Systems | Development | Analytics | API | Testing

Why do testers were initially nervous about Al replacing their work?

Testers weren’t nervous about AI replacing their work, the challenges were actually logistical. Teams struggled with unpredictable pre-production environment changes, global coordination, and unclear deployment windows, which caused confusion during monitoring and adoption. — Mush Honda, Chief Quality Architect at Katalon Follow Katalon for more insights in our series!

The 2025 Kong Year in Review

Another year is wrapping up, and we’re taking a moment to reflect on what made 2025 a defining year for Kong. With major advances in building the AI connectivity layer and soaring enterprise adoption of agentic systems, this year sparked a hockey-stick surge in demand for the infrastructure that powers intelligent agents. Below is a rundown on the updates, the innovations, and the moments that moved the industry in one year-end recap.

Beyond Numbers, Metrics that matter in AI Age | Brijesh Deb | Testflix 2025 | #testingcommunity

AI has transformed how software is built and tested, yet many teams still rely on traditional metrics like pass rates, coverage, and defect counts. While these numbers look good on dashboards, they often fail to answer the most important question in the AI era. Can we actually trust what the system is doing?

Generative AI in Healthcare: Technology, Use Cases, Trends & Future Outlook

‍ The healthcare industry stands at the cusp of a revolutionary change, driven by an emerging technology that can do more than just analyse data; it can create it. That technology is Generative AI, or GenAI, and its arrival in medicine is being hailed as the next frontier in personalised, efficient, and predictive patient care.

Why ClearML's AI Application Gateway is a Critical Layer for Secure, Scalable AI Development Environments

As organizations expand their AI initiatives, they increasingly need to provide users, be they data scientists, AI/ML engineers, researchers, or application developers, with secure access to interactive development environments such as JupyterLab, VS Code, or other internal tools.

Before Building AI we should First Understand Natural Intelligence | Andrew Brown | Testflix 2025

Before building artificial intelligence, it’s worth asking whether we truly understand natural intelligence. Just as early pioneers of flight studied the principles of aerodynamics and observed how birds fly, this session argues that progress in AI requires a deeper understanding of human intelligence and the knowledge that already exists across related disciplines.

Bias in, Bias Out: Knowing various Biases in Testing AI | Maheshwaran VK | Testflix 2025 |

Just like humans, AI systems are shaped by how they are brought up. In the case of Large Language Models, this upbringing happens through data collection, training, and productization. At each of these stages, bias can quietly enter the system through the data we select, the way models are trained, or the assumptions embedded into the final product. These biases, whether intentional or accidental, influence how models think, respond, and interact with users in the real world.

How US Shopping Malls Are Using AI to Increase Foot Traffic and Revenue?

In the United States, the evolution of shopping malls is no longer just about retail, it has also become about experience, engagement, and intelligence. With more than 900 active shopping malls nationwide attracting millions of visitors annually, traditional brick-and-mortar destinations are battling shifting consumer preferences and rising digital expectations. Today’s consumers are blending browsing with dining, entertainment, socializing, and convenience-driven digital interactions.