Day 1:QA to AI Training | Reengineering Test Lifecycle with Selenium, Karate, Playwright MCP, Cursor

Welcome to Day 1 of the ITeLearn.com QA to AI training! This session launched our journey to transition from traditional QA methods to modern, AI-first Quality Engineering (QE). The overall goal is to equip software testing professionals with AI skills, enabling them to modernize QA/QE practices, reengineer the test lifecycle, and accelerate career growth.
In this intensive session, we explored the current world of software testing within the context of AI and laid the foundational groundwork for mastering new concepts and tools.
Key Topics Explored on Day 1:
1. Software Test Life Cycle (Reengineered): We discussed how to reengineer the Software Test Life Cycle, focusing on concepts like Shift-Left AI Testing and the shift from QA to AI-first quality engineering.
2. Test Artefacts using AI: We explored the creation of critical Test Artefacts—including Test Strategy, Test Plans, Test Cases, and Test Data—using AI for both UI and API applications. This included reviewing sample strategies and plans generated for demo applications.
3. Leveraging LLMs for Documentation: We demonstrated the power of Large Language Models (LLMs) like ChatGPT and Claude to quickly generate concrete, well-structured test documents and artifacts.
4. Building Automation Suites with AI Tools: A significant focus was placed on starting the build of a test automation suite using popular tools within the Cursor AI-powered IDE.
◦ We initiated the setup for Selenium and Karate. Selenium is used to teach foundational test automation concepts.
◦ We specifically explored Playwright with MCP (Model Context Protocol). MCP is a critical concept that acts as a connector between AI models and automation teams, allowing AI to autonomously automate browser actions without extensive manual code setup.
◦ Cursor AI was shown assisting in "Vibe Coding" by generating structured Python scripts for Selenium tests, often utilizing the Page Object Model (POM) structure.
5. Environment Setup: We covered the necessity of installing key Python (Py) and other libraries (like Selenium and Webdriver Manager) required to run these new AI-generated tests. Python is considered the fundamental language for building AI solutions and automation frameworks.
We saw strong interest and great energy from the audience. We look forward to delving deeper into these topics in our next sessions as we continue researching and mastering AI-driven testing together.
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Great Energy and a Big thanks ITeLearn students and back office team.