That's a straw man.

You don't know how often we use LLM calls in our workflow automation, what models we are using, what our margins are or what a high cost is to my organization.

That aside, business processes solve for problems like this, and the business does a cost benefit analysis.

We monitor costs via LiteLLM, Langfuse and have budgets on our providers.

Similar architecture to the Open Source LLMOps Stack https://oss-llmops-stack.com/

Also, your last note is hilarious to me. "I don't want all the free stuff because the company might charge me more for it in the future."

Our design is decoupled, we do comparisons across models, and the costs are currently laughable anyway. The most expensive process is data loading, but good data lifecycles help with containing costs.

Inference is cheap and LiteLLM supports caching.

Also for many tasks you can run local models.