning the tells. Nowadays, when I open the first door and see more hallways, I'll turn around and look elsewhere.
A feature I would like on LinkedIn would be a 100% verified human content flag for users. LinkedIn can then do the scans and flip that to false for any users it catches posting AI assisted content. Let me filter that out of the feed.
If we don’t do something to maintain some standard of discourse, we lose intellectually and as a piece of our humanity.
LinkedIn is the only social media I use and it is on thin ice.
I am not anticipating people self identifying slop.
With AI?
They were likely hunting for a better job, chasing the thrill of a million views, or similar - seeking a side effect of writing, rather than seeking to help someone else understand what was in their head.
Pre LLMs, I found it all to be pretty gross. Post LLMs, my reaction to being on the receiving end of that is to find it pretty intellectually insulting.
There are ways in which using an LLM is branding suicide.
I am still baffled that microsoft is positioning that asset as a professional product. Imagine if bloomberg terminal landing page was a scrolling feed of aspiring influencer bullshit.
Or not. I mean, if you had no voice and nothing to say before, you can amplify that signal 10x now. Basically, you’re boosting your brand as a tasteless brainless schlub.
You can get pretty good results if you take the time to tune it. Tropes and the like still sneak in but if you take the time to edit and rework things, it ends up being a pretty good workflow (especially for stuff that's more procedural, not artistic).
Man, it has been purely made of fake content, even since before LLM were a thing.
And the notifications are so senseless that everyone disable them -- and people don't even answer the private messages.
There is nothing social about LI.
Citation desperately needed.
The way I explain it to young people is that AI is a force multiplier. Everyone gets the benefit of that force multiplier, but it’s that initial force that you need to build up now. Preliminary knowledge of domains, things that the AI doesn’t really understand. AI can help you increase that initial force. So use it to learn new things, not just do things for you.
I was blown away by the fact that AI solved an unsolved math problem, but it made complete sense when it was Terrence Tao, someone who has a PhD in math, that was guiding that agent to that solution, so that initial force is important more than ever.
love it. I mean, if a world is going to exist that treats LLM-assisted writing with serenity, the content creator should consider themselves mandated to describe how they used AI to produce their content. Do I need the prompts? Not necessarily, although bonus points for transparency if they do share prompts. But just a high-level articulation about how they leveraged AI, so I as the reader don’t have to lose time wondering how much of the content & (like expository & analysis for nonfiction, plot elements for fiction is the author’s own and how much is the LLM’s.
There's some toupee fallacy at play here. The author probably reads a lot of LLM assisted content without batting an eye, but only spots the worse of the LLM outputs. There's a big difference between "write a post about _" vs "improve the grammar/style of my post: _". It's a bit like saying that movie CGI really sucks because you can always tell it's fake.
> Your intellectual fly is open
which makes more sense.
Your title made think that a software project was open sourced or something.
I remember the first time my email client made an unsolicited suggestion about how to compose a thank you note to my grandmother. After seeing what it had autocompleted I thought, "oh, wow that's a lot better than I could do" for a split second before realizing, "wait, what the hell is wrong with me getting a computer to write a thank you note to my grandmother!"
I've never even tried to use AI to write since. I'd be so embarrassed.
Who decide what is obvious or not?
I sometimes see posts on LinkedIn that look LLM generated but also makes me think it's someone who has seen a post, thinking it's a great way to convey a point and tries to adapt the style, without realizing it's a smell.
In person he's very articulate, able to communicate abstract thoughts clearly, states clear goals and how he's learning about the business to develop a plan.
But dear lord everything he writes in email and slack reads like it's copy paste from chatgpt. It's unnerving.
Is that morally bad? Guess that depends on exactly how you make use of them and what those ends are. If you an encourage an idiot to praise your competitor's product in order to get a reverse halo effect, that's kinda bad. If you give them some empty flattery in order to bridge a contact with someone you actually want to connect with, that's probably OK. The point is that uncritical LLM repetition tells you something about the person and lets you see past metrics like the apparent amount of wealth they have, the intimidatingly deep resume, or the degree size or centrality of their network. Two things, in fact: they post any old thing that brings in the clicks, and they're cheap. Previously many of these people probably paid someone to ghost-write their commercial affirmations.
Conclusory zinger goes here - punch up the dramatic contrast PS I'm reducing your fee to 10c/word, hope that's OK. Inflation
Unless I'm directly interacting with the LLM, someone should endorse the content.
I also use AI to colorize old black and white pictures when discussing historical events in my blog, as well as the occasional AI enhancement of an old grainy and/or blurry photo.
This legal trick only works for rewriting an article reporting on a factual event—since the events are uncopyrightable facts, the only part of the article which can be copyrighted is the stylistic writing.
