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How We AI: AI-Written Test Cases vs. Human Review
Give an AI tool a clear requirement, and within a minute, you can get a structured draft with preconditions, steps, and expected results. A year ago, that felt impressive. Today, for teams already using AI in QA workflows, it feels
Real Devices and Virtual Devices: How to Build an Effective Mobile Testing Strategy in 2026
As device ecosystems become more diverse and user expectations continue to rise, choosing the right testing approach has become a critical decision for mobile teams in 2026. The question is how to combine virtual and real device testing effectively to
How To Prepare a Betting Platform for World Cup 2026
The 2026 FIFA World Cup is the largest in FIFA history: 48 teams instead of 32, stretched across 104 matches over 39 days and hosted in three countries with different regulatory frameworks. Research shows 60% of fans worldwide plan to
32 AI Agents Across 4 Platforms: Building a Robust Evaluation System for AI Solutions
AI agents are entering real business workflows, but their quality is hard to measure consistently. A single request can involve reasoning, tool calls, external data, and several decisions, so teams need visibility into the full workflow before trusting it in
AI-powered Testing and Test Automation: (Not) the Same Approach
AI-powered testing refers to the use of machine learning and data-driven approaches to support test creation, analysis, and optimization, while test automation focuses on scripted, repeatable checks with predefined expected results. Although these two approaches are often confused, and AI
