Recent content by weber.st.michael

Hi everyone! I’m working on a UI for a QA reporting dashboard and I’m struggling with how to present huge amounts of data (fail/pass rates, flakiness) without cluttering the screen. I was looking at how these tools handle it...

Hi all, If your pipeline is struggling with slow test execution or flaky results, you should look into AI-driven **continuous testing services**. I’ve been using **testomat.io** to manage our QA workflows, and their AI failure analysis saves us hours of manual triage every week. It’s a great...

Hi! Our team is struggling with flaky tests in React. Class names are dynamic, and IDs are often missing. I'm thinking of switching back to a heavy XPath in Selenium (https://testomat.io/blog/xpath-in-selenium/) strategy because of its flexibility with axes and text-based locators. Michael...

When implementing unit ai workflows, the most common mistake is trusting the generated mocks without a manual sanity check. AI is great at boilerplate, but it can struggle with complex business logic that isn't explicitly defined in the function's context. To close this gap, I’ve found that a...

Hi everyone! Your comments and real-world insights are very important to me, as the industry is moving so fast right now that official reports rarely capture the full picture of what’s happening in actual production pipelines. I’m currently rethinking our automation strategy and I keep hitting...

We've been experimenting with a few AI agents for test automation lately. While the speed of code generation is impressive, the real struggle is the 'non-deterministic' output. I was reading a good breakdown on generative ai testing challenges here...

Hi everyone! We’ve been implementing a few AI-driven agents for our marketing automation recently, and the biggest headache wasn't the integration—it was the trust. How do you actually prove to a client that the AI won't start hallucinating or giving weird advice? We quickly realized that a...

Has anyone else noticed that as we move to AI-driven QA, the complexity of debugging has tripled? I've been using this 'Debug Therapy' guide for debugging in software testing (https://testomat.io/blog/debug-therapy-a-practical-guide-debugging-in-software-testing/) to train our juniors. It’s...

Hi everyone, I’ve been transitioning our regression suites to include generative models lately, and the biggest bottleneck isn't the AI itself, but how we validate it. Standard testing logic just breaks when the output is non-deterministic. I’m currently digging into llm testing...

I’ve been tracking the evolution of QA workflows, and the biggest shift this year is definitely the move toward autonomous execution. The practical application of generative ai in software testing (https://testomat.io/blog/generative-ai-in-software-testing/) is finally making "self-healing"...

Hi everyone, I’ve been implementing a new QA stack recently and wanted to share a couple of high-quality resources for those working with Java and automation. If you're looking for a step-by-step tutorial on setting up a Playwright Java BDD framework, this guide covers the complete...

Hi everyone, I've been looking into how LLM agents and MCP are changing the QA landscape this year. If you're working on manual testing or looking to upgrade your current QA stack, these two resources provide a lot of technical value: 1. Deep dive into AI in manual...

Hi everyone, I’ve been researching the actual "tax" that production errors put on a project's budget. It’s a well-known fact that the cost of software bugs grows exponentially the later they are discovered. A simple logic error that costs $100 to fix during development can easily turn into a...

In the rush to implement CI/CD, many development teams overlook the fundamental structure of the Software Testing Life Cycle. We often focus on "how to code" but forget "how to verify" systematically. From my experience, a fragmented testing process is usually the result of skipping key STLC...