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This lowers the barrier for developers to leverage AI agents for production ML inference optimization tasks, reducing boilerplate code generation and accelerating the feedback loop between agent-assisted coding and deployment benchmarking on AWS infrastructure.
AWS has introduced a new ai-ml skill for the Agent Toolkit that enables coding agents (Kiro, Claude Code, Codex) to generate optimized SageMaker inference deployment code. Developers can describe inference optimization goals in natural language and the agent generates executable Python SDK v3 code for benchmarking, recommending, and comparing SageMaker deployments.
Read the full article at AWS AI/ML
CoFabrix summarises and comments on this story. The original reporting belongs to AWS AI/ML.
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