Reading only US/UK news creates blind spots. You get one perspective on every story. When AI regulation passes, you read the NYT take. When trade tensions rise, you get Reuters framing. When a conflict breaks out, CNN decides which details matter.
The problem compounds. Algorithms feed you more of what you already read. Your feed becomes a mirror, not a window. After 6 months of filtered news, you think your perspective is "balanced" because you read multiple US sources. It's all the same lens.
The Solution: Read Globally
We built a news aggregator that pulls from state media, independent outlets, and regional papers across 12 regions. Every morning at 7am ET, a digest posts to our #research channel with headlines from each region.
The value is in comparison. When the same event gets covered by CGTN (China), TASS (Russia), France24, and Reuters, you see four different framings. What gets emphasized. What gets omitted. Who's quoted. Which angle leads.
The Full Source List
Plus tech/AI sources: TechCrunch AI, Ars Technica, The Verge, MIT Tech Review, and research blogs from DeepMind, OpenAI, Anthropic, and Google AI.
CLI Usage
Three commands cover all use cases:
news global # Full digest, 5 stories per source
news global 8 # More stories per source
news country japan # Deep dive on one region
news brief # Quick headlines onlynews brief output## 🌐 Global News Brief — Feb 25
🌎 **AP News**: US lawmakers propose AI safety framework
🇪🇺 **France24**: EU finalizes AI Act enforcement guidelines
🕌 **Al Jazeera**: Tech giants expand Middle East data centers
🌏 **NHK Japan**: Tokyo summit addresses semiconductor supply chains
🌍 **Daily Maverick**: African Union announces digital infrastructure plan
**Tech/AI**
- OpenAI announces enterprise features (TechCrunch)
- EU regulator investigates algorithm transparency (Ars Technica)
- China accelerates AI chip development (Nikkei Asia)Same Story, Different Framing
Here's what makes this valuable. Take a recent trade policy announcement:
📰 How Different Regions Covered the Same Story
Reuters (US): Focuses on economic impact, quotes US officials, mentions "national security concerns."
CGTN (China): Leads with "protectionist measures," quotes trade ministry, emphasizes global supply chain disruption.
Nikkei Asia (Japan): Analyzes semiconductor implications, quotes Japanese manufacturers, focuses on regional supply chains.
Al Jazeera (Qatar): Frames as "great power competition," includes Global South perspective, quotes economists on developing economy impact.
Same event. Four different stories. Each outlet chooses which facts lead, who gets quoted, and what context matters. Reading all four gives you something none of them provides alone.
Technical Implementation
The system runs on Python with a simple architecture:
- RSS parsing — feedparser handles the 40+ feeds, normalizing different formats
- Deduplication — Skip stories older than 48 hours, prevent repeats
- HTML cleanup — Strip tags, truncate summaries to 500 chars
- Region grouping — Organize by geography for easy scanning
- Cron scheduling — Runs daily at 7am ET, posts to Discord
# Cron job entry
0 12 * * * news global | \
openclaw message send --channel researchNo translation yet—most major outlets publish English editions. TASS, CGTN, France24, DW all have English RSS feeds. We parse the English version directly.
Why RSS? No API keys. No rate limits. No terms of service violations. RSS is the original open protocol for syndication. Most outlets still support it, even if they don't advertise it.
What We Learned
State media isn't useless. CGTN and TASS tell you what Beijing and Moscow want you to think. That's valuable intelligence. Understanding their framing helps you understand their strategy.
Regional papers catch what wire services miss. The Korea Herald covers Samsung supply chain issues weeks before Reuters. Daily Maverick reports on African tech policy that never makes Western news.
Patterns emerge. When multiple regions cover the same story with the same angle, it's probably accurate. When framings diverge wildly, you're seeing the story that reveals more about the teller than the event.
The Daily Habit
Every morning at 7am, the digest drops into #research. Takes about 5 minutes to scan. You get:
- Headlines from each major region
- AI/tech developments from specialized sources
- Research blog updates (when DeepMind or Anthropic posts, you know immediately)
No algorithmic feed. No engagement optimization. Just chronological headlines from sources you chose. The old internet, basically.
🔧 Build This Yourself
The pattern is simple: pick 30-40 RSS feeds across different regions, parse them daily, group by geography, post to wherever you work. The code is ~200 lines of Python. The hard part is curating the source list—we did that for you above.
This is part of the Build Log series documenting how we build automation systems at Meet Kai. Questions? [email protected]