The AWS Machine Learning Blog presents a four-layer framework for context engineering in production AI agents, arguing that context management is the primary bottleneck in such systems. The four layers are architecture, prompts, file-based tools, and verification agents.
The approach is demonstrated with working code from Deep Insight, an open source multi-agent data analysis solution. It is built on the Strands Agents SDK and Amazon Bedrock AgentCore.
Why it matters
As AI agents move into production, managing the context supplied to models becomes a central engineering challenge. A structured framework paired with a concrete implementation gives teams a reference for how these concerns can be addressed in practice.
Who should care
Developers and teams building multi-agent systems, particularly those working with the Strands Agents SDK and Amazon Bedrock AgentCore, may find the framework and open source code relevant to their work.