Engineering and architecture
Design review comments: what AI learns from QA/QC on drawings
By SourceX Editorial · Updated
Short answer
Design review comments teach AI how experienced reviewers find problems on drawings and how designers resolve them. Each markup, comment, response and backcheck becomes an example for detecting gaps, classifying severity and drafting fixes. The resolution matters most: a comment without a recorded outcome teaches far less than one linked to the revised sheet.
Key takeaways
- A markup with its written comment teaches detection; the designer's response and backcheck teach resolution.
- Comments with recorded dispositions, including rejected ones, help AI separate real issues from false alarms.
- Review logs cannot teach judgment about site conditions, verbal decisions or client preferences that were never written down.
- Firm-authored comments are usually the firm's to use, while agency and third-party peer review comments belong to their authors.
What does AI learn from design review comments?#
AI learns from design review comments the pattern of what experienced reviewers catch on drawings and how those catches get resolved. A reviewer clouds a beam that does not match the framing plan, writes why, the designer revises the sheet, and the reviewer closes the comment. Each step is an example a model can study.
AI tools that check drawings generally need examples like these, whether to train, tune or test them. The more a firm's comments record location, reason, response and outcome, the more they resemble the examples those tools need, whether the firm uses them internally or considers licensing them.
Checking of engineering calculations works the same way. A checker's note that a load combination is missing, the designer's corrected calculation and the checker's sign-off form the same finding-to-fix chain, recorded in calculation packages rather than on sheets.
Review artifact to AI task#
Each review artifact teaches a different AI task. The table maps them, with the ownership check that applies to each.
| Review artifact | What it captures | AI task it can teach | Client-ownership check |
|---|---|---|---|
| Markup on a sheet | Where the issue sits on the drawing | Locating likely problem areas on a sheet | Sits on a client deliverable; check the ownership clause |
| Written comment | The reviewer's finding in words | Describing issues in clear technical language | Usually firm-authored |
| Category or discipline tag | Coordination, code, constructability or drafting | Classifying issues by type | Firm-authored |
| Severity or priority | Must fix before issue versus preference | Ranking findings by risk | Firm-authored |
| Designer response | Accept, reject or clarify, with reasoning | Drafting responses and explaining fixes | Firm-authored; may quote client requirements |
| Backcheck and closure | Whether the fix was verified | Confirming that a revision resolved the issue | Firm-authored |
| Revision delta | What changed between sheet versions | Linking comments to concrete drawing changes | Same as the drawing set |
| Agency or outside peer review letter | An external reviewer's findings | The same tasks from an outside view | Belongs to its author; usually excluded |
- 01Your work records
- 02Personal details removed
- 03You approve the release
- 04Licensed to AI developers
Why the resolution teaches more than the comment#
The resolution teaches more than the comment because it shows whether the finding was right. A comment that was accepted and fixed is a confirmed issue. A comment that was rejected with a reason is just as useful: it shows a model what a false alarm looks like and why an experienced designer pushed back.
Comments left open forever, or closed without a note, teach very little. They cannot tell a model whether the reviewer was right, and they are common in many firms' review histories. A required disposition on every comment, even a single word, changes that from the next project onward.
Severity tags work the same way. A comment marked critical and then fixed before issue tells a different story from one marked minor and deferred, and both are useful only if the tag and the outcome are recorded together.
What a review log cannot teach#
A review log cannot teach what never made it into writing. Firms should be realistic about these limits, both when buying AI review tools and when describing their own records to anyone else.
This is also why AI review output still needs a qualified reviewer. The tools learn patterns from written records; the parts of review that live in people's heads stay with them.
- Site knowledge: conditions the reviewer knew from a visit but never noted.
- Verbal decisions: issues settled in a hallway or a coordination meeting with no written closure.
- Client preferences and budget trade-offs that shaped a design choice.
- Professional responsibility: the reviewer's judgment and the engineer of record's seal.
- Context from other projects that the reviewer drew on without saying so.
Where markup histories live, and what survives#
Markup histories live in several places, and each keeps a different share of the chain from finding to fix.
