AI Application Architecture: Patterns for Building Intelligent Systems
Published by Self-published · Tech
Covers architectural patterns for building intelligent applications, from inference pipelines to multi-agent orchestration.
Who this book is for
AI engineers and software architects designing AI applications, backend engineers adding AI to existing systems, platform engineers building shared AI infrastructure, and technical leaders choosing architectural approaches.
Table of contents
- Why AI Needs Architecture
- Foundational Patterns
- RAG Architecture Patterns
- Agent Architecture Patterns
- Tool Use Patterns
- Orchestration Patterns
- Streaming AI Systems
- Hybrid Pipelines
- Multi-Model Architectures
- Context Management Patterns
- Reliability Patterns
- Anti-Patterns and Decision Framework
Excerpt
Building an AI application is easy. Keeping it running in production is hard. The gap between a working prototype and a production system is the same gap that software engineering has been bridging for decades: the gap between "it works on my machine" and "it works for a thousand users at 3 AM." This chapter establishes why AI systems need architectural discipline, what makes AI architecture different from traditional software architecture, and the cost of getting it wrong.