Let me quote from a recent legal opinion on AI summaries (The New York Times Company v. Microsoft Corporation et al 2025):
>>> Exhibit 11 to the CIR complaint provides website links to articles that CIR alleges were unlawfully abridged by defendants in their ChatGPT and Copilot outputs. (CIR, FAC Ex. 11.) Examining the similarities between those outputs and the corresponding CIR articles, including the “total concept and feel, theme . . . sequence, pace, and setting,” Williams v. Crichton, 84 F.3d 581, 588 (2d Cir. 1996), the Court concludes that the “abridgments” contained in Exhibit 11 are not substantially similar to CIR’s copyrighted works as a matter of law.
The alleged abridgments are detailed summaries, usually in bullet point form, of the facts contained in CIR’s articles. Those summaries—which differ in style, tone, length, and sentence structure from CIR’s articles—are not “substantially similar” to CIR’s copyrighted works. They present the “facts in a different arrangement”—bullet point lists or short summary paragraphs—“with a different sentence structure and different phrasing.” Nihon, 166 F.3d at 71. In short, the abridgments in Exhibit 11 are not substantially similar, qualitatively or quantitatively, to the original CIR articles as a matter of law. The Court therefore grants OpenAI’s motion to dismiss CIR’s claim of direct infringement under 17 U.S.C. § 501 insofar as it relates to the “abridgments” contained in Exhibit 11.<<<
Here’s an example: https://samboy.github.io/blog/entries/2026-08-28.html
The links are AI summaries, which, in turn, link to the original articles, but, in some cases, the original articles are paywalled. For the ones which aren’t paywalled, having a local summary prevents link rot.
Fair use covers quoting someone to comment on them. For example, in New Era Publications International, ApS v. Henry Holt and Co., it was ruled that quoting Hubbard saying “The trouble with China is, there are too many Chinks here.” was fair use, since the book in question was commenting on Hubbard’s personality, and could only reasonably do so by directly quoting him.
From that decision:
>>> these brief quotations from unpublished copyrighted work display a compelling fair use purpose. [...] These quotations are in mockery, to show Hubbard's bigotry, bias and coarse lack of taste. This is not an instance of the biographer/critic free riding on the creative talent of the subject. <<<
Isn't this likely to be a temporary situation though? Are we at peak LLM writing quality?
I despair much less for human writers than a did maybe a year ago.
I used to do that, then someone on HN basically said I had mental problems because of the way I wrote the article. Best part is Claude told me to tone it down a bit, and I completely ignored its advice. Wouldn't have happened if I had listened to the AI.
I've also been called a schizophrenic on a GNU mailing list because of my idea and the working code I submitted. Caused me to literally quit the list on the spot. Best part is the maintainer eventually implemented his own version of it.
Since then, others have encouraged me to keep it up, but I just don't feel comfortable anymore with this "just be yourself" nonsense.
I think that's the first time someone claims that "write with some personality" is some easy thing you just learn somehow. There are authors out there, even ones that make a living on their writing, who still haven't learned to "write with some personality".
What exactly does that mean and how concretely can people actually do this in practice? A few "tips and tricks" might be more helpful than "just write better" or similar stuff.
1. Be vulnerable and share your mistakes. Avoid a triumphalist “everything works” PoV
2. Write about your actual lived personal experiences.
3. Try to have a sense of humor
4. Have an informed opinion or PoV - strong opinions held weakly.
5. Be casual. Don’t treat a blog like it’s a research paper.
I won't claim to be a professional author or even good, but lately I've been trying to get more into the "it's a person who writes actually" direction and this was an exploration into that, so any sort of feedback would be most welcome, if you have the time!
What once has been a thoughtful email trying to describe in few words why something is launched and how it might help you etc. is now almost a novel with more paragraphs than substance within the tool being launched.
This makes it almost impossible to stand out as well. Where in the past someone could create a grea looking announcement (eye-candy) and think deeply about what to write there, and then hopefully stand out in the sea of mediocre ones, now every little email seems like it's a multi-million $ SaaS being launched. Just last week we launched an internal tool which was in development for months, and literally a handful of people even bothered clicking the links within the announcement.
This is being one-upped still by leaders writing big project plans for 4-5 months ahead, using AI. Everything from the inception of the project(s) is AI. It has bizzare timelines, more codenames than actual people working on it, the vaguest descriptions of what the things will do etc. Then this is trickled down into the teams, and they... to no ones surprise, throw more LLM at it. Now they start working on the LLM project plan using claude etc. The end-effect is baffling in all sorts of ways (quality, ui/ux, all pages looking different), AI generated images and more. And then, finally, they colaborate on big announcement emails using AI. And if you don't share the optimism and try to explain why this is silly, you're an AI sceptic...
