Building a Contextual Personal AI News Briefing System with Claude Code

How the System Works

The briefing system operates in two stages. Stage 1 uses Python to fetch data from 17 sources concurrently: Substacks, Reddit, Hacker News, arXiv, GitHub Trending, Bluesky, company blogs (Anthropic, OpenAI, Google, etc.), mainstream news (NYT, Verge, Ars Technica, TechCrunch), HuggingFace papers, MCP registries, and podcasts with Groq transcription. This stage performs basic time filtering and URL deduplication, dumping raw JSON with 200-300 items per run. No LLM calls occur here—it's purely data collection.

Stage 2 involves a Claude Code session launched via shell script with claude -p and tool access including file read/write, web search, and a personal memory system called maasv. This memory system maintains a graph of projects, decisions, and context over time via MCP.

Claude Session Process

The Claude session bootstraps memory to understand what the developer has been working on in the last 48-72 hours, reads the raw feed JSON from Stage 1, performs 5-10 targeted web searches to fill gaps based on current focus, reads previous briefs to avoid repeats and catch multi-week trends, and reads actual source code when news items connect to projects. It writes narrative briefs to .md and .html formats and logs everything to memory for future reference.

Brief Sections

• Front of Mind: Connects today's news to active work. If a dependency was switched yesterday and that vendor appears in today's news, it makes the connection.
• The Brief: 4-6 paragraphs of narrative analysis tying stories together, not in list format.
• Devil's Advocate: Challenges recent decisions with evidence. If a data source was dropped for ethical reasons, it specifies what coverage is being lost.
• Wife's Corner: Curates AI + finance news for the developer's wife who works in venture and M&A at a credit rating agency.
• Code Connections: Maps news to specific files and line numbers in the codebase. For example: "This new open-weight model's specs make it a candidate for your local fallback path at llm/providers/init.py:95-145." It reads the code to write these connections.
• Worth a Click: 10 overflow items that didn't make the narrative but are worth clicking.

Technical Implementation

The system runs M/W/F at 6:30 AM on a Mac Mini using launchd for scheduling. The tech stack includes Python (async httpx, feedparser, beautifulsoup4), Claude Code CLI (claude -p with --allowedTools), maasv (personal memory system via MCP), Groq (podcast transcription), and Markdown with a small HTML converter for mobile reading. Total cost is approximately $6-12/month.

The developer notes that the memory layer (maasv) is key to making the system work effectively, as it maintains context about projects, decisions, family interests, and reading history.