Lisa Pluhm Fatolitis

EVERYONE IS PRAYING FOR QUALITY. Developing software is complex, and writing code is hard. Developers must navigate multiple frameworks and services to develop even simple applications. No matter how good the software developer is, the code always has errors, omissions, contradictions, or dead-ends. These errors are called defects. Fixing defects ensures you don’t annoy your current user base, but it doesn’t attract new users. It takes a pipeline of new features and capabilities to build customer loyalty, drive software price increases for better margins, and ensure market fit. To combat defects, all software development organizations do some form of testing because testing is critical to product quality. But there’s a big problem: testing is broken. Testaify addresses testing’s real problem — poorly designed tests — by transitioning test creation and execution to AI. AI natively understands all testing methodologies and writes more tests much faster, freeing resources for additional development. Machine learning delivers an unparalleled capacity to adapt to incremental changes in the software’s code and will quickly overcome the learning curve, reducing potential false positives. AI isn’t limited by regular work hours or how well the tester documented changes to their test inventory in their test case management solution. Product quality will improve as defects are found and resolved more quickly. Feature development and releases will accelerate. Great testers, which we call system thinkers, will understand what the AI is doing and why. They will validate found issues and help train the AI system to maximize its value. These resources will pick up their crowns as the Beekeepers of the Testaify hive. For too long, the system thinkers, who know the application in and out, have been forced to do or learn skills that are not their core competency. With Testaify, they are back at the center doing what they do best: managing the testing process.