AI Workspace: Quality governance for an agentic SDLC

Agentic development moves fast, and when agents write both the requirements and the code, things can drift apart. Here's how to keep quality governance in place with Tricentis AI Workspace and GitHub. In this demo, Tricentis' Senior VP of Product Marketing Ryan Yackel walks through a workflow that starts with a user story in Jira and ends with a full code quality report. You'll see quality agents score the requirement, pause for human approval, generate test cases in qTest, and push the coding spec to GitHub so requirements, specs, and tests stay connected as code is built.

Key Highlights:

• Score requirements for quality before they kick off development
• Keep a human in the loop with an approval step before any test cases are created
• Full traceability, with test cases synced across Jira, GitHub, and qTest
• Confidence that what coding agents build matches the original requirement, tests, and spec
• A comprehensive report covering code quality, architecture, requirements, and test case documentation

See how AI Workspace keeps your agentic development pipeline traceable: https://bit.ly/4A3gc7X