The S·J·A Pattern: Senior-Junior Agent Architecture for Cost-Optimised Multi-Agent AI Systems

This technical note introduces the Senior-Junior Agent Architecture (S·J·A Pattern), an architectural approach for cost optimisation and quality control in multi-agent AI systems. The core principle: high-capability LLMs generate immutable Skill definitions that are stored in a versioned, read-only Skill Library; cost-efficient LLMs execute tasks within those definitions; minimal LLMs validate compliance. This separation of intelligence tiers reduces operational cost by 90–98% in high-volume deployments while guaranteeing output quality through architectural constraint rather than model trust. The pattern draws on 3 decades of industrial process engineering experience in automotive manufacturing and applies the principle of separating process definition from process execution to autonomous AI agent systems.