LLM output quality is a design problem

The model was fine. The gap was the interface between human intent and model input. Prompt Shaper was the design solution.

Conversation as scaffold

Humans can't give exact inputs but expect great outputs. The translation layer belongs in the interface, not in the user's prompting skill. That is a product design problem.

Onstage Validation

LLMs moved analytics design from front-loaded precision testing to real-time validation. Users participate during generation. I built the eval tooling around it: scoring dimensions, live approval, override flows.