Knowledge Base
High-signal doctrine for production AI architecture and operational discipline. If you're new here, start with the framework path below.
Subject Filter // governance
Framework Reading Path
The shortest route into the doctrine system: model, containment, regression discipline, then release authority.
Probabilistic Core / Deterministic Shell: Containing Uncertainty Without Shipping Chaos
Two-Key Writes: Preventing Accidental Autonomy in AI Systems
The Minimum Useful Trace: An Observability Contract for Production AI
Golden Sets: Regression Engineering for Probabilistic Systems
Fundamentals of AI
0 ArticlesTechnical Deep Dives
7 ArticlesGenerative AI
Technical Guide
Probabilistic Core / Deterministic Shell: Containing Uncertainty Without Shipping Chaos
A production architecture pattern: treat the model as a probabilistic component and wrap it in deterministic contracts, budgets, and enforcement so the system stays operable.
Technical Guide
Golden Sets: Regression Engineering for Probabilistic Systems
Golden sets are unit tests for probabilistic behavior: curated cases, versioned rubrics, and gates that prevent quality regressions from shipping as surprises.
Technical Guide
Error Taxonomy: Classifying AI System Failures Before They Become Incidents
A failure-language doctrine for production AI: classify failures by boundary crossed, control missed, and detection path so incidents stop dissolving into vague model blame.
Technical Guide
Evaluation Gates: Releasing AI Systems Without Guesswork
Evaluation gates are approval gates for AI release engineering. They turn tests, budgets, and policy checks into ship, constrain, block, or rollback decisions.
Technical Guide
The Heavy Thought Model for AI Systems
A governed control-plane doctrine for reliable AI architecture: six layers, three disciplines, and one coherent model for turning probabilistic capability into operable systems.
Technical Guide
Retrieval Boundaries: What Your AI System Is Allowed to Know
Retrieval is not a search feature. It is the runtime memory boundary that determines what evidence your AI system is allowed to admit, cite, and act on.
Technical Guide
Policy Enforcement in AI Systems: Turning Governance into Runtime Control
AI policy enforcement turns governance into binding runtime control across routing, retrieval, refusals, tool permissions, and rollback in production AI systems.