With the traditional waterfall method of testing, achieving quality and faster time to market is difficult. Agile testing has emerged as an alternative, where development and testing take place simultaneously instead of operating in their respective silos. Let’s look at what it means to perform agile testing, what practices are necessary, and how agile testing can benefit your software releases.

Companies that want to reduce testing costs usually try working with fewer people, or even cutting back on the amount of testing done. But with those approaches, quality usually suffers. Releasing a critical bug and suffering the subsequent pain usually costs multiple times what testing would. There are better ways to save money, and it can be done just by being smarter about our test cases and their structure.

We’ve all heard about AI for software testing from some seriously smart people, but there has been a lot of confusion about the idea. This article tackles some of the questions you might be asking: Do I need to be a genius to use AI for software testing? Is AI going to replace me as a tester? Where does AI fit into my testing strategy? With a simple analogy of training a dog, learn how AI fits into testing.

The higher you climb in the organization, the less information you get: An executive might only see red, yellow, and green for a project. Any time different teams need to communicate complex information, there is bound to be some information loss, and maybe some information control. We just need to understand where and why that happens, and—hopefully—how we can mitigate it.