AI coding needs better specifications, not less architecture
The current spec-driven development discussion is a useful reminder: when AI makes implementation faster, unclear product intent becomes the expensive part.
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Kyluke McDougall
The current spec-driven development discussion is a useful reminder: when AI makes implementation faster, unclear product intent becomes the expensive part.
Production-ready AI agents need more than a strong model. They need architecture around context, tools, permissions, validation and operations.
AI-assisted development scales reliably only when system boundaries, data models, and operating rules are clear first.