From Goals to Aspects, Revisited: An NFR Pattern Language for Agentic AI Systems

Researchers have developed a pattern language methodology to systematically identify and modularize crosscutting concerns in agentic AI systems, addressing issues like security, reliability, and cost management that contribute to high AI project failure rates. The approach uses goal models to discover reusable patterns and implements them through aspect-oriented programming in Rust.