How-to· 1 min
Keeping generated images on brand
Post-processing does more here than better prompting.
AI Tools Hub Editorial · published · updated
Why it drifts
- The same prompt returns different results
- Small prompt edits shift the tone a lot
- Several people write prompts differently
- Model updates change the house style
Four levers
| Lever | How | Effect |
|---|---|---|
| Style reference | Pass an existing image as reference | Large |
| Templated prompts | Separate fixed from variable parts | Large |
| Written acceptance criteria | Decide what you will not use | Moderate |
| Uniform post-processing | One colour grade across every image | Moderate |
Template the prompt
Fixed: soft natural light, low saturation, generous whitespace, level horizon, paper-like texture. Variable: subject = X.
Store the fixed half in a file so several people produce matching output, and record any change to it.
Grade at the end
Perfect consistency at generation time is not achievable, so apply one identical colour treatment to everything afterwards. It batches, so the benefit scales with volume, and it is more reliable than improving prompts.
Decide what you reject
No visible faces, no text, no saturated primaries. Negative criteria make selection fast and the set coherent.
FAQ
Should we pin the model?
Where possible. Keep your source files, because providers retire old versions.