AI isn't a side tool in my process - it's a core material. I use large language models across the full product lifecycle: from research and strategy through to design, engineering, and content production.

Claude Code: Full-stack product builds I built Sourceful's marketing website end-to-end using Claude Code in under three weeks - a production site with Shopify integration, automated lead flows (Formspark → Slack → Notion), accessibility features, and AI-powered content generation. No other engineers involved. This isn't about speed for its own sake - it's about a designer who can take a product from concept to production without handoffs.

OpenClaw: AI content pipeline I designed and built a multi-agent content system that autonomously generates, reviews, and publishes content across channels. It uses orchestrated LLM agents to maintain brand voice, editorial quality, and publishing schedules - turning what would normally require a content team into an automated pipeline.

Design system and product architecture I use AI as a thinking partner for systems-level design work - structuring domain models, mapping navigation architectures, stress-testing UX decisions, and generating implementation-ready specs. My workflow with Claude is conversational and iterative: I treat it as a senior collaborator, not an autocomplete.

What this means in practice I'm not a designer who "also uses ChatGPT." I've rebuilt my entire practice around AI-native workflows. I think in systems, I ship in code, and I use AI to collapse the gap between design intent and production reality. If you're building a team that takes AI seriously as a design and engineering capability - not just a feature to bolt on - that's where I operate.