Frameworks, core principles and top case studies for SaaS pricing, learnt and refined over 28+ years of SaaS-monetization experience.
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Early in the life of every AI company, someone makes a small choice that does not feel important at the time. An engineer building the first version of the product has to pick which foundation model will run underneath it. The choice goes into a technical document and gets treated like plumbing.
But it is not really plumbing. It is one of the most expensive choices the company will make. And often, the people who will care about it most are not part of the decision.
Here is why it matters. Every agentic product runs on top of a foundation model. Every time that model does something (reads a document, writes a paragraph, checks its own work), it costs a little money. Usually just pennies. But a few pennies, repeated millions of times a year, add up fast. They become one of the biggest costs the company has. And the size of that cost depends mostly on which model the engineer picked.
The main point is simple. The exact same task, giving the same kind of answer, can cost about a penny on one model and about forty-one cents on another. Multiply that gap across a real company's volume and it turns into a big number: a difference of more than $1.5 million a year, on a single workflow. Not the whole product. Just one workflow.
This is where two groups that rarely talk to each other start to overlap. The engineer picking a model is really making a spending decision worth millions. The finance leader who builds the cost forecast is depending on a technical choice they may have never seen. The space between these two people is one of the most overlooked parts of building an agentic AI company. This chapter is about bringing them together. It is a gap we spend a lot of time on at Monetizely. We will keep it plain, walk through real numbers, and skip the heavy formulas.
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