The author argues for a shift in focus from Developer Experience (DX) to Agent Experience (AX) in data platform engineering. As AI agents increasingly handle coding and system management, the traditional human-centered design of developer portals and systems is becoming outdated. By 2026, the expectation is that platforms need to be optimized for agents, which require structured, predictable, and programmatically accessible environments. The author stresses that if platforms cater only to human users, they risk becoming bottlenecks in their own operations. To support AX, five key technical priorities are outlined. First, the move from visual interfaces to API-first environments is essential; agents rely on command-line interfaces (CLI) or robust APIs rather than graphical buttons. Second, documentation must be machine-readable, shifting from long tutorials to strict APIs and metadata files that provide clear definitions. Third, using structured formats like JSON or YAML ensures communication is clear and interpretable by machines. Fourth, error messages need to include structured recovery paths, allowing agents to self-correct rather than leaving them at a dead end. Lastly, establishing autonomous discovery standards is crucial for agents to navigate multi-repo environments and access tools seamlessly. The transition to AX is not just a technological shift; it also requires a cultural adjustment within teams. Engineers must rethink their roles from designing user journeys for humans to architecting protocols that facilitate agent interactions. The author invites other platform engineers to reflect on their current approaches and consider how to adapt their platforms for this emerging focus on machine users.