Even if you don't want style advice from an LLM (I generally don't, not for blogging), for a technical blogger "please check this post for factual accuracy" is a good way to not look like an idiot. Often it complains about hyperbole, which I tend to ignore since there's no point blogging unless you have some firm opinions, but on at least one occasion it pointed me towards some documentation that undermined my entire post - and led to a much better one a week later once I'd processed and applied that new information. Thanks, LLM.
I do this all the time. It's shocking how well it works. A year or two ago suggesting that someone use LLMs for fact checking would get you laughed out of a room, but today the good ones (Fable, GPT-5.6/6) with a search tool enabled are genuinely excellent at this.
They can even retrieve articles you link to and check that you aren't misrepresenting them.
I fear in the future people will read even less because of how often people cheap out and use AI to write.
I know the author of this article tells you never to use a single word it suggests, however I still, while reading, am checking for any amount of AI used.
This makes reading less enjoyable, and even a bit stressful.
If you can't spend the time to write it, why should anyone read it?
Everything I post is from my own finger tips, only to get a reply from someone using a bot. I'm tired.
> If you can't spend the time to write it, why should anyone read it?
That's actually a legitimate question, and one I've been thinking about, as I've been using LLM tools to compile factual information based on various search tools it uses. The workflow gets sources, fact checks them, filters them according to my needs, and gives me clean urls for source information to hand off to an editor for writing a short listing. It's very hard for the editor to do a much better job at this type of writing; the real benefit of the work was in the research, which was handled by the LLM. The rest is basically just putting the facts in the right order, with some guidance on style, preferred word choices, etc. I'm not comfortable with this at all, as giving work to an LLM that a human could do strikes me as wrong. But using LLM tools gives me a big competitive advantage (for now), in the space I'm doing this in.
> compile factual information based on various search tools it uses. The workflow gets sources, fact checks them, filters them according to my needs, and gives me clean urls for source information to hand off to an editor for writing a short listing.
What’s preventing the editor from using one of your prompts/tooling and replacing you entirely?
There’s zero value in sharing ai-generated output unless your ai has access to something nobody else’s does on which to base things. If all it’s doing is web research you should share your prompt instead. That way people don’t have to deal with ai-written walls of text.
> What’s preventing the editor from using one of your prompts/tooling and replacing you entirely?
Well, they don't have the many other pieces of the business in place that makes this work meaningful. They certainly could try, though. If they succeeded, this aspect wouldn't be what made the difference, though.
>I'm not comfortable with this at all, as giving work to an LLM that a human could do strikes me as wrong
Where does this feeling come from? Is it just because the work is complex? We’re all (excepting maybe the amish) comfortable with using at least some automation, be it mechanical or digital, elsewhere in our lives
Excessive generative AI output devalues all communication media unfortunately. As a greater and greater portion of text, imagery, audio, and video come to be synthetic, I don't see why anybody would be motivated to do deep reading, or listening, or analysis of said media. It's frightening to think what that might do to our civilization, almost like putting us back into a weird version of the ancient past when nobody was literate, save the priest.
Maybe humans can adapt to care about generated content and treat it with the same emotional weight that human communication has. I don't know if that's good or not.
I don't ever watch TV or streaming shows anymore. It's been a huge improvement in my life. It's the same with reading. Reading is mostly a waste of my time, with some notable exceptions. I'm glad I spend way less time doing each of these!
I've seen this in action as well. The biggest value by far is seeing the overused phrases and tics in your writing style. The prompt I like is to tell it to highlight and flag passive voice and run ons since those are my major pain points. I can also tell when its getting out of "real" advice since it'll offer the same "trim 10-15%". Also important to tell it to highlight specifics otherwise it'll give vague editorial advice that isn't anchored. Another fun exercise is to submit other authors writing as well. Say a short story from a magazine. Some of the edits are legit, but do it enough times and you'll start to see the same generic writing advice gets applies to just about any input.
another iteresting thing models can do is to highlight and notice themes and motifs in a piece. I find that helpful when thinking about a piece of work. Might be obvious ones, sometimes it can be subtle themes. Good for stirring your own brain.
Yeah it's very short, but I can't remember if I read all of it, or just flipped through pieces. It has good advice and I think fairly "famous." (edit: this reminded me I still have my copy :-D)
I know someone in a profession that does a lot of writing, and it blew my mind how clearly feedback was communicated by a superior. Made me wish tech people had better written communication skills. ;-;
Can't vouch for that but I can vouch for `Dreyer's English` as both hilarious (if you're the sort of person who relishes finding le mot juste, like me) and excellent as a style guide.
This is similar to how I've come to use them but it's focused too much on the mechanics or writing. I've found them more valuable at role-playing as a specific profile of reader and asking it how they would receive the arguments advanced by the writing and what counterarguments they could present. After some rounds of this process, you either close all the gaps in the argument or realize it's not a strong one.
It's darkly amusing that while the author advises us not to let LLMs pick our words, their post includes this chunk of AI slop:
"Those rethinks are load-bearing parts of your voice. Readers won’t put their fingers on what’s wrong, but they’ll sense that you’ve become artificially-flavored."
