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Coffee With Developers • Mar 16, 2026

Why Testing Matters in AI - Luise Freese and Elio Struyf

Luise Freese , Elio Struyf

Luise Freese and Elio Struyf reveal why letting AI test its own code destroys application stability. Learn how TDD and Playwright provide robust guardrails against unpredictable code generation.

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#1 about 3 min

Adopting modern end-to-end testing for automated deployment pipelines

How quality engineering experience translates into adopting framework tools like Playwright for robust automated test pipelines.

#2 about 2 min

Defining actionable user stories with Gherkin and Playwright

How Gherkin provides structured syntax to describe actionable user stories for scalable automated testing environments.

#3 about 2 min

Writing meaningful test guardrails for AI generated code

Preventing AI coding agents from writing software that merely passes meaningless assertions without verifying actionable functional outcomes.

#4 about 2 min

Preventing unreviewed UI changes with continuous automated testing

Using stable end-to-end testing models to ensure automated coding tools do not silently alter existing user experiences.

#5 about 2 min

Adapting existing test automation scripts for AI agents

How developers can safely reuse existing happy-path test automation workflows to train external AI task agents.

#6 about 3 min

Handling complex API mocks and manual edge cases

Why human validation remains essential for breaking application inputs and correcting inaccurate AI generated API mocks.

#7 about 3 min

Creating shared testing language across diverse engineering disciplines

Reducing organizational friction by uniting developers, quality assurance engineers, and product teams around a common documentation syntax.

#8 about 3 min

Leveraging automated end-to-end tests as living technical documentation

Converting successful product workflows into automated tests to effortlessly generate reliable technical documentation for end users.

#9 about 5 min

Adopting upfront test design for agentic software workflows

Defining strict testing parameters upfront prevents organizations from wasting engineering hours maintaining incorrect AI code generations.

#10 about 8 min

Justifying the return on investment for testing education

Advocating for robust developer training budget by constantly highlighting the overarching business cost of delivering broken software.

Matching moments

2:12 min

The evolving role of software testing in AI development

Jakub Janczyk Jakub Janczyk · World Congress 2026 Europe

1:48 min

The future landscape of artificial intelligence in software testing

Alisa Hrustic Alisa Hrustic · Europe 2026 Virtual

2:06 min

Enforcing behavioral testing patterns in AI development tools

Jakub Janczyk Jakub Janczyk · World Congress 2026 Europe

1:30 min

Integrating artificial intelligence into software testing and requirement engineering

Rene Schenk Rene Schenk · World Congress 2026 Europe

2:49 min

The evolution of software testing using artificial intelligence

Alisa Hrustic Alisa Hrustic · Europe 2026 Virtual

3:01 min

Exploring the expansion of end-to-end testing utility suites

Daniel Afonso Daniel Afonso · World Congress 2025

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