AI agents are redefining modern software—powering chatbots, automation systems, productivity tools, and fully autonomous workflows. By combining Python, LLMs, reinforcement learning, and agent frameworks like LangGraph, LangChain, and n8n, developers can now build intelligent systems that reason, plan, and act.
This book is a practical guide to creating real agentic AI systems from the ground up.If you want to design conversational agents, build task-oriented automation, or deploy fully autonomous decision-making systems, this book provides the tools and step-by-step skills you need.
What You Will LearnCore Agent Foundations- How agent architectures, memory, planning, and tools work
- The difference between reactive, cognitive, and autonomous agents
- How LLMs and machine learning models drive intelligent behavior
Practical ML & RL for Agents- Key machine learning and deep learning concepts
- Reinforcement learning for adaptive decision-making
- Training and improving agent behavior
Hands-On ProjectsBuild real systems, including:
- Conversational chatbots with memory
- Task-executing agents using tools and APIs
- Automation pipelines with n8n
- Multi-agent collaboration systems
- Python-driven autonomous agents
Deployment & Scaling- Packaging agents for production
- Integrating APIs, vector databases, and external tools
- Monitoring, optimizing, and improving performance
Who This Book Is ForDevelopers, engineers, data scientists, and AI enthusiasts who want to build
practical, real-world AI agents. A basic understanding of Python is all you need.
Build the Future of Intelligent AutomationStart your journey into agentic AI and learn how to create systems that think, learn, and act.
Grab your copy and begin building the next generation of AI agents.