Depends on what’s being written, and who the audience is. Anything of any length would be hard to simulate in a way that would fool an author - writing has a certain flow to it. A cadence. The editing and restructuring, deleting of words, typos you don’t catch until some random reread, rephrasing of sections because you want to use the original phrasing later in the piece.
Could you simulate something be typed? Trivially. Could you simulate something be drafted? Honestly, even if you wanted to put in all that time and effort, I’m not even sure LLMs are sophisticated enough to send the logical drafts, loops and edits that would pass a writers sniff test
To claim there was amazing progress in the past therefore there will be amazing progress in the future is an inductive fallacy.
And as someone who gets dozens if not hundreds of AI generated emails I have to go through every day, it is _incredibly_ easy to spot which ones are AI generated and which are human written.
By its nature AI generated content is statistically consistent, the narrative equivalent of monotone speech. I don’t know anyone that can’t spot it a mile away at this point, and the more people are confronted with slop, the more attuned they become to it.
I think it’s safe to say that this will not be consensus. Personally, I am getting increasingly (irrationally) angry at AI generated content. AI generated art quite literally makes me nautious. I mean an actual, physical reaction where I feel queasy.
I know I’m not the only one who feels this way, and notice more and more people reporting the same. Several of my non-technical
AI generated content is bland and soulless. There’s only so much bland and soulless most people can take in their life before they start to get fed up.
When everything feels the same, nothing is interesting anymore.
As a developer who has not been able to get any boost in productivity from coding agents, I find it incredibly easy to deny.
I’m a solopreneur, if I could lighten my load I would. However I have yet to save time using coding agents, with the exception of “I made this change to my model file, update all model to match the new format.” Which is cool, but maybe 0.01% of my job, and took a 1 hour task down to 10 minutes.
Personally I only find his swearing and delivery annoying when he is not delivering his point well (ie reducto ad absurdum). I’d be welling to bet a good amount of the complaints about his swearing are really just from a poor delivery, and people don’t know why, so they latch onto his swearing.
His early stuff was just as degenerate and vulgar, but was much less of an issue for me.
I don’t get me wrong, I’m on Ed’s side and get where he’s coming from. I just think his arguments are normally taken to the extreme, making them less defensible, when he could make the same arguments from a more moderate stance and ultimately be more convincing.
His arguments, albeit valid, can often sound like reductos ad absurdums the way he presents them.
I do think Ed in intentionally ignorant of the capabilities of LLMs. But I also don't know that I would classify LLMs as 'wildly useful' for coding. Most productivity gains seem to be hallucinated, and while it's too early to make any claims on long term outcomes, there are plenty of studies indicating they might be even more negative.
There are definitely use cases for LLMs in coding. And at times, they can be wildly useful. But I feel like the industry atm wildly overestimates their broader/long term utility.
Anecdotally, I have not seen an explosion in quality/bespoke software since LLMs. In fact I've noticed the opposite to quite the extreme. Not only are new products worse in quality, but the quality of existing products is falling off a cliff.
To continue paraphrasing Steve Jobs, focus is the most important thing. When the cost to produce new features/implementations goes down, focus is even harder (and even more important).
It took me probably 5 years of writing Clojure before it clicked. Once you get used to structural editing and repl driven development, it’s really hard to go back to syntactic languages.
It’s kind of like in treesitter style editing, where you can “swap these two arguments,” “select this function,” “wrap this in a try block” with a single keyboard command… but way more standardized and granular. Plus with the ability to execute anything you highlight
All that and then you realize you can store code as data (since it’s just a data structure) and run data as code.
I think most programmers don’t realize how arbitrary the difference is between code and data until they get used to using LISP.
Not in many tasks. I use deepseek as a fallback in https://phrasing.app and it’s always very apparent when it happen (due to mistakes/clear performance drop off)
I think it really depends on what you’re doing. I use mistral for many tasks in https://phrasing.app and they blow models many times their size out of the water.
None of my tasks use reasoning though (reasoning actually kills the performance) so perhaps that’s why. Still, I just had to rewrite my pipeline, and mistral was both faster, cheaper, and substantially better than any alternative
The original comment was used as proof of a trend that vendors are raising prices. Would running out of coupons indicate a trend in rising pizza prices?
If you run out of 50% coupons to your local pizza joint, did they double their prices? Does every company double or triple their prices after Black Friday?
There’s a pretty significant difference between saying someone tripled their prices, and a temporary promotion ended. It’s even more so the case if someone is using it as an example for raising prices as a trend.
I’m 100% in the camp that prices are going up and quality is going down; companies are retiring models and requiring you to use more expensive ones. This has happened to me and there are dozens of examples that one can point to.
But a promotion ending is a strawman argument and does the point a disservice.
Actually, deepseek v4 was 1/3 promotional price for the first month or so. This was pretty clearly communicated. The promotions window just ended is all.
That’s a little bit of a No True Scotsman. Yes there are people who do not review anything; but even people who are reviewing every line from an LLM do not have the same understanding as someone who wrote it themselves.
I’m not making a judgement call about which is better, but it was widely accepted in tech before the advent of LLMs that you just fundamentally lack a sense of understanding as a reviewer vs an author. It was a meme that engineers would rather just rewrite a complicated feature than fix a bug, because understanding someone else’s code was too much effort.
Linguistics, specifically as it pertains to language learning
Edit: Whoops read your question wrong. I do a bunch of NLP on different languages, and use LLMs to pad out and interpret the data. Asking for things like translations, alternatives, transliterations; associating and validating data; transferring data from one language to another; segmentation and cross lingual alignment; the list goes on.
I did manage to get higher quality in the end, so it’s not entirely a regression. But older LLMs were much more capable with less prompting at interpreting disparate data and tying it together.
Most of the work I do does not really have a “right answer,” just a lot of wrong ones, which I think is what trips up LLMs. If I turn on reasoning for any step in my pipeline, the token count goes up 100 fold and the quality gets cut in half.
Edit 2: I did have to move off of GPT though to get the improvements mentioned. Go mistral!
Azure recently discontinued the gpt-4.1 model. I had to move off of this model, and moving to any gpt-5* model was worse (higher failures & less accuracy), and more expensive. I had to rewrite the entire system from high school level prompts to lower elementary school level prompts using non-gpt models.
I would say models entered a bottleneck a long time ago. My personal opinion is now they are overfitting newer models on coding and "agentic" capabilities at great expense of general abilities in other domains.
Could you simulate something be typed? Trivially. Could you simulate something be drafted? Honestly, even if you wanted to put in all that time and effort, I’m not even sure LLMs are sophisticated enough to send the logical drafts, loops and edits that would pass a writers sniff test