Getting Started

Production AI Patterns is a structured pattern library for engineers building AI systems in production. It is not an awesome list of links, not vendor documentation, and not a research paper collection. It is a curated set of named patterns with descriptions, trade-offs, when-to-use guides, and code examples for every layer of a production AI system.

How to Use This Resource

If you know what you are looking for

Browse the sidebar. Patterns are organized into 8 pillars. Each pillar covers a distinct layer of a production AI system.

If you are not sure where to start

Use the Decision Guide to answer a few questions about your system and get recommended patterns.

If you want to understand the landscape

Read through the pillars in order. They roughly follow the lifecycle of a request through a production AI system:

1. Inference & Serving — How requests reach models and how responses come back.
2. Data Patterns for AI — The data foundation every AI system depends on.
3. Reliability & Resilience — Keeping AI systems working when things go wrong.
4. Retrieval & Memory — What knowledge AI systems can access and remember.
5. Observability & Monitoring — Seeing what your AI system is actually doing.
6. Security & Trust — Guardrails, PII handling, and prompt injection defenses.
7. Cost & Efficiency — Running AI systems without unbounded spend.
8. Governance & Compliance — Lineage, model cards, and compliance operations.
9. Graph Patterns — Knowledge graphs, graph-based reasoning, and entity resolution.
10. Evaluation & Testing — LLM-as-Judge, eval pipelines, and regression testing.

Reading a Pattern

Every pattern follows the same structure:

Section	Purpose
What It Is	One paragraph plain-language description
The Problem It Solves	What breaks without this pattern
How It Works	Step-by-step mechanism with diagrams
When to Use It	Specific conditions and workload types
When NOT to Use It	Explicit anti-use-cases
Trade-offs	2-4 honest trade-offs
Implementation Example	Minimal working code snippet
Tool Landscape	Tools that implement or support the pattern
Related Patterns	Links to adjacent patterns
Further Reading	2-4 high-quality external references

The When NOT to Use It section is the most important. It is what makes this resource opinionated rather than encyclopedic.

Pattern Maturity

Each pattern has a status indicating its maturity level:

• Proposed — Pattern identified, not yet validated in production systems.
• Emerging — Used by early adopters, trade-offs still being understood.
• Validated in Production — Widely used by multiple teams, trade-offs well understood.

Contributing

This is an open-source project. If you have used a pattern in production and want to share it, or if you see something that needs correction, see the Contributing Guide.