Arun Baby

ML Researcher → AI Engineer → Architecting intelligent agent systems

Building Multi-Agent Systems That Actually Work

I’m writing a book on AI agent orchestration – the architecture, patterns, and hard-won lessons behind building multi-agent systems that ship to production.

This isn’t another “intro to LLMs” book. It’s for engineers who need to move beyond single-agent demos into coordinated, reliable, production-grade agent systems.

What the Book Covers

Part I: Foundations

  • What agents actually are (and aren’t) in production systems
  • The architecture stack: perception, reasoning, memory, action
  • When single agents fail and orchestration becomes necessary

Part II: Orchestration Patterns

  • Agent communication protocols and message passing
  • Hierarchical vs. flat multi-agent architectures
  • Task decomposition and dependency management
  • Shared memory and state coordination

Part III: Production Engineering

  • Reliability engineering for non-deterministic systems
  • Cost management and token optimization at scale
  • Testing strategies for multi-agent workflows
  • Monitoring, observability, and debugging agent systems

Part IV: Advanced Topics

  • Voice agent orchestration and real-time constraints
  • Human-in-the-loop patterns
  • Scaling from prototype to millions of interactions
  • The future of agent-native software

Why This Book

I’ve spent the last decade at the intersection of speech research and production AI systems – from building TTS systems at IIT Madras to shipping conversational AI at Samsung Research to leading agentic AI as CTO.

The 60+ articles in my AI Agents collection cover the individual concepts. This book connects them into a coherent engineering discipline.

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Preview the Depth

Want a sense of the technical depth? Explore the AI Agents collection – 62 deep-dives on agents, from foundational concepts to multi-agent architectures to production deployment patterns.