Context Kubernetes: Declarative Orchestration of Enterprise Knowledge for Agentic AI Systems
Charafeddine Mouzouni

TL;DR
Context Kubernetes is a novel architecture that applies container orchestration principles to manage enterprise knowledge in agentic AI systems, ensuring secure and efficient knowledge delivery.
Contribution
It formalizes a knowledge orchestration architecture with declarative manifests, permission models, and safety verification, addressing unique challenges beyond traditional container orchestration.
Findings
Full architecture blocks all tested attack scenarios
Intent routing reduces noise by 19 percentage points
TLA+ model-checking verifies safety with zero violations
Abstract
We introduce Context Kubernetes, an architecture for orchestrating enterprise knowledge in agentic AI systems, with a prototype implementation and eight experiments. The core observation is that delivering the right knowledge, to the right agent, with the right permissions, at the right freshness -- across an entire organization -- is structurally analogous to the container orchestration problem Kubernetes solved a decade ago. We formalize six core abstractions, a YAML-based declarative manifest for knowledge-architecture-as-code, a reconciliation loop, and a three-tier agent permission model where agent authority is always a strict subset of human authority. On synthetic seed data, we compare four governance baselines of increasing strength: ungoverned RAG, ACL-filtered retrieval, RBAC-aware routing, and the full architecture. Each layer contributes a different capability: ACL…
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