The rise of AI-generated code and autonomous development agents introduces incredible speed, while simultaneously introducing risk into the cloud native software lifecycle. Platform teams are faced with supporting developer velocity and governing the quality, safety, and compliance of code changes created by and for AI.

This talk explores how platform engineering teams can harness agentic AI to embed continuous, context-aware code quality directly into infrastructure and application pipelines. Based on real-world implementations, platform engineers and AI/ML practitioners will learn how “agentic” workflows enable scalable quality gates that adapt to evolving codebases and organizational standards, assisting human reviews and ensuring trust in AI-driven development.