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AIAgentsRAGAI SDK

AI Agents in Production: Beyond the Demo

How to integrate AI agents, RAG and conversational workflows into production products with observability, security and cost control.

2026-07-05 · 6 min read

Agents are systems, not features

An AI agent in production needs tool boundaries, audit trails, fallback behavior, latency budgets and cost ceilings — the same discipline as any critical backend service.

PATMOS builds AI into real workflows: Apollo (AI education), SARAH operational intelligence and client agent integrations using production-grade patterns.

Architecture patterns that work

RAG with explicit source attribution. Human-in-the-loop for high-risk actions. Structured outputs validated before side effects. Rate limiting and prompt injection defenses at the API layer.

Use the AI SDK with gateway routing, model fallbacks and tracing — not ad-hoc fetch calls from the client.

When to hire senior AI engineering

Bring in senior help when agents touch money, compliance, customer data or operational decisions — not when you need a chat widget on a marketing page.