Cipher
YEAR
FORMAT
Fashion Film
TOOLS
LTX 2.3 // GPT Image // Suno
INTENT
Cipher was an exploration into AI-driven filmmaking, focused on speed, consistency, and how much visual control could be maintained inside a fashion-led narrative. The goal was to see whether LTX could help build something that felt cinematic and cohesive, not just generate a few strong standalone shots.
The story follows a woman being chased by her past, moving through stylized environments where tension and beauty live side by side. More than anything, the project was about testing how far AI could go in supporting a clear visual story while still holding onto character consistency, mood, and overall direction.







SYSTEM BEHAVIOR
One of the biggest takeaways from Cipher was that getting strong results took a lot of iteration, careful prompting, and selective curation. Keeping the main character consistent across multiple shots was possible, but it did not happen naturally. It required refining prompts, adjusting outputs, and being very intentional about which details needed to stay locked in from scene to scene. The strongest moments came when the prompts were focused, the scenes were visually simple enough to control, and the direction stayed rooted in mood, styling, and composition.
The project also made the current limits of the tools pretty clear. Some elements, especially weapons and more complex action, were much harder to reproduce consistently and often introduced visual instability. That made it harder to maintain continuity once the scene demanded more precision. In the end, Cipher showed that AI is already useful for building striking, concept-driven short films quickly, but it still needs a lot of creative oversight. It can get you close, especially for stylized storytelling, but it is not polished enough yet to fully replace a traditional production process when consistency and control really matter.



