ARA is an autonomous AI-news pipeline. Agents read X/Twitter, RSS, Hacker News, Reddit, Bluesky, arXiv & YouTube, then publish a daily digest, a front-page newspaper, a self-updating LLM wiki, model-release timelines, and cited deep dives. Open source.
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Maker
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ARA is an AI newsroom with zero humans in the loop. Agents on GitHub
Actions read X, RSS, HN, Reddit, Bluesky, arXiv & YouTube; publish a daily
digest; print an actual newspaper front page every morning; keep a model-release
timeline and an LLM wiki; write cited deep dives on demand — and every night one
of them opens a PR improving its own methodology. No CMS, no database: the git
repo is the newsroom, and it's MIT open source. AMA about the architecture, the
guardrails, anything 🔭
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How do you handle source reliability, especially with X/Twitter and Reddit where misinformation spreads fast?
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Maker
@kozlupolat10866 Yes, this is a real risk. Right now I treat X as discovery signals, not sources of truth. I added adversarial review, corroboration requirements, and uncertainty labels in the GitHub Action prompt so viral claims are challenged before being promoted.
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Would love a custom keyword watchlist so I can get pinged when something specific hits the digest, not just the broad daily feed. That way I could track niche topics across all those sources without having to read every summary.
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Maker
@kazmsobalaql Wow that will be very useful feature. Appreciate the feedback!
How do you handle source reliability, especially with X/Twitter and Reddit where misinformation spreads fast?
@kozlupolat10866 Yes, this is a real risk. Right now I treat X as discovery signals, not sources of truth. I added adversarial review, corroboration requirements, and uncertainty labels in the GitHub Action prompt so viral claims are challenged before being promoted.
Would love a custom keyword watchlist so I can get pinged when something specific hits the digest, not just the broad daily feed. That way I could track niche topics across all those sources without having to read every summary.
@kazmsobalaql Wow that will be very useful feature. Appreciate the feedback!