Editorial illustration for AWS Launches AI Agent to Modernize Code Across Massive Repository Networks
AWS AI Agent Transforms Legacy Code with Unprecedented Speed
AWS unveils AI agent that modernizes code across thousands of repos
Modernizing code across thousands of repositories is a nightmare of scale, fragmented patterns, inconsistent updates, and endless manual fixes. AWS just turned that nightmare into a conversation. Its new AI agent, Transform Custom, learns from your documentation, natural-language instructions, and code samples, then applies those lessons across entire codebases, from hundreds to thousands of repos.
It doesn't stop at mechanical API swaps; it grasps best practices, spots optimization opportunities in newer SDKs, and even adapts to your enterprise’s unique coding habits. The service couples a CLI for conversational transformations, local or in CI/CD, with a web interface for tracking whole modernization campaigns. Java, Python, and Node.js runtimes?
Covered. Spring Boot migrations or shifting workloads to AWS Graviton? Handled.
Infrastructure as Code? It translates CDK to Terraform and updates CloudFormation. And the agent improves over time, mining developer feedback and manual fixes to refine its own patterns.
This is automated modernization that learns, and scales.
Transform custom applies its learned transformation patterns across large codebases, including hundreds or even thousands of repositories. It learns from documentation, natural-language instructions, and code samples, and then improves over time by analysing developer feedback and the manual fixes teams make during the modernisation process. The service includes a CLI and a web interface.
The CLI supports conversational inputs for defining and executing transformations locally or in CI/CD workflows, while the web interface offers campaign-level tracking for modernisation projects across teams. AWS said the agent supports runtime upgrades for Java, Python and Node.js, and can execute complex transformations such as migrating Spring Boot applications or shifting workloads to AWS Graviton. It can also learn enterprise-specific coding patterns and apply them consistently.
"The service understands not only the mechanical aspects of API changes, but also recognises best practices and optimisation opportunities available in newer SDK versions," the company said. Transform custom extends to Infrastructure as Code, with support for CDK-to-Terraform conversions and CloudFormation updates.
The era of manual, repository-by-repository upgrades is ending. AWS Transform doesn’t just automate the mechanics of code changes, it learns the rationale behind them. For teams drowning in legacy dependencies or struggling to enforce enterprise-wide standards, this tool collapses months of work into hours.
It treats modernization not as a one-time migration, but as a continuous, learned discipline. The real win isn’t faster code changes; it’s the shift from reactive patching to proactive architectural hygiene. That’s a fundamental redefinition of how we manage technical debt at scale.
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Common Questions Answered
How does AWS Transform learn to modernize code repositories?
AWS Transform learns transformation patterns by analyzing documentation, natural-language instructions, and code samples. The tool continuously improves its capabilities by studying developer feedback and manual fixes made during the code modernization process.
What types of repositories can AWS Transform handle?
AWS Transform is designed to work with massive software repository networks, potentially spanning hundreds or thousands of repositories. The tool can apply learned transformation patterns across large and complex code bases, making it particularly useful for organizations with extensive legacy code systems.
What interfaces does AWS Transform provide for developers?
AWS Transform offers both a Command Line Interface (CLI) and a web interface for developers to use. The CLI supports conversational inputs and allows developers to define and execute transformations locally or within CI/CD workflows, providing flexibility in code modernization efforts.
Further Reading
- New Agentic Capabilities in AWS Transform Enable Rapid Modernization of Any Code or Application — Business Wire / Morningstar
- Introducing AWS Transform custom: Crush tech debt with AI-powered code modernization — AWS Blog
- AWS Transform: Agentic AI Automates Legacy Code Modernization and Reduces Technical Debt — Security Online
- AWS Transform launches an AI agent for full-stack Windows modernization — AWS What's New
- Top announcements of AWS re:Invent 2025 — AWS Blog
