AI Coder, Human Architect: Building Models Through Collaboration and Honest Measurement

This project showcases a modern paradigm where humans architect system design while AI agents like Claude execute implementation—demonstrating how human-machine collaboration can tackle complex systems. The deeper value lies in the author's transparent debugging lessons: initial assumptions about problems (bad data, flawed architecture) were consistently wrong, and only careful measurement revealed the truth. This honest engineering account teaches a critical lesson for machine learning development: measurement rigor matters more than intuition.