This volume examines the architecture and implementation of modular agentic workflows in production environments. It focuses on the coordination of specialized AI agents within structured digital assembly lines, leveraging CrewAI for role-based orchestration and LlamaIndex for data-aware indexing and retrieval in complex, multi-step processes. Designed for software engineers, AI system architects, and technical leads with prior experience in large language model applications, the content addresses the design, integration, and optimization of agent teams for scalable, maintainable workflows. Topics include agent role definition, task decomposition, context management, tool integration, workflow monitoring, and advanced patterns for enterprise deployment. The material assumes familiarity with Python, LLM APIs, and basic orchestration concepts, emphasizing practical engineering considerations rather than introductory tutorials. Readers will find detailed explorations of component interactions, performance trade-offs, and architectural decisions relevant to real-world implementations in 2026. If you are an experienced practitioner seeking to advance your capabilities in building robust, modular agentic systems, this book provides structured technical insight into current frameworks and patterns. Add it to your professional library today.
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