# Use a source-to-release checklist for every builder AI draft

A builder AI release checklist traces each draft to its project, its current source files, its audience and its authorized approver. Before issue, check factual claims, unresolved fields, implied commitments, private data and recipients. Save the approved version with the reviewer's name and the source references, so the project record shows what was released and who cleared it.

## What does a reviewer need before opening the draft?

The assignment, the approved source set, the audience and the action that follows approval. Without those four, the reviewer cannot tell whether the agent answered the right question or reached past its authority.

Pin down the project and the document status. A polished draft built on a superseded plan set is wrong. A meeting recap written for internal coordination may be unacceptable as a buyer message. A website paragraph can be true for one house and false as a company-wide practice.

### Who does the review?

The person who understands the consequence and has authority over the output. A project lead reviews field facts. A selections owner confirms status. A warranty owner checks routing. A publishing owner approves public content after the operating facts are cleared. One reviewer does not have to pretend to hold every discipline.

| Review layer | Question | Evidence |
| --- | --- | --- |
| Identity | Right project, buyer, parcel or community? | Controlled project record |
| Version | Did the agent use current sources? | Revision labels and approved file list |
| Facts | Does every statement match the source and the field status? | Plans, notes, logs and direct confirmation |
| Authority | Does the draft make a decision or a commitment? | Operating roles and governing documents |
| Privacy | Is every detail necessary for this audience? | Approved data boundary and permissions |
| Issue | Who may send, publish or enter this record? | Named final approver |

## How do you check facts instead of proofreading?

Read the source beside the draft. Trace each project-specific statement to a sheet, a spec section, an approved selection, a field note, a public source or a decision record. If the draft says an item is complete, confirm what "complete" means in the owning system and that the status is current.

Watch the small words that change obligations: approved, included, guaranteed, scheduled, complete, covered. The agent picks one because it reads well. The source may support only proposed, requested, targeted, observed or under review.

### What happens when the source is missing?

Mark the statement unresolved and send it back to the owner. Do not repair it from memory unless you are the person authorized to supply the fact and you record it in the proper source. The draft shows its gaps. It does not hide them.

The boundary guide, [what AI should not do for builders](/articles/ai-for-builders/what-ai-should-not-do-for-builders/), lists the decisions that better wording cannot rescue.

## Which checklist does every AI output pass?

Attach it to the draft as a release record. Mark each check passed, returned or unresolved, with an evidence reference and the reviewer. If the project or the source version is wrong, return the draft and stop. A completed checklist identifies the exact version approved for issue.

1. **Confirm the assignment.** Requested format, audience and permitted action.

2. **Confirm identity.** Project, parcel, plan, buyer, trade, community and document labels.

3. **Confirm source status.** Every source current, approved and right for the task.

4. **Trace factual statements.** Quantities where supplied, dates, sheet references, product labels, selection states and field milestones.

5. **Find invented bridges.** Remove any fact, reason or conclusion the source never gave.

6. **Check commitments.** Language about cost, timing, scope, approval, completion, payment and warranty.

7. **Check privacy and permission.** Strip unnecessary personal details. Confirm media, recordings and quoted material are cleared.

8. **Check recipients and links.** Addresses, attachments, project links and audience-specific language.

9. **Record approval.** Who approved, when and which version became final.

Sensitive workflows get a discipline-specific list on top. A spec sheet review needs plan coordination and allowance checks. A buyer update needs current field status and commitment review. A content page needs claim support, publishing permission, current links and correct [schema markup](/glossary/schema-markup/).

## How does review change by workflow?

One generic checklist misses job-specific risk. Meeting notes need speaker meaning, decision status and owner confirmation. Follow-up drafts need recipient, conversation context and next-step review. Warranty intake needs project identity, submitted evidence and a human coverage decision.

Specification work needs a stricter version check, because a clean draft carries an old detail straight into purchasing or field communication. Use the source method in [AI specification-sheet drafting](/articles/ai-for-builders/ai-spec-sheet-drafting/). Public content needs a second pass for permissions and unsupported marketing claims, as shown in [AI content production with review](/articles/ai-for-builders/ai-content-production-with-review/).

### When does a draft need two reviewers?

When it crosses responsibilities. The project lead clears field facts while an authorized office role clears the external message. The designer verifies a selection description while the project owner approves its use in a project record. The workflow states which approval is final.

## How do you keep review from becoming a rubber stamp?

Never present the draft as finished. Keep source links and unresolved markers visible. Rotate known failure cases through testing: an old plan, a conflicting selection status, a missing attachment, a wrong project label, an unsupported completion claim. Reviewers prove they catch them.

Track corrections by category, not as made-up performance numbers. Repeated version errors mean a source-control problem. Repeated commitment language means the prompt and the checklist need harder boundaries. If reviewers approve without opening the source, pause the workflow.

### Can another agent do the first check?

Yes. At AgAI Labs, our Claude and Codex AI agents compare drafts with source files, flag missing fields, inspect links and search for unsupported language. People still verify field reality, apply judgment and authorize use. Machine checking prepares the human review. It does not replace it.

## How are approval and corrections recorded?

Save the approved output in the system that owns the work, not only in the agent's conversation. Mark the final version, the reviewer and the source date. Keep working drafts from looking like issued documents. When a correction changes a project record, follow your normal revision and distribution path.

The [AI operations stage](/process/ai-operations/) defines the reviewer, the failure path and the manual fallback for one workflow. The [AI guide for home builders](/guides/ai-for-home-builders/) explains the control model. The [AI for builders library](/articles/ai-for-builders/) applies it task by task.

### Which release check questions come up most?

### Does every AI draft need human review?

Every AI output that touches a project record, a buyer, a trade, a payment, a public claim or an operating decision gets reviewed by the responsible person.

### Is reading the draft carefully enough?

No. Reading for tone is not review. The reviewer compares the draft with current sources and field facts, then confirms authority, audience and downstream action.

### What if the reviewer made extensive corrections?

Record the error patterns, fix the source set or the instructions and retest. Recurring problems do not get buried in manual edits.

### Can approval happen inside email?

Yes, if your approved method keeps the final AI output, the reviewer and the approval status together in a recoverable project record.