I’ve been exploring a hybrid approach to learning that combines the depth of traditional books with the breadth of AI-generated research. Traditional books give me the foundational knowledge and deep insights from experts, while LLM-generated research books allow me to explore specific topics with comprehensive, up-to-date information synthesized from multiple sources.

I find that reading a traditional book on a topic, then diving into an LLM-researched book on a specific aspect, creates a powerful learning combination.

The following are some of the content I am currently reading or have recently read (or re-read). I am not planning to make this a comprehensive list. I will probably add more as I read more.

📚 Books#

🛠️ To sharpen the Craft#

  • Database System Concepts by Avi Silberschatz, Henry F. Korth, S. Sudarshan
  • The Staff Engineer’s Path by Tanya Reilly
  • Hard things about hard things by Ben Horowitz
  • Zero to One by Peter Thiel

❤️ To Feed the Soul#

  • Genghis Khan and the Making of the Modern World by Jack Weatherford
  • A Thousand Splendid Suns by Khaled Hosseini
  • The Godfather by Mario Puzo
  • The Kite Runner by Khaled Hosseini
  • Roma by Steven Saylor

🤖 LLM-Generated Research Books#

These are books (if you can call them that), I’ve created using AI research on specific topics. Each contains deep research and insights synthesized from multiple sources.

📄 Research Papers#

  • Bigtable - A Distributed Storage System for Structured Data
  • BitCask - A Log-Structured Hash Table for Fast Key/Value Data
  • Dynamo - Amazon’s Highly Available Key-value Store
  • ClickHouse - Lightning Fast Analytics for Everyone