Alexandra Owens
AI Creative Systems
I build systems that allow creative teams to produce with AI structurally, including prompt architecture, visual frameworks, governance standards, and production workflows, applying two decades of systemic design work to the problem most organizations are only beginning to understand: how to integrate AI into creative operations with consistency, quality, and scale.
I am both architect and operator, designing the systems that I work inside daily, producing hundreds of images a month while refining the infrastructure around them. I firmly believe that the best systems are built by the people who use them.
WHAT I DO
AI Production Systems
Prompt libraries, model workflows, visual frameworks, and governance standards that make AI-generated creative repeatable, controllable, and production-ready.
Visual Systems & Governance
Asset structures, metadata architectures, and operational standards that create consistency across brands, teams, and platforms.
Creative Operations
High-volume production at 200 to 300+ images monthly. Throughput tracking, bottleneck identification, and the dashboards that justify resourcing.
Cross-Functional Integration
The work between creative, merchandising, product, and technical teams. Aligning visual production with commerce timelines and business outcomes.
Image Craft
2 decades of photography, Photoshop, compositing, and digital image work. Precise control over lighting, surface, scale, and realism, from the camera through to the final output. The foundation that makes my AI image generation different from prompt-and-accept.
AI Production Pipeline & Prompt Architecture
+ view work
Structured prompt architecture and a multi-stage production pipeline that turns AI image generation into a repeatable, production-quality creative system.
Built a four-stage pipeline: scene generation through Nano Banana (feeding multiple reference images for scale, color, and composition), per-product refinement through Flux Kontext Pro, Photoshop finishing (grain, grading, dodge/burn), and final upscaling through Topaz. The system produced a full editorial imagery library for a homepage redesign across 22 category cards with no traditional photography. Prompt architecture is locked into a structured brief format covering role, scale, products, scene, lighting, and quality constraints, producing consistent results across outputs. Supporting infrastructure includes a React-based content tracker, session handoff briefs, and versioned prompt files, making the pipeline reproducible across collaborators and sessions. Prompt methodology built into Weavy and extends across Midjourney and Kling, with LoRA training used for product consistency across generations.
DAM Governance, Architecture & Product Development
+ view work
Structural ownership of a production DAM across 300+ brands and 63,687 assets. Currently building its replacement.
Own the taxonomy governance, metadata schema, ingestion standards, and vendor upload workflows for The Feed's Canto DAM. A complete audit revealed structural failures: 45% of assets missing category data, rigid folder hierarchy requiring duplication, no rendition model linking Shopify-optimized images to source files, and naming misalignment between 286 Shopify vendors and 331 DAM brands. The replacement, Asset Clarity, is a custom Next.js + Supabase application with 63,687 migrated assets, faceted filtering, full-text search, a brand directory, and parent-child rendition linking — architecture documented in a full PRD written as both build specification and portfolio artifact. Previously led a DAM migration consolidating 90,000+ assets to 50,000.
Owns the full surface where AI-produced creative meets the customer: CMS architecture, homepage systems, and content deployment across Contentful and Shopify.
Design and maintain front-end content infrastructure across Contentful, WordPress, and Shopify. Build banner taxonomy systems and homepage architectures that organize how creative work reaches customers across multiple brand verticals. The AI imagery from the prompt pipeline and the assets governed through the DAM both converge here, deployed through systems built for volume, speed, and brand consistency. Delivered a fully responsive homepage architecture in 14 days for Tour de France sponsorship.
Two decades of photography, Photoshop, compositing, and digital painting. The craft foundation that makes everything else work.
Commercial compositing and retouching across wellness, publishing, and consumer products — packaging design built from cut botanical elements, portrait work where a subject has to sit convincingly inside a constructed environment, layouts where a dozen layers have to read as a single coherent image. That precision with light, surface, masking, and color grading is what makes the AI image generation different from prompt-and-accept: knowing when a shadow is wrong, when a surface material isn't reading correctly, when the scale relationship between elements breaks the illusion. Currently learning Python and React to push that work further into programmatic and generative territory.
Numbers
17+
YEARS IN SYSTEMATIC DESIGN
200–300+
IMAGES PRODUCED MONTHLY
300+
BRANDS UNDER GOVERNANCE
90k to 50k
ASSET MIGRATION & CONSOLIDATION
Direction
Moving more deeply into the architecture of AI creative systems. API-level fluency, agent orchestration, multi-model workflows. The trajectory is toward building at a higher level without losing the craft. Building toward organizations that are serious about making AI work well, where systematic design thinking and AI infrastructure are the same discipline.
Years of photo editing and retouching taught me that precision is a form of care. You learn to see what light actually does, what a surface really looks like, when a scale relationship is wrong. That same attention now applies to AI systems, DAM architecture, and production pipelines, anywhere that quality needs to survive volume.
I am interested in the structures that make good work repeatable. Structure is the condition for creativity, not a constraint on it.
