AWS Launches New AI Methodology to Transform Software Development AI-DLC is an openly accessible AI-native methodology designed to help organisations use AI in the software development process for building complex systems at scale

With a vision of to be the best platform to build AI agents, Amazon Web Services (AWS) on Friday unveiled a new approach to software development using generative AI, at its AWS DevSphere 2025 event in Bengaluru.

Swami Sivasubramanian, Vice President of Agentic AI, introduced the AI-Driven Development Lifecycle (AI-DLC) methodology designed to place artificial intelligence at the heart of software development. Alongside this methodology, he also announced the launch of AWS AI-Native Builders Community, a peer-to-peer network of technology leaders united to share breakthroughs, avoid pitfalls, and accelerate the journey to AI-native transformation.

Building on announcements from the AWS Summit in New York last month, Sivasubramanian highlighted how AWS is helping customers build and deploy AI agents that accelerate software development, boost productivity, and transform customer experiences.

AI-DLC is an openly accessible AI-native methodology designed to help organisations use AI in the software development process for building complex systems at scale with tools and frameworks such as Kiro, Amazon Q Developer, and Strands Agents. Sivasubramanian announced at the keynote that AI-DLC is available from today as a freely accessible methodology on AWS, and as a custom workflow in Kiro.

Unlike traditional software development methodologies, AI-DLC is said to place AI at the centre of the development process. "It offers a practical approach to effectively apply AI at each stage of software development, from inception to construction to operation, with human oversight at every step. The methodology helps development teams focus on strategic work while AI handles implementation tasks such as workflow orchestration, task breakdown, coding, testing, and deployments," Sivasubramanian.

According to AWS, the methodology is helping global and Indian businesses such as S&P Global, Wipro, HackerRank, and Dhan, among others, integrate AI into software development to condense complex development processes and timelines from months into days and even hours.

Presenting at the event keynote, Sandhya Arun, Chief Technology Officer at Wipro, elaborated on how Wipro is using AI to deliver better outcomes for their clients. She shared that by implementing AI-DLC methodology and using Amazon Q developer, they were able to build four production-ready modules within just 20 hours.

AWS also announced a new initiative called AWS AI-Native Builders Community, a peer-to-peer network of technology leaders. The community aims to share breakthroughs, learnings, and best practices on AI adoption and implementation to accelerate the journey to AI-native transformation across industries.

"When we talk to customers, one thing is clear: no single company can figure this out alone. That's why we created this community of leaders and innovators who are at the forefront of building, scaling, and improving software delivery with AI across industries," said Neil Fox, Senior Vice President for Generative AI at Persistent Systems and a founding member of the community.

To help early-career professionals with AI-transformed tech careers, AWS is providing AWS Academy students globally with a free subscription to AWS Skill Builder for 12 months. This is expected to them learn foundational and specialised AI content. The goal is to engage with 2.7 million students and early-career professionals globally within the first year.

AWS Academy provides more than 6,600 higher education institutions around the globe with free, ready-to-teach cloud computing and generative AI curricula that prepare students to pursue AWS certifications and in-demand jobs. AWS has also launched the AWS AI League, where developers compete to solve real-world business challenges with generative AI. The program offers up to USD 2 million in AWS credits for developers to get hands-on experience in fine-tuning, model customisation, and prompt engineering.