Building digital experiences for humans and AI systems.
Experiments in AI discoverability, content architecture, analytics, and modern web operations.
Focus Stack
Discovery
SEO, AI search, content strategy, entity clarity.
Systems
Astro, structured content, Markdown collections, CMS thinking.
Measurement
Analytics, visibility signals, citation behavior, experiment design.
Why This Exists
Search is changing. People are no longer only finding information through traditional search engines; they are increasingly asking AI systems to summarize, recommend, and cite sources.
AI Search Lab is a working space for exploring what that shift means for websites, content systems, SEO, analytics, and digital experience teams.
Now Testing
- How AI systems interpret structured content
- Whether metadata changes citation behavior
- How information architecture impacts retrieval
Featured Experiments
Can AI Understand This Website?
What characteristics make websites easier for AI systems to understand and cite?
Can AI Systems Retrieve JavaScript-Rendered Content Reliably?
Testing whether delivery architecture affects how AI systems retrieve, understand, and cite identical content.
SEO vs AI Discoverability
Exploring where traditional SEO ends and AI optimization begins.
Projects
AI Search Lab
A content-driven Astro site exploring AI discoverability, structured content, SEO, and digital experience.
Future Project
Reserved for future experiments, tools, or interactive prototypes.