Articles
Layer-by-layer walkthroughs. Each article links to the academic canon for deeper technical detail.
Practical, regulated-environment ready explorations of each layer in the Adaptive Intelligence Layers™ architecture. These articles connect governance principles to operational reality.
The Intent Layer
Why AI governance begins before a model responds — and how intent becomes enforceable in regulated systems.
The Intent Layer: Why AI Governance Begins Before a Model Responds
How intent specification constrains and governs intelligent systems at the point of authorization.
The Context Layer: Bridging the Gap Between Data and Decision
How AIL makes context structural, observable, and governable rather than implicit.
The Governance Layer: Oversight Before, During, and After Execution
Real-time drift detection, risk evaluation, and enforcement across the AI lifecycle.
The Execution Layer: Controlled Action in Intelligent Systems
How AIL ensures that execution aligns with intent, context, and governance constraints.
The Adaptation Layer: Learning Without Losing Alignment
Constraint-preserving updates that maintain behavioral stability and regulatory compliance.
The Verification Loop: Continuous Alignment Renewal
How AIL detects and responds to drift across pre-execution, runtime, and post-action phases.
The Quant Vault: Evidentiary Infrastructure for AI Governance
Long-term accountability, auditability, and institutional memory for intelligent systems.
Looking for Technical Papers?
Visit the Library for formal academic papers defining the AIL architecture, including layer-specific specifications and implementation guidance.
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