
Explore zero-shot prompting by acting as a QA engineer to generate functional test cases for an e-commerce login, formatted as a simple list.
Explore chain-of-thought prompting to guide large language models to reason step by step, using prompts with role, context, and constraints to build comprehensive test suites.
Explore agile test planning with epics and user stories, unleash generative AI to craft release and sprint test plans, and integrate Jira for automated QA workflows.
Understand Chrome DevTools MCP server for debugging, performance analysis, and deep diagnostics, while installing and configuring it in VS Code, including disabling usage statistics and running accessibility checks.
Sign up for Jira, set up the Atlassian MCP server, and connect Jira with Confluence to create epics and user stories, start a sprint, and prepare AI-driven test plans.
Demonstrates invoking a lead test automation agent to delegate tasks to sub agents and generate Gherkin tests, csv files, and Playwright tests from a Jira ticket in the current workspace.
QA is changing fast, and if you've been in the field for any amount of time, you've probably already felt it. The test scripts that used to be your bread and butter? They're not enough anymore. The engineers who thrive in the next few years won't just be the ones who know how to automate. They'll be the ones who know how to build systems that automate the automation.
That's exactly what this course is about.
This course isn't a "prompt ChatGPT to write your test cases" tutorial. It's a hands-on, ground-up guide to embedding Generative AI into the way you actually work, from the first requirement to the final bug report. You'll build production-grade test suites and set up AI agents that can read requirements, write code, chase down failures, and file bugs without you babysitting them.
Along the way, you'll get real experience with tools that are already reshaping the industry: GitHub Copilot for rapid scripting, Claude Code for refactoring entire codebases straight from your terminal, and n8n for wiring together AI-powered testing workflows that would've seemed like science fiction two years ago. You'll also go deep on the Model Context Protocol (MCP), one of the most exciting developments in AI right now, which lets you connect large language models directly to your testing tools and environments.
By the time you're done, you won't just be someone who uses AI to test software. You'll be someone who builds the agents doing the testing.
That's a very different career trajectory.