The AI-Native Design Org
Most leaders are still writing AI strategy decks. I run AI in production, daily, inside a design org - and the pattern is repeatable at any company.
What's actually running
- Design-to-production pipeline - Figma API automation that takes production comps and generates CMS-ready content for the Salesforce Commerce Cloud storefront, collapsing a manual multi-step handoff into minutes.
- Comps-to-tickets automation - when design files change, Jira tickets are created and synced automatically with exported comps attached. Designers design; the paperwork writes itself.
- LLM-driven analytics reporting - a weekly GA4 report for executive leadership, generated by an AI agent that queries the data, applies the org's measurement rules, and drafts the narrative. I review and send; the machine does the pulling.
- An AI agent as a working teammate - I operate a persistent AI agent wired into Figma, Jira, GA4, VWO, and the data warehouse. It files tickets, runs analyses, QAs tagging, and yes - it designed, built, and deployed this website.
The point: this isn't AI advocacy - it's AI operations. The craft stays human. The toil gets automated. The team ships faster and the data gets more honest.
The leadership thesis
AI in a design org fails when it's treated as a tool rollout, and works when someone senior enough to change the workflow actually rebuilds it. I've done that rebuild: I know which handoffs dissolve, which skills get more valuable, and how to bring a team along without pretending their craft is obsolete.
If your organization is trying to figure out what an AI-native product and design practice looks like - that's the job I want. Let's talk.