After this training, you will:
- Embrace the “Quality as Code” mindset by structuring test plans and specifications in plain files (using formats like Markdown, Gherkin and Gauge).
- Use the essential features of Git to manage all quality assets as a version-controlled ‘single source of truth’, enabling collaboration and control.
- Understand why context is vital for AI and how to prepare a repository to serve as a “brain” for AI assistants.
- Write and understand fundamental browser automation scripts with Playwright.
- Generate and refine Playwright scripts using context-aware AI tools (like KiloCode in VSCode) based on your own Markdown documentation.
- Integrate these automated Playwright tests into a basic CI/CD pipeline (using GitHub Actions) to provide rapid feedback.
The future of quality assurance is not about choosing between manual testing and complex coding. It’s about a mindset: “Everything is a file.” This course bridges the gap between test plans and automation scripts by teaching an end-to-end process that is directly applicable in the real world.
This course teaches you how to apply AI in a practical way by giving it the right context from your own work. You will gain the skills to connect with DevOps teams and participate in a CI/CD process. You will learn not just the tools, but a workflow that enables effective collaboration, making you a valuable contributor to fast, high-quality software delivery.
This course is designed for quality professionals ready to lead the change. It’s the perfect, practical next step for those with a background in testing methodologies like ISTQB or TMap. No prior experience with Git or Playwright is necessary to participate.
- Software Testers and QA Engineers who want to learn a practical and modern automation workflow.
- QA Leads and Senior Testers aiming to implement a future-proof, efficient, and AI-enhanced quality strategy for their teams.
Day 1: The Foundation – “Everything is a File”
Module 1: The New Mindset: From Documents to a Repository
Why scattered documents fail in a fast-paced world.
The ‘Quality as Code’ principle: treating tests and docs like source code.
Hands-on Lab: Structuring your first test plan in Markdown.
Module 2: Git for Quality Professionals
The essentials for this workflow, no more, no less: repository, commit, branch, pull request. How this enables control and collaboration.
Hands-on Lab: Creating a Git repository for your quality assets.
Module 3: Introduction to Browser Automation with Playwright
Core concepts: locators, actions, and assertions. The power of browser control.
Hands-on Lab: Manually writing your first Playwright script based on your Markdown specification.
Day 2: The Acceleration – Intelligent, Context-Aware Automation
Module 4: The Power of Context for AI
Why AI needs your repository: moving beyond simple prompts.
Preparing your repository to be the “brain” for your AI assistant.
Module 5: AI-Assisted Script Generation in Practice
Introduction to advanced concepts like the Model Context Protocol (MCP).
Hands-on Lab in VSCode: Using tools like KiloCode to interact with your browser and generate advanced Playwright scripts based on the full context of your Git repository. This is where the magic happens!
Module 6: Closing the Loop with CI/CD
Integrating your Playwright test suite into a GitHub Actions pipeline.
Analyzing results and understanding the fast feedback loop.
The new workflow: Update the Markdown, commit to Git, and see the pipeline run.
As a software engineer and entrepreneur, Simon Koudijs focuses on a practical goal: building quality software that is delivered reliably. His background in Electrical Engineering taught him to measure and solve problems in small steps; a skillset he has applied everywhere, from embedded programming and small startups to large companies like the pension fund PGGM.
In his daily work, he builds a software product. He uses modern AI tools to get the job done, but isn’t one to be fooled by the hype. This training is based on that hands-on experience. You’ll learn the practical skills and the “why” behind them, so you can confidently apply these methods to build better software, faster.
