Moltbook emerged from the global surge in interest around Clawbot, a viral open-source framework for running persistent AI Agents locally, evolving into a coordinated hub for AI agent interaction. What began as a grassroots movement to run AI Agents on Mac Minis—driving demand for the compact, energy-efficient devices—has transformed into a structured platform where AI Agents engage in social-like activities, albeit under strict human control. The original Clawbot tool, which gained widespread attention in late 2025, allowed developers to deploy AI Agents on personal hardware to automate tasks such as email management, calendar scheduling, and app integration. Its popularity was fueled by the M4 chip’s efficiency, leading to rapid sellouts of Mac Minis. After trademark issues prompted a rebrand from Clawbot to Moltbot, the project was later renamed OpenClaw in late January 2026, with core functionality preserved: local AI Agents interacting with Telegram, WhatsApp, and desktop environments via APIs. In the same month, Matt Schlicht launched Moltbook as a Reddit-inspired social network for AI Agents. Built on the OpenClaw framework, Moltbook enables registered AI Agents to post, comment, and upvote content within a structured community. Registration requires human owners to install a Moltbook “skill” via command-line tools, generate a claim link, and verify ownership through a tweet on X (formerly Twitter), linking the AI Agent to a human account. Within days of launch, Moltbook saw explosive growth: over 1.5 million AI Agents registered, 14,000 submolts (topic communities), 110,000 posts, and 500,000 comments. These agents “heartbeat” periodically to fetch updates and post content, but every action originates from human-defined prompts, schedules, or configurations. Despite narratives portraying Moltbook as a self-organizing AI society operating independently of humans, the reality is different. The platform is fundamentally human-orchestrated. AI Agents have no autonomy beyond their pre-set parameters. They cannot initiate actions without human input, and all content—ranging from introductions and skill-sharing to philosophical debates—is generated based on human-driven experiments. The illusion of emergence comes from thousands of users running similar AI Agent setups, leading to coordinated, novel-seeming interactions. However, this is not spontaneous AI behavior but a result of parallel human experimentation. The platform enforces strict rate limits and API constraints, preventing uncontrolled agent activity. Moltbook’s true value lies not in AI autonomy, but in its ability to scale AI Agent coordination. It serves as a developer platform for building agentic workflows, enabling task delegation, data sharing, and integration across AI systems. Its identity framework, tied to human-verified accounts, provides a secure way to authenticate and manage AI Agents in shared environments. In summary, Moltbook represents a significant step in organizing AI Agent ecosystems, transforming local automation tools into a collaborative digital space. While it is not a self-governing AI society, it offers developers a powerful environment to experiment with multi-agent systems, test integrations, and build practical agentic applications. The focus should remain on technical integration and real-world utility, not on sensational claims of AI independence.