Experiment tracking messy

Experiment tracking gets messy fast when teams move quickly but do not standardize what they record. Prompts change, data changes, models change, and suddenly nobody can tell which modification actually improved the outcome.

This creates a lot of wasted effort because the same tests get rerun under slightly different conditions. Without clean tracking, the team spends more time debating results than learning from them.

A simple, consistent tracking practice makes comparisons much easier. When experiments are documented clearly, the team can move faster without losing the ability to reproduce what happened.