Systems | Development | Analytics | API | Testing

Assume that your enterprise just rolled out a major product update after weeks of development and testing. But within hours of launch, customers are already experiencing problems: checkouts are failing in Safari, logins break in Firefox, and the Android app crashes. What was supposed to be a significant milestone release becomes an expensive fire drill, resulting in loss of revenue and customer trust. This is the harsh reality for many enterprises in 2025.

Every QA engineer has felt the crunch: tighter deadlines, growing complexity, and the same old expectation that everything must work perfectly by release day. It’s not an easy balance. That’s why AI in software testing has become such a hot topic. It promises faster test case generation, smarter insights, and support with tasks that usually eat up hours of time. But let’s be clear: AI isn’t here to replace testers.

Testing is hitting its limits in speed, scale, and insight. AI-augmented and agentic systems can help but only if we adopt them intentionally. This blog series lays out a Crawl–Walk–Run maturity path for adopting agentic testing capabilities safely and strategically. We’ll show you how to move from assistive agents to coordinated systems without losing control or trust.

Every action you automate in Selenium starts with one thing: finding the right web element. That’s where locators come in. They guide Selenium to the exact button, input field, or text box it needs to interact with. Locators in Selenium are essential. Without them, you can't click a button, fill out a form, or verify if a message appears on the screen. They're the foundation of every test case you write. In this article, we’ll walk you through: Let’s get started!

When I started at Speedscale, I looked like this: And after one year of learning, growing, and keeping pace with innovation well, let’s just say the journey has left its mark: Of course, I’m joking (sort of). The truth is, this past year has been intense, energizing, and filled with new challenges. If anything, it’s made me feel younger in spirit, even if the mirror might disagree some mornings.

Databases are the spine of most any app we use today, from a banking app to an online shopping site. Good application is hidden under cover of the user interface, in the basement, in the room where the data is stored, processed and fetched. Database testing is vital for that very reason. It makes data accurate, secure and trustworthy, which in turn keeps apps stable and businesses running smoothly.

When you write a Selenium test, every interaction depends on one crucial step: identifying the right element. Whether it's a button, input field, dropdown, or link, Selenium must find it before it can click, type, or select. This is where element locators come in. These strategies help your Python scripts pinpoint specific pieces of the page, just like a user would. In this guide, you'll learn exactly how to find element in Selenium with Python confidently and consistently.

The AI mandate is real. Boards and executives are demanding that software organizations move faster, embrace AI, and deliver without breaking trust. Development velocity is accelerating at machine speed, but testing has not kept up. The question every QA leader faces today is simple: will quality keep pace, or will it become the bottleneck? This is where the shift from automation to AI-native testing comes in.

Software is now the front door of your business, and when it fails, revenue and trust are on the line. Yet quality assurance is still too often treated as a cost center instead of a growth driver. The AI mandate is raising the stakes: boards expect faster delivery through AI and low-code, but that speed creates more complexity to test. Most QA teams still rely on manual processes, leaving quality as the bottleneck.

Since the release of the Defense Innovation Board (DIB)'s Software Acquisition and Practices (SWAP) report in 2019, the Department of Defense (DoD) has focused on adopting and recommending DevSecOps best practices for aerospace and defense development and software acquisition, as detailed in the DoD's 2024 State of DevSecOps report.