AI Sports Campaign - Creative Direction Engine
Case Study

AI Sports Campaign

A Creative Direction Engine.

AI Automation System & Creative Direction • 2025

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Type
AI Automation System
Role
System Design & Creative Direction
Tools
n8n, Generative Image API, Reference Conditioning
Deliverables
n8n Workflow, Input Spec, Consistency Guardrails, Campaign Demo Outputs

Overview

Everyone can generate "cool" images now. Almost no one can generate consistent campaigns. I built a custom n8n automation—a Creative Direction Engine—that takes one reference campaign shot and lets me swap the model and wardrobe while keeping lighting, environment, and shot DNA stable. The result is campaign-grade coherence produced in minutes—iteration becomes a repeatable loop instead of a re-shoot problem.

Turn creative direction from "slot machine outcomes" into a system you can run on purpose.

The Challenge

Generative AI gives you images. It doesn't give you campaigns.

The baseline problem with generative image workflows is drift: change one thing and everything changes—lighting, texture, camera feel, even the "world" itself. That's fine for one-off visuals, but campaigns demand continuity: the audience should feel like every asset came from the same production. The challenge wasn't making a single strong image. It was building a workflow where the scene stays constant while casting and wardrobe stay editable.

Success Criteria

  • Outputs must read as one campaign, not separate "generations"
  • Swap model + wardrobe without rebuilding prompts from scratch
  • Keep shot anchors stable: environment, lighting, framing, texture
  • Produce usable variants fast enough for real marketing iteration

The Approach

Make it usable: a system, not a poster. The key insight: campaign consistency comes from constraints, not creativity-by-prompt. I designed the automation around a "constants vs variables" model—first locking the non-negotiables of the reference shot, then giving controlled flexibility to casting and wardrobe. The workflow ingests three visual inputs and routes them through a repeatable pipeline that prioritizes continuity over novelty. Output selection stays human-led: I pick the final based on realism, brand fit, and product readability—because campaigns are edited, not merely generated.

Tools & Technologies

n8nGenerative APIReference ConditioningPrompt SchemaOutput Versioning

The Brand System

The Variable

Casting (new model reference) + wardrobe (clothing/product references)

The Constant

Reference shot's lighting logic, environment, framing, and "same shoot" texture cues

The Output

Small set of campaign-consistent variants ready for creative selection

AI Sports Campaign - Workflow and system architecture
AI Sports Campaign - Prompt engineering and consistency techniques
AI Sports Campaign - Featured showcase of campaign consistency system

Results

The system makes campaign iteration fast and controllable: you can adapt casting and styling while keeping the visual world consistent. It replaces "generate until lucky" with a repeatable creative loop—inputs go in, coherent variants come out in minutes, and the final is chosen through judgment, not randomness. Practically, it enables campaign-level decisions without campaign-level burn rate.

This isn't just prompting—it's automated infrastructure for repeatable creative direction.
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