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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,

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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

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Wellness Apps: 5 Quality Obstacles and How To Overcome Them

Wellness apps are integral to self-care. People use them to track workouts, count steps, monitor heart rate, and track data about their bodies. That is a high level of trust,

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