Author: Kevin Surace

QA is no longer a phase.It’s becoming a system. By 2026, software quality isn’t defined by how many tests you write—it’s defined by how effectively systems generate, validate, and govern behavior at scale. And the shift is happening faster than most organizations realize. LLMs Become the Validation Layer The biggest shift in QA isn’t test

Test automation has long been positioned as a cost-saving lever. Invest in tools.Automate regression.Reduce manual effort.Increase release velocity. On paper, the ROI looks obvious. In practice, many CIOs are underwhelmed. Why? Because the true cost of traditional automation is misunderstood—and often hidden. The Illusion of Savings Most ROI models for test automation focus on one

For decades, quality assurance followed a predictable path. Manual testers executed test cases step by step.Automation engineers wrote scripts to scale it.Teams spent more time maintaining tests than validating software. That model is ending. And not because teams suddenly got better—but because the architecture itself has changed. From Manual to Scripted to AI-First Manual QA

There is a quiet truth in enterprise QA right now. Many teams feel let down. For the last several years, vendors have promised an AI revolution in testing. Autonomous agents. Self healing frameworks. Copilots that would “change everything.” Yet when you talk to QA leaders privately, the story is different. Productivity has barely moved. Script

In a startling move that’s rippled through the tech world, IgniteTech CEO Eric Vaughan replaced nearly 80% of his workforce after employees resisted his AI-first strategy—a change he says he’d make again.  An Existential Shift in Culture, Not Just Tools Vaughan believed generative AI wasn’t optional—it was existential. He introduced “AI Mondays,” mandated that every department—from

In the fast-moving world of software delivery, speed and accuracy are everything. Time isn’t just money—it’s market share, competitive advantage, and customer loyalty. Every defect that slips into production is a risk: to your brand, your bottom line, and the trust you’ve built with your users both internal and external. Yet, despite this reality, many

By Kevin Surace, CEO of Appvance Every few months, headlines trumpet the latest “AI breakthrough.” A new co-pilot. A smarter recorder. An incremental feature that saves a few hours here or there. And every time, CIOs and CTOs ask the same question: is this worth the disruption of implementing new systems? Peter Diamandis put it

A recent email from ASTQB warned testers that to survive in an AI-driven world, they’ll need “broad testing knowledge, not just basic skills.” The advice isn’t wrong—but it misses the bigger picture. The real disruption is already here, and it’s moving faster than most realize. AI systems like AI Script Generation (AISG) and GENI are already generating, executing, and

A recent CIO article revealed a startling reality: 31% of employees admit to sabotaging their company’s generative AI strategy. That’s nearly one in three workers actively slowing down, blocking, or undermining progress. Now layer in the math: most AI initiatives involve dozens of employees. That means statistically, almost every project or proof-of-concept is being impacted by one or

For decades, software testing has been built on a simple idea: humans write tests, machines run them. That model has persisted since the first commercial recorders appeared in the mid-1990s. Testers would record a flow, edit a script, maintain it as the application evolved, and repeat the cycle endlessly. Tools improved incrementally, but the basic