The role of a QA engineer is expanding. With AI agents gaining new capabilities through the Model Context Protocol (MCP), testers can leverage them to go beyond detecting defects to reproducing them, pinpointing root causes, and implementing validated fixes. This is making it possible for QA professionals to work across design, development, and testing in ways that were once the domain of separate specialized roles. The traditional boundaries between QA, frontend, backend, and automation engineers are becoming less relevant as AI handles much of the heavy lifting, letting individuals focus on decision-making and delivering quality.

In this talk, we will look at how MCP-enabled AI can become a partner throughout the entire product lifecycle, from the earliest design conversations to validating production releases. You will see how the same workflows that speed up bug detection can also improve coverage, accelerate delivery, and expand the scope of what a single engineer can achieve. Along the way, we will explore what this shift means for building adaptable, cross-skilled teams and for rethinking the way QA and development collaborate in an AI-driven world.