A quick test shows which sources are usable: pick a closed project and try to trace a handful of comments from markup to revised sheet. If most trace cleanly, the history is worth more attention; if not, fix the capture process before investing in tools.
| Source | What usually survives | Common gap |
|---|---|---|
| Bluebeam Studio Sessions | Markups with author, date, status and replies | Sessions never closed or exported |
| Flattened PDF review sets | Visual markups on the sheet | Comments are image only, with no status or response |
| QA checklists in spreadsheets | Checklist items and sign-offs | Not linked to specific sheets or fixes |
| Model review issues in Autodesk tools | Issue, model location, assignee and status | Closed without explanation |
| Comment-response matrices | Comment, response and disposition in one table | Kept as attachments and hard to find |
How to make future review comments more useful#
Firms that want their review history to be useful later can change a few habits now, at little cost to reviewers. The changes help internal QA reporting as much as any AI use.
- Record every review in one system rather than a mix of PDFs, spreadsheets and email.
- Give every comment a category and a severity from a short fixed list.
- Require a designer response and a disposition before a comment can close.
- Link each backcheck to the revised sheet or revision number.
- Use role labels in comment text instead of personal names where practical.
Illustrative: a structural firm uses its review history as an answer key#
Illustrative: a fictional structural engineering firm is evaluating an AI drawing-check tool. Instead of relying on the vendor's demo, a principal pulls sheet sets from closed private projects, as they stood before internal QA review, and sets the firm's own Bluebeam review comments from those reviews aside as an answer key.
Counsel first confirms that the client agreements on those projects allow the test, and the vendor agrees in writing not to train on the uploaded sets. The tool then runs on the pre-review sheets, and its flags are compared with what the firm's reviewers actually found. It catches many drafting and cross-reference problems, such as section callouts pointing to the wrong sheet, but misses findings that depended on load path judgment or on conditions a reviewer knew from a site visit.
The comparison only worked for reviews whose comments carried a category and a recorded disposition; older reviews with clouds and initials alone could not be scored. The firm adopts the tool as a first-pass drafting check, keeps engineering review with senior staff, and makes category and disposition required fields in every new review session.
How SourceX evaluates review comment records#
SourceX evaluates review comment records with the SourceX Enterprise Data Value Framework. Linked comment-to-resolution chains rate well on human-generated signal, domain expertise and data cleanliness; reviewer names and client identifiers add privacy burden; rights depend on each project's contract.
Packages move through the SourceX five-step transaction, Supply, Rights, Preparation, Approval and Delivery, and the firm approves the scope at each step. The first fit check runs on metadata such as review systems, years of history and how comments are recorded, so nothing is shared at that point.
Frequently asked questions
Do reviewer and designer names need to be removed?
Usually yes. Names are rarely needed to learn from a comment, and removing them protects staff and reduces privacy burden. Replace names with stable role labels, such as reviewer or designer, so the comment-and-response structure stays intact.
Are outside peer review comments ours to use?
Usually not. Comments written by an outside peer reviewer, a client's reviewer or a permitting agency belong to their authors and may also fall under the client's contract. Your firm's written responses to them may be yours, but the pair is normally excluded unless the rights are clear.
Will licensing review comments expose our mistakes?
Review comments record errors caught before documents were issued, which is evidence of a working quality process. Licensed packages are de-identified, and the firm approves the scope. Some firms still exclude projects that later became disputes, which is a sensible precaution.
How many years of review history are useful?
There is no fixed threshold. Consistency matters more than length: a few years of linked comments in one system can be more useful than a long history of flattened PDFs. Recency also matters, because current codes and drawing practices make records more relevant.
Do clash detection reports count as design review records?
Partly. An automated clash report on its own is reproducible: anyone can rerun the same models through the same software. The useful part is the human triage around it, such as which clashes were real, which discipline moved, and how the coordination meeting resolved each one. Keep the triage notes and resolutions linked to the clash IDs; the raw report adds little.
Related resources
See if your company qualifies
A short company assessment. No data uploads are needed.