SageMaker AI gets agentic experience for AI model development
Amazon SageMaker AI is introducing a new agentic experience that simplifies and accelerates the development of custom AI models for developers, from data collection to deployment.

What happened?
Amazon SageMaker AI has launched a new agentic experience aimed at automating and streamlining the process of customizing AI models. Developers can now describe their use cases using natural language, after which the AI coding agent guides them through the entire model development lifecycle.
Key facts
| Funktion | Agent-guided workflows (Agentic experience) |
|---|---|
| Plattform | Amazon SageMaker AI |
| Tillgänglighet | Globalt |
”Developers describe their use case using natural language, and the AI coding agent streamlines the entire journey, from use case definition and data preparation through technique selection, evaluation, and deployment.”
Why it matters
This agent-driven workflow improvement addresses the complexity and time-consuming nature of traditional AI model development. By automating steps such as data collection, technology selection, evaluation, and deployment, developers can get their customized models into production faster.
Who is affected?
This primarily affects AI developers and data scientists using Amazon SageMaker to build and deploy machine learning models. Companies investing in bespoke AI solutions also benefit through faster time-to-market.
What else you should know
This feature is available globally and represents a step towards more automated and user-friendly AI development.
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