RELEASE · CODING · #1562
Amazon SageMaker launches aws-ai-ml agent skill for inference optimization
Amazon introduced the aws-ai-ml skill available through the Agent Toolkit for AWS, which plugs into MCP‑compatible coding agents (e.g., Kiro, Claude Code, Codex) to benchmark SageMaker endpoints, recommend deployment configurations, compare performance runs, and generate executable SageMaker Python SDK v3 code. The skill can be used locally via the Agent Toolkit or inside Amazon SageMaker Studio JupyterLab and requires AWS credentials with SageMaker API permissions.
KEY POINTS
- Amazon introduced the aws-ai-ml skill available through the Agent Toolkit for AWS, which plugs into MCP‑compatible coding agents (e.g., Kiro, Claude Code, Codex) to benchmark SageMaker endpoints, recommend deployment configurations, compare performance runs, and generate executable SageMaker Python SDK v3 code.
- The skill can be used locally via the Agent Toolkit or inside Amazon SageMaker Studio JupyterLab and requires AWS credentials with SageMaker API permissions.
- By giving coding agents concrete benchmarking and deployment expertise and producing executable SageMaker SDK v3 code, the skill reduces friction from model evaluation to production deployment.
WHY IT MATTERS
By giving coding agents concrete benchmarking and deployment expertise and producing executable SageMaker SDK v3 code, the skill reduces friction from model evaluation to production deployment.