Building an AI agent costs almost nothing to run.

Building an AI agent costs almost nothing to run. Building it right is the expensive part.

A prospect we spoke with recently put it plainly: their BD process was simple. Firm name, likely email format, a Hunter.io verification. Two tools, not seventeen. The question was whether automating that simple process was worth anything at all.

The answer is yes, but the value is not in the AI call. It is in the scaffolding around it.

An agent that calls Claude directly on every lookup will burn through token budget fast. An agent built with deterministic API calls for the structured steps, and inference only where it is actually needed, costs almost nothing at scale. Same output. One-tenth the cost.

Most teams building AI workflows skip this architecture work. They get a demo that looks right, ship it, and then hit costs or failures they did not expect. The rebuild starts six months later.

The right build: web calls and API requests handle what is predictable. The AI handles what is not. The two layers stay separate. That is the difference between a workflow that runs at 20,000 records and one that chokes at 500.

AI is cheap when you build it right. The build is where you are actually spending money.