The handbook · Working draft
A practitioner's reference for AI personalization, from the first decision to production.
Most companies do not have a data problem. They have a depth problem.
They know who is renewing, who is frustrated and who just hired a new ops lead, then send all of them the same email. This handbook covers the path from that gap to a system that remembers, decides and writes for one customer at a time.
This is a working draft. I'm revising every chapter in the open, so expect changes.
22 chapters · 11 team playbooks · free to read
Writing
What I learn shipping AI products: the architecture, the decisions, the costs and what broke.
A production personalization engine is not a prompt that writes custom copy. It is a governed system that resolves identity, builds trusted context, decomposes content into specialized jobs, generates across channels, validates every important boundary, recovers failed work, and learns from real populations under human supervision. This is the architecture I use.
ReadArtwork
Watercolor, ink and charcoal. Mostly faces: the same habit as the day job, looking at one person long enough to see them.
