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By Alisha Siddhartha
For everyone in QA inside the Atlassian ecosystem, the last few months have made one shift obvious. AI is changing how software gets built, and the quality function must change with it.
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By Klaudia Makiej
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 in the past year because development is moving faster than testing can keep up.
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By Vyshnavi Dabbir
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.
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By Prashant Mohan
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.
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By Temil Sanchez
Teams using TestComplete face a common problem: one small test change can produce a wide set of modified files, and not all of them deserve the same level of scrutiny. The fix is not to review everything equally – it is to classify TestComplete artifacts by risk, then standardize how your team reviews, stages, and merges them. This article outlines this process and offers best practices for using Git effectively with TestComplete projects.
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By Maggie Bean
Testing software at scale has always been a race against change. Then, AI-coding turned what was once a challenge into a crisis: rapid development cycles accelerated by AI have made it impossible to maintain comprehensive test coverage and catch issues before they impact users. In SmartBear’s Closing the AI Software Quality Gap Study, 60% of software experts told us they experienced quality issues as development outpaces testing.
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By Jeff Foley
AI-accelerated development has fundamentally changed how software is built, and across the industry, its impact on quality is already measurable. In SmartBear’s Closing the AI software quality gap study, we found nearly 70% of software professionals report application quality is declining as AI speeds up code generation, with development velocity increasingly outpacing teams’ ability to test effectively.
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By Vyshnavi Dabbir
In 2026, APIs have moved far beyond simple integration points. They’re now strategic business assets powering AI transformation, microservices architectures, and multi-cloud ecosystems. But a critical challenge threatens to undermine digital initiatives: the fragmentation of API testing. As organizations rush to deliver faster, they’re discovering that their testing infrastructure – cobbled together from disparate tools and disconnected processes – has become the bottleneck.
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By Vineeta Puranik
There’s a tension building inside most engineering organizations right now, and not many people are talking about it openly. AI has given development teams an extraordinary gift: the ability to build faster than ever before. Features that once took days can be prototyped in hours. Applications that required large teams can now be scaffolded by a handful of engineers with the right tools. By almost every measure of development velocity, we are living through a remarkable moment.
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By Temil Sanchez
Digital transformation rarely happens in a clean, technical environment. Most organizations aren’t starting from a blank slate – you’re operating across a mix of legacy desktop applications, internal web systems, custom-built interfaces, and business-critical workflows that must remain stable while modernization continues around them. The central challenge is whether that automation can remain reliable as underlying technologies evolve.
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By SmartBear
We've been getting a lot of questions about how Rovo works with Zephyr, so Matt Bonner gives a quick look at a few of the capabilities teams are finding most valuable: Test case generation Test coverage insights Release Risk Analyzer.
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By SmartBear
What did Atlassian Team ’26 reveal about the future of software quality and AI-powered delivery? In this recap from the event floor inside the Anaheim Convention Center, SmartBear shares key themes from the event, including Atlassian Rovo, the Teamwork Graph, AI-driven workflows, and how QA teams are adapting to faster, AI-assisted software delivery inside Jira. See quick highlights from the event floor, SmartBear’s latest Zephyr innovations, and how conversational AI and quality intelligence are becoming part of the modern software delivery workflow.
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By SmartBear
SmartBear ReadyAPI's AI-powered test generation instantly builds functional test cases from a simple natural language prompt. Stop writing API tests manually and let AI do the heavy lifting. In this demo, we show how you can take an OpenAPI spec and generate tests complete with assertions, authentication headers, test data, and request chaining. Whether you test complex microservices or APIs with hundreds of endpoints, ReadyAPI helps QA teams move faster without sacrificing quality or control.
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By SmartBear
AI is changing how testing gets done. As automation grows, so does the complexity of tracking what’s been tested, what passed, and what’s ready to release. See how SmartBear Reflect and QMetry work together to scale AI-powered test automation without losing visibility or control. Reflect makes it easy to create and run automated tests using plain language, while QMetry brings structure to that speed, connecting tests, results, and reporting into a single system of record.
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By SmartBear
SmartBear’s study Closing the AI software quality gap found that 60% of teams have already experienced quality issues tied to AI-generated code, evidence of how increased abstraction is changing how software gets built. When development shifts from well-defined requirements to prompts and generated outputs, it becomes much harder to understand what the system is actually supposed to do, and what you should be testing against.
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By SmartBear
Release day shouldn't mean chasing answers across Jira. SmartBear Zephyr is the Jira-native testing system of record that empowers your team to deliver better software, faster. In this demo, see how Zephyr Skills for Rovo bring test management and automation insights directly into Jira. Connect planning, testing, and delivery in a single, unified workflow within the Atlassian system of work so your team can make faster, more confident release decisions.
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By SmartBear
The tsunami of AI-generated code creates downstream bottlenecks for QA teams, and shift-left or traditional test automation aren't enough in the AI era. In this From the Bear Cave session, SmartBear CEO Dan Faulkner and CMO Kelly Wenzel unpack how AI code generation impacts software quality and why traditional testing struggles to keep up.
