Writing
Notes on verifying what AI systems do.
Essays and open data from the lab: where AI systems behave, where they fail, and how to prove the difference. Every piece links to something you can check or run yourself.
Model collapse is a provenance problem, and provenance is checkable
Over half the open web is now AI-generated, and the next training run will scrape it. The fix is not bigger models. It is data provenance, recorded at the source and checkable later. Why the scaling answer fails, and what a verifiable data discipline looks like.
17 Jun 2026Read →
Google externalised the cost of renaming Gmail
Google shipped Gmail address renaming and never shipped a webhook. 124 open-source projects still key OAuth identity on email. What breaks, and who pays.
12 Apr 2026Read →
124 repositories. Four ecosystems. One broken assumption.
The reproducible data behind the essay: 2M+ repositories scanned, severity tiers, ecosystem breakdown, and the full methodology. A complete audit.
13 Apr 2026Read →