LangChain(@LangChainAI)
Want to run the same harness across multiple interfaces? Try ACP. Deep Agents ships with it out of ...
5.2Score
TL;DR · AI 摘要
LangChain 推出 ACP（Agent Control Protocol）以支持跨接口复用同一 agent harness，Deep Agents 已原生集成，但原文缺乏技术细节与实现说明。
核心要点
- ACP 是一种旨在统一 agent 执行环境的控制协议
- Deep Agents 默认支持 ACP，降低多界面适配成本
- 接口抽象层对 agent 工程化的重要性不亚于模型选型
结构提纲
按章节快速跳转。
- ·核心主张
强调 harness 和接口抽象对 agent 开发体验的关键影响。
- ·产品集成
指出 Deep Agents 已内置 ACP，开箱即用。
- ›背景补充
引用 Mason Daugherty 观点：开源 LLM 在 agent 任务进步显著，但运行时框架更关键。
思维导图
用一张图看清主题之间的关系。
查看大纲文本（无障碍 / 无 JS 友好）
- ACP 协议
- 目标
- 跨接口复用 agent harness
- 载体
- Deep Agents 原生支持
- 动因
- 接口抽象决定开发体验上限
金句 / Highlights
值得收藏与分享的关键句。
Want to run the same harness across multiple interfaces? Try ACP.
Deep Agents ships with it out of the box.
the harness you wrap them in matters just as much as the model itself, and arguably the interface you use to drive that harness matters even more.
#LangChain#agent#ACP#LLM
打开原文Deep Agents ships with it out of the box." / X
LangChain on X: "Want to run the same harness across multiple interfaces? Try ACP. Deep Agents ships with it out of the box." / X
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Want to run the same harness across multiple interfaces? Try ACP. Deep Agents ships with it out of the box.
Quote
Mason Daugherty
@masondrxy
·
12h
open-weight LLMs have come a long way on agent tasks! but the harness you wrap them in matters just as much as the model itself, and arguably the interface you use to drive that harness matters even more. dev workflows are deeply personal. what works well for one developer may
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