Context Engineering

2025-07-30
From Prompt Engineering to Context Engineering: The Secret to Writing Good Agents

[This article is based on a presentation at the Turing Community’s Large Model Technology Learning Camp, Slides Link]

Explore the design philosophy and practical strategies of AI Agents in depth. From the conversational mode of Chatbots to the action mode of Agents, systematically design and manage the information environment of Agents to build efficient and reliable AI Agent systems.

Table of Contents

  1. Part 1: Paradigm Shift - From Chatbot to Agent
  2. Part 2: Core Analysis of Agents
  3. Part 3: Context Engineering
  4. Part 4: Memory and Knowledge Systems

Part 1: Paradigm Shift - From Chatbot to Agent

From Chatbot to Agent: A Fundamental Paradigm Shift

We are experiencing a fundamental shift in AI interaction modes:

Chatbot Era

  • 🗣️ Conversational Interaction: User asks → AI answers → Repetitive Q&A cycle
  • 📚 Knowledgeable Advisor: Can only “speak” but not “act,” passively responding to user needs
  • 🛠️ Typical Products: ChatGPT, Claude Chat

Agent Era

  • 🎯 Autonomous Action Mode: User sets goals → Agent executes → Autonomous planning and decision-making
  • 💪 Capable Assistant: Can both “think” and “act,” proactively discovering and solving problems
  • 🚀 Typical Products: Claude Code, Cursor, Manus
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