Turning AI capabilities into useful business products.

Every business can now access frontier AI models. Very few can turn that access into a product a customer would pay for. The distance between a capability and a product is strategy, design, trust, and operations — the unglamorous majority of the work.

Commerce businesses need a constant stream of product imagery, and AI can generate it — but naive generation creates real problems: inconsistent quality, brand risk, and unresolved questions about the real people whose likenesses AI imagery touches.

The product opportunity was to solve the whole problem — quality, workflow, and the human side — not just to wrap a model in a UI.

Consent is my own product. I own it end to end: product strategy, experience design, engineering, billing, compliance, and operations.

Two convictions shaped the product. First, quality is a pipeline, not a prompt — reliable output comes from layered prompt architecture, sanitization, and review, not from asking a model nicely.

Second, trust is the product. AI imagery that touches real people's likenesses needs explicit consent, fair compensation, and the right to withdraw — designed into the system, not bolted on as a policy page.

The consent framework treats the humans in the system as first-class users: explicit consent terms, configurable revenue share, and a wind-down period when a model withdraws — enforced by the platform itself.

The generation pipeline layers business logic over the models: structured prompt construction, a realism layer, sanitization, and auditability — so output quality is an engineered property, not luck.

The product is designed for merchants, not ML enthusiasts. No prompt boxes as a primary interface — structured creative controls that speak commerce language: product, model, scene, format.

Built and operated as a real business: subscription billing, quota management, and an admin operations layer — with distribution where merchants already work. The Shopify app is live in the Shopify App Store; the Salla app is in pre-launch.

The codebase itself is a case study in AI-assisted engineering — built with Claude Code under human product direction, which is exactly the human-in-the-loop discipline the product preaches.

A live, revenue-generating product with a published Shopify App Store listing and a compliance framework covering every person whose likeness the platform touches.

Pending verification[ADD VERIFIED METRICS — subscribers, generation volume, or merchant outcomes when ready to publish.]

Building an AI product end to end — strategy, design, code, billing, compliance — is the strongest proof I can offer that I understand how AI becomes a business, not a demo. That understanding transfers directly to client and employer problems.