AI Creative Systems
+ Cultural Strategy

Architecting AI-driven creative systems that optimize output while preserving cultural nuance.

What I Do

My work sits at the intersection of AI tooling, creative strategy, and platform behavior. I focus on building systems that make creative output fast, repeatable, and reliable at real scale.

Experience Snapshot

Worked across independent, mid-scale, and enterprise initiatives spanning music, film, and creator-led campaigns, including projects connected to Grammy-nominated and chart-topping artists.

Case Study 01

AI-Powered Creative Engine

Overview

Engineered a proprietary software platform that transforms creative briefs into scalable image and video output. Built from scratch using a full-stack architecture.

The Problem

Clients needed large volumes of organic content with specific creative direction. Manual production workflows could not meet speed, scale, or flexibility requirements.

The System

  • Engineered a custom full-stack application to replace manual prompting and one-off creative workflows.
  • Built an orchestration layer to automatically route creative briefs through multiple AI models for image and video generation.
  • Developed a bulk ingestion feature allowing 500+ theme profiles to be processed via CSV upload in minutes.
  • Coded a centralized gallery UI for real-time review, filtering, and selection of thousands of generated assets.
500+
Campaigns
176M+
Views
1.1M+
Posts
1 Week → 1 Day
Turnaround
Sample Outputs
Case Study 02

Ride the Trend

Cultural Intelligence & Demand Mapping

Overview

Built a cultural intelligence and creator deployment platform to understand how social algorithms respond to demand, replication, and search behavior, and to operationalize that insight through creator-led distribution.

The Problem

Trend discovery was fragmented across platforms, making it difficult for creators and brands to understand what was gaining momentum and why. At the same time, high-performing creators were often mispriced relative to their actual distribution power, creating inefficiencies between brands, artists, and available reach.

Method

  • Monitored replication velocity, engagement behavior, and comment patterns
  • Validated trends using platform signals and search demand
  • Traced trend origins, often identifying non-viral creators as early drivers
  • Curated insights into clear, actionable summaries
  • Identified and activated high-signal creators whose output aligned with emerging demand patterns

Selected Creator Outputs

Selected outputs from creators and editors operating within the Ride the Trend ecosystem to drive viral organic and cultural visibility for brands, artist and film releases.

40k+
Followers Cross-Platform
Became a trusted signal source for creators and brands tracking early cultural momentum.
Case Study 03

Campaign Operations Dashboard

The Problem

Thousands of posts were going live across multiple campaigns without clear insight into system health or failure points. When issues occurred, teams could not quickly identify where workflows were breaking down.

The Solution

  • • Centralized visibility into campaign delivery and fulfillment
  • • Enabled quick identification of workflow failures
  • • Allowed teams to compare performance and decide what to scale or pause

Faster Diagnosis

Rapid issue identification across active campaigns

Operational Response

Improved handling of increased campaign volume

Shared Truth

Unified source for campaign health optimization

Tools I Use

AI IDEs

Cursor
Codex
Antigravity

Models & Generation

Claude (all models)
ChatGPT
Gemini Pro
Midjourney
Higgsfield / Suno / Fal AI

Research & Agents

Perplexity
Genspark
Manus AI