New agent skill: Amazon SageMaker optimized generative AI inference for your coding agent
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Amazon SageMaker AI has introduced a new agent skill called aws-ai-ml, which integrates with coding agents like Kiro and Claude Code to optimize generative AI inference. This tool allows developers to benchmark existing endpoints, identify the most cost-effective instance types for deployment, and compare performance metrics across different configurations. By leveraging the Model Context Protocol, the skill enables agents to generate executable SageMaker Python SDK v3 code based on natural language requests. Users can evaluate models from Amazon S3, SageMaker JumpStart, or Hugging Face Hub without needing deep infrastructure expertise. The system provides detailed quantitative reports on throughput, latency, and concurrency, ensuring transparent and measurable results. Installation is streamlined through the Agent Toolkit for AWS or via pre-configured JupyterLab spaces in Amazon SageMaker Studio. This integration aims to bridge the gap between development intent and production infrastructure by automating complex optimization tasks.
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