AI-driven development lifecycle using Amazon Bedrock AgentCore
Two reference implementations show how multi-agent systems turn the AI-DLC from theory into production code.
Why it matters
AWS demonstrates agent-native patterns for the development lifecycle itself—code generation, security analysis, and diagram creation—using AgentCore. Practitioners building with agents get concrete implementation examples for real workflows.
The key facts
8 to knowAmazon Bedrock AgentCore used as the platform
Two reference implementations: SQL-to-ER-diagram generator and multi-agent code security analyzer
Focus on AI-Driven Development Lifecycle (AI-DLC) construction phase
Integration with Kiro and Claude Code
Published by AWS ML blog (vendor content)
Amazon Bedrock AgentCore as the deployment platform
Multi-agent architecture patterns for engineering workflows
Integration with Claude Code for code-generation tasks
Go to the source
AWS Machine Learning Blogaws.amazon.com
Publisher excerpt: Engineering teams adopting the AI-Driven Development Lifecycle (AI-DLC) often struggle to turn concepts into working code. This post walks through two reference implementations on Amazon Bedrock AgentCore, Kiro, and Claude Code: an SQL-to-ER-diagram generator and a multi-agent code security…