When people ask how to keep an AI character consistent, the answers split into two camps: "write a really detailed prompt" and "use a reference image." Both are right, and both are incomplete on their own. They solve different halves of the problem. Understanding what each actually does tells you when to use which — and why the best results stack them.
What a prompt description controls
A written description — "a woman with short curly black hair in a mustard raincoat" — steers each generation toward the same traits. Its strength is that it travels: you can repeat the exact words in every scene and every episode, and because each scene is generated in isolation, that repetition is what stops the model re-inventing the look. Its weakness is precision. Words leave room; "black hair" covers a hundred slightly different faces, so pure text tends to hold the type but wander on the exact identity.
What a reference image controls
A reference image — a fixed portrait the model looks at while generating — locks identity far more tightly than words can. It carries the specific face, not just the description of one. This is the single strongest lever for "the same person every time." Its limit is that an image alone doesn't tell the model what the character is doing, wearing in a new context, or how the scene is lit — that still comes from the prompt.
Why the seed matters too
Where a tool exposes it, the seed controls the randomness of a generation. A fixed seed makes output repeatable instead of rolling fresh variation each time. It's not an identity lever on its own, but combined with a reference image and a repeated description it removes one more source of drift. Reference image plus repeated words plus stable seed is the full recipe.
Use both, in that order
Anchor identity with a reference portrait, then use the written description to carry that character's fixed traits — hair colour, clothing, one distinguishing detail — verbatim into every scene, including for side characters, who drift the most. The image holds the face; the words hold everything the image can't see across separate generations. Neither alone is enough for a whole series; together they're what consistent channels rely on.
Where CASTMINT fits
CASTMINT combines these for you: pin a character portrait to a series and each episode renders from that same reference, while the script keeps each character's exact description repeated across scenes. You type the idea and review every scene before it publishes. It won't write your story for you, but it handles the reference-plus-description bookkeeping that makes character consistency work in practice.