T-Tip #2 Let an agent review the tests, not just run them | AI Workspace
AI-generated test cases are fast but imperfect. The typical response is to have a human review them: slow, manual, and easy to skip under deadline pressure.
A better pattern is to build a validation workflow in AI Workspace that acts as a structured reviewer before anything reaches execution.
An agent step checks generated test cases against criteria you define, such as coverage completeness, naming conventions, and presence of expected assertions. Anything that fails gets routed back: a comment on the Jira ticket, a flagged test in qTest, or a hold at an approval step where a reviewer signs off before the workflow continues. It's the QA equivalent of a linter, triggered on a schedule or by webhook as part of the workflow.
You configure it in AI Workspace using a template or the Workflow Assistant. Describe the review you want in plain language, connect Jira or qTest through an API toolset or MCP connector, and add the approval gate. No code required.
