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Home > Computing and Information Technology > Computer science > Artificial intelligence > Natural language and machine translation > Building Agentic AI with Rust: Design and Deploy Retrieval-Augmented Generation (RAG) Systems, Autonomous AI Agents, and LLM Powered Applications Using Secure, High-Performance Ru
Building Agentic AI with Rust: Design and Deploy Retrieval-Augmented Generation (RAG) Systems, Autonomous AI Agents, and LLM Powered Applications Using Secure, High-Performance Ru

Building Agentic AI with Rust: Design and Deploy Retrieval-Augmented Generation (RAG) Systems, Autonomous AI Agents, and LLM Powered Applications Using Secure, High-Performance Ru


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About the Book

Agentic AI-autonomous systems capable of perception, reasoning, and action-is redefining how we build intelligent applications. From AI customer service agents and healthcare assistants to real-time financial analysis tools, these systems integrate Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and goal-oriented control. Rust, with its unmatched performance, safety guarantees, and asynchronous power via Tokio, is the ideal language to build scalable, high-concurrency AI agents that are production-ready. Written by a seasoned systems engineer and AI practitioner, Building Agentic AI with Rust is the first comprehensive guide focused on using Rust to build high-performance, autonomous AI agents. With deep real-world experience, clean architectural patterns, and a practical teaching style, this book bridges the gap between cutting-edge AI research and robust, deployable software engineering practices. This hands-on guide shows developers how to architect, implement, and deploy agentic AI systems using Rust and modern AI tools like OpenAI, Hugging Face, and vector search engines. Each chapter provides a step-by-step approach, from designing the agent loop to implementing a scalable RAG system and deploying with Docker and cloud services. You'll learn best practices for async programming with Tokio, profiling for performance, and implementing real-world use cases across industries. Implementing the Perceive-Reason-Act loop in Rust Architecting modular AI agents with traits and async tasks Integrating OpenAI and Hugging Face LLMs using structured prompts Building Retrieval-Augmented Generation (RAG) pipelines Scaling with Tokio, caching, and vector stores like Qdrant Packaging, containerizing, and deploying agents to AWS and GCP Monitoring, logging, and optimizing agents for production Full case studies: customer support, healthcare, and financial AI This book is written for Rust developers, AI engineers, system architects, and technical enthusiasts looking to build powerful autonomous agents with real-world capabilities. If you're comfortable with Rust and want to extend your skills into modern AI systems, this guide is for you. No prior experience with LLMs or RAG is required-concepts are introduced clearly and practically. Agentic AI is no longer experimental-it's production-ready, and it's here now. As the field of generative AI evolves rapidly, learning to build scalable, secure, and performant agents with Rust puts you ahead of the curve. Don't wait to catch up with the future-become one of the first engineers building it. Master the intersection of systems programming and generative AI. Build fast, safe, and intelligent autonomous agents with Rust today. Get your copy of Building Agentic AI with Rust and start coding the future of AI, now.


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Product Details
  • ISBN-13: 9798287613884
  • Publisher: Independently Published
  • Publisher Imprint: Independently Published
  • Height: 254 mm
  • No of Pages: 238
  • Returnable: N
  • Sub Title: Design and Deploy Retrieval-Augmented Generation (RAG) Systems, Autonomous AI Agents, and LLM Powered Applications Using Secure, High-Performance Ru
  • Width: 178 mm
  • ISBN-10: 8287613884
  • Publisher Date: 10 Jun 2025
  • Binding: Paperback
  • Language: English
  • Returnable: N
  • Spine Width: 13 mm
  • Weight: 471 gr


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Building Agentic AI with Rust: Design and Deploy Retrieval-Augmented Generation (RAG) Systems, Autonomous AI Agents, and LLM Powered Applications Using Secure, High-Performance Ru
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Building Agentic AI with Rust: Design and Deploy Retrieval-Augmented Generation (RAG) Systems, Autonomous AI Agents, and LLM Powered Applications Using Secure, High-Performance Ru
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