Honest, technical writing about AI watermarks, what they are, what can and cannot be detected or removed.
What a statistical token watermark is, and why third-party tools cannot read it without the private key.
How different providers approach watermarking and content provenance.
The four categories of "AI detection," what each can actually verify, and how to choose.
What humanizers actually do, and how to evaluate one without falling for undetectability claims.
A practical framework for EU and US transparency rules: preserve provenance, disclose, log.
Batch, API, privacy, and audit: what to look for when buying for a group.