Most news aggregators are glorified RSS readers with an algorithm. myown.news is different — it runs a full AI newsroom. An LLM editor-in-chief ingests raw sources (HN, arXiv, GitHub Trending, RSS, newsletters), performs cross-source dedup, then generates a structured daily edition with lead stories, features, briefs, and editorial commentary. Output is a classic broadsheet layout, not a feed. One finite edition per morning. 8 languages via parallel LLM translation.
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Maker
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Hey PH! I'm the maker of myown.news.
The idea started from a simple frustration: every news product is a feed. Feeds are infinite, algorithm-driven, and all look the same. But newspapers had something right — a finite, curated edition with editorial structure. I wanted to see if AI could replicate that editorial process, not just summarize links.
Here's what's under the hood:
AI newsroom pipeline: A scheduler crawls HN, arXiv, GitHub Trending, RSS feeds, and newsletters every few hours. Then an LLM (Claude Opus) acts as editor-in-chief — it cross-references sources, deduplicates across topics and past editions, selects stories by news value, and writes a full edition with proper article types (lead, feature, brief, filler) and editorial commentary.
Not a wrapper: The output is structured Markdown with semantic metadata (importance, source type, figures, quotes). The frontend parses this into a real multi-column broadsheet layout — no templates, no cards.
Edge-native stack: Cloudflare Workers + D1 + R2 + Hono. The entire app runs at the edge. Image quality is scored by GPT-4 Vision with a 4-level fallback chain.
Parallel LLM translation: 8 languages generated concurrently using a mix of Azure, Claude CLI, and Subrouter to optimize cost and latency.
Cross-edition dedup: A similarity pipeline prevents the same story from appearing across days or topics.
Everything is built by one person. I'd love technical feedback — especially on the editorial pipeline and layout rendering. What would you want to see next?