Originally published on AI Tech Connect.
What you need to know There is a particular shock that arrives a few weeks after a team ships its first genuinely useful agent. The demo was cheap; production is not. Nobody added a bigger model, yet the per-task cost has quietly multiplied. The instinct is to blame the reasoning, and the instinct is usually wrong. In a tool-heavy loop, the expensive part is everything the model has to re-read before it is allowed to think — and two things get re-read on every single turn. Your tool definitions: the full schema for every tool the agent might call, whether it calls them or not. And your tool results: every row and payload a previous tool handed back, sitting in the conversation history. One grows with your integration surface, the other with the length of the task. During 2026 both major…
