AI Tools Skip Key Features Because They Lack a 'Completeness Baseline'

A developer noticed that AI-built projects often omit critical components — such as an About page or an accessible admin panel — not out of laziness but due to a structural gap in how AI tools verify output. Current tools check only internal consistency, confirming that declared elements link correctly, but never validate whether a deliverable meets the expected standard for its type. The author proposes a 'completeness baseline' — a classification system where each kind of project carries its own checklist of what 'done' actually looks like. Completeness is broken into three layers: whether something exists, whether it is reachable, and whether it is fully substantiated with real content and functionality. The concept echoes a sentiment from Thomson Reuters' Claude Forge write-up, which noted that passing tests alone is not sufficient — a gap the industry has felt but not yet formally addressed.