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Learn how to build reliable, deployable AI agent systems by applying containerization principles to overcome the operational chaos that typically plagues AI development in this conference talk. Discover why testing outputs alone is insufficient when dealing with unpredictable LLMs and opaque workflows, and explore how the creator of Docker approaches these challenges by engineering reproducible execution workflows built on rigorous architectural discipline. Understand how containerization can be applied not just to deployment but to each individual step of an agent's workflow, providing essential isolation and environmental consistency. Master the combination of granular container approaches with patterns like immutable state management to contain agent chaos, unlock effective testing capabilities, simplify debugging processes, and bring essential control and predictability to AI agent development. Gain insights from Solomon Hykes' experience in tackling infrastructure complexity as he demonstrates how platform engineering principles can be applied to the emerging AI landscape, helping you move beyond fragile prototypes to build powerful AI agents you can ship with confidence.
