AWS Architecture Blog

Category: Kiro

How Dynata scaled AI across the development lifecycle with AI-DLC and Kiro IDE

How Dynata scaled AI across the development lifecycle with AI-DLC and Kiro IDE

Dynata reimagined its development lifecycle with AI, moving from AI-assisted coding to the AI-Driven Development Lifecycle (AI-DLC) methodology with Kiro IDE. Learn how the company reduced the development phase of full-stack features from three to four sprints to roughly one, with every team aligned from the start.

This diagram illustrates a comprehensive continuous integration and continuous deployment (CI/CD) pipeline architecture using AWS services, featuring feedback loops that connect development, testing, and production environments.

Architecting for agentic AI development on AWS

In this post, we demonstrate how to architect AWS systems that enable AI agents to iterate rapidly through design patterns for both system architecture and code base structure. We first examine the architectural problems that limit agentic development today. We then walk through system architecture patterns that support rapid experimentation, followed by codebase patterns that help AI agents understand, modify, and validate your applications with confidence.