AI Text Watermarking Under the EU AI Act: What Publishers, SEOs, and Creators Actually Need to Know

A writer drafts a 1,200-word analysis piece. The ideas are entirely their own — the structure, the argument, the research. They run the draft through Claude to catch awkward phrasing and tighten two passages. Then they publish. The published text now carries an imperceptible, statistically embedded mark indicating that a language model processed it. The ideas have not changed. The mark cannot be seen by any reader, cannot be read by any tool without Anthropic’s private key, and cannot be stripped without degrading the text. Nothing about who thought what has been recorded.
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Markdown Ads You Can't See, Sold on Numbers Nobody Can Check

This post is the second half of a two-part argument. The first half examined llms.txt advertising and found it fails on delivery — the file almost never gets fetched, so the impression never happens. This half examines an advertising product where delivery is solved. The failure is one layer up. Disclosure: this site builds and operates agent-detection infrastructure. The verification gap described in the close is one this operation would benefit from commercially. The analysis is published because the argument follows from the evidence, not from the incentive.
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