AI-driven development lifecycle using Amazon Bedrock AgentCore
Machine Learning Blog
This article demonstrates practical AI-driven development lifecycle (AI-DLC) patterns using Amazon Bedrock AgentCore, showing how AI can collaborate across software development while maintaining human oversight.
- SQL schema to ER diagram generation: Serverless agent automatically creates Mermaid diagrams from SQL files using AgentCore runtime and memory for persistent context
- Secure software handoffs: Multi-agent architecture analyzes code for security vulnerabilities, CVE risks, and policy violations through AgentCore Gateway and MCP tool integration
- Local development tools: Kiro, OpenAI Codex, and Claude Code accelerate inception and construction phases with spec-driven development and custom agent skills
- AgentCore capabilities: Runtime execution, persistent memory with semantic search, gateway-mediated tool invocation, and observability through OpenTelemetry
- Best practices: Separate agent concerns, use persistent memory for context, instrument with tracing, secure with OAuth2, implement chunked processing, and apply Bedrock Guardrails
Amazon Bedrock AgentCore enables production-ready agentic workflows by combining cloud runtime infrastructure with local development tools, bridging the gap between AI-DLC concepts and working implementations.
The AWS News Feed is currently looking for gold sponsors. If you want to support the AWS community and reach a large audience of AWS professionals, consider sponsoring the AWS News Feed.
Related articles
The AWS News Feed is currently looking for silver sponsors. If you want to support the AWS community and reach a large audience of AWS professionals, consider sponsoring the AWS News Feed.