Part I—Foundational Principles: Adapting Human-Centric Review for AI
Decomposing the Gold Standard
AI as "Enhanced Linter" is insufficient. Core of what human review observes:
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Design: Does change fit architecture?
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Functionality: Does it work as intended? / User value
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Complexity / Maintainability: Simplification room / Future understandability
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Tests: Appropriate and inclusive?
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Naming / Comments / Style / Docs: Consistent readability
Health of Review itself:
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Small, Focused (~400 lines / review target)
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Collaborative / Non-adversarial, Start with Questions not assumptions
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Polite and Constructive feedback
Role as Architecture Guardian
AI should become an Architecture Suitability Checker visualizing dependency graphs, boundaries, and layers. Embed Continuous Improvement into decision logic so valuable changes are not blocked by minor nits.