Explores how AI-powered coding assistants are transforming software development, with a focus on using LLMs as tools to build systems rather than deploying them as the systems themselves. Discusses practical approaches for leveraging state-of-the-art models in production through human-in-the-loop distillation, enabling teams to create smaller, faster, and more maintainable AI components that can be run in-house. Emphasizes the continued importance of code and open-source ecosystems in the AI development landscape.
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