Raw AI models are great at many things, but can we really trust them out of the box when it comes to scalability? We’ve all heard about AI’s tendency to hallucinate and the need for caution—but is there a way to reduce this risk? In our upcoming webinar, we’ll walk you through a customer case where we did exactly that.
In this session, we’ll present a customer case where we developed a test case generator. We relied on the model’s ability to cover requirements and acceptance criteria in the test cases it produced, and we’ll share our approach to fine-tuning the model. You’ll gain insights into:
Internal GPT parameters
Mitigating known drawbacks
Best practices for writing GPT system instructions
Please note: This webinar assumes a basic understanding of ChatGPT.
This webinar is intended for anyone working with software testing and quality assurance, or those interested in learning how to get more out of their GPT models. It is particularly relevant for:
Testers or Test Managers
Product Owners
Team Leads
Anyone interested in future testing tools and methodologies
The webinar was held on Wednesday, May 28, 2025, from 09:00 – 10:00 (CET).
This webinar was held in Danish
TestHuset/Trifork QI, Head of Technolog & Innovation
The webinar was hosted by TestHuset Head of Technology & Innovation, Ermin Duna.
With broad experience in testing and technology — and a deep understanding of testing processes and the potential of AI — Ermin will provide valuable insights into how you can optimize AI for your own processes.
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