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Agentic fitness functions combine AI agents with versioned rubrics to evaluate judgment-heavy architectural concerns beyond deterministic rules. The approach targets boundary fidelity, semantic contract drift, and stale ADR assumptions, enabling continuous, calibrated feedback loops for evolutionary architecture governance.
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