你公司用AI agent写代码？小心token费用悄悄翻倍。作者亲测案例，推荐Orq网关统一管理模型调用，省心省钱。
一位客户的token账单在过去几周内翻了三倍，原因是AI agent重构函数时需要执行读取文件、获取上下文、规划变更、编写代码、检查错误、更新测试、重试失败等十多个调用。每个调用都产生费用，agent越自主，费用越高。问题在于很难追踪谁在哪个模型上花了多少钱。解决方案是在agent和模型提供商之间部署一个网关，让所有请求先经过网关，从而获得可见性和控制力。Orq AI的API支持500多个模型和30多个提供商，可将廉价路由分配给便宜模型，昂贵模型留给复杂任务。
The token bill of one of my clients tripled over t…
The token bill of one of my clients tripled over the last couple of weeks.
There was nothing broken.
The better these agents get, the more tokens they are eating.
You ask your agent to refactor a function. It looks like a simple request, but behind the scenes, the agent is making a dozen calls:
• Reading files • Pulling relevant context • Planning the changes • Writing the code • Checking any errors • Updating the tests • Retrying anything that failed
Every call costs money. The more autonomous these agents get, the more we'll pay for them.
Multiply that across a few teams, and your bill will blow up.
Worst part of all of this:
It's really hard to know who is spending the money, on which models, and for which tasks.
Nobody sees where all the money is really going.
The solution:
You need a gateway between your agents and the model providers.
You want every request to pass through your gateway first. No exceptions.
A gateway buys you freedom, visibility, observability, flexibility, control, and a bunch of other benefits.
More importantly, it lets you see spending, route cheap work to cheap models, and keep the expensive models for the hard tasks.
I work with @orq_ai. They route to 500+ models across 30+ providers behind a single API.
Check this out: https://t.co/akGVJVV3zW
Thanks to the @orq_ai team for partnering with me on this post.