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By SmartBear
Testing complex UI elements like CAD software, Google Maps, or Citrix environments often leads to brittle tests and false negatives. Vision AI solves these automated testing challenges by recognizing elements just like a human would, reducing manual testing efforts, and improving accuracy. Discover how vision AI strengthens automated testing for visually complex applications. This tutorial shows you how to enhance object recognition in SmartBear TestComplete and eliminate test failures caused by 3D applications, canvas-based apps, and virtualized environments.
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By SmartBear
Recent SmartBear research shows that 70% of teams are already seeing quality degrade with AI-generated code, creating a real bottleneck in the software-development lifecycle (SDLC). As output increases, QA teams are left choosing between delaying releases to validate changes or shipping faster with less confidence in what’s actually working. In this From the Bear Cave clip, SmartBear CEO Dan Faulkner and CMO Kelly Wenzel dig into a growing gap in modern software development: how AI is accelerating code generation but testing and quality validation aren’t scaling with it.
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By SmartBear
Now, more than ever, the success of your business hinges on your ability to ensure a quality Web experience for both internal and external users. We're not talking about just design, either. Your customers are demanding fast access to quality Web content that displays properly on any mobile or web device of their choosing. Download this eBook, and see if you're running the right tests to be sure your website is adapting.
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By SmartBear
We rely on APIs for critical aspects of our digital infrastructure. Much like the nails that connect and support a house's foundation, APIs ensure that the necessary parts of your digital network are connected. Understanding how they are behaving is vital to gain full visibility into the performance and availability of your digital assets.
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By SmartBear
Our AlertSite team supports businesses in monitoring and maintaining a stellar user-experience with accurate, actionable performance insights for web and mobile applications, websites, and APIs.
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By SmartBear
We've all heard the stories about the overnight sensation that took decades to achieve. The "API Revolution" has that same feel to me. Some version of APIs has been at the heart of application development for many years, but as the web application world grew more and more connected and developers learned to leverage code built outside their own application, the API industry began to boom and flourish.
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By SmartBear
When it comes to APIs, performance is just as important as accuracy. No matter how good the features and functionality of your application might be, if it performs poorly by crashing or loading slowly, your users will lose interest quickly. With this in mind, we've put together a comprehensive guide to the fundamentals of API load testing.
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By SmartBear
Where do performance testing and monitoring fit into the Agile and DevOps development process? Implementing a process for improving the performance of your applications requires the right tools to help you do it. These tools go beyond the responsibilities of your development team to ensure that applications are tested in pre-deployment and monitored after your application is live in production. This eBook will provide the tactical advice you need to implement a strategy that works for your organization.
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By SmartBear
Modern applications are developed, tested and delivered to end-users in ways that simply didn't exist five years ago. In order to meet increasingly high user expectations, businesses need to deliver higher quality software at a faster rate, and those that fail to do so will lose market share to competition that does.
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By SmartBear
There are two primary techniques for monitoring web and mobile applications-synthetic monitoring, and real monitoring-each with very different capabilities, advantages and disadvantages. How do you know which technique to use?
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By SmartBear
While APM solutions have been mitigating poor user experiences since the early 90s, only recently have these tools begun to deliver on the promise of proactively identifying and diagnosing performance issues before users are impacted-but they are still far from perfect. For starters, why the lack of unified functionality? Why do we still need multiple tools in order to deliver a single APM solution? Or do we?
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By SmartBear
Now, more than ever, the success of your business hinges on your ability to ensure a quality Web experience for both internal and external users. We're not talking about just design, either. Your customers are demanding fast access to quality Web content that displays properly on any mobile or web device of their choosing. Download this eBook, and see if you're running the right tests to be sure your website is adapting.
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SmartBear provides high-impact, easy-to-use tools for software teams to plan, build, test, and monitor great software, faster. We create the software tools that development, testing, and operations teams use to deliver the highest quality and best performing software possible, shipped at seemingly impossible velocities.
With products for code review, API and UI level testing, and monitoring across mobile, web and desktop applications, we equip every member of your team with tools to ensure quality at every stage of the software cycle.
The World’s Best Software Development Teams Use SmartBear Tools:
- SoapUI Pro integrates with your entire API delivery ecosystem, from design and mocking to issue reporting and deployment. With an open core plugin framework, integrations to the following areas make ReadyAPI and SoapUI Pro the most extensible and connected API testing suite in the world.
- With LoadUI Pro, you can reuse your functional API tests built on the industry's #1 open-source based API testing tool, SoapUI Pro to speed testing and reduce the time it takes you to deploy high performance REST and SOAP web services.
- SwaggerHub is engineered to give organizations and teams the best possible experience for maintaining and scaling their API development, from design to deployment.
- AlertSite gives you full visibility into the health of your websites, web applications, mobile applications, cloud applications, and APIs, so you can deliver an exceptional end-user experience. Key features of the AlertSite Platform include: Hybrid Deployment, Real-Time Alerts, Codeless Web Recorder, Real Browser Playback, Single-Sign On.
Release your passion to create great software, think bigger, and build smarter.