The hidden multiplier nobody budgets for When we moved from single-turn chatbots to agentic workflows in early 2026, the first thing that broke wasn't the code — it was the budget spreadsheet. A simple chat completion costs one API call. An agent that plans, selects tools, executes them, evaluates the results, and synthesizes a final answer? That same user request now triggers 5 to 20 LLM calls . Sometimes more. I ran an experiment last month with a production agent doing research tasks — web search, summarization, multi-hop reasoning. A single user prompt averaged 14 LLM round-trips across GPT-5 and Claude 4.6 Opus. At GPT-5's input/output pricing, that one "simple question" cost $0.47. Multiply by 1,000 daily active users and you're looking at $470/day you never planned for. Where the cost actually hides After instrumenting our gateway logs for two weeks, here's what I found: 1. Planning overhead Every agent loop starts with a planning step.…