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EuroSTAR Conference

Europe's Largest Quality Engineering Conference

Tutorial A

One Agent to Watch Them All: Building an AI Test Monitor

Paula Bassagañas

09:00 - 12:30 CEST, Monday 15th June

Are you tired of keeping one eye on your CI/CD pipelines — checking builds, digging into logs, and chasing down failing commits? Talking to AI about it won’t help much: testers need actions, not just words.

In this hands-on tutorial, you’ll learn how to build your own AI test monitor using Model Context Protocols (MCPs). MCPs act like a modern USB port for AI: they turn your existing APIs into contracts that AI can actually use. With them, you’ll create an agent that:

  • Watches CI/CD executions in real time
  • Reads build outcomes, failing commits, and test metadata
  • Analyses results to surface root causes and impacted areas
  • Sends a structured email or notification with logs and evidence

 

By the end of the session, you’ll have a working MCP-powered agentic AI that doesn’t just chat — it acts. You’ll walk away with a repeatable blueprint to extend this approach to your own pipelines, tools, and reporting needs, turning AI into a teammate in your software delivery process.

What you will learn

  1. Learn what Model Context Protocols (MCPs) are and how they let AI connect safely to existing APIs
  2. Build your own AI test monitor that watches CI/CD pipelines, analyzes failures, and reports results
  3. See how to integrate MCPs with tools like GitLab, Github or Playwright for end-to-end workflows

Session Details

  • Intermediate
  • 3hrs
  • Interactive Tutorial
  • Implementing/integrating AI tools
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Check out this video from Paula Bassagañas to hear more about her talk on Building an AI Test Monitor.

We look forward to welcoming you to EuroSTAR 2026.

Session Speakers

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Paula Bassagañas

Boehringer Ingelheim, Germany

Paula is an IT Architect based in Germany, specializing in Test Engineering and Backend development. Her career spans various industries, with a focus on the health sector, where she has developed data platform test strategies, particularly for ETL processes.

Currently, Paula’s working on implementing AI in testing to enhance automation and efficiency. She has extensive experience in DevOps, backend development, cloud computing, and testing methodologies to ensure high-quality software.

Additionally, Paula teaches at Pompeu Fabra University, mentoring future IT professionals. Paula is committed to continuous learning and sharing her knowledge to drive growth and excellence.

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