{"product_id":"agentic-rag-with-crew-ai-in-action-build-smarter-ai-systems-with-agentic-reasoning-task-chaining-and-dynamic-knowledge-access-9798292020509","title":"Agentic RAG with Crew AI in Action: Build Smarter AI Systems with Agentic Reasoning, Task Chaining, and Dynamic Knowledge Access","description":"\u003cp\u003e • Author(s): Devin Albert\u003cbr\u003e • Publisher: Independently Published\u003cbr\u003e • Publisher Imprint: Independently Published\u003cbr\u003e • BISAC: Artificial Intelligence - General\u003c\/p\u003e\u003cp\u003e\u003cb\u003eAgentic RAG with Crew AI in Action: \u003c\/b\u003e\u003cbr\u003e\u003cb\u003eBuild Smarter AI Systems with Agentic Reasoning, Task Chaining, and Dynamic Knowledge Access\u003c\/b\u003e \u003c\/p\u003e\u003cp\u003e\u003c\/p\u003eModern AI isn't just about generating answers-it's about building systems that can think, retrieve, and act autonomously. Agentic RAG with Crew AI in Action shows you exactly how to combine Retrieval-Augmented Generation (RAG) with Crew AI to create intelligent, modular, and scalable multi-agent systems that reason through problems, retrieve knowledge when needed, and chain tasks together toward a goal.\u003cbr\u003eThis book takes you inside the architecture of smart agentic systems, guiding you step-by-step as you design agents with roles, memory, planning capabilities, and tool use. You'll understand how to build agents that know when to query a vector database, when to rely on memory, how to use APIs or file systems, and how to collaborate across multiple agents with distinct responsibilities.\u003cbr\u003eBuilt for developers, ML practitioners, and AI system architects, the book offers everything from foundational concepts to advanced implementation techniques. Every chapter includes practical explanations, real-world code examples, and complete workflows-no fluff, no hand-waving.\u003cbr\u003e\u003cb\u003eYou'll learn how to: \u003c\/b\u003e\u003cbr\u003eUse Crew AI to define roles, assign tasks, and coordinate agent behavior\u003cbr\u003eIntegrate RAG pipelines using LangChain, LlamaIndex, and vector databases\u003cbr\u003eStructure multi-agent workflows with memory, feedback loops, and adaptive planning\u003cbr\u003eBuild agents that retrieve data, use tools, reflect on output, and make decisions\u003cbr\u003eHandle logging, debugging, security, and scaling across distributed environments\u003cbr\u003eYou'll also explore powerful use cases like automated research assistants, legal brief generators, and business data analyzers-real projects that showcase the full potential of agentic systems in action.\u003cbr\u003e\u003cb\u003eThis book isn't just theory-it's a full engineering guide for the next generation of AI.\u003c\/b\u003e\u003cbr\u003eIf you're ready to stop building static chatbots and start building AI systems that can think through tasks, work with knowledge, and operate autonomously across complex workflows, this is your playbook.\u003cbr\u003e\u003cb\u003eBuild smarter. Build faster. Build agentic AI that works. Get started today.\u003c\/b\u003e","brand":"Atlantic Books","offers":[{"title":"Paperback","offer_id":46334679122071,"sku":"9798292020509","price":1839.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9798292020509.webp?v=1768672896","url":"https:\/\/atlanticbooks.com\/products\/agentic-rag-with-crew-ai-in-action-build-smarter-ai-systems-with-agentic-reasoning-task-chaining-and-dynamic-knowledge-access-9798292020509","provider":"Atlantic Books","version":"1.0","type":"link"}