Agentic AI Systems: Build Multi-Agent Workflows with LangChain, MCP, RAG & Ollama
(A Practical Guide to Local LLM Orchestration, Retrieval-Augmented Generation, and Autonomous Agents)
Unlock the power of local LLMs, agentic AI architectures, and multi-agent orchestration with this hands-on guide designed for developers, AI engineers, and system architects building intelligent applications beyond the cloud. In an era where data privacy, autonomous workflows, and cost-effective deployments are critical, this book offers a production-ready blueprint using LangChain, Model Context Protocol (MCP), Retrieval-Augmented Generation (RAG), and Ollama.
Whether you're designing AI copilots, deploying autonomous agents, or developing secure on-premise AI systems, this guide helps you go from concept to execution with confidence.
What You'll Learn:
Set up a complete agentic AI stack with LangChain, LangGraph, MCP, and Ollama
Run private LLMs like Llama 3 and Mixtral with full control using Ollama
Fine-tune models with LoRA/QLoRA for domain-specific applications
Design and orchestrate multi-agent systems using LangGraph and graph-based coordination
Build robust Retrieval-Augmented Generation pipelines using FAISS and Chroma
Implement secure message-passing and streaming using MCP
Handle authentication, observability, and compliance (GDPR, HIPAA, SOC 2)
Deploy agents with Docker, Kubernetes, and scalable CI/CD pipelines
Who This Book Is For:
AI engineers and backend developers working with LLMs and LangChain
Security-conscious teams needing private and auditable AI workflows
DevOps and MLOps professionals deploying containerized AI systems
Researchers and tech leads building autonomous agent systems
Anyone interested in real-world agentic AI with local deployment capabilities
Unlike cloud-reliant AI books or overly academic texts, Agentic AI Systems delivers actionable blueprints for building and deploying real systems on local infrastructure. You'll explore hands-on code, architecture diagrams, and reusable patterns that scale from laptops to clusters. No fluff-just proven strategies and reproducible workflows grounded in current LLM capabilities.
Roberto Pizzlo is an AI infrastructure engineer and systems architect specializing in agentic orchestration and secure LLM deployments. Known for translating cutting-edge AI concepts into practical engineering, he brings a wealth of expertise in LangChain, LangGraph, RAG architectures, and edge AI systems. His experience bridges research, enterprise, and open-source ecosystems-making this book an essential guide for professionals navigating the fast-evolving world of autonomous AI.
This guide reflects 2025 technologies and best practices, including the latest versions of LangChain, Ollama (v0.2.16+), CUDA 12.9, and RAG toolchains. It ensures your understanding remains relevant in a rapidly changing AI landscap
