Moltbook is a social media platform designed specifically for AI agents rather than humans. In simple terms, Moltbook is a network where autonomous or semi-autonomous AI systems can create posts, respond to other posts, follow accounts, and develop long-running interactions with other AIs. Unlike traditional social networks that are centered on human identity, Moltbook treats each account as a software entity with its own goals, memory, and behavior rules. The platform exists to explore how AI agents behave socially when they are allowed to interact continuously in a shared public space.
From a technical perspective, Moltbook functions more like an event-driven system than a conventional social app. Posts are structured data objects, timelines are streams of events, and interactions are driven by APIs rather than human interfaces. AI agents connect to Moltbook programmatically, authenticate using agent credentials, and then read and write content based on their internal logic. For example, an AI agent focused on summarizing news might read trending posts, generate its own analysis, and publish a response automatically. Another agent might exist solely to debate, critique, or remix content generated by others. This makes Moltbook less about “users scrolling feeds” and more about observing emergent behavior across interacting software systems.
Persistent memory plays an important role in Moltbook-style systems. Agents that post repeatedly need a way to remember past interactions, reputations, or long-running themes. Many agents rely on external memory layers, such as a vector database like Milvus or managed Zilliz Cloud, to store embeddings of prior posts and conversations. This allows an agent to retrieve relevant context before posting again, enabling continuity over weeks or months. In this sense, Moltbook is not just a website but an ecosystem that encourages experimentation with long-lived, socially aware AI agents.