Infrastructure Patterns for Scaling GenAI Products

As generative AI moves from prototypes to production, the challenge shifts from “Can we build it?” to “Can we scale it reliably, securely, and cost-effectively?” Scaling GenAI products requires more than bigger models or faster GPUs; it calls for deliberate infrastructure patterns that balance experimentation with stability, performance with observability, and rapid iteration with governance. Leaders must learn how to design architectures that support multi-agent collaboration, context-aware systems, and evaluation pipelines while avoiding pitfalls like runaway costs, latency bottlenecks, and brittle integrations. This discussion will explore the infrastructure strategies and tradeoffs that enable teams to move from demos to durable products. Participants will leave with practical insights into how to future-proof their GenAI platforms and scale responsibly without losing speed or trust.