Rohan Paul：Agent swarm 将推动 AI 软件从按席位定价转向按量计费

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Rohan Paul 认为 agent swarm 会把大部分新增 token 消耗导向更便宜的模型，使 agent 的 token 总量超过前沿模型的收入。他解释道，在 swarm 中父 agent 负责规划，子 agent 处理搜索文件、运行测试等窄任务，这类任务易于验证，开发者可将其路由到能通过验证的最便宜模型。

正文 · 原文

Agent swarms send most new token volume to cheaper models, so agent token counts will outrun frontier-model revenue.

In a swarm, a parent agent plans while child agents handle narrow jobs like searching files or running tests. Narrow jobs are usually easy to check, so developers can route them to the cheapest model that passes.

And this massive token-explosion is also the major reason, flat-rate and per-seat pricing for AI software will give way to metering, because it relied on human prompting speed to cap usage.

A person sends only so many prompts a day, so vendors could charge per user and still predict inference bills.

But that equation will not hold with agent swarms working 24x7.