This section highlights selected writings and articles by James Murray on AI, addiction recovery, vector intelligence, and the future of search. The focus is on practical, system-level thinking: how to move from hand-waving about “AI” to tools that actually help people.

Featured Themes

• Recovery Technology: Designing AI tools that support—not replace—human care, especially in high-stress situations.
• Vector Intelligence: Why embeddings and semantic search are the real infrastructure shift behind modern AI.
• Future of Search: Moving beyond keyword SEO toward intent, context, and vector-native search experiences.
• Crypto & Market Systems: Using embeddings, signals, and on-chain data to reduce noise in markets.

Sample Article Topics

• “Why Recovery Needs Vector Search, Not Just Hotlines”
  A look at how semantic search can cut through contradictory rehab information and connect people with relevant options faster.
• “From Blue Links to Answers: Building RAG-First Websites”
  A technical and strategic guide to shifting a content site from traditional search to RAG-backed answer layers.
• “Semantic SEO in the Age of Embeddings”
  How to think about content clusters, internal links, and entity graphs when vector databases are in the loop.
• “Designing AI Systems for People in Crisis”
  Lessons from addiction recovery work: safety, clarity, and the importance of not overwhelming users.

Who These Articles Are For

• Recovery centers and treatment organizations wondering how AI can help without losing human connection.
• Technical teams building RAG, vector search, or AI-assisted content platforms.
• Founders and leaders preparing for a world where search is semantic, conversational, and vector-driven by default.

As more essays, case studies, and technical deep-dives are written, they will be linked from this page or integrated into project-specific sections like Vector Database Search and AddictionTube RAG FAQ.