Organizations must transform their infrastructure to accommodate agentic AI, as existing systems built for humans are proving inadequate. Meta's VP of Engineering, Barak Yagour, highlights a 30x increase in agentic queries hitting Meta's data systems in just six months, reflecting a broader trend where automated traffic now surpasses human traffic on the internet. This shift is breaking fundamental assumptions around capacity, identity, and velocity within enterprise infrastructure. Capacity issues arise as a single engineer can spawn numerous agents, generating massive load overnight, necessitating agent-aware infrastructure with dynamic controls. Identity is also strained because agents do not fit traditional access control categories, requiring new frameworks. Velocity, too, is impacted as faster code generation by agents outpaces the rest of the development pipeline, demanding acceleration across the board. Data is particularly critical, with Meta developing "trusted data environments" to maintain governance and human oversight while granting agents more autonomy. Furthermore, Meta's reasoning models require extensive, real-time data, leading to a shift from batch processing to real-time streaming and schema-aware storage to prevent GPU starvation. This evolution in data infrastructure directly feeds into conversational recommendation systems that reason about user intent rather than simple keywords. Yagour emphasizes that agents, data, and recommendations form a reinforcing flywheel, driving continuous innovation. He warns that the industry has a limited window, perhaps 20 months, to rebuild infrastructure for a future where humans and agents collaborate at scale.