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Learn to build comprehensive AI evaluation frameworks in this hands-on workshop that guides you through the complete AI evaluation lifecycle using Braintrust, covering everything from initial prompt testing to production monitoring. Master both offline and online evaluation strategies to ensure your AI applications perform reliably in real-world scenarios. Explore practical techniques for implementing logging and feedback systems that capture meaningful performance data throughout your AI application's lifecycle. Discover how to establish effective human review processes that complement automated evaluation methods and provide qualitative insights into AI system performance. Gain expertise in transitioning evaluation practices from development environments to production systems, ensuring continuous monitoring and improvement of AI application quality. Understand how to design evaluation metrics that align with business objectives and user expectations while maintaining technical rigor. Practice implementing evaluation pipelines that can scale with your AI applications and provide actionable insights for iterative improvement.
