OpenClaw Configuration Sheet Open Source
Discover how Google's senior AI lead built 8 autonomous OpenClaw agents using only Markdown files. A complete 40 day deployment roadmap inside.
OpenClaw is currently igniting a truly phenomenal AI frenzy around the world. Online and offline, whether developers or cutting-edge tech enthusiasts, everyone is chasing this viral sensation. After installing OpenClaw, but having no idea how to “raise lobsters”? Then this article is tailor-made for you.
In the past couple of days, I came across a post by Shubham Saboo — Google’s senior AI product manager and the author of the 99k-star GitHub open-source project Awesome LLM Apps. He shared his ultimate, battle-tested OpenClaw Agent deployment solution after 40 days of hardcore iteration. In my opinion, this is currently the most impressive setup out there. Everyone should take a look — the practical roadmap is attached at the end of the article.
This Google guy’s OpenClaw Agents are evolving every single day. Without fine-tuning prompts, without switching underlying models, and without ever refactoring the system architecture.
He does only one thing: talk to the agents, give them feedback, and watch them record that feedback.
Forty days ago, his content agent would still write tweets full of emojis and hashtags; his research agent couldn’t even extract meaningful signals from massive amounts of information. Correcting their mistakes sometimes took him longer than just doing the task himself.
