How to Prompt a Consistent AI Influencer

Anyone can generate one striking AI portrait. The real problem starts at image two: a slightly different nose, a new jawline, hair that changed length, and suddenly your "influencer" reads as a different person in every post. Consistency, not raw quality, is what separates a believable AI persona from a folder of pretty strangers.

There are three levers that control identity across a set: the reference, the prompt structure, and the model you choose. Get all three right and the same face survives across dozens of scenes.

1. Anchor identity with a reference, not adjectives

Describing a face in words ("green eyes, sharp cheekbones, freckles") drifts every time the model re-rolls. The reliable anchor is a reference image fed into an edit model. Nano Banana 2 in edit mode preserves the reference identity while restyling the scene around it, which is exactly what you want for a recurring persona. Pick one clean, well-lit reference and reuse it for the whole set.

2. Separate identity from scene in the prompt

Structure every prompt the same way: an identity clause that never changes, followed by a scene clause that does. The identity clause restates the persona (age range, build, hair, the fact that it is the same individual as the reference); the scene clause carries everything else, like location, wardrobe, lighting, camera, and pose. When the identity block is byte-for-byte stable across prompts, the model stops reinventing the person.

• Identity clause: fixed across every prompt in the set.
• Scene clause: the only part that varies (place, outfit, time of day).
• Camera and grain: a consistent capture profile (for example an iPhone-style block) so the whole feed feels shot on one device.

3. Match the shot to the right model

Nano Banana 2 and GPT Image 2 have different strengths, and forcing one to do everything is where consistency breaks down. As a rule, reach for Nano Banana 2 when you want identity-locked edits from a reference at high resolution, and GPT Image 2 when peak realism matters and you can invest in careful prompting. The full breakdown is in the model comparison guide.

Skip the trial and error

Every pack in the PROmpt library is built on this structure: a stable identity block, a varied scene block, and a fixed camera profile, tested on a live model before it ships. Each prompt is shown next to the exact image it produced, so you can see the consistency before you copy anything.