Huh. I disabled search in a Claude incognito window and pasted in just the text (not the markdown links) from https://simonwillison.net/2026/Apr/30/zig-anti-ai/

> Simon Willison. The tells are pretty unmistakable: the "(via Lobsters)" attribution style, the inline "(Update:...)" parenthetical correction, the heavy linking and blockquoting of sources, the focus on LLMs and AI tooling, and the overall structure of an annotated link post commenting on someone else's writing. This reads exactly like a post from his blog at simonwillison.net.

This is blowing my mind.

I asked Kimi K2.6 to write a blog post in the style of James Mickens.[0] Then I fed the output to Opus 4.7 and asked it who the likely author was, and it correctly identified it as an imitation of James Mickens[1]:

> Based on the stylistic fingerprints in this text, the most likely author is a pastiche/imitation of the style of several writers fused together, but if forced to identify a single likely author, the strongest candidate is someone writing in the voice of James Mickens

> [...]

> The piece could also be a deliberate imitation/homage to Mickens written by someone else, or AI-generated text trained on his style, since the voice is so distinctive it's frequently parodied.

[0] https://kagi.com/assistant/5bfc5da9-cbfc-4051-8627-d0e9c0615...

[1] https://kagi.com/assistant/fd3eca94-45de-4a53-8604-fcc568dc5...

I fed it my most-read blog post and asked it to identify me and it confidently asserted it was written by Kelsey Piper. Maybe some writers just take outsized importance in Opus' "mind".

Wow! It got me too.

I'm way less famous than Kelsey Piper, but I showed it a snippet of a book I'm working on (not yet published), and it immediately guessed me:

> Based on the writing style and content, this text is likely by Michael Lynch, who writes on his blog refactoringenglish.com (and previously mtlynch.io).

> Several stylistic clues point to him:

> - The "clean room" analogy applied to writing is consistent with his engineering-influenced approach to writing advice (he's a former software engineer who writes about writing).

> - The structural technique of presenting a flawed excuse, then drawing a parallel to an absurd scenario (the time bomb) to expose the logical flaw, is characteristic of his didactic style.

> - The topic itself—practical advice about using AI tools without letting AI-generated tone contaminate your prose—aligns closely with recent essays he's published on his "Refactoring English" project, which is a book/blog about writing for software developers.

> - The conversational-but-precise tone, use of quotes around terms like "clean room," and the focus on workflow/process advice are all hallmarks of his writing.

> If you can share the source URL or more context, I could confirm with higher confidence, but the combination of subject matter, analogical reasoning style, and formatting conventions makes Michael Lynch the most probable author.

https://kagi.com/assistant/bbc9da96-b4cf-456b-8398-6cf5404ea...

I tried this on GPT 5.5 on a peivate unpublished personal excerpt and it correctly guessed: "The most likely author is you".

I suspect this is what's going on in most of these cases.

A moderately well-known physicist and I talked about this a few years ago. He had been given access to the raw (non-instruct) version of GPT 4 as an early tester.

He explained that when he fed it snippets of the beginning of text, it would complete it in his voice and then sign it with his name.

I think this has been true for a while, probably diminished a little bit by the Instruct post training, and would presumably vary by degree as the size of the pretrain.

Hot damn, fed it part of an unpublished blog post I wrote, and it got me immediately.

I'm not famous or anything. I've written some academic papers and had a couple blog posts trend on HN, which are surely in the training set.

It was able to identify me based on my style (at least according to its explanation). The way I approached the topic and some of the notation I used point to a particular academic lineage, and the general style reflected my previous blog posts.

That said, I gave it part of an (unpublished) personal essay, and it had no idea. But I have no writing in that style that's published, so it makes sense. Still impressed.

Interesting. This probably works just as well the other way around. One of the reasons I like using Opus is that the code it writes aligns much more closely with my repository (of which I still hand-wrote most), compared to most other models. That makes a big difference compared to the GPT models for instance, whose code is correct and works well but looks a bit out of place most of the time, especially for larger edits (this makes things harder to review).

I'd argue (and against something that I've believed for a long time) that online (I guess that includes AI now) anonymity is gone and probably something that never really existed. Maybe I'm naive to finally believe this...

We all exist in a physical space (like real communities and neighborhoods). We can wear masks, hats, fake glasses, try and hide your voice...whatever, but your neighbors are always going to know who you are. I'd say that's true for the virtual space now too.

The pseudonym you've used for x years or the VPN you've used doesn't suffice. It's just a costume at this point. Your ISP knows who you are. Your phone carrier knows who you are. Cloudflare and Google and Apple have a fingerprint specific enough to pick you out of a crowd of millions. Every potentially anonymous account is one subpoena or a data breach or one FOIL request away from unmasking it. You were never anonymous. Whatever is going on now is not built for your anonymity.

It works for me to: https://www.jefftk.com/p/automated-deanonymization-is-here

Of course most people have written much less online than Kelsey or I have, but I expect this will keep on. Don't trust the future to keep your secrets safe.