Why Particle News Is Betting on Comprehensive Stories, Not Individual Articles

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When Sara Beykpour left Twitter after 11 years, she had watched digital news break in real time. Clickbait. Misinformation. Algorithms designed to maximize engagement, not inform users. For people without expensive subscriptions to specific publications, staying informed meant navigating a jungle of competing incentives.

Then came 2022 and 2023. Two turning points converged: Generative AI became widely accessible, and Elon Musk took over Twitter. Beykpour and her co-founder Marcel Molina, also a Twitter veteran, asked themselves a question: Could we build a platform that helps people stay informed on their own terms, with users, rather than advertisers, at the center?

The answer is Particle, a news app that aggregates articles and organizes the information into straightforward, digestible stories. Those stories are what Beykpour calls "liquid," or able to take different formats based on how users want to experience the content at any given moment.

In a recent meeting with German media executives (Chefrunde Study Tour) in San Francisco, which I co-organized, Beykpour explained Particle’s mission: "It needs to be easier for people to stay informed. Users are left to contend with clickbait, misinformation, algorithms that are not serving their best interests. Maybe there's something we could do to help people get connected to what is most important to them in a way that meets them where they are."

Particle does not just collect and present news articles. It aggregates information to produce a story, which Beykpour defines as a synthesis of all relevant points from multiple sources on a single topic.

Take the US election as an example. Instead of seeing 15 separate articles from Newsweek, Fox News, AP, or Breitbart when scrolling through their newsfeeds, users see one aggregated story that summarizes the different publications’ reporting and perspectives. The information consolidates, and users avoid the paradox of choice that leaves them either overwhelmed or misinformed.

This model inverts the traditional aggregation approach. Most news apps surface individual articles and hope users will read multiple perspectives. Particle assumes they won't and delivers the synthesis up front.

The real innovation: The stories are not static.

Beykpour describes Particle's content as "liquid." Users can transform any story through different lenses depending on their context and needs.

Available transformations include:

Users can also ask questions about stories. The underlying philosophy challenges a core assumption of modern media: that users should spend hours in an app. Beykpour's team knows that some busy people only have time to check the news weekly, not daily. Personalized digests delivered via push notifications support this behavior.

One of Particle's most popular features is the Political Spectrum, which visualizes which media outlets cover a story and where those outlets sit on a left-to-right political spectrum.

The feature works best in the United States, where Particle has the most data. If a story appears only in left-leaning outlets, users see that immediately with blue dots clustering on the left side of the spectrum. The same goes for right-leaning coverage.

Particle explicitly flags when a story has visible political bias. Users can then choose to see how each side reports on it or stick with their preferred perspective. Either way, the choice becomes conscious instead of algorithmic.

This transparency distinguishes Particle from social media feeds, where algorithms optimize for engagement metrics that platforms never fully explain. As Beykpour puts it, users know "through which lens they're getting the information. No hidden algorithms, no black box."

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Particle allows users to customize their feeds with precision. Want tech news and politics but nothing else? Done. Only video game news? No problem. Only specific subsets of video game news? Also possible.

The team is building exclusion features as well. Users who want tech news but prefer to avoid hearing about Elon Musk will soon have that option.

One important distinction: Particle ranks content primarily based on user preferences, not on maximizing engagement. This creates a fundamentally different dynamic than social media, where algorithmic feeds prioritize time spent on a platform over user satisfaction.

Particle has signed licensing deals with major publishers including Associated Press, Reuters, AFP, Time, and Fortune. The model involves compensating publishers for private and optimized digital feeds of their content, summarizing it with AI, and linking back to the original articles, which – for partnered publications – are available natively in the Particle app. 

For publishers, this represents a new revenue stream as Google's zero-click searches threaten traditional traffic models. Particle offers publishers a new opportunity to drive engagement and value for their content. 

Rebecca Ozarow, Particle's Media and Partnerships Lead, emphasizes that some members of the team come from journalism backgrounds, which gives Particle consistent journalist perspectives and sets them apart from other AI companies. They want to work with the industry, not extract value from it.

But challenges remain. "There are no industry standards for AI licensing," Ozarow explains. "I'm having conversations with publishers who don't know how to price their content for this use. It's a shared journey."

Publishers accustomed to straightforward syndication deals now face questions about how to value content that gets transformed, summarized, and redistributed in multiple formats. Both sides are learning in real time.

Particle remains free today – no paywalls, no ads. The team has chosen to avoid advertising for now based on their learnings and experiences at Twitter and Snapchat, where, sometimes, ads can create what Beykpour calls "a race to the bottom."

Soon, Particle will offer subscriptions for users who want access to even more personalization features. The open questions: How much will users pay? When is the right moment to introduce subscriptions? The team continues testing.

Particle News is, of course, not alone in addressing this particular challenge. Audiences are often frustrated with the quality of free, ad-supported news, but converting frustration into willingness to pay remains difficult.

Particle aggregates from across the political spectrum: Fox News, Breitbart, MSNBC, and outlets from left and right. But the team draws lines. No conspiracy theories. No extreme fringes.

The goal is showing diverse perspectives without sliding into toxic territory. Users should understand how different sides frame a story without encountering hate speech or deliberate misinformation.

Beykpour acknowledges this balance is difficult but essential. In an era when algorithms push users into bubbles, Particle deliberately offers breadth of perspective.

The challenge: maintaining engagement while preserving diversity. Users naturally gravitate toward comfortable perspectives. How do you keep them informed across viewpoints without alienating them? Particle continues to experiment with ways to push users a bit outside of their comfort zones while still delivering on their customized news experience.

Beykpour sees a shift happening in media trust: people trust people, not institutions anymore. Individual voices like podcasters, creators, newsletter writers gain authority.

Particle is exploring how to aggregate these voices. Not just traditional publishers but podcasts, newsletters, and social media content from trusted individuals.

The vision: users get perspectives from people they trust, organized and diversified so they avoid falling into bubbles.

This creates new complexity. How do you keep content engaging but diverse? How do you prevent users from sliding into algorithmic rabbit holes? Particle is working through these questions.

Today, many of Particle's users are tech-curious people. But they ultimately want to reach people who simply want to stay informed: local news consumers, general news audiences.

Apps like NewsBreak and SmartNews reach these users. Particle wants to as well. "We just need to figure out how to reach them”, says Beykpour.

Building for tech-savvy early adopters is one thing. Scaling to mainstream audiences requires different strategies, different features, and possibly different business models.

Whether it succeeds commercially or not, Particle demonstrates that choices exist. News aggregation does not have to optimize for doom scrolling. AI can enhance journalism. And publishers can partner with AI companies in ways that create value instead of extracting it.