A Three-Day Rapid Software Testing Class
This class builds on the Rapid Software Testing methodology and applies it to AI. We show how RST can be used to test AI, and we show how you can use AI to help your testing.
Over the last few years, AI has gone from a set of emerging technologies to an industry obsession. Testers are being pressed to test products with AI features, and to use AI in their work. But too much of that work is “slop.” Too much of it is fake testing.
Whether designed for classification or prediction, or for generating text or code, all forms of AI have this in common: they are black boxes, imbued with magical behaviors and properties, whose behavior is neither controlled, nor understood, nor otherwise known to be safe. A responsible approach requires us to know enough about them to be aware of the risks—which means we must know how to test them. When we use AI to help us test, we must be able to critically analyze the work that AI does for us.
Testing has traditionally been framed as formalized, procedurally structured test cases that check output against specific, prescribed results. We never thought that was a good way to think about testing, but it is even less useful for testing AI technologies whose output is non-deterministic by design. The Rapid Software Testing approach—including its approach to automation—is designed to address that problem by building the test process around skilled testers rather than a set of canned practices or templates.
The RST methodology is focused on agency and skill, which come together to make responsible testing possible. We put testers at the center of testing, even as testers make extensive use of tools. In the age of popular AI, this is more important than ever. In a manner of speaking, all serious users of AI must become testers, now.
In this class, we will challenge you to use assistive AI to help you perform testing. Therefore you will need access to some sort of GenAI tool such as ChatGPT, Gemini, Claude, etc. We will also be talking about the use of agentic coding tools in testing, so you might also find it useful to have access to a tool such as Claude Code, Cursor, or Copilot.
RST: Testing, Automation, and AI can be presented in person or online.
About the Authors
This class has been co-developed by James Bach and Michael Bolton, the authors of the Rapid Software Testing methodology.
Michael Bolton started in technology work as a programmer in 1988. Since then, he has worked in testing, program management, consulting, training, customer support, and documentation, developing and using tools all the way along.
James Bach is a developer-turned-tester involved with automation in testing since 1987. James’ team was among the first to use spreadsheets to implement data-driven and keyword-driven automation. One of his most popular articles ever was Test Automation Snake Oil, written about the exaggerations and lies told by test tool companies in the 1990’s — the same silliness common among tool vendors today.
Who Should Take This Training
RST and AI is for you if you take testing seriously and want to have pride in your work:
- If you are a tester with a basic understanding of how to use tools like ChatGPT and who needs to test AI or wants to use AI in testing.
- For best results, we recommend that you first take the foundational RSTE class. But it is not a requirement.
- If you are an experienced tester, we will help you put words to the tacit skills you have gained over time and provide exercises that help you refine them. You will appreciate that RST is a practitioner-centered methodology– you are in control.
- If you are a technical tester, you will learn how your technical knowledge and ability to write code can supercharge the testing process.
- If you are a developer who does some testing, your deep knowledge of product internals is both a crucial resource and a potential liability. You’ll learn how to improve the intrinsic testability of the product and how to manage your biases.
- If you manage people who test, you have the power to steer them and create an environment to help them do their most effective work. You will learn what good testing looks like, how to judge the progress of testing, and how to set high, yet reasonable expectations for the testing process.
- If you are a domain expert who does some testing, we will help you apply your deep knowledge of how the product is used and who uses it. You’ll learn how to find better bugs during acceptance testing—and help others do it too.
- If you work with people who test, you will gain an appreciation for the challenges of testing, discover how you can support the testing process, and learn what good testing can do for you.
Goals of RST and AI
- To teach you how to plan and administer a test strategy that makes effective use of AI and other kinds of automation.
- To teach you how to approach the testing of an AI-powered product.
- To introduce you to RST methodology if you have not yet been exposed to it.
Main Topics Covered
This class is taught Socratically, with exercises, discussions and illustrations of automation within the RST methodology. Class discussions and debate address students’ questions and specific needs. We all learn from the unique perspective that each student brings to the class.
Here are some of the topics we can cover based on time and on the needs of the participants:
- What Rapid Software Testing is and how differs from other methodologies
- The general nature of AI and why it is the hardest thing to test
- What test strategy is, why it matters, and how to construct one
- How to think about automation in testing
- How testing with AI requires a manageable tempo and constant vigilance
- How testing AI requires highly probabilistic and exploratory methods
- How agentic coding allows testers to make powerful test tools like never before
How This Class Compares To Our Other RST Classes
We talk a lot about test strategy and a little about automation in each of our classes. This class focuses on incorporating tools and automation into your test strategy. However, this class does not attempt to teach you the mechanics of how to code or how to test.