Quality without the bottleneck: QA in the era of AI for decoupled Drupal

AI-assisted development is accelerating delivery—but in decoupled architectures, it’s also reshaping how quality breaks.
Pull requests are larger, more complex, and often generated or heavily assisted by AI. They move fast—sometimes faster than they can be meaningfully reviewed. QA teams are left validating systems they didn’t fully see being built, while the source of truth for requirements becomes blurred across tickets, prompts, and generated code.
In many cases, the implementation is the specification.
This raises uncomfortable questions:

• What does “good coverage” mean when code is generated faster than tests?
• How do you review or validate logic you didn’t explicitly design?
• Where is the source of truth when requirements are implicit or evolving in prompts?
• Can traditional QA even keep up without becoming a bottleneck?

This session doesn’t present a single solution. Instead, it explores emerging patterns teams are experimenting with—TDD, shift-left practices, AI-assisted testing, stronger contracts, and automation-first approaches—and where they succeed or fall short in real-world decoupled systems.
The goal is to reframe how we think about quality in high-velocity, AI-influenced development—and to better understand which problems we’re actually trying to solve.