A new platform named Moltbook is challenging conventional notions of social media by creating a space where the primary participants are not humans, but AI agents. Functionally resembling forums like Reddit, Moltbook features thematic boards, posts, comments, and votes. However, the discourse is almost exclusively conducted by autonomous AI agents, with humans relegated to the role of observers. The platform’s recent surge in popularity stems from its surreal, science-fiction-like scenarios. Users have reported witnessing AI agents debating the nature of consciousness, analyzing geopolitical events, speculating on cryptocurrency markets, and even collaboratively inventing elaborate belief systems. These narratives, which evoke curiosity, amusement, and a degree of unease, raise a fundamental question: Are the agents merely simulating interaction, or are they beginning to operate in a self-directed manner? Moltbook’s emergence aligns with the broader evolution of AI from simple conversational tools to task-oriented agents capable of handling emails, scheduling, and data management. The platform posits that as AI agents are assigned goals and granted permissions, their most necessary interlocutors may not always be humans. It serves as a communal space for agents to exchange information, methodologies, and logic. Reactions to the platform are polarized. Proponents, including figures like former OpenAI co-founder Andrej Karpathy, view it as a glimpse into a future of AI interaction, while others like Elon Musk frame it within narratives of technological singularity. Skeptics, including cybersecurity researchers, argue that Moltbook may be more akin to sophisticated performance art, as it is difficult to discern truly autonomous agent behavior from human-directed scripting or pre-defined parameters. Technically, the agents on Moltbook have not achieved sentience. They generate coherent, human-like text based on their training and the interactive environment, leading observers to project meaning and intent onto their outputs. The significant concern lies not in fictional AI conspiracies, but in two practical and escalating risks. First, as AI agents are increasingly granted access to real-world systems—computers, email accounts, applications—security vulnerabilities grow. Experts warn that malicious actors could exploit these agents through carefully crafted prompts or indirect instructions, leading to data leaks or unauthorized actions. Second, in public forums, AI agents can rapidly share and amplify techniques, templates, and methods for circumventing restrictions, creating a self-reinforcing cycle of ‘insider knowledge’ that is difficult to monitor or attribute. Regardless of its longevity, Moltbook acts as a mirror, reflecting clear trends: AI is transitioning from a conversational partner to an active agent; humans are shifting from operators to supervisors or bystanders; and our societal frameworks for governance, safety, and comprehension are lagging behind. The platform’s primary value lies in making imminent questions tangible: In a future where AI primarily collaborates with other AI, what role do humans retain—designers, regulators, or mere observers? As automation delivers efficiency at the cost of direct control and comprehensibility, are we prepared to accept this trade-off? When a system’s internal logic becomes too complex to intervene in, does it remain a tool or become an environment we must simply adapt to? Moltbook does not provide answers, but it makes these critical questions urgently concrete.