LEARN. PRACTICE. GROW.Concept and mechanism
An AI-generated claim about a dependency should be treated as a hypothesis until evidence confirms it. The same care with assumptions applies to quality: green local tests do not prove message contracts are compatible. Use frequent integration checks to discover incompatibilities before handover. A build pipeline does not resolve the gap if it only compiles code and leaves integration until the end. Choose checks representing product risks and retain evidence of what actually ran. Automation can accelerate feedback, but results only cover configured checks. Do not confuse absence of a reported error with absence of a defect.
Guided application
A permanent dependency on one WebSphere specialist can be reduced through supported work, documentation, and practice within appropriate authorization. Shared competence does not mean anyone can change production without preparation. Also include operational quality in necessary work: detection, recovery, capacity, and support. A functional demonstration may pass while recovery evidence remains missing. Make that distinction understandable to the Product Owner and release owners. A technical requirement should have a purpose and observable criterion, such as demonstrating that support can execute the procedure in a safe environment. Avoid postponing all operational learning until the service is already exposed.
An incompatible message contract needs integrated checking; repeating only the local test may continue showing green.
Common pitfalls
Compilation as complete quality; AI as infallible evidence; collective knowledge as uncontrolled access; demonstration as operational readiness.
Related topics: Priorities, dependencies, and PI Planning · Integrated execution, release, and improvement
Useful quality includes integrated behavior and operating conditions.
Reference: Built-In Quality · AI-Empowered SA; official study guide May 27 2026; current product page publishes different ranges in three domains