Turn prompt writing into a feedback loop: define quality, score outputs, and iterate
Problem
Prompt iteration is often manual and subjective. Teams generating repeated AI outputs frequently adjust prompts without knowing whether quality is genuinely improving.
Approach
Built an AI evaluation platform that generates custom rubrics, scores outputs against defined criteria, produces multiple prompt variants, and iteratively improves toward stronger outputs.
What I Learned
AI systems need gold standards — writing ideal outputs yourself first is what made evaluation calibrate. Without a human-defined north star, the AI optimised toward its own scoring.
Outcome
Created a repeatable evaluation process across several workflows — replacing ad-hoc prompt tweaking with a systematic method, leading to a 5–10 point increase on evaluated prompts.