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Stanford CS146S 如何教 AI 原生工程:访谈 Mihail Eric

原标题:[One Million AI Engineer Special] How Stanford Teaches AI-Native Engineering — Mihail Eric, Monaco

Latent Space 在 AI Engineer 频道百万订阅特辑中访谈 Stanford CS146S 授课教师、Monaco AI 负责人 Mihail Eric。第二期课程引入开源维护者,要求学生学习陌生仓库、提交修改并向可能合并代码的维护者讲解补丁;访谈还展示了 Monaco 的 agent workspaces、接入 Datadog 和 GitHub 的 on-call agent,以及团队在自建与采购工具间的取舍,完整视频和十周课程大纲可在 YouTube 查看。

为什么值得看

访谈公开了 Stanford CS146S 的教学设计思路,并对比 Monaco 团队自建与采购工具的实际取舍,对工程团队有参考。

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原文

← The conversationsLatent Space Podcast

What do you assign when a coding agent can finish last year’s homework in one prompt? In the second run of Stanford’s CS146S, Mihail Eric brought open-source maintainers into the course. Students have to learn an unfamiliar repo, propose a change, and ...

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What do you assign when a coding agent can finish last year’s homework in one prompt? In the second run of Stanford’s CS146S, Mihail Eric brought open-source maintainers into the course. Students have to learn an unfamiliar repo, propose a change, and explain the patch to the person who might merge it.

We invited Mihail, who teaches The Modern Software Developer at Stanford and leads AI at Monaco, to celebrate one million subscribers on the AI Engineer YouTube channel. He opens up the course syllabus and shows us which lessons survived contact with his own engineering team. Monaco built its agent workspaces, bought its code review tools, and gave an on-call agent access to Datadog and GitHub. We ask how he decides which tools his team needs to own.

Watch the full interview and screenshares on YouTube.

Show notes

Timestamps

0:00 One million AI Engineer subscribers and the CODE Summit
0:51 Mihail Eric and Stanford CS146S
5:26 What junior engineers need to learn now
10:02 Open-source maintainers review the students’ code
15:04 A tour of the ten-week syllabus
24:04 The loop, tools and harness inside a coding agent
32:18 Context engineering for a large codebase
38:15 Skills that make you understand the diff
46:42 The Monaco.com dispute and the airplane banner
50:23 What Monaco does for sales teams
59:21 Inside Monaco’s engineering team
1:01:40 “You buy to learn, and you build to keep”
1:05:24 Making repos agent-ready and closing the on-call loop
1:12:37 When code review becomes the bottleneck
1:20:37 Security, dependencies and permissions
1:30:13 Background agents and Stripe’s Minions
1:34:16 MCP portals and why infrastructure converges
1:41:22 Building the software factory
1:45:24 What work is left for developers?
1:52:16 From personal adoption to team autonomy

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原文版权归 Latent Space 及原作者所有,本站转载仅供阅读。如需删除,请联系 support@aisa.one。

事件综述

斯坦福CS146S课程更新:以开源贡献取代旧作业

2026年11月8日,Latent Space 在 AI Engineer 频道百万订阅特辑中发布对 Mihail Eric 的访谈(T2级别报道)。Mihail Eric 是斯坦福 CS146S(The Modern Software Developer)授课教师,同时任 Monaco AI 负责人。 访谈介绍了 CS146S 的课程更新:第二期课程引入开源维护者,要求学生学习陌生仓库、提交修改并向可能合并代码的维护者讲解补丁,以向开源项目贡献代码取代旧作业,由维护者评审学生补丁。十周课程大纲覆盖构建编码 Agent、上下文工程、skills、Agent-ready 代码库、代码评审、安全、后台 Agent 与软件工厂等主题。 在 Monaco 的实践方面,团队经过评估选用 Devin 做代码评审,自建 Agent 工作空间(agent workspaces),并构建了可接入 Datadog 和 GitHub 的 on-call agent,以及能调查故障并开 PR 的内部系统 Hal。Mihail 提出的原则是“买来学习,构建以保留”,团队在自建与采购工具之间进行取舍。 完整视频和十周课程大纲可在 YouTube 查看。该期节目同时为次周举办的 AI Engineer CODE 峰会做了预热。两篇报道内容一致,未见矛盾。

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