SmartBear

Recent SmartBear research shows 70% of teams are already seeing quality degrade with AI-generated code. As output increases, QA teams are stuck between: → Delaying releases to validate changes → Or shipping faster with less confidence This clip from our "From the Bear Cave" YouTube series is a preview of a bigger conversation between Dan Faulkner, CEO, and Kelly Wenzel, CMO, on why testing isn’t scaling with AI-driven development and what it means for application integrity. 🎥 Watch the segment here: https://bit.ly/3QE0qz0 ▶️ Full episode drops next week, stay tuned!

20 years of SoapUI 🎉 If you’ve ever written a test, debugged an API, or learned something new with SoapUI, we’d love to hear your story. 💬 Share your experience, memories, or milestones: 👉 On our community page: https://bit.ly/3OItCV0 👉 Or on Reddit: https://bit.ly/4tnNjR6

Most teams are juggling 3+ tools for API testing. The result? Duplicated work. Inconsistent data. Bugs that only show up in production. We mapped the 6 biggest bottlenecks killing API quality (swipe through 👉) Stop adding more tools. Unified testing solves this with one platform, one source of truth, zero duplicate effort. Drop a comment 💬 which of these 6 hits closest to home for your team? https://bit.ly/41DGvmg

SmartBear is introducing new Swagger capabilities to help teams govern, validate, and scale APIs in the age of AI. As AI accelerates development, APIs are being created and modified faster than ever, making visibility and continuous validation critical. New capabilities include a revamped Swagger Catalog for centralized API discovery and lifecycle tracking, Swagger Contract Testing with drift detection to continuously validate runtime behavior against OpenAPI contracts, and automated governance with policy enforcement to maintain quality at scale. You can confidently build and manage APIs for AI-driven development – without sacrificing trust. Learn more: https://bit.ly/4cJKt2P

As teams scale automation, test data doesn't always keep up. Results end up spread across CI/CD pipelines, tools, and reports, making it harder to get a clear view of quality. Bringing that data into one place can change how teams operate: 👀 Gain real-time visibility into every test run with results centralized in QMetry 🔗 Strengthen release confidence by ensuring every execution is tracked and aligned with what's deployed 📁 Stay audit- and compliance-ready with a complete, traceable record of testing activity from your pipelines The QMetry GitLab Component, now available in the GitLab CI/CD Catalog, automates this connection with no manual uploads and no gaps in visibility. This is a more structured approach to test management, without adding manual steps. Read more: https://bit.ly/4meDrGH

AI is accelerating development. But it’s also reducing visibility into what’s being built. More speed → more chaos More abstraction → less clarity So now you’re not just validating functionality. You’re trying to validate intent. How do you ensure application integrity at AI speed and scale? Learn more: https://bit.ly/4mlTW3N

API quality isn’t a testing problem anymore. It is a release confidence problem. Most teams aren’t struggling to write tests. They’re struggling to: – Keep them from breaking – Reuse them across use cases – Run them early enough to matter The result? Slower cycles, duplicated effort, and less trust in what’s being shipped. The shift we’re seeing: teams are building API quality strategies that are resilient, reusable, and scalable by design. Less fragility. Less duplication. More coverage. Faster delivery. (We’re breaking this down in more detail, link in comments.)

There’s a quiet shift happening in software development right now. AI is enabling teams to build at unprecedented speed, but it’s also exposing a long-standing constraint: quality doesn’t scale the same way. Vineeta Puranik, CPTO at SmartBear, breaks down why traditional and even AI-assisted testing approaches fall short in an AI-driven world, and what it looks like to move toward truly autonomous QA. A must-read for engineering and product leaders navigating this transition: https://bit.ly/4tdDrcN

Fitz Nowlan (VP of AI & Architecture) joins the Stack Overflow Podcast to break down what AI really means for testing. Spoiler: the old rules don’t apply anymore. Worth the listen if you’re building in this space 👇