Most teams blame their model provider when the inference bill spikes. They're looking at the wrong line item.
The real leak is architecture — and it's the difference between a token bill that scales with value and one that scales with chaos. Here's what we see shipping agentic systems in production.
The hidden multiplier: agent loops
A "2-minute task" is never one call. An agent fires 30–60 tool calls per run, and most frameworks stuff the entire conversation history into every prompt. So a job you'd estimate at ~4K tokens becomes 40 calls × 8K context = 320K tokens — billed at frontier rates.
Frontier pricing per call looks cheap. Multiplied by agent-loop iterations, it quietly becomes the largest line in your cloud bill.
