SmartBear BearQ adds Sources and Workflows for autonomous QA

SmartBear has added Sources and Workflows to BearQ, its agentic quality assurance system, to help teams connect what an application does with what it is supposed to do and the testing already in place. The additions address a practical problem for teams shipping AI-generated code: running more tests does not necessarily tell you whether the right things have been tested.

Sources brings requirements, bugs, and existing coverage into BearQ through connections to Atlassian Jira, SmartBear Reflect, and SmartBear Zephyr. Workflows coordinates the activities that follow, with teams choosing the triggers and the amount of autonomy allowed at each step. The announcement builds on SmartBear’s earlier work in GenAI-powered test automation in Jira, while extending the focus to how QA work is selected and managed.

Sources connects requirements with existing coverage

Sources gives BearQ context beyond the application under test. Jira supplies information about requirements and bugs, while Reflect and Zephyr help it recognize the tests that already exist. SmartBear says that combined view can help identify coverage gaps, avoid duplicate tests, and focus new testing where it is needed. The company said additional Sources were planned for the fourth quarter of 2026.

That context matters because a successful test run only answers the questions represented in the tests. A changed requirement or a known defect can call for a different set of checks. Connecting those records with coverage gives teams a more useful starting point for deciding what to test next. It also fits the broader move toward test management that brings planning, defects, and results together.

Alan Braun, head of product ecosystem at Atlassian, said Jira tasks are only part of what QA has to reconcile, alongside bug reports and existing manual and automated tests. His point is straightforward: the useful question is whether the testing reflects the work the team actually needs to validate.

SmartBear BearQ adds Sources and Workflows to coordinate QA

Workflows lets teams arrange sequences of QA activities and decide when they run. A schedule, a BearQ event, or an external system such as a continuous integration and delivery pipeline can trigger the work. Activities can include preparing environments, running targeted or regression tests, and updating connected systems. Teams can configure how much autonomy BearQ receives at each step.

For engineering teams, the distinction is between automating an individual test and coordinating the process around it. Environment preparation and follow-up updates still have to happen, even when test execution is automated. SmartBear has previously brought functional and load testing into a shared workflow. BearQ applies the coordination idea to a wider set of QA activities informed by requirements and coverage.

The additions also extend a product direction that includes AI-assisted API contract testing and test data generation. The practical value of any such automation depends on whether it produces useful evidence about the software, and whether the team can review the decisions that led to that evidence.

Human review sets the pace for autonomy

BearQ uses what SmartBear calls progressive autonomy. Teams can begin with people reviewing and approving its work, then automate more as confidence grows. Review steps and focus areas provide controls over how independently the system operates. SmartBear says trust was the biggest barrier to autonomous testing in its recent survey, a reminder that adoption depends on more than the ability to execute tests.

Bridges Smith, vice president of product management for AI at SmartBear, described the aim as connecting application behavior, team intent, and existing testing investments. In that approach, people define the guardrails and the level of control. It follows the company’s longer-standing emphasis on developer visibility across the software lifecycle.

For a team evaluating BearQ, the sensible starting point is a bounded QA process with clear review criteria. Check whether the connected requirements are current, whether existing coverage is represented accurately, and whether the workflow produces results people can understand and act on. More autonomy is useful when the underlying information and review process justify it. SmartBear’s announcement describes the capabilities, but it does not by itself establish how well they will perform against a particular application or test estate.