Infini Founder Christian: Large-scale "Personification Expression" Becomes Core Barrier, Agent Moat Shifting from Model to Application Layer

April 21st — At the "Decoding Web 4.0: When AI Agents Take Over On-Chain Authority" panel discussion, Christian, founder of Infini, introduced the "Agent Moat" concept. He emphasized that from a product and growth standpoint, AI’s core competitiveness still hinges on large language models’ (LLMs) language processing capabilities—specifically, the **human-like quality of their content output**. He noted that unlike early models’ mechanized, template-driven responses, today’s users prioritize whether AI can deliver expressions and content that mirror real human conversations. This directly impacts its practical value in external communication and team collaboration. Christian added that as LLM capabilities evolve, basic information processing is becoming increasingly commoditized. When LLMs can handle roughly 90% of standardized tasks, relying solely on the model itself makes it hard to build long-term competitive advantages. AI agent competition is shifting away from raw model capabilities toward **specific application use cases and workflow design**. In the future, true differentiation will no longer be limited to simple information processing or desktop automation. Instead, in complex use cases like finance and transactions, agents will deliver higher-level task execution and decision support by deeply understanding business workflows.