01 — LLM System Patterns
Purpose
[stub: llm-system-patterns]
See Also
- Agentic AI Engineering — Parts 02 (Memory Systems) and 05 (Retrieval & Knowledge Systems, incl. RAG) hold the build-level detail behind this chapter’s pattern vocabulary
- Building & Evaluating Agents — Part 01 (Multi-Agent Systems) holds the build-level detail for this chapter’s multi-agent patterns
Metadata
| Author | Amit Singh |
| Scope | patterns |
Local graph
Related notes
02 — AI Infrastructure Patterns
Model Routing, Prompt Chaining, Guardrails, Human-in-the-Loop, and Evaluation Pipelines — the operational scaffolding that makes an LLM system reliable enough to run in production.
Patterns
A book-shaped table of contents for reusable engineering patterns spanning object-oriented design, enterprise architecture, distributed systems, messaging, APIs, cloud infrastructure, observability, security, concurrency, AI/agentic systems, and organizational design — grounded in production experience at scale.
02 — Pattern Selection & Trade-offs
How to choose between competing patterns under real forces: naming the context, weighing trade-offs and consequences, composing multiple patterns together, and recognizing when a pattern has outlived its fit.
03 — Transaction Patterns
Unit of Work, Identity Map, Lazy Loading, and Optimistic vs. Pessimistic Locking — the patterns that keep an object graph and its persisted state from drifting apart.