AI Cost Control & Model Routing Playbook

AI Cost Control & Model Routing PlaybookMost teams discover AI cost problems the hard way.Early prototypes feel cheap. Then agents move closer to real workflows. Tool calls multiply. Context windows grow. Retries increase. Suddenly the monthly bill is an order of magnitude higher than expected — and no one can clearly explain why.This is not mainly a model pricing problem. It is an architecture and operating problem.This 13-page playbook gives platform, SRE, and engineering leaders practical patterns for keeping agentic systems useful without letting them become unpredictable cost centers.What’s inside:• The real cost drivers (input tokens, output tokens, tool-call amplification, retries, logging overhead)• Model routing fundamentals (simple, intelligent, and fallback routing)• Routing strategies that actually work in production• Practical architecture patterns (central routing layer vs per-agent policy vs hybrid)• Observability for cost — including why “cost per successful outcome” beats raw token volume• Guardrails and controls (budget caps, rate limits, kill switches, default-to-cheap policies)• Common anti-patterns that quietly burn money• A decision framework + print-and-pin readiness gate• Implementation checklist you can run with your teamWritten for people who need agents to stay reliable and cost-predictable in real environments.This playbook is for personal and internal team use.

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