English中文日本語

Part 3: Context and Memory

How does an Agent remember past conversations? How does it manage limited context windows?

What This Part Covers

This part explores how Agents handle information across conversations:

  • Chapter 7: Context Window Management — Strategies for fitting information within token limits
  • Chapter 8: Memory Architecture — Short-term, long-term, and semantic memory systems
  • Chapter 9: Multi-Turn Conversation Design — Maintaining coherence across dialogue turns

Key Questions Answered

  • How do you decide what to keep vs. discard when context overflows?
  • What's the difference between conversation history and memory?
  • How do you implement semantic search for relevant memories?
  • When should you summarize vs. truncate context?

Prerequisites

  • Understanding of Agent fundamentals (Part 1)
  • Basic knowledge of tool calling (Part 2)

Continue to Chapter 7: Context Window Management →

Cite this article
Zhang, W. (2026). Part 3 Overview. In AI Agent Architecture: From Single Agent to Enterprise Multi-Agent Systems. https://waylandz.com/ai-agent-book-en/part3-overview
@incollection{zhang2026aiagent_en_part3_overview,
  author = {Zhang, Wayland},
  title = {Part 3 Overview},
  booktitle = {AI Agent Architecture: From Single Agent to Enterprise Multi-Agent Systems},
  year = {2026},
  url = {https://waylandz.com/ai-agent-book-en/part3-overview}
}