The Era of Hybrid Testing

Back in the late 1990s and early 2000s, when I first stepped into the world of software testing, everything was done manually. That was the golden age of the waterfall development model—clear stages, defined processes, and that ever-familiar “Testing Phase” at the end of the cycle.

Despite having a designated testing period, it always felt like there was never enough time to thoroughly test the applications. Testing new features was exciting—each one felt like uncovering something new. But Regression Testing? That was another story.

Regression Testing was time-consuming and usually prone to error because we had already found the hard bugs the first time we tested the software.

Regression Testing was repetitive and prone to human error. By the time you got to that stage, the big, tricky bugs had already been squashed in earlier rounds. What was left was the tedious task of running the same steps over and over to ensure no new bugs had crept in after code updates. Frankly, it was boring.

The Dawn of Test Automation

Enter the early 2000s, and with it, a glimpse into the future: test automation tools from Mercury Interactive and Rational Software. These tools promised to change the game. The idea was simple—let the machines handle the repetitive tasks prone to human error.

We focused our efforts on automating regression tests since they were the most time-consuming and had to be repeated with every major code build. But adopting these tools wasn’t without its challenges. We had to learn new skills, debug scripts, and contend with flaky tests that would pass one day and fail the next for no apparent reason.

Even with these hurdles, the value was undeniable. Test automation dramatically reduced the time we spent re-running tests and minimized the errors that manual re-execution introduced.

The Need for Speed

As companies from all industries evolved into becoming software companies, the pace of software delivery skyrocketed. Testing had to keep up. It couldn’t be the bottleneck in the release process.

For the past 20 years, Test Automation has been the primary approach to accelerating the testing effort.

Over the past 20 years, test automation has been the primary way to speed up testing—despite its imperfections. It’s played a vital role in enabling faster feedback for developers, especially during regression cycles.

The Persistent Gap Between Manual and Automated Testing

Since the early days, there’s been speculation that manual testing would fade away, replaced entirely by automation. But here we are, a quarter of a century later, and manual testing remains essential. It’s often the go-to method for uncovering business-critical bugs that automated tests simply can’t catch.

Automation excels at regression testing, and that's where most organizations see the biggest return on investment (ROI). But there’s always been a gap. Manual and automated testing serve different purposes, require different skills, and often happen at different times in the software development lifecycle (SDLC).

Test automation vendors have tried to bridge this gap with features like record-and-playback, low-code, and no-code solutions. The idea has always been to make automation more accessible and introduce it earlier in the SDLC.

Some teams have succeeded with these approaches, but for many traditional testing teams, manual and automated testing still live in separate worlds, often managed by different teams with different priorities.

Manual + Automated + AI-Augmented = Hybrid Testing

In recent years, the rise of Generative AI has shaken things up. Tools like OpenAI's ChatGPT have brought AI into the mainstream, and software testing is no exception.

I’ve spent the past couple of years working with and helping teams adopt AI-augmented testing tools designed to boost tester productivity. We’ve learned a lot—both about what works and what doesn’t. And here’s the exciting part: I’ve seen firsthand how Generative AI can bridge the gap between manual and automated testing—and even go beyond it.

If you're interested in some of those lessons learned, watch this.

The challenge we face now is an unrealistic expectation of perfection. Some in the industry believe that AI needs to be flawless before they can adopt it

The challenge we face now is an unrealistic expectation of perfection. Some in the industry believe that AI needs to be flawless before they can adopt it. But perfection isn’t the goal. After 25 years in the field, I can tell you that test automation is still far from perfect. Yet, it’s delivered incredible ROI to countless teams, despite its limitations.

Generative AI features specifically designed for software testing are already enabling teams to:

• Achieve the benefits of automation without the heavy lift of writing and maintaining test scripts.
• Increase test coverage through AI-assisted manual testing.

Your Next Steps

So, what does this mean for you? Don’t wait for perfection—aim for progress. Explore the new wave of tools that enable a hybrid approach to testing. These tools combine manual, automated, and AI-augmented capabilities to create something more powerful.

It’s an incredible time to be a tester. We now have three distinct approaches to testing at our fingertips—manual, automated, and AI-augmented—and the ability to blend them. This is the era of the Hybrid Tester, a term first coined by Cristiano Caetano. The hybrid approach empowers testers to be more productive, creative, and impactful.

In my next blog, I’ll dive into the key features a Hybrid Testing platform needs to support this new breed of testers, drawing from my own experience building such a platform.

In the meantime, I’d love to hear from you. Are you already leveraging a hybrid approach to testing? How has it impacted your productivity? Let me know in the comments.

Happy bug hunting!