When an AI agent is asked to prepare a quote, the task does not resolve into a single reply: it calls for a sequence of verified steps, each one a precondition for the next, to arrive at a result you can rely on.
Gathering and checking the initial data
The first step is establishing what is actually needed: product, dimensions, customer, any special requirements. A well-designed agent does not proceed on incomplete or ambiguous data but asks for clarification before calculating anything — an error here would propagate through every later step.
Working out the requirement before the price
Before proposing a price, the agent works out what the product physically needs — materials, waste, processing hours — using a deterministic calculation engine, not a generic inference. Only with those verified numbers can it move on.
Proposing a margin, and confirming before saving
With the costs calculated, the agent proposes a margin consistent with the customer's history or the company's parameters, shows the result for a human check, and only saves the quote after explicit confirmation. That final confirmation is what keeps the commercial decision in the person's hands rather than the system's.