MuleRun CTO Shu Junliang emphasized a shift in competitive advantage for AI agents from traditional technology moats to speed and data during a panel discussion on April 21. He noted that the performance gap between leading AI models is narrowing due to rapid advancements in model capabilities and development efficiency. This has led to a decline in the "functional moat" as open-source solutions enable quick replication of agent frameworks and modules. Junliang identified two key areas for future competitiveness: the ability to iterate products at a high frequency and the possession of exclusive data resources. Platforms with unique data acquisition capabilities and accumulated user data will establish natural barriers, enhancing user retention and product competitiveness. As AI technologies become democratized, the focus is shifting towards leveraging data assets and execution efficiency.