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Article: Agentic Fitness Functions: Extending Evolutionary Architecture Beyond Deterministic Rules

Deterministic rules safeguard hard metrics, but what about architectural intent? Discover how agentic fitness functions combine AI agents and versioned rubrics to evaluate complex, judgment-heavy concerns—such as boundary fidelity, semantic contract drift, and stale ADR assumptions. Elevate evolutionary architecture governance with continuous, calibrated feedback loops. By Hemant Kumar Mahato, Łukasz Sieczkowski, Vijayasenthilkumar Kuppusamy

2026-08-17 原文 →
AI 资讯

Article: Comprehension as an Architectural Characteristic: A System That Is Not Understood Cannot Evolve Safely

As AI commoditizes code output, system comprehension silently decays, creating cognitive debt that threatens safe architectural evolution. This article explores why human understanding must be treated as an essential architectural characteristic, offering actionable strategies, socio-technical metrics, and design checkpoints to preserve intent across modern engineering teams. By Jacobus Meintjes, Narayana Rengaswamy, Paul Katsande, Sureshbabu Bikki

2026-08-10 原文 →
AI 资讯

Article: Enabling Evolutionary Architecture Through the Preservation of Change Locality

Why do simple features suddenly require cross-team negotiations? In this article, explore how boundary drift quietly destroys change locality and increases cognitive load across teams. Learn practical sociotechnical strategies - redistributing mechanics, exposing essential policy, and rehearsing exception paths - to restore domain boundaries and enable a truly evolutionary software architecture. By Michael Fischer, Nicholas Lawrence, Monica Karekar

2026-08-03 原文 →