Felipe Huici explains how Unikraft achieves millisecond cold boots, stateful scale-to-zero, and extreme density for sandboxing AI workloads. He discusses isolation primitives, Linux kernel optimizations, and snapshotting tricks, demonstrating how to maintain sub-10ms performance at scale while integrating seamlessly into Kubernetes environments with hardware-level security.

The panelists explain how platform teams adapt to support AI-assisted engineering, highlighting which capabilities belong in the platform. They discuss trade-offs between standardization and developer autonomy, while sharing strategies to manage AI tooling, security guardrails, and shifting workflows.

Joe Cassavaugh shares his journey from software engineer to successful solopreneur with a $2M+ indie franchise. He explains how he scaled production to 10 games in 5 years, adopted Unity to boost velocity 4-6x, optimized content pipelines, and leveraged refactoring patterns. He discusses key trade-offs between corporate engineering and solopreneurship for senior devs and leaders.

Zhou Yu discusses why AI agents stall in demo phase and shares how simulation-driven testing solves compliance and reliability bottlenecks. Learn how Columbia and Arklex AI use synthetic user personas, trajectory entropy, and automated CI/CD pipelines to evaluate multi-turn agents, catch edge cases before deployment, and scale self-learning workflows in production.