Build a working AI agent that can reason, plan, and execute multi-step tasks!
LLM-powered AI agents are the next leap in applied AI, capable of reasoning and collaboration to achieve even complex, multi-step goals. Using new protocols like MCP and A2A, agents can use software tools, retrieve relevant knowledge, and adapt to feedback. This book guides you step by step in creating an AI agent from the ground up, with clear, detailed explanations you can follow to build your own custom assistants!
In
Build an AI Agent (From Scratch) you will learn how to:
- Implement a ReAct (Thought → Action → Observation) loop
- Use MCP to integrate tools calls into your agent’s workflow
- Agentic RAG for relevant responses
- Create memory modules that store facts, context, and evolving goals
- Enable agents to plan, reflect, and self-correct
- Build specialized agents, including a code execution agent
- Design multi-agent systems
In
Build an AI Agent (From Scratch), bestselling author
Jungjun Hur and AI expert
Younghee Song guide you through creating a complete research assistant agent framework. You’ll learn how agents function under the hood—all without hidden abstractions, black boxes, or frameworks lock-in. You will implement each piece as you develop a mental model of how agents really work.