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Learning path · Enterprise Patterns & Governance · 85

Enterprise AI Patterns

Reference architectures for secure, multi-tenant GenAI—VPC deployment, SSO, audit logs, staged rollouts.

Why it matters

  • Bridges prototype notebooks to platform engineering.
  • Aligns AI features with existing SDLC and IT controls.
  • Reported industry case studies emphasize observability and routing.

Key ideas

  • Landing zones
  • Shared services
  • Progressive delivery

Top resources

  1. 01ArticleAnthropic

    Building effective agents

    Why this resource. Paved-road agent/workflow design that a platform team can support.

    Covers in this concept

    • workflows
    • tooling
  2. 02DocsNIST

    AI Risk Management Framework

    Why this resource. How those patterns map to risk management, not only architecture diagrams.

    Covers in this concept

    • govern
    • map
    • measure

Video

Enterprise patterns standardize embedding pipelines, prompt registries, eval gates, and secret management. Provide golden paths: approved models, connector templates, and telemetry defaults. Stage features behind feature flags with kill switches. Central platform teams enable product squads without each rebuilding RAG from scratch. Offer paved-road templates for RAG and agents so product teams inherit security, logging, and eval defaults by default. Measure platform adoption by counting squads on paved roads versus bespoke stacks.

Updated 2026-08-09 · Full learning path