Self-directed R&D project, created to demonstrate a repeatable AI photography workflow for clients producing AI-driven video content (music videos, brand films, motion graphics, fashion campaigns). The broader context: most AI-generated portraits look impressive as single images but fall apart the moment a client needs the same character across multiple shots — which is exactly what video production requires.

Acted as prompt engineer, AI photographer, and post-production artist. Designed the character concept and wardrobe, engineered a reusable prompt architecture for identity consistency, directed lighting and framing across the full set, and handled 4K upscaling for delivery-ready output.

Text-to-image tools are excellent at producing one great image, but character identity typically drifts across regenerations — face shape, hair, and wardrobe shift frame to frame. This makes AI images unusable for video pipelines, which need continuity across many keyframes. The challenge: prove a single AI-generated character could hold up across 8 distinct shots without losing continuity.

Ideogram 3.0, custom prompt engineering, Z-Image upscale, editorial/cinematic photography prompt structuring (lens, lighting, and color-grade language)

8 final cinematic portrait frames, 4K resolution

A reusable prompt template separating fixed identity elements from variable shot elements

A sequence-ready keyframe set formatted for direct use in AI video tools (Runway, Kling, Luma-style pipelines)

Achieved consistent character identity across 8 separate generations — same face structure, hair, and wardrobe held with zero manual retouching

Delivered fully at native 4K after upscaling, meeting production-ready resolution standards

Produced a documented, repeatable prompt framework that can be reapplied to any new character concept, cutting future project turnaround time

The biggest lesson: consistency comes almost entirely from prompt discipline, not luck — reusing the identical identity block was more important than any single generation setting. Next iteration will test image-to-image reference locking (rather than text-only prompting) to push consistency even further, and extend the workflow into an actual animated sequence using the frames as motion keyframes.