MuleRun CTO Shu Junliang: Building a Trustless AI Agent Infrastructure to Promote On-Chain Interaction for the Masses

On April 21, Shu Junliang, the Chief Technology Officer of MuleRun, the world’s first self-evolving personal AI project, shared at the offline event themed “Decoding Web 4.0: When AI Agents Take Over On-Chain Permissions” that, from a product definition perspective, AI Agents should essentially be viewed as “personal assistants,” with the core goal of continuously reducing usage costs and barriers through technological means. Based on this positioning, the capabilities of the Agent can be abstracted into a multi-dimensional structure, including modules for “mouth (interaction capability),” “eyes and ears (perception capability),” “brain (reasoning and decision-making),” and “memory and knowledge (long-term learning),” with different capabilities corresponding to different underlying technological systems. In terms of interaction, he pointed out that AI Agents are gradually expanding from traditional text dialogues within web pages or apps to multi-channel communication, including mainstream platforms such as Telegram, Discord, Feishu, DingTalk, and WeChat, achieving a “no-interface” natural interaction experience, thereby significantly lowering the user entry barrier. Regarding core on-chain scenarios, MuleRun proposed an infrastructure solution centered on “funds permission security,” which includes sandbox isolation, cloud execution, and a full-chain traceability mechanism, creating a trustless operating environment to address potential security issues during the Agent’s automatic execution process. In terms of capability evolution, the Agent will feature a self-evolving decision-making model that can continuously learn users’ trading strategies and risk preferences, forming a personalized investment research and execution system. Additionally, through a knowledge network mechanism, it will enable strategy accumulation and sharing, promoting the reuse and diffusion of on-chain cognition and capabilities. Shu Junliang further noted that as the capabilities of AI Agents improve, the division of labor in on-chain transactions will be restructured: Agents will gradually take over information processing and execution, while humans will focus on higher-level strategy formulation and key decision-making.