If you think about how you speak in your native language, it probably has a certain rhythm of long and short sentences, with some "shallow" sentences that just say one thing, but then sentences that nest other clauses that could be whole sentence of their own, and then a hanging sentence fragment that makes sense in context, etc. As far as I know, every spoken language, English or otherwise, looks like that when humans are writing it.
The human mind's "buffer of verbalization" seems to be quite short, basically around one grammatical "clause" in size. So humans, when writing (or speaking) "off the cuff", generally only try to keep "a non-verbalized concept of what they want to say" plus "the verbal pattern for the current grammatical clause" buffered in their heads. A human speaker will only start deciding how to glue the next clause onto the current clause—whether to make it a new sentence, or use some preposition or conjunction, or to "verbally backtrack" / "interrupt themselves" to add detail "before" what they said—when they get to near the end of speaking/writing a clause. Much of the "reason" for the grammars of spoken languages to be structured the way they are, is to allow for this kind of narrow-buffered "streaming" composition.
Human written language can look different when someone has sat down and taken this "off the cuff" writing as a first draft, and intensively edited and rearranged and polished it. But the result of doing this still usually retains a lot of the original positive qualities of the "off the cuff" writing that went in. (Editors are told to not over-edit, because doing so will remove the "author's voice" from the writing. The particular grammatical gymnastics a speaker/writer uses to connect their thoughts can be a large part of this "author's voice.")
LLMs, despite "streaming" in a much more literal sense than humans do, seem to avoid "off the cuff" generation of successive grammatical clauses using "whatever grammatical glue works to get to the next thought." Instead, they seem to have been forced by their training into favoring particular sentence structures that allow them to never end up needing to reach for artful just-in-time grammatical connections in the first place. Mainly, they like using sequences of short sentences that each say exactly one thing.
(I hypothesize they like these forms because, in some internal layer of the model, these "simple" sentences can be represented all-at-once as plans [with that same plan getting reconstructed on each successive inference-step during emission of the sentence]; and so this kind of sentence can be emitted in a token order that results in the "polished, edited writing" style rather than the "off-the-cuff speaking" style. Much of the base-model training dataset — the stuff that made the model understand language and writing at all — came from polished, edited writing rather than casual/conversational writing. However much the model is trained to adopt a casual style, it's doing so on top of a language-generation "module" that learned to write by trying to emit "polished, edited writing" one token at a time. And the only way it managed to do that was by limiting itself to constructing sentences that could look like "polished, editing writing" despite a bounded ability to plan.)