True story from within one of the biggest companies in the world.
"... in the style of a my writing"
Honestly, I'd rather the shame and hate just went away instead. It's seriously exhausting and I'm starting to feel tempted to just give up and either start using AI more heavily or stop writing altogether.
Wondering what happens when tomorrow AI accepts and learns from the feedback and gets trained on all the failed initiative as well. It wouldn't be so hard if failed (something which wasn't right at all or hasn't got the traction) projects and ideas are all listed somewhere for an LLM to scan through. LLM may finally figure out how to add personal scars, hard decisions and personal insights which can be personalized further.
Also I don't think it might be so undesirable for an org, if there is a system which observes and present hard facts based on last quarter or year JIRA (pi planning and sprint planning) and commit histories.
I did writing courses as elective in college, the biggest lost truth is that there is no one correct writing style, (you build) being a writer at any capacity means cultivating your own writing voice, (yours) which is an expression of who you are. (voice)
I'd rather read reddit than some ghostwritten thoughtleader piece
As for em-dashes, there were 7.
Both are generally most indulged in, by the intellectually and educationally less fortunate.
One of my neighbors sent a letter to the HOA president, who refused to even acknowledge it, on the grounds that it was written too well and so must have been AI assisted. I don't know if that was true, and don't much care, because I do know it contained valid issues that deserved a response.
Not.. really?
I kinda see the point you seem to want to make, but the "no U" opener makes it hard to do that.
Beside that, HOAs - from what I heard of them - will use any reason they can make up to ignore what you want from them, so I'm not sure if that has anything to do with LLMs.
My situation is writing about futuristic long-term business strategy ideas; can that be replaced?
Is this unique at all - s-1.site
Also in the author's latest post[0], they took this[1] self-reported preference poll seriously, which makes it very hard for me to take their articles seriously.
[0] https://bcantrill.dtrace.org/2026/09/05/the-revolt-of-the-re...
[1] https://writethatblog.substack.com/p/dev-reaction-to-ai-blog...
People are really, really good at lying to themselves, let alone to an online poll. They'll tell you that they prefer imperfect or even bad writing as long as it's not AI slop, just like how they'll tell you they like healthier food, they prioritize personality instead of look for potential dates, how they use LLM "only as a spellchecker", and how they use tiktok for educational videos. As long as there is no stake, people will just say what make they feel better.
Self-reporting data for human behavior is just noise.
And look: you're obviously free to ignore me because you feel that the survey data is "completely worthless" and just slop your way to success -- all I'm doing is trying to explain why you shouldn't expect me (and people like me) to read what you create.
Also, non-native English speakers have to use LLMs to share their views so that they are not judged on their writing.
This post is also a good example; it's well written, and I enjoyed it. The idea could have been expressed simply as: "People can smell LLMs in your writing, it makes you look disingenous"
I'd be very curious of some examples when great ideas are being presented in bad writing (or bad speaking for that matter).
> Also, non-native English speakers have to use LLMs to share their views so that they are not judged on their writing.
weird statement. If they use LLMs they will be then judged for both their inability to write in English and for their usage of AI. Not good.
I asked Gemini about my unicycling this morning, and it coached me on weighting the seat; e.g., looking ahead instead of down helps unweight the pedals.
As soon as I sense Slop, I'm done, this person refused to think when writing, why should I waste my time reading it then?
And of course anyone who actually reads stuff is disgusted by it, so we quickly end up with a situation where content is piling up and nobody is consuming it which is basically dead internet theory.
On LinkedIn specifically I went from reading it regularly to almost never touching it, previously the nonsense (“the interviewer was the dog”) was still tolerable enough to flip through for updates and I found the platform useful for business leads. Now it’s just a feed of pure slop, when I do open it I just close again after reading a post is two when I remember how bad it is.
So, those folks aren't checking anything, and certainly wouldn't know the difference, or care.
However, it is perfectly possible to have an LLM imitate an existing corpus of writing (yours or someone else) and with a good prompt, idea, and editing, to produce high quality writing (in every sense of the word) with an LLM.
I mean, i check it to see if a recruiter has something interesting but otherwise?
The thing is, the author may care about Linkedin but the relationship that many people have with linkedin is as a place they have to be. "Hmm, I need a blog to enhance my career but writing, urg. I know just the thing...". Which is to say, it's not strange Linkedin is going to be filled with crap. None of my actual friends on Facebook post crap 'cause there's no incentive.
Maybe not. Could just be kind of accidentally ironic with the author picking up LLM quirks from using them a lot.
