For most of journalism’s history, the article has been the atomic unit of news: a fixed container, written once and served the same way to everyone. That’s beginning to change. AI is moving out from behind the scenes, where it quietly powered efficiencies, and into the interface itself, where it can assemble, personalize, and adapt the news to each reader.

On this week’s episode of Newsroom Robots, host, Nikita Roy speaks with Jim Friedlich, Executive Director and CEO of The Lenfest Institute for Journalism, and Kevin Delaney, Editor-in-Chief of The San Francisco Standard.

Earlier this year, The Standard became a part of the Lenfest AI Collaborative and Fellowship Program, funded by OpenAI and Microsoft. As part of the program, it received a grant to build a genuinely AI-native news app, where the article isn’t the building block anymore. Instead, the raw materials are atomic like a quote, a piece of data, a few lines of reporting, all assembled by AI into an experience that adapts to each reader.

In this episode:

01:47 — What “AI-native” actually means, and the three areas where AI is uniquely good

04:56 — “Personalized obsessions” — why readers follow stories, not sections and the app’s early results

10:00 — Kevin’s “news as farming” analogy

12:36 — Jim walks through the reader experience of the app

15:33 — The shift from Mode One to Mode Two and how the Lenfest AI Collaborative’s thinking has evolved

26:34 — Atomic content and the reporter’s CMS: unlocking the interviews, notes, and quotes that never make the 800-word article

42:48 — How they control for accuracy by grounding AI in their own journalism

50:28 — Everyday newsroom wins, from a sports contract calculator to “find me a juicy story” in a document dump

This episode of Newsroom Robots is supported by The Lenfest Institute for Journalism.

Sign up for the Newsroom Robots newsletter for episode summaries and insights from host Nikita Roy.

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At The Seattle Times, an AI tool identified a new prospect and helped close additional ad revenue in a single day. The Seattle Times is one of 11 news organizations participating in the Lenfest AI Collaborative and Fellowship Program, funded by OpenAI and Microsoft. Through this initiative, AI engineering fellow Rajesh Barade worked with the advertising team to address their challenges and developed a prospecting agent. This tool enables sales representatives to enter a category or focus area, identify businesses spending in that market, find decision-makers, access advertising spend data, and generate personalized outreach.

The Seattle Times deliberately began its AI efforts in advertising rather than the newsroom. Early successes helped build momentum across the organization. This led to listening tours across finance, HR, and eventually the newsroom, where a municipal meeting listening tool is now in development.

This week on Newsroom Robots, host Nikita Roy speaks with Kati Erwert, Senior VP of Product Marketing and Public Service at The Seattle Times, and Tristan Loper, Head of National Programs at the Lenfest Institute, to explore how the prospecting agent works, why starting in advertising was key to unlocking organization-wide adoption, and what it takes to turn early AI successes into lasting capability.

In this episode:

02:07 — How The Seattle Times built internal momentum for AI adoption

05:51 — What the Lenfest AI Collaborative is and how it works

09:29 — Inside the prospecting agent: how a sales rep closed business in one day

14:11 — Why starting with advertising drove cultural change across the organization

17:07 — The buy vs. build decision in a fast-moving AI landscape

19:03 — How open-source code sharing works across the 11-newsroom cohort

24:44 — Building the municipal meeting listening tool and beyond

37:07 — Navigating the tension of blocking AI bots

45:47 — How smaller newsrooms can get started with AI today

This episode of Newsroom Robots is supported by The Lenfest Institute for Journalism.

Sign up for the Newsroom Robots newsletter for episode summaries and insights from host Nikita Roy.

Hosted on Acast. See acast.com/privacy for more information.

For years, the aggregator model was simple: curate the best journalism from thousands of publishers and send audiences their way. Now that contract is being rewritten, and Yahoo News is one of the most interesting places to watch it happen.

In this episode of Newsroom Robots, host Nikita Roy speaks with Kat Downs Mulder, Senior Vice President and General Manager of Yahoo News, about how the platform is layering AI across every surface of a product that reaches an estimated 180 million people in the U.S. alone each month. Kat previously spent more than 14 years at The Washington Post as chief product officer and managing editor before taking on the challenge of modernizing one of the internet's original news destinations.

The conversation explores Yahoo's acquisition of Artifact, the AI news app built by Instagram's co-founders, which gave the platform a new recommendation engine that prioritizes time spent reading over clicks. It also digs into Yahoo Scout, the company's new AI answer engine that synthesizes information with rich citations and visual context, and an AI-powered daily audio digest designed to turn personalized news into a listening habit. Each of these products makes Yahoo more useful to its audience, but each also changes the relationship between Yahoo and the publishers whose journalism powers the platform.

When an answer engine can deliver what a user needs without a click-through, when an audio digest summarizes a story so well the article never gets opened, and when personalization makes the aggregator the destination instead of the pass-through, the old economics stop working for publishers. Kat is candid that the compensation models haven't been figured out yet, noting that Yahoo is working with the Microsoft Publisher Content Marketplace to develop new frameworks, but that the industry is still writing those rules in real time.

She makes a strong case for how Yahoo is approaching this differently, from how Scout prominently surfaces publishers to the rev-share model they operate, and why she believes the quality flywheel they are building actually rewards better journalism. Kat argues that original, distinctive journalism will become more valuable in an AI world because AI agents will seek out what is unique.

This episode covers:

03:20 — Why Yahoo acquired Artifact and how it shifted recommendation algorithms

06:20 — The shift from click-based metrics to deeper engagement signals such as session time and retention

08:50 — Inside Yahoo Scout, Yahoo's new AI answer engine built to support publishers and the open web

12:40 — The changing economics of news as AI platforms begin generating answers instead of sending traffic

17:40 — Yahoo's personalized AI-generated audio news digest and why multimodal news experiences matter

22:00 — How Yahoo's editorial and AI teams collaborate on quality control at scale

31:00 — How AI is transforming newsroom product development and prototyping

36:10 — The tension between personalization and journalism's civic responsibility

40:00 — What smaller newsrooms can learn from their AI product playbook

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