English中文日本語

Part 1: Agent Fundamentals

Understanding the essence of AI Agents, from LLMs to autonomous intelligent entities

Chapter List

ChapterTitleCore Question
01The Essence of AgentsWhat is an Agent? How does it differ from a regular Chatbot?
02The ReAct LoopHow does an Agent think and act?

Learning Objectives

After completing this Part, you will be able to:

  • Understand the definition and autonomy spectrum of Agents
  • Master the ReAct (Reason-Act-Observe) basic loop
  • Distinguish the fundamental difference between Agents and traditional Chatbots
  • Understand the overall design philosophy of Shannon architecture

Shannon Code Guide

Shannon/
├── docs/multi-agent-workflow-architecture.md  # Architecture overview
├── go/orchestrator/internal/workflows/strategies/react.go   # ReactWorkflow (workflow layer)
└── go/orchestrator/internal/workflows/patterns/react.go     # ReactLoop (pattern layer)

Prerequisites

  • LLM fundamentals (Prompt, Token, Temperature)
  • Basic programming ability (Go/Python either one)
Cite this article
Zhang, W. (2026). Part 1: Agent Fundamentals. In AI Agent Architecture: From Single Agent to Enterprise Multi-Agent Systems. https://waylandz.com/ai-agent-book-en/part1-overview
@incollection{zhang2026aiagent_en_part1_overview,
  author = {Zhang, Wayland},
  title = {Part 1: Agent Fundamentals},
  booktitle = {AI Agent Architecture: From Single Agent to Enterprise Multi-Agent Systems},
  year = {2026},
  url = {https://waylandz.com/ai-agent-book-en/part1-overview}
}