This is the second article in a three-part Agentic QA series. The first article — Agentic QA Architecture: Reasoning Loops, Self-Healing DOM & Autonomous Testing — covered how AI agents use Plan-Act-Verify loops to autonomously generate and execute test scripts. This article focuses on the prerequisite layer: evaluating and certifying the reliability of the LLM… Continue reading Continuous Evaluation: How to Build an LLM Regression Testing Pipeline in 2026
Category: LLM Testing Tool
LLM testing tools are essential for evaluating the performance, reliability, and safety of Large Language Models (LLMs). These tools help identify and address potential issues like bias, toxicity, hallucinations, and inaccuracies in LLM outputs.
Beyond the Basics: Advanced LLM Evaluation Metrics and Strategies for QA Success
The integration of Large Language Models (LLMs) into applications is rapidly transforming the software landscape. As we discussed in our Guide to LLM Testing and Evaluation previous post, while LLMs offer unprecedented capabilities, their non-deterministic nature presents unique and evolving challenges for quality assurance. As QA professionals and developers, we’ve moved past the initial awe… Continue reading Beyond the Basics: Advanced LLM Evaluation Metrics and Strategies for QA Success
Unleashing Generative AI Across the Software Lifecycle
Introduction Software development that is both efficient and effective is becoming more important as the world becomes more dependent on technology. To guarantee that systems and applications perform as expected, software testing is an essential part of software development. Businesses are starting to use generative AI more and more as a result of the fast… Continue reading Unleashing Generative AI Across the Software Lifecycle
Embracing the future: The Rise of AI in Software Engineering
New, game-changing technologies have emerged in the ever-changing field of software engineering as a result of the relentless search for efficiency and creativity. Platform engineering, AI coding assistants, and AI-augmented software engineering (AIASE) are predicted to achieve widespread acceptance in the next 2-5 years, according to the Gartner, Inc. Hype Cycle for Software Engineering, 2023. When it comes to Quality Assurance, software… Continue reading Embracing the future: The Rise of AI in Software Engineering