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A controlled swap on six frontier models shows the orchestration layer, not the model, sets the cost of agentic AI. #
Have you ever watched two teams run the exact same frontier model and walk away with invoices that aren’t even close?
Same Claude. Same Gemini. Same prompts on paper. One team burns a fortune. The other doesn’t. For years I chalked that gap up to prompt skill or luck, or somebody leaving a debug loop running over a weekend. I was wrong about where it comes from. The gap doesn’t live in the model. It lives in the software wrapped around it.
I’ve spent the last couple of years building agent systems for a living, and I read AI infrastructure research the way some people read box scores. So a claim that the orchestration layer moves your cost more than swapping your priciest model for your cheapest one stops me cold. Let me show you why I now think it holds up.
The word most people skip past #
An agent request is not about one LLM call. Ask it to “reconcile these two contracts and draft the redline,” and that request unfolds into a dozen turns. System prompt, tool schemas, retrieval payloads, model reasoning, tool…