AI-assisted development productivity involves more than measuring code output alone.
PROJECT / 07Academic Research
RAPEF AI Productivity Evaluation Framework
Research framework for measuring AI-assisted developer productivity
SELECTED WORK · RESEARCHRAPEF AI Productivity Evaluation FrameworkPublishedCASE STUDY · 2026
01OVERVIEW
The idea behind the work.
Academic research project developing a rule-based evaluation framework for assessing productivity improvements when using AI-assisted development tools. The framework uses a weighted scoring algorithm across multiple dimensions.
02CHALLENGE / APPROACH
A clearer way through the complexity.
The research framework applies weighted scoring across multiple productivity dimensions.
03PROJECT HIGHLIGHTS
What makes this project work.
Led research as Research Lead on AI productivity metrics
Developed weighted scoring algorithm for productivity evaluation
Created framework for code velocity and quality assessment
Defined parameters for structural quality and security evaluation
04ENGINEERING
How the system fits together.
Python-based analytical framework that processes developer workflow data and computes productivity scores using the RAPEF methodology.
TECHNOLOGY STACK