Artículo: AMZ-B0G2GS38J2

Agentic Testing with Playwright: Build, Generate, and Heal E2E Tests with AI Agents, GitHub Copilot, and the Model Context Protocol (MCP)

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  • Stop Guessing. Start Knowing. For decades, E2E test automation has been a paradox: the more tests we build to ensure quality, the more fragile, high-maintenance code we create. We spend more time healing brittle locators than building new features. While vision-based AI promised a solution, it only traded one form of flakiness for another: probabilistic guesswork. This book provides the real solution. Agentic Testing with Playwright introduces a fundamental shift from test automation to test autonomy. The breakthrough is the Model Context Protocol (MCP), a new standard that gives AI agents direct, deterministic access to the browser's accessibility tree. The AI no longer guesses; it knows. This hands-on guide is for professional automation engineers, QA leads, and full-stack developers ready to evolve. You will move beyond writing scripts and learn to orchestrate a team of specialized AI agents: The Planner Agent: Ingests a PRD or user story to autonomously generate a comprehensive test plan. The Generator Agent: Takes the plan and writes production-ready, accessibility-first Playwright code. The Healer Agent: Monitors test execution, detects failures, and autonomously repairs broken locators, finally solving the maintenance nightmare. Inside, you will learn to: Configure the Playwright MCP server to connect AI to a live browser. Use GitHub Copilot as a "browser-aware" pair programmer to build and verify UI features in real-time. Build a natural language automation bot that can complete complex tasks from a single prompt. Secure your agents for enterprise use, addressing the "confused deputy" problem and prompt injection. Build a capstone project that generates an entire E2E test suite from scratch. The role of the automation engineer is not disappearing; it is being elevated from script-writer to AI orchestrator. This book is your blueprint for that transition
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