Budgeting the Performance Envelope

Use when the user asks how to control an AI agent's cost, latency, or token spend — "our LLM bill is exploding", "which model should each task use?", "how do we cap agent spend?", "how do we stop a runaway agent loop?", "is prompt caching worth it for our traffic?", "is the batch API discount worth it?", "set rate limits or quotas so one team can't starve the rest" — or when engineering tokens, latency, reliability, cost, and capacity as one surface. Walks through cost-per-outcome instrumentation, tiered model routing, caching and batch economics, harness token waste, layered budget enforcement, and budgeting eval spend, with concrete prices and thresholds. Not for arrang…