Systems | Development | Analytics | API | Testing

SmartBear BearQ, an agentic QA system, has won a 2026 CRN Tech Innovator Award. CRN, a brand of The Channel Company, named BearQ a winner in the Application Development and DevOps category, calling it out among the most innovative technologies shaping the IT channel this year. AI has changed how fast software gets built, but for many organizations, testing hasn’t kept pace.

You're preparing for a release readiness meeting. The Test Plan contains hundreds of Tests. Development continued until late yesterday, several Defects were resolved overnight, and only a few hours remain before stakeholders need an update. There is enough time to execute part of the Test suite, but not all of it. The question isn't whether testing should continue. It's which Tests should be executed first. Every release forces QA teams to make prioritization decisions.

Flaky tests erode trust in the pipeline one rerun at a time. Learn why tests flake, how to tell a flaky test from a real regression, and how to fix the root cause instead of just hitting rerun.

July was an enterprise month. Most of what shipped answers the questions that come up once a test team grows past a handful of people: how do we hand documentation to an auditor, where is the evidence for this step, who changed this result and when, and how do we run the same suite against a feature branch without rebuilding the integration every time.

I made an API endpoint 13 times faster. Then I realized my first verification only checked the status, headers, and response schema. I had not checked the totals. I had made the bug faster. That is the problem with giving an AI coding agent one kind of evidence. A CPU profile can show where the application is slow, but not whether an optimization preserves behavior. A traffic replay can prove that behavior stayed stable, but not explain why the code burns CPU.

Key takeaway: When code moves at AI speed and testing stays manual, the widening gap between a code change and its test coverage becomes your biggest quality risk. SmartBear ReadyAPI MCP reduces that gap by letting you generate, run, and heal API tests in plain language, right inside the Claude, Copilot, or Cursor session that wrote the code.

Shift left vs shift right testing isn’t really a debate. Teams that treat it as one end up with gaps that neither approach covers alone. Shift left catches defects before they reach production. Shift right learns from what happens after they do. The teams shipping most reliably in 2026 don’t choose between them. They run both and build a feedback loop where each approach makes the other more effective.