AI Agent Authorization: Approval Is Not a Blank Check
Bind agent approval to the exact action, identity, target, policy, and validity window. Revalidate changed conditions and give uncertain execution and recovery their own authority rules.
access control
Binding AI Agent Approvals to Kubernetes Changes
Bind approval to the exact Kubernetes request, object identity, starting state, executor, and validity window. Use conditional patches while keeping authorization, approval consumption, and uncertain outcomes separately governed.
From Simulation to Kubernetes: Testing Agent Identity and Admission
Move from an offline simulation to a disposable Kubernetes cluster. Test separate agent, executor, and observer identities, resource-scoped permissions, admission rules, and independent state readback.
A Citation Is Not Proof: Building an Evidence and Disclosure Control Layer
Make RAG citations useful evidence rather than decorative references. Validate source identity, claim support, applicability, and disclosure permission while keeping citation destinations under application control.
Retrieval Permissions Must Follow the User, Not the Service Account
Carry the effective user’s permissions through the entire RAG workflow. Enforce access before generation, preserve restrictions through caches and history, and test behavior when permissions change.
Your RAG Pipeline Is a Data Boundary, Not Just a Search Feature
Treat ingestion, chunking, embedding, and storage as governed data processing. Preserve source restrictions and lineage, control processing routes, and design revocation and recovery before expanding the RAG corpus.
Production Vector Database Operations: Backup, Recovery, Reindexing, and Access Control
Recover the retrieval service, not just vector database files. Coordinate metadata, lineage, embeddings, permissions, and configuration, then validate authorized retrieval before reopening production traffic.