Nightberry
YEAR
TOOLS
LTX 2.3 // GPT Image // Nano Banana // Suno
INTENT
This project was a stress test on sequence control. The specific question was whether first-frame and last-frame workflows could provide enough direction to shape transitions, preserve character consistency, and guide motion from one beat to the next without losing the thread.
The secondary focus was 3D-style animation inside an AI pipeline — where stylized motion, product interaction, and camera choreography could hold up and where they would start to break. The goal was not a finished ad. It was a map of the system’s limits under controlled conditions.
Suno generated the score end to end.




SYSTEM BEHAVIOR
First and last frame setups gave useful directional control but still required careful shot design to avoid broken transitions, warped product handling, and inconsistent character detail. Product interaction — especially hand-to-can contact — proved more fragile than wider pose-based shots. Surveillance angles and controlled push-ins held better because they reduced complexity while still reading as cinematic.
The clearest takeaway: AI-driven 3D-style animation is not there yet. Some shots suggest the aesthetic, but the output is not consistently polished enough to replace a true 3D pipeline when precision and clean product interaction matter. It can hint at the look. It still breaks under scrutiny.



