Federal AI Governance Research

DOCTRINE

Authoritative research on AI governance, compliance automation, and agent architecture for federal systems. From sandbox to production, from theory to operations.

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Deep technical research spanning core domains of federal AI governance, compliance automation, and operational deployment.

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Featured Research

Selected papers from the DOCTRINE series addressing critical challenges in governed AI deployment.

WP-IDEA-20whitepaper

Finding the AI Lagrange Points: The Three-Body Problem of Regulated AI

The document presents the Three-Body Problem framework—originally developed for classified Department of Defense AI governance—as a universally applicable model for managing regulated AI systems across commercial sectors including financial services, healthcare, energy, and insurance.

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// Flagship Publication

DOCTRINE Series

The Harness Horizon

Trust Convergence on the Edge of Artificial Intelligence

Linc M. Williams

The Harness Horizon: Trust, Autonomy, and the Architecture of Governed AI

A comprehensive ebook spanning three parts and twelve chapters that establishes the theoretical foundations, practical architecture, and strategic implications of harness-based AI governance.

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