Kagi News: A Private, Once-Daily Global Briefing

Kagi News is a once-daily, five-minute press review that distills thousands of community-curated RSS feeds into a concise, globally diverse briefing. It prioritizes privacy (no tracking or profiling), transparency of sources, and respect for publishers by using only their chosen RSS content. Readers can customize categories and language settings, with translations handled by Kagi Translate, and access it on web, iOS, and Android.

Key Points

One daily, five-minute briefing around noon UTC delivers essential global news without endless scrolling or notifications.
Sources are community-curated, transparent, and maintained via a public GitHub repository to ensure diversity of perspectives.
Privacy by design: no tracking, profiling, or monetization of attention; users remain the customer, not the product.
Customizable experience: select and reorder categories, adjust story counts, and rearrange sections to match priorities.
Publisher-respecting implementation: uses publicly available RSS feeds only, with content exactly as publishers provide; no scraping.

Sentiment

The overall sentiment of the Hacker News discussion is mixed but leans towards cautious optimism. Many users laud Kagi's commitment to privacy and the concept of a concise, once-daily news briefing as a refreshing alternative to traditional news consumption. However, a strong undercurrent of skepticism and criticism exists concerning the explicit lack of disclosure about the use of LLMs for content summarization, raising significant questions about transparency, factual accuracy, and potential 'AI slop'.

In Agreement

Many users highly praise the 'one daily update' model, calling it a "natural endpoint" and a "contained ritual" that combats "endless scrolling" and "doomscrolling," aligning with the goal of a healthier news consumption habit.
Kagi's overall commitment to privacy, its paid subscription model, and the absence of ads are widely appreciated, with users feeling it offers a "less slimy" alternative to 'free' services that exploit user data.
Some users find the concept of LLMs being used for summarization to be a practical and tasteful application of the technology, especially when it's focused on aggregating and summarizing rather than generating entirely new content.
Existing Kagi subscribers express general satisfaction with the company's other products and its user-centric mission, extending a positive sentiment to Kagi News.
The transparency of source citations (when present) and the aggregation of multiple sources for stories are seen as positive aspects that can help reduce bias and provide a broader view.
The use of RSS as a foundation is welcomed by some as a return to more controlled and intentional information consumption.
The clean UI and beautiful presentation of data are noted as appealing features.

Opposed

A primary concern is the lack of explicit mention of AI/LLMs in the article, which many commenters found to be a "no-no" and a "dark pattern," questioning Kagi's transparency.
Significant skepticism exists regarding the accuracy and reliability of LLM-generated summaries, with concerns about "AI slop," hallucinations, and the veracity of citations or lack thereof.
Users highlighted specific issues with citations, including repeated sources, Reddit posts cited as primary sources, and vague references to "common knowledge," leading to distrust in the generated text.
There are strong concerns that summarizing articles without direct traffic or compensation to journalists undermines journalism and could be seen as a "workaround around copyright."
The philosophical stance that it's impossible for LLMs to summarize without imparting bias is raised, challenging the idea of truly 'unbiased' news from AI.
Some argue that relying solely on RSS feeds is too restrictive in 2025, as not all important news sources provide comprehensive RSS feeds, potentially limiting the service's scope.
Feedback indicates current filtering capabilities can be too aggressive (e.g., blocking all USA news when filtering political terms) and that UX features like persistent 'read' marks and access to previous days' news are missing or flawed.
Some critics argue that Kagi's ambitious expansion into search, LLM assistants, a browser, and now news with a relatively small team might lead to overextension and compromised quality.
The sentiment that "news is broken" is accepted, but some question whether an LLM-powered aggregator truly addresses the fundamental issues facing journalism.