AI testing

The rise of artificial intelligence has redefined the boundaries of software testing. Whether you are testing AI models for bias and accuracy or using generative AI to automate your test suites, staying updated is crucial. Here, we explore the intersection of AI and QA, covering everything from MLOps validation to advanced AI-powered testing tools that help teams achieve unprecedented scale and efficiency in 2026.

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AI for QA

AI for Quality Assurance: Automating Modern Testing Workflows

QA teams are drowning in repetitive work: writing test cases from scratch, maintaining outdated test suites, hunting for coverage gaps across hundreds of features. AI in quality assurance shifts where your time goes. Instead of generating boilerplate test cases manually, QA engineers spend their hours reviewing what AI drafts, catching edge cases the model missed, […]

Vitaliy Mikhailyuk

Apr 24, 2026

Autonomous-testing

AI testing testing guides

Autonomous Software Testing: Tools, AI Models & Guide 2026

Most test automation still requires a human to write every script, maintain every selector, and decide what gets tested. Autonomous testing refers to something different: software testing where AI handles the generation, execution, and analysis of tests without step-by-step human instruction. That’s a meaningful distinction. Traditional test automation automates the execution of tests a human […]

Mykhailo Poliarush

Apr 21, 2026

Generative AI Testing

Generative AI in Software Testing: Practical Guide & Strategies

Companies spent 33.9 billion dollars on generative AI per year. Yet 74% of teams struggle with implementation. The problem is not adoption. The problem is making AI testing tools actually work. QA teams face specific challenges when testing generative AI systems. Traditional testing methods fail when applications generate unpredictable outputs. Test case creation becomes exponentially […]

Mykhailo Poliarush

Mar 26, 2026

Testing LLM Applications

LLM Testing Frameworks: Top Tools & Evaluation Strategies

Testing LLM applications differs from traditional software testing in fundamental ways. A chatbot built on large language models produces different outputs for identical inputs. Regression tests that worked yesterday fail today without code changes. QA teams trained on deterministic systems struggle with non-deterministic AI responses. Gartner reports 85% of GenAI projects fail due to inadequate […]

Vitaliy Mikhailyuk

Mar 19, 2026

Manual Testing with AI in Testomat.io

AI testing Insights

Manual Testing with AI: Optimize QA with Minimal Intervention

Hi everyone, my name is Ira, and I work as a QA Engineer at MEV. I have been in the testing industry for about seven years, working on a variety of interesting projects – testing web, desktop, and mobile applications. Every day I use AI tools. In my opinion, they are a very convenient assistant […]

Mar 06, 2026

Testing with Testomat.io & Playwright Agents

AI testing Insights test management testing guides

From Manual QA to QA Automation Engineer: A 2026 Guide with Playwright & AI

There’s a particular kind of frustration that lives in the gap between knowing what to test and knowing how to automate it. You’ve written the steps. You understand the logic. You know exactly what the button should do when clicked. But the moment someone mentions TypeScript, page objects, or async/await, the mountain starts looking very […]

Vitaliy Mikhailyuk

Feb 27, 2026

Evolution-of-testing

agile AI testing automation testing Insights jira testing theory

Software Testing Trends 2026: The Ultimate QA Guide

The software testing industry has witnessed more transformation in the past few years than in the previous decade combined. Remember when “automation” meant recording macros in Excel and teams debated whether Selenium was worth the learning curve? Those days feel like ancient history now that AI-driven testing tools can generate comprehensive test scenarios faster than […]

Mykhailo Poliarush

Jan 09, 2026

Test Case Generation Using LLMs

AI AI testing automation testing test management

Test Case Generation Using LLMs: How AI Is Transforming Software Testing

According to different estimates, the global number of software testers doesn’t exceed 9 million. Given the meteoric spike in the production of all kinds of IT products and the respective quantity of software tests to be conducted, QA teams can’t get them covered, no matter how hard they try. The only way to ensure a […]

Vitaliy Mikhailyuk

Dec 30, 2025

Python MCP Server

AI testing MCP test management

Python MCP Server: Building AI Context with Examples

The current practice of using external data and tools for AI model testing and development brings substantial benefits, but the need for custom system connections leads to major problems with system expansion capabilities. Thanks to the Model Context Protocol (MCP), you can establish a standardized client-server framework to enable LLMs to connect with external systems […]

Michael Bodnarchuk

Dec 26, 2025

chatgpt for test case generation

AI AI testing automation testing Insights

AI Test Management Solutions vs. ChatGPT: What’s Better for QA Documentation Analysis?

Let’s be real: software testing can be exhausting. While running automated suites is easy, the prep work—analyzing requirements, brainstorming scenarios, and writing test cases—drains hours of engineering time. While general AI tools like ChatGPT help with ad-hoc prompts, modern QA teams increasingly rely on specialized ai test management solutions to bridge the gap between requirements […]

Vitaliy Mikhailyuk

Dec 22, 2025

Best MCP Server Testing Tools in 2025

AI AI testing automation testing Insights MCP

Best Tools to Test MCP Server: A Complete Automation Guide

The Model Context Protocol (MCP) represents a fundamental shift in how AI agents interact with external tools and data sources. Developed by Anthropic and quickly becoming an industry standard, MCP creates a universal way for large language models to securely access information and execute actions across different systems.

Michael Bodnarchuk

Nov 18, 2025

AI-Driven Test Design

AI AI testing testing tool

AI-Driven Test Design: Transform Requirements into Intelligent Test Cases

As the need for digital solutions in the contemporary IT-fueled world grows exponentially, development teams find it increasingly hard to churn out websites, apps, e-commerce platforms, ERP systems, etc., in sufficient numbers. And the non-negotiable requirement for all these products is unimpeachable software quality, validated through out-and-out software product testing.

Michael Bodnarchuk

Nov 14, 2025

AI testing jira MCP test management

Building Jira MCP Server integration with test management

With the Model Context Protocol (MCP) you can communicate with Attlasian’s Jira or Confluence tool through natural language interactions. It delivers a strong ability to eliminate the need to leave the current AI application to complete Jira-related tasks

Mykhailo Poliarush

Nov 08, 2025

AI-Powered Monitoring

AI AI testing testing tool

AI-Powered Test Monitoring: How to Eliminate Flaky Test Noise

The process of creating and delivering software is speeding up, and automation testing has become one of the critical aspects of continuous integration and deployment (CI/CD). Automated tests are able to process thousands of cases in minutes and generate lots of valuable data.

Michael Bodnarchuk

Oct 24, 2025

AI testing MCP playwright

Playwright MCP Claude Code: Complete Guide to AI Test Automation

The test automation space is turning into a huge coding AI partnership for development and testing teams and AI. Claude Code, which is combined with Playwright Model Context Protocol (MCP), transforms the way developers and QAs approach browser automation and testing. With the MCP Playwright server,

Mykhailo Poliarush

Oct 15, 2025

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