Pronab Pal , Shubhasmita Behera , Minati Subudhi , Dipti Das , IntentixLab, Australia

Modern cloud-native applications distribute business logic across multiple layers: application code, orchestration frameworks, service meshes, and infrastructure configurations. This distribution creates hidden logic-execution rules embedded in infrastructure that are invisible during design and difficult to trace at runtime. We present unique user level behavior addressability and transparency of Intention Space [16] , a computing model built on the CPUX (Common Path of Understanding and Execution) paradigm brings, that consolidates all business logic into explicit, design-time declarations using plain-language state pulses. In our model, Design Nodes (DNs) contain computation while Gatekeepers declare execution conditions as named pulses (e.g., payment validated: Y). The infrastructure provides only mechanical enforcement through an Intention Loop that matches runtime state to Gatekeepers without adding decision logic. We demonstrate that complex workflows-traditionally requiring nested if-then branching and explicit loops-can be expressed as linear CPUX sequences where execution paths emerge from data state rather than code branching. Our Golang implementation shows complete elimination of orchestration code while maintaining full cognitive traceability. Beyond technical innovation, CPUX addresses a critical social computing crisis: the lack of accountability in distributed social platforms. By creating unique, user behavior level CPUX footprints for every interaction, our model enables verifiable traceability from device identity through user intention to executed action-restoring accountability to social computing while preserving privacy. We argue this separation of intent (CPUX) from enforcement (infrastructure) is essential for building LLM-integrated, auditable, and socially responsible distributed systems.

CPUX, Intention Space, Design Nodes, Cognitive Computing, Data-Driven Execution, Microservices Architecture, Cloud Computing, LLM Integration, Social Computing Accountability.