No, it's not. (As should not be a surprise given how extensively LLMs are used to draft English-language articles these days.) It's actually incredibly blatant. Just look at this second paragraph:
> The same six months I had closed three other tickets against the same product, each of which had presented to its filer as the only bug. A customer's name had appeared with its letters unjoined on a printed agreement, the way a sign-painter would have laid them out in 1962, because the PDF library on the receipt server pre-dated the existence of a shaping engine in its language runtime. A search index had been returning empty for accounts the customer service team could see in the database because a 2017 import had encoded twelve thousand names using fossil Unicode codepoints from 1991 instead of regular ones from 1995, and the index, very reasonably, treated the two encodings as different strings, So, that ragged-left ticket was the smallest of the four, HOWEVER, it sat on top of the same iceberg and pointed at the same thing.
Blatantly Claude (which he recently started using, judging by https://lr0.org/diary/2026-02-26/ and https://lr0.org/diary/#08062026 - note how LLM-written the second one sounds, a little ironically).
And you can punch the essay into Pangram if you have any doubt (omit Arabic text and formatting if you do this, focus on just plain English to be safe). For example, go to the end* and try "Everything in this story that actually works was paid for by almost nobody...Somebody will close it, probably unpaid, possibly reading this (or writing it? who knows)." '100% AI.'
Or just compare it to his older writings. Does this 2023 piece https://lr0.org/blog/p/d/ or this 2024 piece https://lr0.org/blog/p/democracy/ sound like OP?
* I always check sections towards the end instead of the beginning, because a lot of authors will write the introduction by hand and then give up and let the AI write the rest; and also more advanced sloppers will fiddle with the opening until it beats Pangram, which is not hard since Pangram heavily favors false negatives on AI contribution, and skip the rest because they assume readers will be too lazy to check beyond that.