Smartbear Blog
SmartBear at Atlassian Team ’26: AI, quality intelligence, and the System of Work
For everyone in QA inside the Atlassian ecosystem, the last few months have made one shift obvious. AI is changing how software...
Alisha Siddhartha
May 26, 2026
Editor's Pick
How to scale AI test automation without losing test visibility
The challenge: Software integrity at AI speed According to SmartBear’s Closing the AI Software Quality Gap study, 93% of teams are already using AI to generate code. The same study found that 60% expect AI to produce nearly half of all code within the next year. This shift in development velocity is already impacting software testing and quality. Most teams say application quality is suffering, and 60% have experienced quality issues.
May 20
The API testing gap: How AI-accelerated development challenges software quality
The uncomfortable truth about AI and software quality While AI accelerates development velocity by a factor of ten, a critical consequence remains: testing hasn’t kept pace. According to SmartBear research, 70% of software professionals report that their application quality has already degraded due to AI-accelerated development. Even more concerning, 60% have experienced quality issues in the past year as development velocity outstrips testing capacity. This isn’t a future problem we need to prepare for – it’s a present gap that’s accumulating technical and business debt.
May 18
How Tata Is Advancing AI-Driven API Innovation with SmartBear Swagger
At SmartBear, we’re seeing a shift in how teams design, build, and evolve APIs – faster, more intelligent, and increasingly powered by AI. Today, we’re proud to recognize A. Singh, senior developer from Tata Consultancy Services, as a winner of the AI Builders Award for Swagger. His work shows how teams can move beyond experimentation.
May 13
SmartBear Receives Atlassian Partner of the Year 2026: AI Innovator
Tackling the release readiness question Most teams working inside the Atlassian ecosystem know the routine: check test coverage in Zephyr, cross-reference requirements in Jira, pull execution reports from a separate layer, and try to build a coherent picture of where things stand before a release. Evaluating release readiness, when your data is siloed, can feel challenging.
May 05
Reflect vs. Playwright: Choosing the right test automation approach
Organizations with AI mandates face a fundamental choice in test automation: adopt AI-native testing tools like SmartBear Reflect or use AI coding tools to accelerate adoption of code-based frameworks like Playwright. Reflect is a cloud-based, no-code test automation platform built around accessibility and speed. Playwright is Microsoft’s open-source, code-based testing framework built for flexibility and engineering control.