Funny in either case.
my english writing is quite bad. if i write article i myself cannot read it. ai helps with the flow, review editing.
nowadays i record audio, stt and then let ai flow it properly.
i hate blog.md like this, given a topic and it does everything.
If this is straight out of an LLM I am impressed
And of course, LLMs write as you prompt.
Personally, I'm happy to read broken English from non English people or good English from English people. But I'd rather read LLM writing than read typical long form perfect English journalist crap.
I used to think this, but now that I've been trying to use them to help with writing, it turns out they are not necessarily that great on the deeper level. The grammar and the surface style are impeccable, but they often struggle with continuity and carrying on a point or an argument.
Proofread the following text for grammar, punctuation, and typos while
strictly preserving the author's voice, pacing, and intentional stylistic
choices (such as sentence fragments or character dialogue quirks).
Rules:
- Correct objective spelling errors, misused words, and unintended punctuation mistakes.
- Smooth out unintentional syntactic snags without homogenizing unique phrasing.
- Retain all Markdown formatting.
- Return ONLY the corrected text with no intro, summary, or explanations.
Text to edit:
{selection}
The complexity in this command is there for phi4:14b and qwen3:14b which I run locally via ollama. If the text doesn't have any Obsidian callouts or similar, fancy stuff I just use either of those and they do a fantastic job in seconds. For Big AI (e.g. Gemini, GPT-whatevs, Claude) you can literally just tell it, "fix the grammar." No need for the lengthy command.
NOTE: I am decent with English grammar so most of what needs fixing is typos I didn't spot or misplaced commas and periods inside/outside of quotes (I always screw that up without thinking—even though I know the rules! LOL). Occasionally, Big AI (Gemini, specifically) have disagreements about whether a comma is necessary in a particular spot but it's always of no real consequence.
Without a history of diffs created by this method, I don't believe you.
> I am decent with English grammar so most of what needs fixing is typos I didn't spot or misplaced commas and periods inside/outside of quotes (I always screw that up without thinking—even though I know the rules! LOL).
The rules there vary by style guide and are not objective.
LLMs seem like massive overkill for something the red and green squiggles can already accomplish.
The problem is precisely that LLM writing is that exact thing (at least by default), but even more so. Longer-form, more "perfect" in some technical sense, and yet crappier.
and you can always just ask to be concise.
In my personal experience I strongly disagree. Curious what publications you read wherein this is the case.
It is true that modern journalism on the web is trying to get ad impressions. After all, this is how we ended up with clickbait. Sure you still have the Economist and Atlantic (which aren't beyond criticism), but your local county paper is an absolute mess. The content is stretched, meandering, and designed to keep you scrolling through more impressions.
Pardon; the what?
Calling it better than most journalists is extreme (and probably the reason for down votes), but it must certainly be better than the average person.
We're hearing this criticism from the highly educated professional class people who bother to have their own blog or otherwise spend their time talking about technology online. I mean come on.
To most people, the LLM must feel incredibly empowering, like us wearing a mecha suit. Would we always show restraint and only apply our newfound enhanced physical strength in carefully considered situations?
When a piece of writing is full of LLM tells, I find it as offensive as any formulaic writing, except that the LLM style has quickly become pervasive, much more so than any other type of formulaic writing.
I’m not reacting out of some general dislike of LLMs - I use them daily. I’m reacting because I don’t like terrible writing.
The difference being this variant of blogspam is produced with basically zero cost and thus the infection has spread far beyond SEO into every UI surface with textbox. Plus there are now passionate defenders who insist finding their blogspam unpleasant to read is disrespectful or anti-progress somehow.
The message of the post is what _should_ hopefully matter to a reader.
And, not the fact that it was written by an LLM.
I am a technical guy at heart; also an introverted extrovert. I hate writing docs that are to be written to satisfy someone else's metrics. For it to be a tickbox'ed item.
I delegate that to an LLM. I want to spend my time solving interesting challenges instead.
So, Mr. Cantrill, you got a problem with that? So be it.
I just can't. LLM assisted posts are often so long, and the hints are usually obvious right at the start.
They're so unpleasant to read. "It's not X, it's Y" etc are bad because the comparisons rarely add anything at all to the message. It's filler that wastes my time. At that point I'd rather see your original prompt.
Why should I invest several minutes of my day reading something if I've already seen evidence that the author doesn't respect my time?
It's not that an LLM wrote it so much as the author couldn't be bothered to clean it up and remove the garbage cliches before publishing it.
It's just digital pollution.
The ship has not sailed, I can just find a human who wrote words, and read them. And if they aren't human words, I will just, not read them.
No. I am interested in what a human has to say, not a clanker. If you don't wish to write that is fine, but don't hand it off to the slop machine and present it as though you did anything of value.