Evals and Guardrails in Enterprise Workflows (Part 3)
Analysis
This article, part of a series, likely focuses on practical applications of evaluation and guardrails within enterprise-level generative AI workflows. The mention of Arize AI suggests a collaboration or integration, implying the use of their tools for monitoring and improving AI model performance. The title indicates a focus on practical implementation, potentially covering topics like prompt engineering, output validation, and mitigating risks associated with AI deployment in business settings. The 'Part 3' designation suggests a deeper dive into a specific aspect of the broader topic, building upon previous discussions.
Key Takeaways
- •Focus on practical implementation of AI evaluation and guardrails.
- •Collaboration with Arize AI suggests use of their tools for monitoring and improvement.
- •Likely covers topics like prompt engineering and output validation.
Reference
“Hands-on patterns: Design pattern for gen-AI enterprise applications, with Arize AI.”