OpenClaw reached 273,000 GitHub stars in under a year. Install guides, skill packets, and cron job templates are spreading everywhere. This office hour shows what it looks like after four weeks in one real setup: cron jobs, live MCP integrations, GitHub-managed skills, and an agent updating its own strategy without being asked.
I’ve been running OpenClaw for a couple of months, and it’s the first agent framework that has made a lot of my Claude Code project ideas feel concrete. MCPs, skills shaped by the same logic behind my best Claude Code prompts, scheduled workflows, and memory all come together in one live setup.
In this office hour, I show the OpenClaw system actually running in my stack: 18 cron jobs, Telegram as the interface, GitHub-managed skills, and MCP connections to outside tools.
The moment that made me want to show it publicly came when one of my agents analyzed two weeks of engagement data across X and Bluesky, updated its own strategy file, and told me to stop posting on X and focus on Bluesky. I read it. I followed it.
I hadn’t asked. It ran on a schedule, watched its own results, and updated its strategy. That’s what makes it an agent and not a chatbot.
Two weeks ago, I asked the community if anyone wanted to see my OpenClaw setup live. At least one person said yes. That was enough.
I wrote about OpenClaw after running it for a few weeks, but this session lets you see the system in action. This is the breakdown: what I showed, what we discussed, and what you can take for your own build. If you want the framework for where OpenClaw, n8n, and Claude each belong, 4 Levels of AI Automation: When Claude, n8n, and OpenClaw Each Win maps it out.
The recording is embedded above. But you don’t have to watch it. Everything is here.
In this session:
