In this episode, we explore the concept of the 10-Minute Test Plan and why “failing fast” is beneficial for agile development. We’ll discuss the ongoing importance of manual testers in the software development lifecycle and delve into the unique culture of “Googliness” at Google. We also discuss the benefits of Story Mapping.

We’ll emphasize the importance of empowering your team to make decisions and why allowing them to make mistakes can lead to growth and innovation. We also cover the significance of measuring what matters and adopting a holistic approach to software engineering.

Additionally, we highlight Google’s Auto-Test system and the practice of dogfooding, as well as the value of fast feedback loops. Finally, we examine the key characteristics that define a good leader in the tech industry.

Join us for a deep dive into effective testing strategies and leadership principles.

References:

• The Weasel Speaks Blog
• How Google Tests Software
• Holistic Testing: Weave Quality into Your Product
  

In this episode, we delve into the principles of holistic testing and the whole-team approach, emphasizing the importance of creating an environment where every team member feels empowered and takes ownership of their work. We discuss strategies for accurately estimating project timelines and explore how Google employs “dogfooding” — testing products internally before releasing them to external customers.

We also highlight the significance of fostering a continuous-learning mindset within your team. Finally, we explore how the “Goal-Question-Metric” approach can be used to identify the metrics that genuinely matter for your projects.

Join us to learn how to build a culture of empowerment, continuous improvement, and effective measurement in your software development and testing processes.

References:

• The Weasel Speaks Blog
• The Feiner Points of Leadership: The 50 Basic Laws that Will Make People Want to Perform Better for You
• Leadership on the Line: Staying Alive through the Dangers of Leading
• Holistic Testing: Weave Quality into Your Product
• How Google Tests Software
  

In this episode, we delve into the world of Prompt Engineering, specifically tailored for software testers.

Discover how to extract the most precise information from Large Language Models (LLMs) using three distinctive frameworks:

• RACE: Role, Action, Context, Expectation

• COAST: Context, Objective, Actions, Scenario, Task

• APE: Action, Purpose, Expectation

Learn why it’s crucial to define the AI’s role and provide ample context to ensure accurate responses. Find out how to refine your queries if you’re unsatisfied with the answers, and explore techniques like asking for more details or inquiring about the AI’s confidence in its response.

We also explore innovative ways to enhance your testing processes, such as uploading UI screenshots to generate test cases or even having the AI produce test cases in CSV format for seamless integration with your test case management system.

Additionally, we discuss the intriguing decline in Stack Overflow traffic due to the rise of AI, and the potential long-term impact on AI quality as these models rely on platforms like Stack Overflow for training data.

Tune in to gain valuable insights and elevate your software testing with the power of AI!

More Resources:

• https://www.linkedin.com/pulse/prompting-testers-jason-arbon/
• https://testsigma.com/blog/prompt-engineering-for-testers/
• https://www.linkedin.com/feed/update/urn:li:activity:7256493948087476224/