Marketers everywhere are anxious about what fortune the cookieless future holds — but I think we should embrace what will be a refreshing change.

The topic of testing AI and ensuring its responsibility, safety, and security has never been more urgent. Controversy and incidents of AI misuse have increased 26-fold since 2021, highlighting growing concerns. As users quickly find out, AI tools are not infallible; they can make mistakes, display overconfidence, and lack critical questioning. The reality of the market is that AI is prone to error. This is exactly why testing AI is crucial. But how do we test AI?

When you think about improving your website, consider the impact user feedback can have. It comes directly from those who navigate and use your site. Let’s say visitors struggle to find information on your website. They may suggest adding a search function. Implementing their suggestion can dramatically enhance user experience. Such an update can make your site more navigable and efficient. It will allow users to find what they need quickly.

From the end user’s perspective, the microapps and microservices often seem to provide the same functionality. However, development teams need to think about microapps vs. microservices when building products. Before you commit time to microapps or microservices architecture, take some time to consider how these options will affect user experience (UX), user interface (UI), and security of your websites, web apps, and mobile apps.

Extracting values from server responses is a common operation in scripting scenarios for performance testing. In most cases it is a mandatory step in order to reproduce realistic traffic using dynamic values generated on server side like sessionIds or Tokens. The most known way to extract values is using regular expression. While regular expressions are efficient for raw text-based responses, they are less efficient for structured responses like XML or JSON.