Abstract
This disclosure specifies a multi-tiered software and network architecture designed to resolve the systemic bandwidth, cognitive load, and training-data saturation bottlenecks (collectively termed the Epistemic Squeeze) that occur when linear human operational capacity interfaces with exponentially scaling technological and informational systems. The architecture establishes a structured, three-tiered human-machine orchestration environment that shifts human input from low-level manual execution to high-abstract intent orchestration. By introducing a middleware context-translation layer (AI Scaffolding), the system automates semantic embedding mapping across hyper-isolated, domain-specific ontologies, drastically reducing the multi-decade training lifecycle traditionally required to reach technological frontiers.
Furthermore, to mitigate the socio-economic displacement of human physical and cognitive labor by automated systems, this document specifies a decentralized, ledger-verified resource distribution protocol (Compute Dividends). This protocol programmatically routes the productivity yields of autonomous infrastructure directly to human stakeholder nodes, thereby stabilizing human sociological structures and minimizing resource-driven tribal friction. The complete deployment timeline is mapped across a 5-generation (125-year) macro-historical adoption curve, establishing a reproducible blueprint for a managed transition toward an integrated Kardashev Type 1 planetary infrastructure.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Eckes, Christopher L., "System Architecture for Cross-Domain Intent Orchestration, Institutional Latency Mitigation, and Distributed Post-Labor Commerce", Technical Disclosure Commons, ()
https://www.tdcommons.org/dpubs_series/11331