Systems | Development | Analytics | API | Testing

Technology in the enterprise is evolving at a record pace, making it increasingly difficult to keep up with the latest "tech du jour." AI has only accelerated this evolution, bringing about a data reckoning—especially as more organizations adopt hybrid models to manage their data. Both users and organizations are seeking data platforms that can connect the dots of their data today while adapting to tomorrow's demands. This shift underscores the growing demand for open standards. But what does that kind of platform experience look like today?

What’s next for software testing in 2025? In this episode of Test Case Scenario, Jason Baum, Evelyn Coleman, and Marcus Merrell discuss the trends shaping the future of testing. From AI advancements to accessibility regulations, they explore what’s on the horizon for testing tools and methodologies.

“AI is changing the game in software testing – but are we ready?” In the first episode of Test Talks, our speakers at Katalon explore the transformative impact of AI on testing, breaking down challenges like integrating AI with legacy systems, data privacy concerns, and how to scale AI solutions within enterprises. Join us on December 7th for a deep dive into how testing teams are navigating this AI-driven revolution. Don’t miss it!

Lewis Prescott helps us answer this question. But... we want to hear yours too! Do you use AI for your API testing sessions?

Spotter makes AI insights accessible to everyone—not just experts. With Spotter as your dedicated AI Analyst, you can use GenAI to drive meaningful outcomes in your business.

With ThoughtSpot Embedded’s modern developer tools, you can embed Spotter into any of your business applications. Spotter integrates effortlessly into your preferred platforms, seamlessly embedding within existing business applications, digital productivity tools, and custom agents to meet you where you work, so your users can ask questions of their data anywhere, at any time.

A short live demo on how to easily migrate from Zookeeper to Kraft with Confluent for Kubernetes (CFK) in 4 simple steps.

There’s a new way to approach quality. In game testing, "shift-left" is all about catching issues earlier in the development process rather than waiting until production. @Mac Clark from Sauce Labs explains how game engines like Unity and Unreal allow for a shift-left approach using AI agents to automate testing before a game reaches players. This proactive method can help identify potential crashes and errors at the engine level, ensuring a more stable product launch.