The metaphor at the start is AI-like weirdness too: "without pasteurizing and jacking it with corn syrup." Pasteurising is good, corn syrup is bad - what the heck am I supposed to make of it? It's nonsense.
It may even have been handwritten by the author, but it's slop nonetheless.
You may be telling yourself that you're disciplined and you're just using the LLMs for review. But while you're reading their output, the slop makes its way directly into your brain anyway - and then it drips out into your writing.
I saw "load-bearing" there and instantly assumed Thomas was making a deliberate point that it's OK to use terms that LLMs have poisoned provided you use them effectively and in a way that adds to the piece.
I'm personally furious that "load-bearing" has become an LLM tell, it's a really useful metaphor!
"Those rethinks are load-bearing parts of your voice."
Loved the (possibly not deliberately ironic) use of the LLM'S favourite analogy, load-bearing.
Nice wee article though. I particularly agree with "Don’t take all of the model’s copyediting advice." I've been using LLMs to review teaching material and often it just doesn't get the point of teaching. It's good for prompting reflection on your writing but it's still an idiot savant.
- Establish a single thesis an external reviewer could recover from the diff.
- Unify vocabulary across code, comments, tests, and commit message.
- Use the same vocabulary consistently to refer to the same concepts.
- Keep every hunk that serves the thesis; consider the removal or deferral of the rest.
- Introduce abstractions at the point of need.
- Align tests to narrate the same story as the implementation.
- Reconcile the commit message and the diff.
- Order changes expositorily, not chronologically.
- Explain what the change does and why. Do not explain the details of the development process.
- Prefer to edit subtractively.
- Recompile and run all relevant tests after edits.
- Iterate.
They can even retrieve articles you link to and check that you aren't misrepresenting them.
If you can't spend the time to write it, why should anyone read it?
Everything I post is from my own finger tips, only to get a reply from someone using a bot. I'm tired.
That's actually a legitimate question, and one I've been thinking about, as I've been using LLM tools to compile factual information based on various search tools it uses. The workflow gets sources, fact checks them, filters them according to my needs, and gives me clean urls for source information to hand off to an editor for writing a short listing. It's very hard for the editor to do a much better job at this type of writing; the real benefit of the work was in the research, which was handled by the LLM. The rest is basically just putting the facts in the right order, with some guidance on style, preferred word choices, etc. I'm not comfortable with this at all, as giving work to an LLM that a human could do strikes me as wrong. But using LLM tools gives me a big competitive advantage (for now), in the space I'm doing this in.
What’s preventing the editor from using one of your prompts/tooling and replacing you entirely?
There’s zero value in sharing ai-generated output unless your ai has access to something nobody else’s does on which to base things. If all it’s doing is web research you should share your prompt instead. That way people don’t have to deal with ai-written walls of text.
Well, they don't have the many other pieces of the business in place that makes this work meaningful. They certainly could try, though. If they succeeded, this aspect wouldn't be what made the difference, though.
Where does this feeling come from? Is it just because the work is complex? We’re all (excepting maybe the amish) comfortable with using at least some automation, be it mechanical or digital, elsewhere in our lives
Maybe humans can adapt to care about generated content and treat it with the same emotional weight that human communication has. I don't know if that's good or not.
E.g. in one country, 21% of high school students do not even achieve “sufficient reading literacy”…
So the question should be - what are we going to do with this? LLM can produce texts but we as people will not be able to understand anyway…
About PISA research for example here: https://www.edweek.org/leadership/reading-ability-craters-on...
another iteresting thing models can do is to highlight and notice themes and motifs in a piece. I find that helpful when thinking about a piece of work. Might be obvious ones, sometimes it can be subtle themes. Good for stirring your own brain.
Does anyone know about "Style: Lessons in Clarity and Grace" ? Seems like an interesting book
I know someone in a profession that does a lot of writing, and it blew my mind how clearly feedback was communicated by a superior. Made me wish tech people had better written communication skills. ;-;
This is what you need to know. Seriously, after 25 years in news (writing), you realize that you need “second eyes”, not the first hands.
"Those rethinks are load-bearing parts of your voice. Readers won’t put their fingers on what’s wrong, but they’ll sense that you’ve become artificially-flavored."
The metaphor at the start is AI-like weirdness too: "without pasteurizing and jacking it with corn syrup." Pasteurising is good, corn syrup is bad - what the heck am I supposed to make of it? It's nonsense.
It may even have been handwritten by the author, but it's slop nonetheless.
You may be telling yourself that you're disciplined and you're just using the LLMs for review. But while you're reading their output, the slop makes its way directly into your brain anyway - and then it drips out into your writing.
I'm personally furious that "load-bearing" has become an LLM tell, it's a really useful metaphor!
Loved the (possibly not deliberately ironic) use of the LLM'S favourite analogy, load-bearing.
Nice wee article though. I particularly agree with "Don’t take all of the model’s copyediting advice." I've been using LLMs to review teaching material and often it just doesn't get the point of teaching. It's good for prompting reflection on your writing but it's still an idiot savant.
TLDR: Don’t.