You ever read a work of literature with such flowery language that right after you've read a paragraph, you pause and realize you have no clue what you actually read, only to read the paragraph maybe a second or third time and have your mind space out again and again on each successive attempt?

Yeah, for me, that's what parsing huge volumes of LLM-produced text like "direct model calls as replaceable semantic workers" does to my brain. Maybe others don't really have this issue, but after any long output, I prompt the agent "Go back and decompress any LLM-speak in light of the higher level task goals. Eliminate deictic language."

The revised output documents are solely for my personal usage to expedite understanding. The LLMs can slowly converge on their own language for all I care; I retain raw agent output for future agent usage (to avoid the "lossy" problem the author mentions), but that doesn't eliminate the need for some intermediate translation I can use to actually help get my work done instead of spending hours attempting to understand what a "load-bearing pinned gate" is.

I agree.

I've come to believe this is also a side effect of the desire for less (/goal: no) human in the loop on the part of the people driving all this capex spend. I think if you actually want to manually review output there will be a moment where you will actually want a separate interface to a stupider or "simpler" model. I suspect sometimes dealing with Fable 5 that this threshold has already been crossed. It's not that the raw code output is so good, it's that it just doesn't speak to me in a way I would like. Perhaps the verbosity is worthwhile when generating code as a sort of first pass some other model can auto or adversarially chop down. The best place for a human is probably outside of this part of the loop all together.

So I might as well just let it auto /goal it's own thing with sufficient constraints while myself and a model that can converse in parallel with less "deictic" (thanks for this word btw) volume as you put it for the areas of the code where I want to "frame" the vocabulary or where my personal understanding is of high value. I know people already do this in many ways, like use one company's model for planning and another for coding. It just feels inevitable at a certain point that the "natural language" output of LLMs writing the bulk of the code is not targeted towards humans. And really, why should it be?

The effect you describe reminds me of reading Edward W. Said's "Orientalism" when I was younger. Fable suddenly started with this kind of lingo, iirc, and Opus 5 sounds exactly the same. Tin foil: it's ultimately a vendor lock-in strategy, you'll get the best results with agents from the same tribe, others will trip over the mountain of idiosyncratic metaphors.

Well, now I had to ask an LLM to give me examples of what "deictic language" means...

This has recently become a pretty pressing issue for me, as it's starting to severely hinder my ability to be productive with the models. It's hard to tell if its getting worse with every model release, specific to Anthropic's models, a reflection of my ADHD, all/none of the above, but holy shit do I get aggravated when I'm forced to parse the most unintelligible, jargon-dense bullshit explanations in whatever the model output is. And then I feel silly getting genuinely tilted by the model's inability to just... explain something semi-normally, without it requiring me to berate it into simplicity.

For some discrete skills I use, I include a final step on the the output that runs through 1+ subagents to de-slop the text and to actually simplify it, but so far nothing has worked as well I've hoped. Considering hopping off Anthropic's models to try out others to see if they're less egregious.