AI

Introducing GLM 5.3 on Amazon Bedrock

Coding and agentic workloads are asking more of AI models than ever: refactor a repository spanning hundreds of files, sustain a multi-hour agentic workflow without losing context, and reason through complex systems problems with tool use at every step. Meeting those demands with open-weight models has historically meant provisioning and operating your own inference infrastructure. […]

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New agent skill: Amazon SageMaker optimized generative AI inference for your coding agent

Engineers increasingly use coding assistance tools to accelerate their development workflows. Today, Amazon SageMaker AI optimized generative AI inference introduces the aws-ai-ml skill, available through the Agent Toolkit for AWS. This skill gives coding agents like Kiro, Claude Code, and Codex deep expertise in inference optimization and benchmarking. Install the skill, and your existing agent

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Making Amazon Quick enterprise-ready: Automated, auditable cross-account resource promotion

Amazon Quick is Amazon’s agentic AI companion built for work. You build agents that reason over your data, call action connectors, and carry multi-step tasks to completion. Promoting those resources (chat agents, action connectors, knowledge bases, flows, and spaces) from a development to a production AWS account, the way you would any other application, has

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Agentic retrieval with LangChain and Amazon Bedrock Knowledge Bases

When a user asks the support assistant, a Retrieval Augmented Generation (RAG) application built with LangChain to compare two products across three dimensions, they’re effectively posing six questions simultaneously. Similarity search uses a single query vector to encapsulate all the intents. The retriever then generates the best approximation of the average of those intents. The

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Downgrading user roles in Amazon Quick

Managing access permissions effectively is an important aspect of maintaining a secure and collaborative environment in Amazon Quick. Quick supports versatile user management options designed to accommodate various identity types and organizational needs. You can provision users natively through Quick Identity or manage them through enterprise identity providers such as AWS IAM Identity Center or

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Evaluating multi-agent systems for explainability and helpfulness with Amazon Bedrock AgentCore

A critical challenge that emerges as multi-agent systems move from experimentation to production is making sure that these systems are consistently helpful, accurate, and explainable in real-world scenarios. Enterprises are increasingly adopting multi-agent systems to solve complex, real-world problems that require reasoning across data sources, tools, and business constraints. From supply chain planning to financial

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