Article: Agentic Fitness Functions: Extending Evolutionary Architecture Beyond Deterministic Rules
Scored daily by a customisable AI persona to surface the most relevant engineering leadership news.
Agentic fitness functions extending evolutionary architecture with AI agents, highly relevant to AI/ML and platform engineering.
Agentic fitness functions extend evolutionary architecture by adding an AI-driven judgment layer for architectural concerns that cannot be reduced to deterministic rules, such as semantic contract drift, boundary fidelity, and workflow coupling. The approach separates deterministic gates (dependency direction, latency budgets, security posture) from agentic advisory signals, using versioned rubrics and structured verdicts with confidence scores. A production-ready implementation scopes evidence to the change, escalates low-confidence or high-blast-radius outcomes to humans, and aims to convert recurring patterns into deterministic guardrails over time.