AI For Editorial Excellence
I've crafted stories that make people laugh, think, and act. AI tools are now part of how I work, the infrastructure that frees me to do more of the work only a human should do.
Here are the principles that guide the practice.
Knowledge Architecture
I run two dedicated AI projects: one for ongoing market intelligence and synthesis, one for active work. Each maintains its own context and purpose. The goal isn't to produce more content faster — it's to be better informed before I write anything.
Domain Authority
AI is only as good as the judgment you bring to it. You need to know what story to tell, who you're telling it to, and why it matters — before you prompt anything. The tool amplifies your thinking. It doesn't replace it.
Point of View
Generic content serves no one. I apply editorial taste to every AI output — cutting what's algorithmic, keeping what's true. Audiences trust distinct perspectives, not content that sounds like everyone else using the same prompt.
Clear Guidelines
Organizations need clear AI governance: transparent policies about which tools are permissible and why, ongoing education for teams, and frameworks that align with company values and editorial standards.
Intentionality
AI isn't for outsourcing decisions, values, or strategy. Overreliance creates content indistinguishable from everyone else using the same prompt structures. The discipline is knowing when to use it and when to stay in the chair yourself.
Honesty
I'm transparent about how I use AI in my work. It accelerates production and research. It doesn't make decisions, set strategy, or substitute for human judgment. That responsibility stays mine.