Gen AI pro Web UI testing

Test analysts, manual testers, test automation engineers, QA leads, and developers who want to start systematically using GenAI and LLM in their daily practice when testing web applications.

• LLM models – basic overview
• Vibe coding (examples with Lovable)
• LLM workflows (examples with Playwright AI bot)
• AI agents (planning and reasoning, tools, memory)
• AI-augmented testing – opportunities
• Introduction to MCP: Wopee.io, Playwright, GitHub, Jira
• The future of (AI?) testing

• Introduction
  A brief introduction to GenAI in testing and an overview of the main goals of the workshop. Participants will gain a high-level understanding of where GenAI makes sense in testing today and where its limits are. We will align expectations and define the concrete outcomes participants should take away from the workshop.
• LLM models – basic overview
  We will explain what LLM models are, how they work, and why they are relevant for testing. We will go through the differences between various types of models and ways to deploy them in practice.
• Vibe coding and examples with Lovable.dev
  We will demonstrate the concept of “vibe coding”, meaning rapid creation of functionality and prototypes using LLM-based tools such as Lovable.dev. Participants will see how simple applications can be generated. In the practical part, they will try how an application can be created from a testing assignment.
• LLM workflows
  We will show how to compose workflows from individual LLM calls that genuinely help testing teams. Using examples with the playwright-ai-bot tool, we will demonstrate test generation from user scenarios, screenshots, or an existing application.
• AI agents (planning and reasoning, tools, memory)
  We will explain the difference between a simple LLM call and a real AI agent that plans, uses tools, and works with memory. We will go through concrete testing scenarios where agents can take over part of the tester’s work, such as exploratory testing or building regression suites. In the practical part, participants will try how to use such an agent in a testing context.
• AI-augmented testing – opportunities
  We will look at how to gradually integrate GenAI into existing testing processes without a “big bang” change. We will show where to start with quick wins, from generating test scenarios and planning tests, through review and maintenance, to generating test reports.
• Introduction to MCP: Wopee.io, Playwright, GitHub, Jira
  Participants will be introduced to the concept of MCP (Model Context Protocol) and how it enables LLMs to work directly with tools such as Wopee.io, Playwright, GitHub, or Jira. Through practical examples, they will see how an AI agent can, for example, run tests, read issues, create tickets, or analyze results. In exercises, they will try what these integrations can look like.
• The future of (AI?) testing
  Finally, we will look at trends in AI and the future of testing. We will discuss how the tester’s role may change and which skills will become critical. We will open a discussion about what specifically makes sense to introduce in your team in the near future.