v.j.k.

Traditional AI coding metrics (lines of code per prompt, time saved) are like judging a chef by ingredient count—they miss what matters. The **CAICE framework** (pronounced "case") measures AI coding effectiveness across 5 dimensions: Output Efficiency, Prompt Effectiveness, Code Quality, Test Coverage, and Documentation Quality. Real case studies show that developers with high traditional metrics often create technical debt, while those with strong CAICE scores build maintainable, team-friendly code. It's time to measure what actually matters for sustainable development velocity.

v.j.k.

A data-driven analysis of why combining Test-Driven Development with AI assistance creates superior outcomes compared to industry-standard approaches