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It may come from using less AI, more intelligently.

That distinction is becoming increasingly important as companies move from AI experimentation to production. The goal is not to make every step of a workflow dependent on a model. The goal is to 设计 系统 that use AI where it creates the most value, and deterministic software everywhere else.

Our thesis is simple:

Use AI aggressively to build 系统, automation, and logic. Once the 系统 is mature, let deterministic software handle repetitive work 24/7. Bring AI back only when genuine reasoning is required.

We saw this shift firsthand. Our usage dropped from approximately 32 billion 令牌 during development to around 3 billion 令牌 per month after the core 系统 became operational.

That is more than an efficiency gain. It changes the economics of AI.

更少算力.
更低 operating costs.
Greater scalability.
Stronger margins.
More sustainable infrastructure.

The principle is straightforward:

Use AI to build the machine. 然后 let the machine do the work.

Companies that learn to scale intelligence without scaling compute at the same rate could create a significant competitive advantage. Over time, that advantage could translate into billions of dollars in future 企业 and investment value.

The future of AI will not be defined solely by bigger models or more 令牌.

It will be defined by better architecture, and by knowing when not to use AI at all.