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Deploying AI agents from research labs into real-world production environments presents significant hurdles, according to a recent online discussion. Key challenges identified include rigorous pre-deployment testing and evaluation to ensure reliability and safety, maintaining runtime visibility and debugging capabilities for effective monitoring and issue resolution, and achieving comprehensive control over the entire agentic stack. These issues underscore the intricate nature of transitioning AI from theoretical models to practical applications and highlight the need for robust development and deployment strategies. The discussion originated on Reddit: [https://old.reddit.com/r/artificial/comments/1ofjpcz/whats_the_hardest_part_of_deploying_ai_agents/]