Environmental morphism in blockchain ecosystems: ai-agent-based transmission between chains

The diversity of modern blockchain platforms has created an ecosystem rich in functionality yet fragmented in design. Each chain implements its own execution semantics, transaction models and security principles. While this heterogeneity stimulates innovation, it complicates the portability of decentralised applications and the reuse of domain specific features. This thesis proposes Environmental Morphism, an artificial-intelligence driven approach that enables the transmission of blockchain features across heterogeneous environments. Instead of transferring tokens or source code directly, Environmental Morphism models, extracts and regenerates functional features for example, object based ownership or implicit transaction ordering. So that they can reemerge natively within a different blockchain environment. Using Ethereum and Sui as representative case studies, we design a multiagent pipeline built on the CrewAI framework that performs bidirectional translation and validation between Solidity and SUI Move contracts. Experimental results demonstrate that the proposed pipeline can automatically reproduce Sui specific properties such as object ownership and implicit resource safety within Ethereum's account based model. This work thus contributes both a conceptual foundation and a practical methodology for AI‑assisted feature migration between blockchain ecosystems, offering new opportunities for interoperability, cost reduction and long term software sustainability.