BlockBeats News, April 21st - During the "Decoding Web 4.0: When AI Agent Takes Over On-Chain Authority" roundtable discussion, Infini founder Christian discussed the "Agent Moat" concept, emphasizing that from a product and growth perspective, AI's core competitiveness still depends on the language processing ability of large models, especially the "humanization level" of content output.

He pointed out that compared to the early models' mechanized and templated response approach, current users are more concerned with whether AI can provide expressions and content quality close to real human conversations. This directly impacts its actual value in external communication and team collaboration.

Christian mentioned that as model capabilities continue to evolve, basic information processing abilities are becoming more homogeneous. When large models can complete around 90% of standardized tasks, relying solely on the model itself has become challenging to establish a long-term competitive edge.

The competition of AI Agents is gradually shifting from model capabilities to specific application scenarios and workflow designs. In the future, truly differentiated capabilities will no longer be limited to simple information processing or desktop automation but will instead, in complex scenarios such as finance and transactions, achieve higher-level task execution and decision support through a deep understanding of business processes.