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  • Prompt engineering fundamentals for Amazon Quick

    Prompt engineering in Amazon Quick shapes how accurately its AI-powered features respond to your requests. Part 1 of a two-part series covers the foundational principles and reusable frameworks (specificity, context-setting, few-shot examples, and the CRISPE framework) for consistent, high-quality…

    AWS ML Blog11 min read
  • Prompt engineering by Quick component: Patterns and pitfalls

    Part 2 of our Amazon Quick prompt engineering series goes component by component. Learn the prompt patterns that get the best results from Amazon Quick Research, Quick Flows, Quick Sight, chat agents, and action integrations, plus the common pitfalls to avoid.

    AWS ML Blog12 min read
  • Grok 4.7 is now available on Amazon Bedrock

    xAI's Grok 4.7 is now available on Amazon Bedrock: a frontier model for coding, long-running agents, and knowledge work. It offers a 500K token context window and four configurable reasoning effort levels, reachable through the Responses, Chat Completions, and Converse APIs.

    AWS ML Blog11 min read
  • NarrateAI: production-ready LLM quality assurance on Amazon Bedrock

    NarrateAI delivers production-ready LLM quality assurance on Amazon Bedrock. This post details five techniques—adaptive pipeline orchestration, cross-account multi-model failover, real-time streaming evaluation, composite evaluation, and data accuracy verification—that reach about 99% numerical…

    AWS ML Blog21 min read
  • Build a multi-account AI agent with AgentCore Gateway and MCP

    Build a multi-account architecture that keeps each team's data in its own AWS account while giving AI agents a unified way to query across them. A central platform account runs the agent using Amazon Bedrock AgentCore Gateway and MCP, while line-of-business accounts expose their data as MCP servers…

    AWS ML Blog18 min read

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