AWS open-sources Deep Insight: how a production multi-agent system tackles 5 key challenges
AWS ML Blog · rss · 2026-10-22
The AWS Solutions Architecture team opened a three-part series on Deep Insight, a production-grade multi-agent system now open-sourced on GitHub.
System overview: Given a CSV and a natural-language prompt, eight specialized agents (Coordinator, Planner, Plan Reviewer, Supervisor, Coder, Validator, Reporter, Tracker) collaborate to run analyses, generate charts, and produce a cited .docx report.
Five production challenges and solutions:
- Execution flow: Strands Agents SDK's Graph pattern plus human-in-the-loop branching and the Agents-as-Tools pattern
- Model assignment: Claude Haiku for routing, Opus for planning, Sonnet for execution on Amazon Bedrock
- Production ops: Amazon Bedrock AgentCore managed runtime with session isolation and private VPC deployment
- Safe execution of AI-generated code: per-session ephemeral Fargate sandboxes behind an ALB as a custom Code Interpreter
- Monitoring: DynamoDB + SNS + Cognito for an admin dashboard and failure alerting
Three deployment options: a 10-minute self-hosted CLI version, a no-code Web UI with plan review (HITL), and a production AgentCore deployment — all sharing the same architecture. Parts 2 and 3 will cover Context Engineering (applying Anthropic's techniques) and harness engineering from dev to production.
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