---
title: "AI proposal drafts from your price sheet and scope rules"
description: "Build a proposal draft from approved prices and scope rules, with source versions, calculated totals, visible gaps, and a human decision before sending."
canonical: "https://scalewithsearch.com/articles/ai-proposal-drafts-price-sheet-scope"
---
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# How do you draft AI proposals from your own price sheet?

Give the drafting function your current price sheet, scope rules, approved terms, and the prospect's confirmed request. Require every proposed line item to identify its source. Keep arithmetic in a fixed calculation, and stop when the request falls outside approved rules.

A proposal function should prepare a commercial decision for review. It should not decide which exceptions your business can afford or promise work that nobody has scoped.

The existing [proposal memory guide](/articles/ai-memory-for-proposal-writing) explains how to organize reference material. This article follows the next step: turning those records into a bounded drafting function with checks and an owner.

## Make the price sheet usable as a source

Give each service a stable identifier, description, unit, price reference, and effective date. Name the person responsible for maintaining the sheet.

State which currency applies and whether the proposal needs additional charges under your approved policy. Do not leave the drafting function to infer commercial treatment from old documents.

Keep replaced price sheets available for historical review, but mark which version applies to new proposals. Define what happens when a prospect has an existing approved offer. A new price sheet should not silently rewrite that offer.

Before drafting, the function should identify the version selected and why it applies. If two sheets both appear current, hold the proposal for the owner. A plausible choice is insufficient for a commercial commitment.

## Write scope rules beside the prices

For each service, state the included work, exclusions, required inputs, and conditions that require a custom decision. A service label alone does not define the work.

Imagine a fictional design firm offering a defined document package. Its approved scope might specify document types, the number of revision rounds, and customer-supplied material. A request for extra formats should appear as an unresolved scope question until priced and approved.

Keep delivery conditions explicit. If timing depends on receiving complete source material, carry that condition into the draft. Do not let the summary promise an unconditional delivery date.

Use rules that a reviewer can test. Replace broad instructions such as keep the proposal reasonable with specific triggers for owner review.

## Confirm the request before mapping it

Create a request record containing the prospect's stated requirements, source references, open questions, and approved assumptions. Separate the customer's request from the firm's interpretation.

If a note says the prospect might need a second deliverable, mark it unresolved. Do not turn tentative language into an agreed requirement. Ask the responsible person to confirm it.

The function should map each confirmed requirement to an approved service identifier. Unmatched requirements belong in a visible exceptions section. Exclusions should remain visible when they affect the customer's stated goal.

Use [the brief versus prompt guide](/articles/brief-vs-prompt) to write the assignment. Name the required sections, approved source locations, reviewer, and stopping point before the function prepares prose.

## Assemble the commercial schedule first

Have the function prepare a structured schedule before writing the proposal narrative. Each row should show the requirement, service identifier, quantity, unit, source version, and unresolved condition.

Use a deterministic calculator for permitted quantities and totals. Pass its verified output into the drafting step. Require the proposal to preserve those amounts and units exactly.

Do not ask the model to invent a discount or fill an empty rate. If the price sheet has no matching service, return a blocked line item. The owner can issue a specific decision that becomes a source for the next draft.

For the fictional document package, an extra format should stay unpriced until that decision exists. The remaining known work may still be assembled for review, clearly labeled as an incomplete proposal.

## Show where each commitment came from

Prepare an internal evidence table alongside the customer document. Link every material commitment to its governing record.

| Commitment | Governing source | Required check |
|---|---|---|
| Work included | Approved scope rule | Match the requested service |
| Quantity and amount | Current price sheet and calculation | Verify units and totals |
| Timing | Approved delivery conditions | Preserve prerequisites |
| Revision allowance | Current terms | Copy the applicable condition |
| Claimed experience | Approved evidence record | Omit unsupported claims |

The table is for review. Keep internal paths and unresolved notes out of the outgoing document. Give the reviewer access to both versions so the polished proposal remains traceable.

If a material claim lacks an approved source, remove it or hold it for a decision. Do not use an old proposal as proof that a claim remains approved.

## Draft around the verified schedule

Ask the model to explain the proposed work in plain language using the assembled schedule. Keep the customer problem, deliverables, exclusions, dependencies, and acceptance conditions distinct.

Require the summary to agree with the detail. If the scope excludes content creation, the opening should not describe a complete content service. If timing remains unresolved, do not add a confident date in the closing.

Preserve the approved commercial language where exact wording matters. Let the owner decide which sections may be rewritten and which must be inserted without alteration.

Do not hide missing decisions with persuasive language. A clear gap gives the reviewer a task. A smooth sentence that conceals the gap leaves the proposal unready for release.

## Test the commercial boundaries

Write acceptance cases from the actual rules. Include a standard request, missing quantity, replaced price sheet, unpriced addition, conflicting scope note, and an unsupported experience claim.

For each case, state the expected line items and expected stopping point. A request outside the rules should remain blocked even if the model can write an attractive proposal for it.

NIST's Measure guidance recommends testing whether an AI system is fit for its purpose and defining acceptable performance limits. Use that principle to evaluate commercial correctness. [NIST AI RMF Playbook: Measure, checked 2026.10.26](https://airc.nist.gov/airmf-resources/playbook/measure/)

Check the output against the verified schedule, rather than asking whether it sounds convincing. Keep the cases when changing the model or updating the workflow.

## Put a person before the commitment

The reviewer should check the request, schedule, totals, exclusions, assumptions, terms, and destination. Record approval against the exact document version.

If a colleague changes a line item after approval, return the document to review. Use the same rule for new attachments or a changed recipient. A previous decision should not authorize a different proposal.

The [agent approval matrix](/articles/ai-agent-approval-matrix) covers this action boundary. A drafting-only function should stop at an approved file and leave sending to the existing process.

When sending is included in scope, record the action result separately from draft acceptance. Preserve uncertainty when the service cannot confirm the action. Have someone verify before retrying.

## Keep the function's operating record

Each run should record the request identifier, source versions, calculation result, draft location, reviewer state, selected model, and cost. Label estimates instead of presenting them as settled charges.

Give the function a monthly AI spend limit, alert recipient, and retry boundary. Define whether other service charges sit inside or outside that limit. Keep the definition in the runbook.

When the owner approves a one-time commercial exception, attach it to that proposal. Update the standard price sheet only through a separate accepted rule change.

This follows the [AI systems method](/ai-systems): direct the job, prepare from an owned record, and check the result. Keep the record, function, tests, and training in the business's control.

## Start with an ordinary proposal

Choose a recent proposal with clear scope and current commercial rules. Remove identifying customer material before using it as a training example for the design discussion.

Write down which fields should come from records, which require a calculation, and which need your decision. Use that map to define the function's first acceptance check.

For a scoped proposal function, [send your brief](/work#send-your-brief). Include the proposed output, available source records, and the exceptions your team must continue to approve.


## Related: Owned Memory

- [Build a proposal memory file so AI drafts proposals in your format](/articles/ai-memory-for-proposal-writing)
- [A Brief Is Not a Prompt](/articles/brief-vs-prompt)
- [An AI Agent Approval Matrix for Small Teams](/articles/ai-agent-approval-matrix)

----

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```
