Ant Lingguang Unveils New Version Beta to Rival Meta Muse in Personal AI Agent Race

Ant Group’s AI product, Lingguang, has recently launched a limited internal beta of its latest version, closely mirroring Meta’s personal intelligent agent, Muse, which debuted in September. According to insiders familiar with the project, Lingguang’s development has been underway for six months, undergoing multiple iterations, with a full public release scheduled for this month.
This major upgrade transforms Lingguang from a basic chat and app-generation assistant into an AI-native personal agent equipped with long-term memory and the capacity to proactively manage complex tasks. By leveraging Skills and MCP, the updated version enables cross-application actions, such as sending messages on DingTalk and controlling smart home devices.
Internal testing scenarios focus on long-term, multi-variable situations, including helping professionals monitor market trends, assisting parents with DingTalk attendance tracking, and automatically adjusting travel itineraries during flight delays or attraction closures. This iteration highlights how major domestic tech firms are accelerating their deployment of proactive AI agents, pushing applications toward comprehensive, end-to-end task management.
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Ant Group’s AI product, Lingguang, has recently launched a limited internal beta of its latest version, closely mirroring Meta’s personal intelligent agent, Muse, which debuted in September. According to insiders familiar with the project, Lingguang’s development has been underway for six months, undergoing multiple iterations, with a full public release scheduled for this month.
This major upgrade transforms Lingguang from a basic chat and app-generation assistant into an AI-native personal agent equipped with long-term memory and the capacity to proactively manage complex tasks. By leveraging Skills and MCP, the updated version enables cross-application actions, such as sending messages on DingTalk and controlling smart home devices.
Internal testing scenarios focus on long-term, multi-variable situations, including helping professionals monitor market trends, assisting parents with DingTalk attendance tracking, and automatically adjusting travel itineraries during flight delays or attraction closures. This iteration highlights how major domestic tech firms are accelerating their deployment of proactive AI agents, pushing applications toward comprehensive, end-to-end task management.
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