Build context-rich research agents with Deep Agents and Bedrock AgentCore

This article demonstrates building a competitive research agent using LangChain Deep Agents and Amazon Bedrock AgentCore, with parallel browser automation and data analysis capabilities.

• Deep Agents orchestrates specialized subagents to manage context window efficiently
• Three parallel browser subagents research competitors in isolated MicroVMs concurrently
• Analyst subagent uses Code Interpreter to generate comparison charts and reports
• AgentCore Memory stores insights for retrieval in future research sessions
• Coordinator agent manages workflow, checks memory, and synthesizes findings
• CloudWatch and LangSmith provide observability into multi-agent architecture
• Agent can be deployed to AgentCore Runtime as managed service with stable endpoint
• Pattern applies to due diligence, content creation, and data pipeline orchestration

This architecture enables faster, context-aware research by delegating deep work to isolated subagents while keeping the coordinator focused on high-level reasoning and synthesis.