Product Feature

AI Issue Drafting for Design QA

AI automatically converts visual differences into implementation-ready Jira issues with exact CSS values, selectors, and fix context.

From visual diff to structured issue

Writing good bug reports from design feedback is tedious. You need to describe the element, explain what's wrong, provide the expected values, and add visual context — for every single discrepancy. OverlayQA's AI drafting feature automates this entire process. When you flag a visual difference, AI analyzes the overlay comparison and generates a complete, structured issue ready to send to Jira or Linear.

Each AI-drafted issue includes the affected element's CSS selector, the current computed values, the expected values from the design spec, a screenshot showing the discrepancy, and a clear description of what needs to change. This means developers receive actionable context instead of vague feedback — reducing the time from "spotted a problem" to "shipped a fix" from hours to minutes.

AI drafts can be reviewed and edited before sending, giving designers control over issue wording and priority. Issues are sent directly to Jira or Linear with the project, labels, and assignee you choose — so they arrive in the right queue, ready for a developer to pick up without any additional triage.

Why AI issue drafting matters

• Saves time for product designers — Instead of spending minutes writing each bug report, every product designer can flag an issue and let AI handle the formatting in seconds.
• Eliminates ambiguity — AI-drafted issues include exact CSS selectors, computed values, and expected values from the design spec, so development teams know precisely what to fix.
• Improves the QA process — Structured, consistent issue reports mean every team member provides the same level of detail regardless of their technical background.
• Protects user experience — Faster issue resolution means UI issues get fixed before they reach the final product and affect real users.