这是一篇归档文章,最后收录于 2026-10-28 19:00(北京时间)。下方指标保留各自的采集时间,不代表当前热度。

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从零学习构建可靠编程代理

10-28 14:14 · 北京时间

AI 编程

有实践材料可继续查看

代码仓库教程线索

原文与观测指标

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从零学习构建可靠编程代理

Tech with Mak
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点赞107采集时的累计值
每小时增长+40.5赞 / 小时 · 观测区间平均值
观测增量+81两次有效记录之间的变化

发布时间:2026-10-28 14:14 · 北京时间

指标采集:10-28 18:00

对比区间:10-28 16:00 至 10-28 18:00 · 2.00 小时 · 净增量 +81

摘要

材料介绍一套从头构建AI编程代理的开源课程,涵盖上下文管理、任务规划、测试验证、自动化循环和多代理协作,并通过循序渐进的项目讲解相关工程实践。

摘要由 AI 生成,请以原文为准。
观测历史 · 最近 4 条 展开 / 收起

缺失不计为零;增长只比较同一指标来源的有效记录,按实际间隔折算每小时。上游缓存可能延迟数值更新。

采集时间 · 北京时间指标数值来源状态
10-28 18:00:14点赞107Agent 应用案例已取得
10-28 18:00:08点赞107AI 编程实战已取得
10-28 16:00:14点赞26Agent 应用案例已取得
10-28 16:00:08点赞26AI 编程实战已取得
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Harness Engineering from Scratch 🚀 Found this excellent 21K+ star GitHub repo that teaches you how to build reliable AI coding agents, from t...

Harness Engineering from Scratch 🚀 Found this excellent 21K+ star GitHub repo that teaches you how to build reliable AI coding agents, from the ground up. An entire open-source curriculum with 14 lectures, 8 hands-on projects, and 8 progressive learning phases. What makes it useful is the approach: instead of just learning concepts, you gradually build the engineering environment around an AI agent, using the same real application throughout the course. What's inside: → Agent instructions and repository structure → Context management and persistent memory → Multi-session continuity and task handoffs → Task planning, scope control, and progress tracking → Testing, verification, and observability → Automated coding loops and maker-checker workflows → Graph orchestration, parallel execution, and rollback Includes practical projects, reusable templates, a harness-creator skill, and technical breakdowns of how Claude Code, Codex, Pi, and DeepSeek build their harnesses. Available in 15 languages. Perfect for software engineers and AI developers who want to move beyond prompting and understand how reliable coding agents are actually built. Completely free and open source. Here's the GitHub Repo: https://github.com/walkinglabs/learn-harness-engineering