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Explore how organizations can successfully scale AI initiatives beyond pilot projects through dedicated platform teams in this 14-minute conference talk. Discover the parallels between introducing AI and previous technology adoptions like Agile, DevOps, and Cloud computing, where initial pilot projects eventually require centralized infrastructure and governance. Learn about the essential shared components of an AI stack including proxies, caching, testing frameworks, feedback collection systems, and guardrails that platform teams must manage. Understand the practical steps and common challenges involved in enabling AI capabilities across entire engineering organizations through hackathons, training programs, and abstraction layers. Examine how AI platform initiatives integrate with existing Software Development Life Cycle workflows and processes including testing, versioning, observability, and security measures. Gain insights into leveraging collective knowledge from various platform teams including CloudOps, SecOps, Developer Experience, data platforms, and AI platforms to address critical concerns around security, permissions, and performance optimization in AI deployments.
