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Break the context window barrier with Amazon Bedrock AgentCore

Amazon Bedrock just solved the context window problem. Here's how to process unlimited-length documents without rewriting your stack.

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The KeyNews take

Why it matters

Amazon is shipping a practical workaround to context-window limits via AgentCore's Code Interpreter, enabling enterprises to process arbitrarily long documents through recursive sub-LLM calls—a key competitive move against OpenAI's extended context models.

The key facts

12 to know
  1. Amazon Bedrock AgentCore Code Interpreter enables Recursive Language Models (RLM)

  2. Supports document processing with no upper bound on context size

  3. Uses persistent working memory for iterative document analysis

  4. Integrates Strands Agents SDK for orchestration

  5. Sandboxed Python environment for sub-LLM calls

  6. Published May 21, 2026 on AWS ML blog

  7. Amazon Bedrock AgentCore Code Interpreter launched with RLM support

  8. Enables document processing with no upper bound on context size

  9. Strands Agents SDK integration for orchestration

  10. Persistent working memory for iterative analysis

  11. Sub-LLM calls from sandboxed Python environment

  12. Solves context window limitation without model switching

Go to the source

AWS Machine Learning Blogaws.amazon.com

Publisher excerpt: In this post, you will learn how to implement Recursive Language Models (RLM) using Amazon Bedrock AgentCore Code Interpreter and the Strands Agents SDK. By the end, you will know how to process documents of varying lengths, with no upper bound on context size, use Bedrock AgentCore Code…
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