Building an AI agent is one thing. Building one that is reliable, secure, and ready for real-world use is another.
If AI agents, RAG, tool calling, workflows, or multi-agent systems feel complicated, Building Production AI Agents with Agno gives you a clear, practical path forward.
You do not need prior experience with Agno, AgentOS, multi-agent systems, or advanced machine learning. With basic Python familiarity, you can follow the book step by step as you build a real agent application from the ground up.
Rather than using disconnected examples, the book develops OpsPilot, a continuing project that evolves from a simple AI agent into a secure, stateful, observable, production-ready platform. Each chapter adds one practical layer at a time, helping you understand not only what to build, but why each production decision matters.
Mistakes, failed requests, unexpected outputs, and integration problems are treated as a normal part of learning. Small wins build confidence as you progress.
Key FeaturesStep-by-step development with Python, Agno, and AgentOS
One complete project that grows throughout the book
Practical coverage of RAG, MCP, tools, memory, Teams, and Workflows
Human-in-the-loop controls for sensitive actions
Testing, evaluation, tracing, logging, and observability
Security, authentication, authorization, secrets, and guardrails
Containerization, deployment, scaling, and production operations
Practical exercises, verification checklists, and key takeaways
What You Will LearnYou will learn how to:
Build and configure reliable Agno agents
Create custom Python tools and safe agent actions
Add sessions, persistent state, and user memory
Build knowledge systems with retrieval-augmented generation (RAG)
Connect external context through Model Context Protocol (MCP)
Design multi-agent systems with specialized Teams
Build sequential, parallel, conditional, and iterative workflows
Add human approval to higher-risk operations
Run production services with AgentOS
Test, evaluate, monitor, secure, deploy, and scale agentic applications
Who This Book Is ForThis book is ideal for:
Beginners entering AI-agent development
Python developers exploring Agno and AgentOS
Software engineers building practical LLM applications
Self-learners who prefer hands-on projects over heavy theory
Developers interested in RAG, MCP, tool calling, memory, and AI workflow orchestration
Professionals moving from prototypes to production AI systems
Table of ContentsChapter 1: Agno Foundations and Project Setup
Chapter 2: Engineering Reliable Agents
Chapter 3: Tools and Safe Agent Actions
Chapter 4: Sessions, State, Memory, and Persistence
Chapter 5: Knowledge, RAG, and External Context
Chapter 6: Building Multi-Agent Systems with Teams
Chapter 7: Workflows and Human-Controlled Orchestration
Chapter 8: Running Production Agents with AgentOS
Chapter 9: Testing, Evaluation, Observability, and Reliability
Chapter 10: Security, Deployment, and Production Operations
Chapter 11: Capstone - Building the Production OpsPilot Platform
By the end, you will understand how to move from a basic Python agent to a production-style AI system with tools, memory, knowledge, workflows, security, observability, and deployment.
Start building today and turn AI-agent development into a practical skill you can use with confidence.
