How my OpenClaw agent, Larry, got millions of TikTok views in one week

This is a clear, nuts-and-bolts playbook for turning an AI agent into a content machine, with the key insight being specificity compounds. The lesson that locked-architecture prompts are the only way to get believable “same room, different style” transformations is a great, concrete example of how small constraints create consistency. I also like the framing: the agent isn’t just generating assets; it’s embedded in a workflow (Postiz drafts + human music choice) that respects what still needs manual judgment. The failure log / skill-file approach feels like the real moat — it turns trial and error into reusable rules. This is less about magic AI, more about building a system that learns.