Building Production-Grade Agentic AI Systems: A Senior Architect’s Blueprint for Scalability, Latency, and Trust

Short summary

A senior architect's guide to moving agentic AI from prototype to production, treating agents as distributed state machines rather than LLMs in loops. Covers ingress guardrails, orchestration engines, dynamic model routing, multi-tier memory (L1/L2 caching analogies), tool registries via MCP, and observability pipelines. Emphasizes system engineering over prompt engineering for scalability, latency control, and trust.

• •Agents are distributed state machines, not LLMs in loops — production requires system engineering not prompt engineering
• •Multi-tier memory strategy (L1 working memory, L2 semantic summary) prevents context bloat and cost explosion
• •Architecture isolates concerns: guardrails, orchestration, routing, memory, tools, and observability as separate testable layers

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