Bring deep SageMaker AI expertise to your coding agent with the AWS AI/ML skill in the Agent Toolkit for AWS
The AWS AI/ML skill is now integrated into the Agent Toolkit for AWS, enabling coding agents to select, train, optimize, and deploy models on Amazon SageMaker AI through a single natural-language workflow.
The Agent Toolkit for AWS now integrates new AWS AI/ML skills, allowing coding agents to select, train, optimize, and deploy models on Amazon SageMaker AI through a single natural language workflow. It replaces previous AWS Labs skills and plugins with a unified installation and update path, pre-installed in SageMaker Studio JupyterLab for use with Kiro or your preferred coding agent. The skill extends SageMaker AI support to include inference optimization, end-to-end fine-tuning workflows, serverless training, MLflow, experiment tracking, model lifecycle management, and JumpStart model deployment and recommendations. The AWS AI/ML skill is available at no additional cost, billing only for AWS resources used. To get started, install the skill from GitHub’s Agent Toolkit for AWS or use the pre-installed version in SageMaker Studio JupyterLab.
Why it matters
This update benefits developers and data scientists who want to leverage SageMaker AI's advanced capabilities through their coding agents. Integrating natural language processing into SageMaker workflows improves development efficiency and model deployment speed.