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Learn how to scale AI engineering capabilities across organizations through dedicated AI Platform teams in this conference talk from the AI Engineer World's Fair. Discover the evolution from pilot AI projects to enterprise-wide AI platform implementation, drawing parallels to successful Agile and DevOps transformations. Explore the shared components of the AI stack including proxies, caching, testing, feedback collection, and guardrails that form the foundation of scalable AI infrastructure. Understand the practical steps and challenges involved in enabling AI capabilities across entire engineering organizations through hackathons, training programs, and abstraction layers. Examine how AI platform engineering integrates with existing Software Development Life Cycle workflows and processes, covering testing, versioning, observability, and security considerations. Gain insights into leveraging knowledge from existing platform teams including CloudOps, SecOps, Developer Experience, and Data Platform teams to address security, permissions, and performance challenges in AI implementations. The presentation provides a comprehensive framework for organizations transitioning from individual AI engineers to systematic AI platform engineering approaches.
