As AI tools become increasingly sophisticated, they offer developers new ways to streamline workflows and generate content. However, the true value of these tools lies not in their outputs alone, but in how we critically evaluate and refine those outputs. This is especially crucial when using AI to generate user stories and other project documentation. In this post, we’ll explore essential critical thinking skills and practical steps for evaluating AI-generated content, ensuring it aligns with project requirements and serves as a catalyst for deeper team discussions. ...more

Imagine this scenario: You’re deep into an Agile project, racing towards your next milestone. Amidst the flurry of sticky notes, stand-up meetings, and code reviews, a crucial question arises: “Didn’t we tackle a similar challenge last month?” The memory of a discussion lingers, but the specifics are hazy, and documentation is nowhere to be found. This situation is common in many Agile teams. ...more

As we continue to integrate AI into the process of software development, it’s essential to look beyond just writing user stories. While user stories are fundamental in defining the “what” of a project, there are tools and techniques that can greatly enhance our understanding of the “how.” This post will explore how Gherkin, sequence diagrams, and Mermaid notation can be used in conjunction with AI to bring greater clarity to functional requirements and streamline the process of automated testing. By leveraging these tools, we can create a more comprehensive and actionable set of specifications that bridge the gap between high-level user stories and detailed technical implementations. This approach not only enhances communication between stakeholders but also paves the way for more efficient development and testing processes. ...more