As a test professional, I’ve seen countless projects where defects are treated as disasters rather than learning opportunities. But what if we flipped that mindset? What if software development projects embraced failure as SpaceX does—not as an end, but as the beginning of progress?
Testers can now convert video recordings into detailed defect reports. This groundbreaking functionality accelerates project timelines with AI-powered speed and accuracy. Not only does this technology provide the holy trinity of speed, quality and cost savings, but it also solves a huge—often unspoken—issue on many projects: the breakdown of dev/test relations at the worst possible time.
Imagine being able to record a user story and instantly turn it into manual and automated tests—how much time and effort would you save? Whether you’re preparing for SIT, UAT or streamlining regression testing, you can now generate manual and codeless automated test cases directly from video recordings, leveraging cutting-edge AI technology to streamline your testing processes.
As great as OpenText is at software development, it’s not always the best at keeping people informed about changes. So, today, I’m sharing a few recent updates to the OpenText automation tools. These are just a tiny sample of recently implemented changes. They focus on cloud capabilities, AI-powered object detection, codeless testing, and streamlined workflows that make test automation more accessible and efficient than ever.
Over the next five years, software and software testing are set to evolve at a rate we’ve never seen. In fact, it has already started. Over the last few years, everyone remotely involved in tech has witnessed the constant change in the way things are done. This seemingly non-stop innovation has been driven by emerging technologies, shifting development paradigms, and businesses reevaluating their priorities… and is set to accelerate.
In the race to protect us against rogue AI, our best defence might not be scientists or politicians, but the often-overlooked heroes of the tech world: software testers. As AI systems increasingly mediate healthcare, criminal justice, and military decisions, this unlikely profession could hold the key to preventing existential catastrophe.
It’s 2025 and software testing AI can no longer be ignored. AI innovations in software testing can deliver unprecedented efficiency gains and bridge the gap between manual and automated workflows. This article contains four software testing AI breakthroughs you can’t ignore in 2025.
It’s been years since the pandemic. Still, many companies I speak to have struggled to adapt to changing practices and have failed to implement effective working habits. Unfortunately, you can’t just continue as if nothing has changed—this approach just won’t cut it anymore. In this week’s insight, I provide four actionable approaches that I have picked up from the many successful testing projects I talk to. These easy fixes will help you prevent collaboration disasters in your remote testing teams.
You see them everywhere. Top 10 this, top 20 that. We have all searched for lists that rank products. Whether cars, phones, software, or anything else. But how trustworthy are the ‘top software’ lists on the internet?
I have heard some say that their aim is for 100% test automation. But 100% test automation isn’t practical or desirable. In fact, I would argue that—for practical and desirable risk mitigation—100% test automation isn’t even possible.
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