BDD automation is often where expectations and reality start to drift apart. Teams talk about “automating BDD” as if it is the goal in itself. In practice, automation is just one part of the picture. It’s useful only if it reinforces the behaviour that was agreed earlier — not if it quietly replaces it. Automation […]
Gherkin scenarios in Jira are often treated as the point where BDD becomes “real”. In practice, formulation is where BDD either becomes genuinely useful — or quietly turns into another artefact that people stop trusting. Formulation sits between discovery and execution. It is the stage where discussions and examples are turned into something precise enough
Most Agile teams say they practise Behaviour-Driven Development. Fewer can clearly point to where the behaviour was actually agreed. That usually comes down to discovery. Discovery is the point where teams are supposed to align on what a system should do before development starts. It’s also the stage that quietly gets rushed, diluted, or pushed
AI-driven BDD is increasingly being used by Agile teams to support the creation and maintenance of Behaviour-Driven Development scenarios. AI is starting to play a role in how Agile teams create and maintain Behaviour-Driven Development (BDD) scenarios. Its value, however, is often misunderstood. AI does not replace collaboration, product ownership, or decision-making. In modern BDD
Scaling BDD in Jira often starts with good intentions. Teams collaborate, scenarios are discussed, and behaviour is clearly understood. The challenge appears later — when teams grow, projects multiply, and delivery becomes more complex At that point, BDD can either mature into a shared, scalable practice, or quietly degrade into a set of artefacts that
