Before (the problem)
The disciplines that make AI agents governable — inventory, baselines, drift
detection, thresholds — are being reinvented under fragmented vocabulary across the
industry. The diagnosis gets published; the operational answer rarely does. There
was no canonical, public articulation of configuration management for AI agents.
What we built
A growing body of published articles establishing configuration management for AI
agents (CM-AI) in the open:
- A named framework, articulated publicly rather than held as a private pitch deck
- A series of long-form articles, each with article + audio + visual companions
- LinkedIn companions (institutional and founder voice) paired to each drop
How it works
- Each piece advances a specific part of the CM-AI framework.
- Articles publish to the website blog (Eleventy → Netlify) on a set cadence.
- Audio and infographic companions ship alongside via the research-to-content
pipeline.
- LinkedIn posts carry the framing on the day of each blog drop.
Outcomes
- A public, citable framework — proof the thinking is in the open
- Establishes an essentially uncontested term (configuration management for AI
agents) in the open literature
Stack & role
Long-form writing · Original framework. Built & operated in-house.
Timeline
Ongoing — a living series, not a one-time drop. The series finale pairs with the
white-paper drop.
What it proves
The framework stands in public. Anyone can read it, test it, and cite it — which is
a stronger position than a methodology that only exists inside a sales conversation.
