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AI-native workflow

I design at the pace AI makes possible. Product judgment stays in the work.

AI compresses the gap between a product decision and its first working form. This portfolio — 16 pages, custom design system, Astro static build — was designed, built, and shipped using the workflow below.

  1. Research

    Gather source material, market context, user pressure, and constraints.

    AI assist

  2. Figma - Figma Make

    Shape flows, interface models, component logic, and visual direction.

    human judgment

  3. Claude - Codex - Antigravity - Lovable

    Generate, scaffold, and iterate on code across AI-native tools and platforms.

    AI assist

  4. Astro - WordPress - Custom Apps

    Ship fast static product-led websites and case-study systems.

    AI assist

  5. GitHub

    Keep decisions, code, and deployment flow versioned and reviewable.

    Technical assist

  6. QA - Audits - Code and Security Review

    Check accessibility, performance, responsive behavior, and content clarity.

    AI assist

  7. Iteration

    Use review cycles to reduce friction instead of adding decoration.

    human judgment

What this means for product teams

  • Engineers spend less time translating specs, deliverables are implementation-aware from the start.
  • Design and development cycles compress without adding ambiguity, AI handles the mechanical parts, judgment handles the rest.
  • I can move across design, prototyping, and code review in the same session, which reduces round-trips and handoff friction.