Niudo Modern Sushi: Nigiri vs Uramaki

1. The Problem — Or the Opportunity?
2. Defining the Campaign’s Aesthetic & Concept
3. Implementing the AI Workflow
4.1 Assets Design: Instagram
4.2 Assets Design: Video
5. Feedback & Revisions
6. Metrics & Impact
7. Results & Learnings

1. The Challenge

Teníamos que promocionar el evento saraza que era importante, la [sushi party night]. Con tanta competencia en tiktok y restaurantes generando contenidos similares. Queríamos destacar generando nuestros propios personajes animados. Que se iban a enfrentar en la batalla final. Nigiri vs Uramaki por un lugar en la [sushi party night].

2. La Estrategia Visual (The Visual Strategy)

My research started by looking into the sneaker itself. I learned that the design of the shoe, and the entire Air Jordan 4 Retro line, are some of the most important milestones in the history of street culture and sports footwear. I also learned that they were designed by legendary designer Tinker Hatfield and originally released in 1989.

From there, I went down exploring sports milestones (Michael Jordan’s “The Shot”), fashion (minimalism, neutral colors, relaxed styling), film (Do the Right Thing, White Men Can’t Jump), and design (April Greiman, Wolfgang Weingart, New Wave, Grunge, Pixel, Macintosh). I cover my research process in detail in my article Visual Inspiration: A Journey Through 1980s Graphic Design. To keep it short for this case study, my research helped me consolidate the moodboard, color palette, typography, and the central concept for the campaign.

At the same time, the reference moodboard I created would later become the input for my Aesthetics Builder—but we’ll get into that in the next step.

3. AI Workflow Implementation

Once the aesthetic was defined and the visual foundations were in place, it was time to move on to the campaign photography. Since I had practically zero existing assets to work with, this was the perfect opportunity to build my AI Workflow: Infinite Photo Shoots & Models using Variables in Figma Weave.

In the article, I break down the process step by step and share the workflow in case you want to remix, improve, or reuse it. Basically, the workflow allows me to define variables that control the aesthetics, model characteristics, storytelling pose, sneaker model, and photoshoot location.

By combining these variables, I can scale asset production, iterate faster, and generate virtually infinite combinations.

Starting from a single photo—a right-side view of the sneaker—that Christian sent me, I used AI to generate multiple views of the sneaker from different angles for the e-commerce website, as well as campaign photography and product videos featuring models for social ads.

4.1. Assets Design: Instagram Ads

I incorporated the photography, color palette, and typography, while creating reusable layouts and templates.

Since we already had a system in place for generating infinite photo variations, it made sense to build scalable templates that could be reused across future campaign assets.

7. Results & Learnings

1. Faster production, lower costs
   Developing the AI workflow for generating photo shoots significantly accelerated the project timeline and reduced production costs for my client.
2. Faster iteration based on feedback
   I was able to quickly iterate on the photography and make adjustments based on client feedback. Christian knows the target audience better than I do, so his suggestions—whether regarding the model, age, or other characteristics—were always valuable.
3. A/B testing
   Since we can modify the variables behind each photo shoot, we can generate specific variations and use them to test, compare, and evaluate performance.

I learned a lot about the Air Jordan Retro models and about many of the important things that happened during the 1980s in sports, fashion, and design.

When building the workflow, I learned how important it is to do solid pre-production research and feed the AI with the best possible inputs. The better the foundation, the fewer random or unexpected results we get.

I would have spent more time understanding how negative prompts work and how to use them effectively with certain video models.

Telling AI what we don’t want it to do can sometimes be just as important as telling it what we want it to do. A better understanding of this would have helped me avoid wasting credits during the asset generation process.

Building this AI workflow gives us a powerful tool for generating the next assets for this campaign—and potentially for future campaigns for the brand.

But it also comes with the responsibility of continuously improving it: iterating, refining, and adding new variables to gain even more control over every detail of our photo shoots.