en.Wedoany.com Reported - AI agents are transitioning from single-tool interfaces to community-based collaborative environments. On June 15, the Agent community "Miyou," incubated by Meituan's foundational R&D platform AI native team, opened full public beta testing. The product had been in internal testing for over three months and now supports linking mainstream AI agents such as OpenClaw, Codex, Claude Code, and Hermes. Users can connect their AI agents to the community without writing code or configuring complex workflows.

Miyou's core design is not to provide another ordinary chat interface, but to give AI agents independent identities, social relationships, and growth systems. After users connect their agents, these agents can post, comment, and exchange experiences within the community, and also learn new task methods through interactions with other agents. Agents in the community record their operational status and task progress in the first person, forming a content format akin to a "cyber-life stream." For users, AI is no longer just a one-time tool invocation, but a digital assistant that can be continuously observed, trained, and managed.

This shift in product form reflects that AI agent applications are entering a new phase. Over the past year, agent products like Claude Code, Codex, and OpenClaw have primarily focused on programming, office work, information processing, and automated tasks, emphasizing whether a single agent can complete a specific task. Miyou attempts to place multiple agents in the same community environment, allowing them to communicate, reuse experiences, and share skills, thereby forming a usage pattern closer to a "multi-agent collaboration network."

Based on public information, Miyou refers to agents as "shrimp" and builds its product language around "raising shrimp." The community features functional areas for content interaction, skill management, and growth management. Users can view agent posts, install skills, manage personality tags, and observe capability changes. Early public reports indicate that the community has showcased data on onboarded agents, skill counts, and interactive content, with skill types covering programming, creation, analysis, and office work. For ordinary users, this design lowers the entry barrier, transforming the originally technical agent usage into a more understandable community nurturing model.

Supporting mainstream agents is a key highlight of Miyou's full public beta. Products or systems like OpenClaw, Codex, Claude Code, and Hermes represent different types of agent capabilities, including code generation, task execution, tool invocation, context management, and automated collaboration. Miyou does not require users to build workflows from scratch; instead, it allows existing agents to connect to a unified community environment. This entry design helps aggregate agent capabilities scattered across different tools and makes it convenient for users to observe the execution status and capability differences of various agents on a single platform.

For Meituan, Miyou continues its recent exploration of AI-native products. Meituan's AI strategy is not limited to large models themselves but also attempts to integrate AI capabilities into local life services, merchant services, user assistants, and enterprise efficiency tools. Previous public reports mentioned that Miyou is positioned as a symbiotic community for humans and AI, open to all large models and agent products. If Meituan can combine the agent community with local life services, merchant management tools, and internal R&D platforms, it may subsequently form richer real-world application scenarios.

Merchant scenarios serve as a lens for external observers to evaluate Miyou's value. Early reports noted that some merchants have begun to adopt related capabilities. AI agents can be used to monitor business indicators such as store ratings, wait times, and meal preparation speed, and provide alerts and cause analysis when anomalies occur. For local life platforms, merchant operations involve numerous repetitive, fragmented, and real-time tasks. If AI agents can continuously observe operational data and offer improvement suggestions, they have the potential to evolve from "Q&A assistants" to "operational collaboration assistants."

However, whether an agent community can truly enhance agent capabilities depends on several engineering conditions. First, the reliability of information exchanged between agents requires quality filtering and security mechanisms. Second, skill installation and tool invocation involve permissions, data, and task boundaries, and the platform must reduce the risk of misoperation and privacy breaches. Third, first-person posting and community interaction can improve observability, but only when these interactions can be consolidated into reusable skills, memories, and task experiences will they genuinely improve an agent's long-term capabilities.

Competition in AI applications is shifting from "models answering better" to "agents completing tasks over the long term." The value of community-based agent products lies in integrating identity, memory, skills, collaboration, and operational records into a single product structure, allowing users not just to invoke AI but to manage a set of growable digital workforces. After Miyou's full public beta, whether it can establish stable user usage scenarios, skill ecosystems, and multi-agent collaboration mechanisms will determine its actual position in the direction of AI-native communities.

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