LangChain 创始人手把手教你如何迭代改进智能体，从构建到上线再到优化，全是实操干货，适合所有做 AI Agent 的团队。
Harrison Chase 指出，发布第一版只是构建智能体工作的一小部分，更关键的是建立可重复的改进生命周期。该流程包括 5 步：1）Build——搭配 agent、tools、context、prompts 和 workflows 构建可用原型；2）Test——使用 evals 评估 agent 行为是否正确，而非仅输出类似内容；3）Deploy——将 agent 部署到生产环境；4）Monitor——通过 traces 追踪 agent 实际调用的工具、使用的上下文和失败点；5）Improve——从真实使用中学习，优化 prompts、tools、evals 和 agent 本身。Chase 将在 6 月 24 日的“The Agent Development Lifecycle 101”网络研讨会中详细讲解。
One thing we’ve seen pretty consistently: shipping the first version is only a small part of the wor...
One thing we’ve seen pretty consistently: shipping the first version is only a small part of the work A key part of building reliable agents is having a repeatable lifecycle for improving them over time Here’s what that looks like: 1/ Build. Start with the agent, tools, context, prompts, and workflows needed to get something useful in front of users 2/ Test. Use evals to understand whether the agent is doing the right thing, not just returning something that looks right 3/ Deploy. Get agents into production environments where they can actually be used 4/ Monitor. Look at traces to understand what the agent actually did: what tools it called, what context it used, where it failed 5/ Improve. Take what you learn from real usage and turn it into better prompts, better tools, better evals, and better agents We think this type of lifecycle is something every team building agents will need I’m going to walk through this in more detail on June 24 in The Agent Development Lifecycle 101 Sign up here: events.langchain.com/webinar/the-ag… 💬 5 🔄 2 ❤️ 20 👀 2685 📊 8 ⚡
- LangChain06-22 17:01原文