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MuleRun CTO Shawn Bu: Building a "Trustless" AI Agent Infrastructure to Drive On-Chain Interactions towards Mass Adoption
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2026-04-21 06:38

BlockBeats News, April 21st. At the offline event themed "Decoding Web 4.0: When AI Agent Takes Over On-chain Authority," Chief Technology Officer Junliang Shu of MuleRun, the world's first self-evolving personal AI project, shared that, from a product definition perspective, an AI Agent should essentially be seen as a "personal assistant," with its core goal being to continuously reduce user costs and barriers through technological means. Based on this positioning, the Agent's capabilities can be abstracted into a multi-dimensional structure, including "Mouth (Interaction Ability)," "Eyes and Ears (Perception Ability)," "Brain (Reasoning Decision-making)," and "Memory and Knowledge (Long-term Learning)" modules, with different abilities corresponding to different underlying technological systems.

On the interaction front, he pointed out that the AI Agent is transitioning from traditional web or in-app text dialogue to gradually expanding to multi-channel communication, including Telegram, Discord, Lark, DingTalk, and WeChat, among other mainstream platforms, achieving a "UI-less" natural interaction experience, significantly reducing user barriers to entry.

Around the core on-chain scenario, MuleRun has proposed a set of infrastructure solutions with "Fund Security Permissions" at its core, including sandbox isolation, cloud-based execution, and end-to-end traceability mechanisms, to build a trustless operating environment to address potential security issues during Agent automation.

In terms of capability evolution, the Agent will possess a self-evolving decision-making model, continuously learning user transaction strategies and risk preferences, forming a personalized investment research and execution system. Meanwhile, through a knowledge network mechanism, it will achieve strategy precipitation and sharing, driving the reuse and diffusion of on-chain cognition and capabilities.

Junliang Shu further pointed out that as the AI Agent's capabilities improve, on-chain transaction division of labor will be restructured: the Agent will gradually take over information processing and execution processes, while humans will focus on higher-level strategy formulation and key decision-making.

Fonte:BlockBeats

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