Model. Harness. Context. The 3 Main Components of Agents
TL;DR · AI Summary
LangChain identifies three core components for agents: Model, Harness, and Context, and introduces LangSmith Context Hub to manage context efficiently.
Key Takeaways
- Agents are composed of three key parts: Model, Harness, and Context.
- With more agents being built, Context needs dedicated management—LangChain creat
- Context includes AGENTS.md, skills, policies, examples, and generated research f
Outline
Jump quickly between sections.
Mindmap
See how the topics connect at a glance.
查看大纲文本（无障碍 / 无 JS 友好）
- 智能体架构
- Model
- Harness
- Context
- AGENTS.md
- 技能
- 策略
- 示例
- 研究文件
- 管理工具
- LangSmith Context Hub
Highlights
Key sentences worth saving and sharing.
Model. Harness. Context. The 3 main components of agents.
As you build more agents, context increasingly lives in AGENTS.md, skills, policies, examples, + generated research files.
That’s why we built LangSmith Context Hub.
The 3 main components of agents.
As you build more agents, context increasingly lives AGENTS.md, skills, policies, examples, + generated research files.
Context needs its own home. That’s why we built LangSmith Context Hub. https://t.co/OLr85Nh27n" / X
LangChain on X: "Model. Harness. Context. The 3 main components of agents. As you build more agents, context increasingly lives AGENTS.md, skills, policies, examples, + generated research files. Context needs its own home. That’s why we built LangSmith Context Hub. https://t.co/OLr85Nh27n" / X
Don’t miss what’s happening
Model. Harness. Context. The 3 main components of agents. As you build more agents, context increasingly lives AGENTS.md, skills, policies, examples, + generated research files. Context needs its own home. That’s why we built LangSmith Context Hub.
·
7
18
90
65
Read 7 replies