Enterprise AI bills keep rising because task chains are expanding faster than token prices fall
rohanpaul_ai · x · 2026-07-23
The thread argues that enterprise AI costs are rising because the problem is architecture, not token price alone.
A single request now fans out into retrieval, tool calls, reasoning loops, and multi-step execution, so tokens per task are growing faster than token prices are falling. The post says routing and better context management beat simple model swapping because they are engineering fixes, not just cheaper inference.
It also highlights a Glean benchmark claiming roughly 30% fewer tokens and 2.5× more preferred answers than other MCP tools, with the advantage increasing on larger tasks.
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