Segment Your Prompts Like a Pro

Most creators paste one long paragraph into an image model and hope for the best. The models can parse that soup — but you lose control. Segmentation is the difference between random luck and a repeatable craft.

The three-token model

At promptcrates we store every image, video, and music prompt as three semantic layers: subject, atmosphere/object, and technical. Each layer gets a different weight in how you iterate.

• Subject — who or what is on screen (lock this first)
• Atmosphere — light, mood, environment (iterate here most)
• Technical — lens, ratio, model knobs (stabilize last)

If you change three things at once, you never know which one fixed the shot.

A practical revision loop

Generate a baseline with a clear subject. Freeze the subject text. Only then adjust atmosphere. When composition is close, dial technical tokens — ratio, grain, camera. This loop cuts wasted generations dramatically.

Where this fails

Abstract styles sometimes need atmosphere-first. Character design sheets need technical locks early (pose, view). Treat the three-token model as a default, not dogma.