An organization does not become AI-native by buying a coding assistant. The larger shift happens when specifications, architecture, policy, tests, operational knowledge, and customer context become legible enough for people and agents to work from the same source of truth.

That changes the bottleneck. Producing code gets cheaper, while framing the right problem, defining quality, constraining risk, and evaluating outcomes become more valuable. Engineering leaders have to redesign workflows and ownership—not simply ask teams to generate more output.

The goal is not maximum automation. It is a system where judgment is applied at the right layer, routine translation work disappears, and teams can spend more of their attention on product and operational consequences.