New agent skill: Amazon SageMaker optimized generative AI inference for your coding agent
AWS gives coding agents a new skill: SageMaker inference optimization. Your agent can now benchmark and compare deployment strategies in Python.
Why it matters
Amazon SageMaker adds an agent-consumable skill for ML inference optimization via AWS Agent Toolkit, letting coding agents generate executable benchmarking and deployment-recommendation code. This is a feature for agents building with AWS infrastructure, not an agent product itself.
The key facts
11 to knowAWS Agent Toolkit now includes aws-ai-ml skill for SageMaker inference
Skill targets coding agents: Kiro, Claude Code, Codex
Generates executable SageMaker Python SDK v3 code for benchmarking, recommendations, and deployment comparison
Natural-language interface: describe what you want, agent writes the code
Published October 5, 2026 via AWS machine-learning blog
New aws-ai-ml skill in Agent Toolkit for AWS
Targets coding agents: Claude Code, Kiro, Codex
Auto-generates SageMaker Python SDK v3 code
Focuses on inference benchmarking, deployment comparison, and optimization recommendations
Delivered as a blog announcement with no GA/preview status stated
No pricing, quotas, or integration limitations disclosed
Go to the source
AWS Machine Learning Blogaws.amazon.com
Publisher excerpt: Amazon SageMaker optimized generative AI inference introduces the aws-ai-ml skill through the Agent Toolkit for AWS, giving coding agents like Kiro, Claude Code, and Codex deep expertise in inference optimization and benchmarking. Describe what you want, and your agent generates executable…