- Why System Design Changed
- The AI System Design Framework
- LLM API Gateway
- Prompt Caching and Context Management at Scale
- Design: AI-Powered Chat Service
- Embedding Storage and Vector Search at Scale
- Design: RAG System for Enterprise Search
- Design: AI Content Moderation Pipeline
- Agent Orchestration Engine
- Design: AI Coding Assistant Backend
- Cost Optimization Architecture
- Reliability and Fault Tolerance for AI Systems
- Observability for AI Systems
- Design: Multi-Modal AI Platform
- System Design Interview Strategies for AI Systems
- Appendix: Reference Tables
AI-Assisted System Design
AI-Assisted System Design
This book is 100% completeLast updated on 2026-07-22
The system design book for the AI era. Five complete end-to-end designs (chat service, RAG, content moderation, coding assistant, multi-modal platform), a structured six-step framework, and chapters on cost optimization, reliability, and
observability — all with realistic capacity estimates and production-grade code.
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About
About the Book
Traditional system design books predate AI. They teach you to design URL shorteners and chat apps, but not systems where LLMs are core components with their own constraints: non-determinism, token economics, high latency, context windows,
and continuous quality monitoring. This book fills that gap. You learn a structured six-step framework for AI system design, then apply it to five complete designs: an AI-powered chat service, a RAG system for enterprise search, a content
moderation pipeline, an AI coding assistant backend, and a multi-modal AI platform. Supporting chapters cover the infrastructure that makes AI systems production-ready: LLM API gateways, prompt caching at scale, vector search, agent
orchestration, cost optimization architecture, reliability patterns, and observability. Every design includes realistic capacity estimates with actual numbers, trade-off analysis, and Python code for critical components. Whether you are
preparing for system design interviews or designing real production systems, this is the architecture guide for AI in 2026.
Author
About the Author
CAIO INCAU
aio Incau é Engineering Manager com experiência liderando times de engenharia de software em larga escala. No dia a dia, combina gestão de pessoas com profundidade técnica para entregar produtos que impactam milhões de usuários. Começou a usar Claude Code por curiosidade, virou adepto por produtividade, e escreveu este livro para que outros desenvolvedores não precisem descobrir tudo sozinhos.
Contents
Table of Contents
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