Agentic AI Technical Reference Vol 2

Agentic AI Technical Reference – Volume 2 is the practical implementation guide for engineers who want to move beyond concepts and build production-ready AI agents using today's leading frameworks.

While Volume 1 introduced the foundations of agentic AI, this volume focuses on deep framework mastery. Through progressively structured chapters, production patterns, architectural guidance, real-world code examples, troubleshooting advice, and complete capstone projects, you'll learn how to design, deploy, optimize, and scale enterprise-grade AI agents.

Inside this volume you'll gain hands-on expertise with:

• LangChain architecture, LCEL, tools, memory, and production RAG
• LangGraph for stateful workflows, routing, reflection loops, streaming, and multi-agent orchestration
• CrewAI for role-based autonomous teams, YAML configuration, Flows, and multi-LLM systems
• AutoGen conversational agents, GroupChat, code execution, and autonomous engineering teams
• OpenAI Agents SDK including handoffs, tracing, runners, and guardrails
• Agentic RAG including Corrective RAG, Self-RAG, Adaptive RAG, RAPTOR, and multi-hop reasoning
• Function calling, structured outputs, and advanced agent memory architectures
• Agent swarms, debate patterns, Constitutional AI, and alignment strategies
• Cost optimization through caching, model routing, token budgeting, and reliability engineering
• Low-code automation using n8n, LangFlow, and Flowise
• Security, prompt injection defense, guardrails, evaluation, benchmarking, testing, and observability
• Docker, Kubernetes, asynchronous execution, production monitoring, and enterprise deployment
• Industry applications across finance, healthcare, coding assistants, customer support, research, and engineering automation
• Multiple end-to-end production projects with complete implementations and deployment guidance

Unlike introductory AI books, this reference emphasizes production engineering. Every chapter combines conceptual understanding with practical implementation, common failure scenarios, debugging strategies, and best practices drawn from real-world AI systems.

Whether you're building enterprise copilots, autonomous workflows, multi-agent platforms, AI research assistants, or production RAG systems, this volume provides the knowledge needed to build reliable, scalable, and maintainable agentic applications.

Ideal for:

• AI Engineers
• GenAI Engineers
• Machine Learning Engineers
• Software Engineers
• Backend Developers
• AI Architects
• Technical Leads
• Data Scientists
• Students transitioning into Agentic AI
• Professionals building production LLM applications

Continue your journey from understanding AI agents to engineering production-ready autonomous systems with Agentic AI Technical Reference – Volume 2.