Gen AI & Agentic AI for Software Automation Testing

Welcome to this practical, hands-on course on Generative AI and Agentic QA for Software Testing, where you will learn how to integrate modern AI technologies into real-world software testing activities.

This course goes beyond using ChatGPT to generate test scripts. You will explore how AI coding agents such as OpenAI Codex, GitHub Copilot, Claude Code, and Pi Coding Agent can work with Playwright, MCP servers, command-line tools, and LLMs to assist with end-to-end software testing.

Here’s what you’ll master:

• Understand Generative AI, Large Language Models (LLMs), AI Agents, and how they are transforming modern software testing.

• Master Prompt Engineering and Context Engineering to get better results from AI-powered testing tools.

• Generate manual test cases, test plans, BDD scenarios, and test data from software requirements using Generative AI.

• Explore RAG and CAG to generate context-aware test cases using requirements, product documentation, and local AI models.

• Run Local LLMs using Ollama and LM Studio for private, secure, and cost-effective AI-assisted test development.

• Understand Model Context Protocol (MCP) and use Playwright MCP Server with AI Agents to automate real web applications.

• Use Playwright CLI and Agent SKILLS with AI coding agents for intelligent browser automation and testing.

• Build Agentic End-to-End Test Automation using OpenAI Codex, GitHub Copilot, Claude Code, and Pi Coding Agent.

• Leverage Generative AI for API Testing using Swagger, RestSharp, Postman, and AI-powered test generation.

• Explore self-improving automation tests and intelligent locator healing using LLMs with Selenium and C#.

• Integrate automated tests into CI/CD pipelines using GitHub Actions and AI-assisted workflow generation.

• Build GitHub Agentic Workflows to automate repository-level testing, smoke tests, and issue-triggered QA activities.

By the end of this course, you will understand how to apply Generative AI and AI Agents across multiple stages of the software testing lifecycle—from requirements analysis and test design to automated execution, API testing, and continuous integration.

Learn to move beyond traditional test automation and explore the next generation of AI-powered software testing.