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AWS details nine-stage evaluation framework for production AI agents on Bedrock AgentCore

AWS's SMGS Operations team describes a production multi-agent system for its field sales organization and the nine-stage continuous evaluation framework it built on Amazon Bedrock AgentCore Evaluations. The framework spans quality definition, experiments, CI/CD gates, canary scoring, adversarial testing, drift detection, live monitoring and automated feedback. The post documents real pre-launch failures, such as revenue misreported in millions and ungrounded figures, and reports that a mismatche

AWS Machine Learning Blog1d agoScore 75

Amazon Bedrock AgentCoreAI agent evaluationAWS

Tutorial

AWS shows self-improving agentic document processing on Bedrock AgentCore

AWS published a tutorial describing a multi-agent intelligent document processing system built on Amazon Bedrock AgentCore. Eight specialized agents classify, extract, validate, and save reusable instructions for new document formats using AWS services including Amazon Textract, S3 Vectors, Aurora DSQL, Lambda, and AgentCore Gateway. The post provides a deployable sample repository, sample purchase order flows, estimated costs, and guidance for adapting schemas, validators, and prompts to other

AWS Machine Learning Blog3d agoScore 72

Amazon Bedrock AgentCoreAWSDocument AI

Tutorial

AWS sample automates Amazon Bedrock private pricing grant activation

AWS published a tutorial for managing Amazon Bedrock access through AWS Marketplace Private Pricing Offers and managed entitlements. It shows two approaches: a lightweight script for one-time activation of trusted received licenses, and a CDK-based event-driven automation that listens for Marketplace agreement events, verifies a seller allowlist, creates distributed grants, and activates them via License Manager. The event-driven path uses EventBridge, Lambda, DynamoDB, and CloudWatch Logs to re

AWS Machine Learning Blog4d agoScore 69

Amazon BedrockAWS License ManagerAWS Marketplace private pricing

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How ShipStation Global built an AI IT help desk on Amazon Bedrock AgentCore

ShipStation Global built Deckhand, a Slack-based AI IT help desk agent on Amazon Bedrock AgentCore, using Strands Agents, AgentCore Gateway MCP tools, and Amazon Bedrock Knowledge Bases. The system answers routine IT and company questions, reads error-message screenshots, and creates or updates Jira Service Management tickets, with logic for staying silent when humans are already handling a thread. In its first three months after an April 2026 launch, it handled 1,935 messages, replied to 97.5%

Why it matters: Offers a detailed, metrics-backed architecture for building a production agentic IT help desk on AWS.

AWS Machine Learning Blog4d agoScore 82

Amazon Bedrock AgentCoreAI agentsIT help desk automation

Tutorial

Accessing OpenAI GPT-6 models on Amazon Bedrock with global cross-Region inference in APAC

AWS describes how to invoke OpenAI GPT-6 Sol, Luna, and Astra through Amazon Bedrock global cross-Region inference profiles from Singapore, Jakarta, Malaysia, Thailand, and Taipei. The post shows configuration through the Converse API, OpenAI-compatible APIs, and the ChatGPT desktop app or Codex CLI, including required IAM and SCP permissions. It also covers quota management, data retention, and monitoring with CloudWatch and CloudTrail while keeping billing, quotas, and logs in the source Regio

AWS Machine Learning Blog5d agoScore 72

Amazon BedrockOpenAI GPT-6AWS cross-Region inference

Tutorial

Deploy decision models with llama.cpp on Amazon SageMaker AI

The AWS Machine Learning Blog details serving quantized GGUF models with the AWS Deep Learning Container for llama.cpp on Amazon SageMaker AI, exposing OpenAI-compatible chat completions through InvokeEndpoint. It then extends the runtime with a SemIf child image that returns probabilities over caller-declared options using last-position logits, without generating answer tokens. A provided code sample covers CPU and GPU deployment paths, including CodeBuild/ECR image builds and SageMaker instanc

AWS Machine Learning Blog5d agoScore 76

Amazon SageMaker AIllama.cppSemIf

Tutorial

Run Multi-Node LLM Inference with Ray LLM Deep Learning Containers on EKS

AWS details a tutorial for deploying one large language model across two GPU nodes on Amazon EKS using the multi-node Ray LLM Deep Learning Container. The setup separates prefill and decode phases onto different nodes behind a single OpenAI-compatible endpoint, using vLLM, Ray Serve, NIXL, and the EFA stack. The article walks through cluster creation, GPU node group setup, KubeRay installation, RayService deployment, and model invocation. It also explains how the container removes much of the de

AWS Machine Learning Blog5d agoScore 79

AWS Deep Learning ContainersRay Serve LLMAmazon EKS

Tutorial

Postman's Agent Mode Architecture on Amazon Bedrock for 40M Developers

Postman and AWS detail the architecture behind Postman's Agent Mode, an AI agent running on Amazon Bedrock that works across API testing, documentation, discovery, and implementation. At scale, the team found context rather than model capability was the main bottleneck, and that tool-selection errors increased once the visible toolset exceeded roughly 40 tools. Their patterns include dynamic tool scoping (narrowing 170+ tools to about 15 per task), schema-based reads via a ClickHouse query tool,

AWS Machine Learning BlogOct 9, 2026Score 79

Postman Agent ModeAmazon BedrockAI agent architecture

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Microsoft Research open-sources Agent Lightning v1.0, a 3,500-line agentic RL framework

Microsoft Research Asia released Agent Lightning v1.0, a lightweight framework that implements a complete agentic reinforcement learning control plane in roughly 3,500 lines of code. It introduces Harnessed Agentic RL, where the same agent harness used in deployment participates directly in training via an OpenAI-compatible LLM proxy, avoiding the need to reimplement the agent inside the training framework. The framework runs agents as standard Kubernetes jobs instead of paid commercial sandbox

Why it matters: This gives AI engineers an open, reproducible way to fine-tune real deployment harnesses with RL, backed by a concrete SWE-bench gain and a Kubernetes-native design that avoids sandbox costs.

Microsoft ResearchOct 8, 2026Score 83

Agent Lightning v1.0Microsoft Research AsiaHarnessed Agentic RL