代理型适应度函数：将进化式架构扩展到确定性规则之外
原标题：Article: Agentic Fitness Functions: Extending Evolutionary Architecture Beyond Deterministic Rules
AI 摘要
本文探讨了将代理型适应度函数（agentic fitness functions）扩展到进化式架构中，以处理那些无法通过确定性规则判断的架构问题。作者认为，确定性适应度函数应继续作为可测量不变量的主要执行机制，而代理型适应度函数则适用于证据充分但依赖判断的架构风险，如边界保真度、语义契约漂移等。文章强调，生产级实现应分离确定性门禁与代理型咨询信号，并采用版本化评分标准，将低置信度或高影响结果升级给人工审查。长期来看，代理型适应度函数使架构判断更可观察、可校准、可审计，并能在模式重复时转化为确定性护栏。
正文节选
Key Takeaways - Evolutionary architecture makes the next change safer by turning architectural intent into continuous feedback rather than relying on periodic reviews, tribal memory, or late-stage governance. - Deterministic fitness functions should remain the primary enforcement mechanism for measurable invariants such as dependency direction, contract shape, latency budgets, security posture, and policy checks. - Agentic fitness functions add value when architectural risk is evidence-bound but