AWS enters the context layer race with a graph that learns from agents, not manual curation

Back to Devoured - June 22, 2026

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AWS enters the context layer race with a graph that learns from agents, not manual curation

AWS is introducing a knowledge graph layer designed to dynamically learn context from AI agent interactions rather than static manual curation.

What: AWS Context, S3 Annotations, and Glue Data Catalog integration allow enterprise AI agents to access metadata stored in Iceberg tables via Athena, Redshift, and Spark.

Why it matters: This indicates a shift where infrastructure providers are building native 'context stacks' to reduce the hallucination and grounding problems inherent in standard RAG architectures.

Decoder

RAG (Retrieval-Augmented Generation): An AI framework that improves model accuracy by retrieving data from external sources rather than relying solely on training data.

Original article

AWS announced a context stack for AI agents: AWS Context, S3 Annotations, and skill assets in Glue Data Catalog. AWS Context builds and improves a knowledge graph from enterprise data, rules, and domain knowledge, with IAM and Lake Formation access control. Metadata sits in Iceberg on S3 Tables and is exposed through Athena, Redshift, Spark, and MCP tools.

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