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.
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.
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.
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.
A complete walkthrough of configuring OpenClaw from its default state into a personal assistant with identity, persistent memory, and proactive capabilities