Part 9: Building AI-Native Architecture — Semantic Caching, Gateways & Resilient LLM Workflows
Prerequisite: Strong understanding of embedding vectors, cosine similarity math, Redis cluster architecture, HTTP reverse proxy routing, and resilience patterns. Answer-first: Architecting production AI-Native applications demands decoupling LLM inference from core business logic using Model Context Protocol and smart AI Gateways. Resilient systems integrate semantic caching to cut API latency by 80%, implement dynamic fallbacks across frontier and open-weights models, and enforce token budget limits. Scalable AI platforms prioritize observable telemetry, deterministic retries, and strict schema validation. ...