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Reusable instructions for compatible AI agents.
Counts cover every published resource in this section. A resource can belong to several fields and platforms.
Conduct periodic access reviews and certifications. Implement access governance and recertification workflows. Use when managing access compliance.
Build automated evaluation suites for AI agents using golden datasets, rubrics, and regression gates. Use when shipping agent features, validating prompt changes, or gating deployments on quality.
Instrument AI agents with tracing, token metrics, latency, and cost visibility. Use for reliability and debugging.
Secure AI agents against prompt injection, tool abuse, and data exfiltration with defense-in-depth controls.
Secure AI coding agents (Claude Code, Cursor, Codex, Copilot) with permission boundaries, secret protection, code review gates, and safe sandbox configurations for team environments.
Use verified service mesh patterns for AI inference traffic management, mTLS, canary releases, policy enforcement, and cross-cluster resilience.
Orchestrate AI/ML pipelines for data ingestion, model training, batch inference, and RAG indexing using Prefect, Airflow, or Dagster.
Run structured AI red team exercises for jailbreak resistance, data exfiltration risk, harmful output controls, and agent tool abuse resilience.
Harden AI/LLM deployments against prompt injection, data exfiltration, model theft, and supply chain attacks.
Build AI-focused SRE incident response practices for LLM outages, degraded quality, runaway cost events, and safety regressions.
Set up alerting rules, configure on-call rotations, and manage incident response workflows.
Implement GitOps with ArgoCD for declarative Kubernetes deployments.
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