We start with foundations: what broken testing actually costs teams, and Playwright from scratch architecture, your first test line by line, and how it looks from the browser's point of view. Then we make tests survive real-world change with role-based locators, auto-waiting, and fixtures, and we cure flaky tests at the root: all five causes, each with a one-to-two-line fix.

Then the heart of the course: AI agents for QA. You'll learn what an agent really is (no hype, no magic), then put agents to work on the three highest-value jobs in testing: self-healing tests that repair their own locators and open a pull request for review, generating runnable test specs directly from user stories, and agent-driven exploratory testing with Playwright MCP, where you give the agent a mission instead of a script.

Finally, we make it pay off in production: a CI/CD pipeline with an AI triage brain that classifies every failure as a real bug, a flake, or an environment issue and routes it automatically. The capstone assembles everything into a complete AI QA assistant, and you leave with the adoption staircase: the exact order to introduce each capability at your company. By the end of the course, you'll have a portfolio-worthy AI-powered QA toolkit you can use at work from day one.

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