{"version":1,"type":"story","url":"https://digestai.news/story/aws-adds-sagemaker-ai-inference-skill-for-coding-agents","json":"https://digestai.news/story/aws-adds-sagemaker-ai-inference-skill-for-coding-agents.json","markdown":"https://digestai.news/story/aws-adds-sagemaker-ai-inference-skill-for-coding-agents.md","slug":"aws-adds-sagemaker-ai-inference-skill-for-coding-agents","headline":"AWS adds SageMaker AI inference skill for coding agents","summary":"AWS has released the **aws-ai-ml skill** for its **Agent Toolkit**, enabling coding agents like **Kiro**, **Claude Code**, and **Codex** to optimize **SageMaker AI** inference. The tool benchmarks endpoints, recommends deployment configurations, compares performance runs, and generates **SageMaker Python SDK v3** code for deployment. It supports **Model Context Protocol (MCP)**-compatible agents and integrates with **SageMaker Studio JupyterLab** or local setups via the **Agent Toolkit for AWS**.\n\nThe skill automates complex tasks—such as selecting instance types, evaluating models from **S3**, **Hugging Face Hub**, or **SageMaker JumpStart**, and comparing benchmark results—without requiring deep infrastructure knowledge. Users describe their goals in natural language, and the agent provides executable code with performance metrics (throughput, latency, concurrency). AWS emphasizes safety: agents confirm before running benchmarks on live endpoints and clarify missing details. The tool is free to install but requires **AWS CLI 2.35+** and proper IAM permissions.","keyPoints":["AWS’s **aws-ai-ml skill** lets coding agents optimize **SageMaker AI** inference with benchmarks, recommendations, and Python code generation","Supports models from **S3**, **Hugging Face Hub**, or **SageMaker JumpStart**; compares configurations with real metrics (throughput, latency)","Available via **Agent Toolkit for AWS** (local) or **SageMaker Studio JupyterLab** (pre-configured image); requires AWS credentials with SageMaker permissions"],"whyItMatters":"This bridges the gap between AI developers and cloud infrastructure, letting teams deploy models faster with data-driven decisions—no deep SageMaker expertise needed. Useful for startups scaling models or enterprises optimizing costs.","category":{"slug":"agents","name":"Agents & Tools","url":"https://digestai.news/category/agents"},"entities":{"companies":["Amazon","AWS","Amazon SageMaker","Hugging Face","Kiro","Claude Code"],"models":["Qwen3-8B","Qwen3-1.7B"],"people":[]},"firstPublishedAt":"2026-10-05T17:23:19Z","updatedAt":"2026-10-05T17:23:19Z","sourceCount":1,"hasPrimarySource":true,"sources":[{"outlet":"AWS Machine Learning Blog","title":"New agent skill: Amazon SageMaker optimized generative AI inference for your coding agent","url":"https://aws.amazon.com/blogs/machine-learning/new-agent-skill-amazon-sagemaker-optimized-generative-ai-inference-for-your-coding-agent","publishedAt":"2026-10-05T17:23:19Z","type":"primary","primary":true,"lead":true}],"sourceNotes":null,"discussions":[],"thread":{"title":"AWS Expands AI Tools For Search And Conversion","url":"https://digestai.news/thread/aws-shows-how-contextual-bandits-lift-conversions-in-acquisition-funnels","storyCount":3},"cite":{"text":"Digest AI, \"AWS adds SageMaker AI inference skill for coding agents\", 5 October 2026, https://digestai.news/story/aws-adds-sagemaker-ai-inference-skill-for-coding-agents","publisher":"Digest AI","title":"AWS adds SageMaker AI inference skill for coding agents","datePublished":"2026-10-05T17:23:19Z","url":"https://digestai.news/story/aws-adds-sagemaker-ai-inference-skill-for-coding-agents"},"generatedBy":"Written by Digest AI's editorial model from the linked sources; the sources are the record.","license":"Headlines, digests and key points are written by Digest AI and may be quoted with a link to the story page. Linked articles belong to their publishers. Terms: https://digestai.news/terms#reuse"}