AWS DevOps & Developer Productivity Blog
Category: Amazon Q
Building with AI-DLC using Amazon Q Developer
The AI-Driven Development Life Cycle (AI-DLC) methodology marks a significant change in software development by strategically assigning routine tasks to AI while maintaining human oversight for critical decisions. Amazon Q Developer, a generative AI coding assistant, supports the entire software development lifecycle and offers the Project Rules feature, allowing users to tailor their development practices […]
Open-Sourcing Adaptive Workflows for AI-Driven Development Life Cycle (AI-DLC)
AI-Driven Development Life Cycle (AI-DLC) holds the promise of unlocking the full potential of AI in software development. By emphasizing AI-led workflows and human-centric decision-making, AI-DLC can deliver velocity and quality. However, realizing these gains hinges on how organizations effectively integrate AI into their engineering workflows. Through our work with engineering teams across industries, we […]
Boosting Unit Test Automation at Audible with Amazon Q Developer
Audible, an Amazon company, is a leading producer and provider of audio storytelling. With a vast library of over 1,000,000 titles including audiobooks, podcasts, and Audible Originals with specific curated offerings available in each marketplace, Audible makes it easy to transform everyday moments into extraordinary opportunities for learning, imagination, and entertainment through immersive audio experiences. […]
Multi-Cloud Code Deployments using Amazon Q Developer with Echo3D
Overview Founded in 2018, echo3D built a revolutionary 3D digital asset management (DAM) platform to address the surging demand for immersive content across industries. The company’s platform enables enterprises to seamlessly store, secure, optimize, and share 3D content, serving over 200,000 professionals across energy, healthcare, gaming, retail, and beyond. echo3D’s platform has become the go-to […]
Accelerating AWS Infrastructure Deployment: A Practical Guide to Console-to-Code
In today’s cloud-first environment, Infrastructure as Code (IaC) has become crucial for managing cloud resources effectively. However, organizations often face significant challenges in adopting IaC practices, including steep learning curves, complex syntax requirements, and difficulty translating manual operations into code. Amazon Q Developer‘s Console-to-Code feature addresses these challenges by providing an intuitive bridge between manual AWS […]
AWS named as a Leader in the 2025 Gartner Magic Quadrant for AI Code Assistants
We are excited to share that AWS has been named a Leader in the 2025 Gartner Magic Quadrant for AI Code Assistants for the second year in row. This recognition highlights for us Amazon Q Developer’s commitment to innovation and delivering exceptional customer experiences. We believe this Leader placement showcases our rapid pace of innovation, […]
Introducing an Interactive Code Review Experience with Amazon Q Developer in GitHub
Code reviews are one of the most valuable rituals in software development. They help ensure quality, maintain consistency, and foster growth as engineers. But they’re also one of the most time consuming steps in the software development lifecycle. A common pattern I’ve seen is a developer opening a pull request (PR), receiving automated or peer […]
Measuring Developer Productivity with Amazon Q Developer and Jellyfish
Modern software development teams face increasing pressure to deliver high-quality code faster, while managing growing system complexity. Developers often spend significant time on necessary, but undifferentiated work, or “toil”. Toil is often manual, repetitive, and of limited enduring value, making it a strong candidate for automation or delegation to generative AI tools. The re:Invent 2024 […]
Mastering Amazon Q Developer with Rules
When I first started working with Amazon Q Developer, I was impressed by its capabilities, but I quickly found myself in a familiar pattern. Development teams using AI assistants face a common challenge: repeatedly explaining coding standards, workflow preferences, and established patterns in every conversation. This repetitive setup reduces productivity and creates inconsistent AI guidance […]
Introducing AWS Cloud Control API MCP Server: Natural Language Infrastructure Management on AWS
Today, we’re officially announcing the AWS Cloud Control API (CCAPI) MCP Server. This MCP server transforms AWS infrastructure management by allowing developers to create, read, update, delete, and list resources using natural language. As part of the awslabs/mcp project, this new and innovative tool serves as a bridge between natural language commands and AWS infrastructure […]









