Systems | Development | Analytics | API | Testing

Worried an AI teammate could rack up a surprise bill? In this video, you’ll learn how SmartBear BearQ gives you real governance over AI testing spent – built with pre-baked monthly limits, so your team always knows what to expect before a single agent gets to work.

In this AI transformation roundtable, Nate Custer, Principal Technologist at TTC Global, shares how to measure productivity on an agentic quality engineering team. Drawing on a mainframe regression story, he explains why saving time only matters if you use it to close coverage gaps. He also argues that QA teams should track how often they have to fix AI-generated code, and why that measurement might mean more than speed or headcount.

Someone opens a spreadsheet, pastes data from two systems side by side, and compares row by row, hoping to catch every error before it reaches production. In conversations with enterprises, nine out of ten still test data this way. In this short video, Adnan Ćosić, Senior Product Marketing Manager at Tricentis, explains why "stare and compare" and custom scripts can't keep up with modern data landscapes, and how Tricentis Data Integrity automates data testing end to end so you can trust every decision.

Requirements change in Jira all the time, and QE teams have to catch every edit to update their test cases. Connect Tricentis AI Workspace agents to Jira and qTest, so any requirement change generates and updates test cases for you with the right context. In this walkthrough, Senior VP of Product Marketing Ryan Yackel, will show you how a Jira edit triggers an agentic workflow, pushes test requirements into qTest, and creates test cases with a human-in-the-loop checkpoint.

Learn how to test your application's fallback mechanisms by intentionally injecting chaos and simulated dependency failures into recorded API traffic. Easily configure scoped rules to inject status code errors or delays during mock runs to verify your app handles failure gracefully. Learn more: speedscale.com.

Learn how AI handles different types of testing, from simple unit tests to complex end-to-end setups. Discover where AI succeeds in writing test code and where human strategy is still needed. Learn more: speedscale.com.