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AI Lehel Briefing

Independent signal, primary sources

The important moves in artificial intelligence.

Models, research, coding tools, open source, infrastructure, and major product releases—ordered by publication time.

Product news AWS Machine Learning

Introducing Claude Haiku 5.5 on AWS

Claude Haiku 5.5 is now available on Amazon Bedrock and Claude Platform on AWS. According to Anthropic, it is the fastest, most efficient model in the Claude 5.5 family, built for subagents and high-volume, cost-sensitive work, and costs around 75% less than Claude Haiku 4.5 for most tasks. This post covers its improvements and how to get started.

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Developer tools AWS Machine Learning

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

Amazon SageMaker optimized generative AI inference introduces the aws-ai-ml skill through the Agent Toolkit for AWS, giving coding agents like Kiro, Claude Code, and Codex deep expertise in inference optimization and benchmarking. Describe what you want, and your agent generates executable SageMaker Python SDK v3 code to benchmark, recommend, and compare deployments.

Infrastructure AWS Machine Learning

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

Promoting Amazon Quick resources (agents, action connectors, knowledge bases, flows, and spaces) from a development to a production AWS account has been a manual, error-prone chore. This post shows how to automate cross-account promotion with an idempotent, auditable MCP server on Amazon Bedrock AgentCore.

Infrastructure AWS Machine Learning

Agentic retrieval with LangChain and Amazon Bedrock Knowledge Bases

Build a Retrieval Augmented Generation (RAG) application on Amazon Bedrock Managed Knowledge Base with LangChain, and see how agentic retrieval handles the multi-part questions that single-shot retrieval answers poorly. Run the same query through both paths, read the trace events, and compare what each retrieval path costs.

Infrastructure AWS Machine Learning

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

Multi-agent systems need deeper guarantees than fluent responses: they must select the right tools, respect constraints, and explain their decisions. Learn how to build a Strands-based multi-agent supply chain decisioning system and evaluate it with Amazon Bedrock AgentCore Evaluations using built-in, custom, and explainability evaluators.