龙虾调教（完结篇）：从零搭建项目管理的 OpenClaw 助理
前四篇文章解释了为什么这样设计。这篇只讲怎么做——从零开始，把 OpenClaw 配置成一个帮你跑 Linear + GitHub 全链路项目管理的 AI 助理。
龙虾调教（四）：项目管理工程实践优化
把 OpenClaw 从「流程可用」推到生产：持久记忆、脚本执行层、端到端项目自动化。逐项拆解每个改动背后的判断。
龙虾调教（三）：OpenClaw 软件产品开发的项目管理工作流
本文分享如何以 Linear + GitHub 为管理底座，让 OpenClaw 担任敏捷教练和项目管理角色，覆盖需求收集、Sprint 规划、Code Review、验收到回顾的完整开发节奏，让人只在关键决策点介入，其余监控与自动化全部交给 AI。
龙虾调教（二）：让 OpenClaw 帮你把重复工作变成 SOP
本文介绍如何在 OpenClaw 中构建三层 Workflow 系统——通过 AGENTS.md 元规则、WORKFLOW.md 索引和 Playbook 文件，将重复性工作 SOP 化，让 AI 助手读完几个文件就能独立执行任何重复任务，无需每次重新解释。
OpenClaw Training (Final): Building a Project Management AI Assistant from Scratch
The first four posts explained the design rationale. This one is purely about how to do it — configuring OpenClaw from scratch into an AI assistant that runs your full Linear + GitHub project management pipeline.
OpenClaw Training (IV): Production-Grade Engineering Upgrades
Pushing OpenClaw from 'functionally usable' to production-ready: persistent memory, a script execution layer, and end-to-end project automation. A breakdown of every change and the reasoning behind it.
OpenClaw Training (III): A Project Management Workflow for Software Teams
How to use Linear + GitHub as the management foundation while letting OpenClaw serve as agile coach and project manager — covering the full development cycle from requirement intake to sprint retrospectives, with humans only at key decision points.
OpenClaw Training(II): Using OpenClaw to Turn Repetitive Work into SOPs
How to build a three-layer Workflow system in OpenClaw — using AGENTS.md meta-rules, a WORKFLOW.md index, and Playbook files — to turn repetitive tasks into SOPs that an AI assistant can execute independently after reading just a few files.