Architect a mature generative AI foundation on AWS

Generative AI applications seem simple—invoke a foundation model (FM) with the right context to generate a response. In reality, it’s a much more complex system involving workflows that invoke FMs, tools, and APIs and that use domain-specific data to ground responses with patterns such as Retrieval Augmented Generation (RAG) and workflows involving agents. Safety controls need to be applied to input and output to prevent harmful content, and foundational elements have to be established such as monitoring, automation, and continuous integration and delivery (CI/CD), which are needed to operationalize these systems in production.

Many organizations have siloed generative AI initiatives, with development managed independently by various departments and lines of businesses (LOBs). This often results in fragmented efforts, redundant processes, and the emergence of inconsistent governance frameworks and policies. Inefficiencies in resource allocation and utilization drive up costs.

To address these challenges, organizations are increasingly adopting a ...