Systems | Development | Analytics | API | Testing

If you recall part one of this blog post, we were going to use ChatGPT in parallel with how we would work to cover these aspects of performance testing. We left the first part of this blog post at the point at which we had compared Requirements Gathering and Risk Assessment, we will pick this post up by looking at Script Creation before concluding with Results Analysis. Our performance testing tool of choice will be JMeter.

If you believe many articles online you would believe that automation in testing will soon be defined, managed and executed by Artificial Intelligence (AI). AI is embedded in many organisations technology landscape and to think that this model will change is shortsighted. AI is here to stay undoubtedly in one form or another, but should it be responsible for the automated testing of your applications under test?

Census makes it easy to turn warehouse data into AI-ready vectors — without building a single pipeline.

Artificial Intelligence (AI) is reshaping Quality Assurance (QA) by accelerating testing, improving accuracy, and uncovering insights that once required hours of manual analysis. Yet, with great capability comes great responsibility. As AI begins to influence how tests are designed, executed, and interpreted, ensuring that it’s used ethically has never been more important. Responsible AI in QA isn’t only about compliance — it’s about trust.

Discover how Sauce Labs' Apple Silicon-powered virtual devices deliver faster, more accurate iOS testing with up to 40% improved execution times and native ARM architecture support.

‍ Users expect a single pane of glass for budgets, net worth, investments, goals, and safe bank connections that “just work.” Building a personal finance app that people trust isn’t just a design exercise; it’s a data, security, and distribution challenge. Investors are backing winners in this space.

Ever wondered how you can walk out of a modern store, without even scanning a single item, and still get a perfectly accurate bill on your phone? Or how retailers seem to know exactly when shelves need restocking before you even notice they’re empty? Well, that’s the power of computer vision in retail, an AI that gives machines the ability to see, interpret, and make decisions in real time. And it’s not emerging anymore because it’s scaling fast.