Such a silly choice of words. I wish the human directing the LLM writing the article put some effort into rewriting the worst examples of LLM style.
> But it did extremely well, and the promise was immediate and specific: builds finishing in less than half the wall-clock time, at 27% lower cost, scoring at or above our incumbent on completed work.
The way the LLMs write (Claude perhaps?) With short phrases separated by colons, commas or full stops, is so poor and frustrating.
There some good insights behind this article, so it's worth reading, for example below, but it isn't easy to read.
> Earlier GPT models cached implicitly on partial prefix matches, which gave decent hit rates for free. GPT-5.6 dropped partial-prefix matching:
I've found the same thing showing with Claude-coded/designed front ends that overuse the same semi-monospaced fonts, Blue/Yellow/Red palette and rounded corner borders. It isn't that it is bad, but it often isn't fit for purpose.
You're right it wont change anything, but authors shouldn't be surprised when people who care about their time/attention comment on low/no effort pieces.
I also think that people should focus on substance and not if AI was used, but AI writes like shit and I find myself retching a bit when I have to read long AI-written documents. Do they say something useful? Maybe, but when my eyes are glazing over because it's just so exhausting trying to parse what's written, I can't tell.
I certainly think less of people when they have such poor taste that they think writing like that is acceptable.
Which is a shame as real insights are buried inside some of these articles, which if the author bothered to write in his own words could have reached an audience that would have appreciated them.
Writing is one of the areas where I want no LLM involvement.
Only so much time in the day, its a quick signal to not waste anymore of it.
Pointing out they generated it at least encourages them to write a shorter article that says what they meant.
I appreciate these comments, they save me time for procrastinating elsewhere.
And let’s be real: I had a post this year that was #1 on HN for a while, and an LLM “wrote” the whole thing, but it was very much my writing style and NO ONE called out the post as LLM slop. If you use an LLM correctly for writing, it’s not detectable. It seems that most folks don’t go through that effort.
Yup llmish (from now on it's called "llmish") sucks.
But I'd say: at this point it's probably trivial to write a browser extension that detects llmish and that rewrites the worst sentences: from llmish to something less irritating to read. Heck, I could spent tokens on that: an extension that changes on the fly llmish found on webpages.
Also I'd say there's typically no swearing at all in llmish: llmish is too politically correct for swearing. So the rewrite could maybe also use a few "offending" words.
Offending words that, btw, are not going to go well with Gen Zers. Poor Gen Z... They've been raised with the state and its institutions (like school and then universities) hammering them with the notion that they were precious little unique snowflakes and now they arrive on the job market only to be told they've been pre-emptively replaced by AIs. And because they cannot stand a single curse word (because it's "offensive to minorities" or something), they'll be driven off by text rewritten to contain curse words. So they're condemned to read the bland, dumb, AI-generated llmish for the rest of their lives.
Honestly sucks for them. Fuck that.
If wokeness actually did capture a whole generation then why even bother complaining?
I think a lot of people miss that for many companies, a model upgrade like this is basically a one liner.
Even if you have an amazing model router architecture (which we do for our golden flows), it’s just not worth it. Not to mention reliability and so on
Well, unlike OP I haven't run a rigorous test, but I still would expect Fable to be significantly better at building marketing websites than Opus. It sure is way better at building decks.
I would consider Luna for parts of the workload that touch actual tools. It is surprisingly capable and it runs fast.
Sol is great at talking to the human and orchestration of agent calls, but it's just too expensive to use everywhere.
You can get 5 Luna runs for the cost of 1 Sol run. Statistically speaking, going from one to five samples is a pretty big deal.
So depending on how heavily agents are used on what tasks, it's entirely possible that you get worse work for more cost.
This is a feature if your goal is to obtain many samples. Independence is critical. This makes it easier to accurately model the uncertainty of a decision.