The infrastructure handbook for building AI agents that survive real users. Move beyond prompt chains and learn the production principles that treat agents like the distributed systems they are – not another framework tutorial.

“After 30 years building distributed systems, I've watched the AI industry repeat every mistake we made – and solved – decades ago. Those lessons are now applied to autonomous AI.”
– Ran Aroussi, Author

Book description

Most AI systems today fail in production. They chain prompts together and call it "agentic." They rely on a dozen stitched-together tools and collapse under real-world pressure. The gap between demo and production remains enormous.

This book bridges that gap.

It provides a comprehensive guide to the architecture, design principles, and infrastructure patterns needed to build autonomous AI systems that actually work in production. Moving beyond vendor-specific tutorials and framework documentation, you'll understand the universal principles that make agentic systems reliable, observable, and deployable at scale.

What you'll learn

• The three pillars of true autonomy - What separates real agents from chatbots with tool access
• Multi-tier memory architecture - Design systems that scale from buffer to persistent storage
• Intelligent orchestration and multi-agent coordination - Task decomposition and adaptive workflows
• Observability for non-deterministic behavior - Track, debug, and audit autonomous systems
• Avoid vendor lock-in - Multi-model routing with automatic failover and resilience
• Ship complete production examples - Real deployments, not toy demos

About the Author

Ran Aroussi is a self-taught software engineer with 30+ years building production systems – from ad-serving engines delivering 3 billion ads daily to creating yfinance, one of the world's most widely adopted data libraries (10M+ monthly users).

Frustrated by the gap between AI demos and production reality, he wrote this book for engineers tired of hype and ready to build infrastructure that actually works at scale.

Through his companies, he continues to champion pragmatic engineering and open infrastructure that actually works at scale.