Building a Personalized AI News Pipeline with Claude
A developer on r/ClaudeAI shared their custom-built system for processing 200+ articles daily to create a personalized morning briefing. The pipeline filters noise and delivers only relevant content based on personal interests.
Pipeline Architecture
The system follows a five-step workflow:
- Ingest: 12 RSS feeds pull content overnight from industry news, competitor blogs, and subreddits, collecting approximately 200 articles daily.
- Score: Each article gets a relevance score against a personal keyword list using Claude Haiku for speed and cost efficiency. Articles scoring below 0.4 are dropped, reducing the pile from 200 to 15-30 articles.
- Triage: Scored articles are classified into three categories: PASS (goes to briefing), PARK (save for later), or REJECT (discard).
- Analyze: PASS articles receive deeper analysis using Claude Sonnet, focusing on practical implications rather than summaries. The analysis answers questions like: "What does this mean for my work? Is there something I should act on? What should I watch?"
- Brief: Everything compiles into a structured morning email with three sections: Signal (act on this), Watch (monitor this), and Deferred (revisit later). The email delivers at 6:30 AM.
Technical Stack and Costs
The implementation uses Python, FastAPI, Supabase for storage, Claude API (Haiku + Sonnet), and Resend for email delivery. It runs on a $7/month Render instance.
API costs remain under $5/month, with Haiku handling the scoring (costing pennies) and Sonnet only processing the 5-8 articles that survive triage. The developer notes that Deepgram would be the most expensive component if audio briefings were added.
Key Insights
- The scoring step matters more than the analysis step. If too much content passes through the filter, Claude wastes tokens summarizing noise. "The filter is the product."
- Structured output with clear sections (Signal/Watch/Deferred) proves more useful than a wall of summaries. The developer tried "summarize these 10 articles" first and found it unreadable, while three categories with one sentence each gets actually read.
- RSS remains underrated as an ingestion layer. Most publications, subreddits, and GitHub repos still provide RSS feeds, making it the cheapest and most reliable option.
📖 Read the full source: r/ClaudeAI
👀 See Also
Batch API Cost-Effective for Multi-File Code Changes
A developer reports using Claude Sonnet and Opus for batch processing to modify 30+ files and generate 3k lines of code for approximately £2, with specific prompts and tools like Repomix for content gathering and Minimax for cleanup.
Developer Rebuilds LinkedIn Research Agent After Account Restriction
A developer rebuilt their OpenClaw agent to use LinkedIn's API instead of browser automation after mass-visiting 200 profiles triggered an account restriction. The new approach uses direct API calls for cleaner data and avoids detection.
Building a Contextual Personal AI News Briefing System with Claude Code
A developer built a personal AI news briefing system that runs on a Mac Mini three times weekly, pulling from 17 sources and using Claude Code with memory integration to create personalized briefs. The system costs $6-12/month and includes sections connecting news to active projects, code references, and family interests.
Practical Criticism of LLM Memory: Immutable Reflections & Ephemeral Sessions as Solutions
A critique of long-running sessions, life-companions, and LLM-wiki memory, offering solutions like immutable reflections, issue-bound session chains, and prompt templates to avoid intent loss and context overload.