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Generative AI for Testers

Forum|Forum|1 year ago
April 29, 2025
184 replies
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Generative AI for Testers

By Rahul Parwal

In this on-demand Generative AI for Testers session, you'll learn how to confidently apply Generative AI in software testing and quality engineering.

TL;DR/Key Takeaways

Learn the fundamentals of Generative AI for software testing, including what AI can and cannot do within QA workflows.
Understand Large Language Models (LLMs) in practical terms, including tokens, training data, APIs, and how AI-generated outputs are created.
Explore a proven GenAI framework for testing that covers:
- AI as an assistant
- Experimentation and transformation
- Coding and test automation
- Learning and summarization
Apply GenAI to:
- Test case generation
- Test data creation
- Requirements reviews
- Risk identification
- Bug report authoring
- Test documentation
Improve test automation productivity through AI-assisted code generation, refactoring, debugging, modularization, and rapid prototyping.
Master prompt engineering for testers using practical prompting techniques that improve consistency, clarity, and accuracy.
Understand how to ground AI responses through Retrieval-Augmented Generation (RAG) and when to use in-context learning versus fine-tuning.
Learn how to evaluate and select the right model based on cost, performance, context window size, relevance, and ecosystem support.
Recognize and mitigate common AI risks, including hallucinations, bias, context loss, and reliability challenges.
Gain hands-on experience with modern AI workflows, including text-to-visual generation, tool discovery, multi-model environments, and local AI solutions.
Follow AI safety and responsible usage practices, including data privacy considerations and protecting sensitive company information.
Demonstrate business impact by measuring productivity gains, quality improvements, and team adoption outcomes.

About This Session

Generative AI is rapidly becoming part of everyday software testing and quality engineering practices.

This on-demand Generative AI for Testers session is designed to help testers explore practical applications of Generative AI, understand its strengths and limitations, and discover ways it can support testing activities. Through real-world examples and hands-on exercises, participants can build knowledge, experiment with new approaches, and develop skills they can apply within their own teams and projects.

📁Chapters:

🧠 What You'll Learn

By the end of this session, you will have a stronger understanding of how Generative AI can support software testing and quality engineering. You'll explore practical techniques, tools, and workflows that can help you:

Understand core Generative AI concepts and terminology.
Experiment with AI-assisted testing approaches.
Evaluate where AI can add value throughout the testing lifecycle.
Apply prompting techniques and model selection considerations.
Explore strategies for introducing AI into testing workflows responsibly and effectively.

These outcomes will prepare you to confidently apply Generative AI in real-world testing scenarios.

👨‍🏫 Led by Rahul Parwal

This session is led by Rahul Parwal, a highly experienced software testing professional, speaker, and author.

With extensive expertise across web, desktop, API, and mobile testing, Rahul combines practical testing knowledge with modern AI approaches to sharing practical experiences, lessons learned, and examples from real-world testing environments.

📜 Certificate of Completion

Participants who complete the session content, exercises, and assessments may request a Certificate of Completion.

The certificate recognizes participation in the ShiftSync learning experience and completion of the suggested activities. It is intended to acknowledge continued learning and skill development within the community.

Participants will also receive a digital badge on their ShiftSync profile that highlights their accomplishment and engagement with the topic.

Completion Requirements

You may revisit any completed step at any time for review.
A minimum score of 75% is required for all quizzes and assessments.
Example score breakdown:
- Quiz 1: 75/100
- Quiz 2: 75/100
- Quiz 3: 75/100
- Quiz 4: 75/100
- Final Assessment: 80/100
- Total: 380/500
Exercises and final assessments may be resubmitted if you would like to improve your score.

Please note: Certificates of Completion are typically issued within one business day of successfully completing all session requirements.

🚀 Get Started

Explore practical applications of Generative AI in software testing, learn from real-world examples, and earn a Certificate of Completion recognizing your participation in the session.

👉 Start Learning Now

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D

Dhanashree

Apprentice

🎓 Course Overview: Generative AI for Testers

TL;DR/Key Takeaways

Learn Generative AI for software testing fundamentals, including what GenAI can and cannot do in QA workflows.
Understand LLMs for testers in plain language, including how models use tokens, training data, and APIs to generate outputs.
Apply a practical GenAI framework for QA: assistant, experimentation and transformation, coding and test automation, learning and summarization.
Use GenAI for test case generation, test data generation, requirements review, risk identification, bug report writing, and test documentation.
Improve test automation productivity with GenAI support for boilerplate code, refactoring, modularization, debugging, and rapid prototyping.
Master prompt engineering for testers with proven prompt patterns that improve clarity, accuracy, and repeatability.
Learn how to ground answers using RAG (Retrieval Augmented Generation) and when to use in-context learning vs fine-tuning.
Choose the right model using LLM selection criteria such as cost, performance, context window, relevance, and community support.
Identify and mitigate common LLM risks: hallucinations, bias, context loss, and other reliability syndromes.
Practice with real tools and workflows, including text to visuals, tool discovery, multi-model workspaces, and private local model options.
Follow AI safety for QA basics, including data privacy and avoiding sensitive company information in public LLMs.
Prove business value with metrics by measuring time saved, quality improvements, and adoption outcomes for your testing team.

Generative AI is revolutionizing software testing, transforming it from a futuristic concept into a present-day necessity. To equip testers with the skills needed to navigate this evolving landscape, Tricentis presents the Generative AI for Testers course. This interactive mini-course is designed to help testers understand, apply, and benefit from Generative AI in their testing processes.

📁Structure of the course: