Summary

The article discusses how organizations can leverage platform engineering principles to accelerate the development and deployment of generative AI applications. It highlights the challenges faced by organizations in experimenting with generative AI and emphasizes the importance of building reusable components to manage costs and improve efficiency. The article outlines the architecture of generative AI applications, including the integration of various data layers and the role of large language models. It also covers best practices for observability, orchestration, and governance in AI workflows.

Data Problems Addressed

Technologies Referenced