GPT-6 Sol and GPT-6 Luna are now generally available on Amazon Bedrock, giving you more options to match intelligence and efficiency to each workload.  ( 116 min )

Claude Opus 5.5, Anthropic's most capable Opus model for agentic coding, knowledge work, and long-running tasks, is now available on Amazon Bedrock and Claude Platform on AWS. This post covers what's new in Opus 5.5, practical guidance, and how to start building with the model on Amazon Bedrock.  ( 116 min )

Skills let you encode domain-specific procedures as reusable, portable instructions for agents, but a fluent answer doesn't prove the agent picked the right skill or followed it. Learn how to measure skill selection and instruction following with Strands Evals and Amazon Bedrock AgentCore Evaluations.  ( 122 min )

Reactiv used Amazon Bedrock AgentCore to build a multi-agent AI Scheduler that autonomously refreshes Shopify merchants' mobile apps on a schedule, reducing merchant configuration time by 80% and getting to production 33% faster.  ( 119 min )

Concurrency sweeps help you right-size a generative AI endpoint on Amazon SageMaker AI by systematically benchmarking it at increasing load levels. This post walks through deploying a model, running automated concurrency sweeps with the CreateAIBenchmarkJob API, and using the results to make data-driven capacity decisions about fleet size.  ( 119 min )

In about four weeks, Trane Technologies built an AI-powered agentic solution on Amazon Bedrock AgentCore that reduced a 20-minute, multi-screen building diagnostic workflow to a 20-second natural language interaction, a 60x improvement in time-to-insight. This post shares the architectural approach and key design decisions behind the solution.  ( 122 min )

Learn how Tata Elxsi built IRIS, a real-time industrial safety platform on AWS. IRIS filters camera video at the edge, streams metadata through Amazon Kinesis, runs computer vision on Amazon SageMaker AI, and correlates detections into high-confidence alerts, detecting unsafe conditions in seconds instead of minutes.  ( 120 min )

Public sector agencies process large volumes of unstructured evidence, such as body camera footage and scanned documents. This post shows how to combine Amazon Bedrock Data Automation with the Model Context Protocol (MCP) to turn that data into structured insights and surface them through natural language queries in Salesforce Agentforce.  ( 122 min )

xAI's Grok 4.6 is now available in Amazon Bedrock: a frontier model for long-running agents, coding, and knowledge work, with a 500K token context window and four reasoning effort levels. It runs on both the bedrock-mantle and bedrock-runtime endpoints, with Converse API and cross-Region inference support.  ( 122 min )

BMW Group operates CLEA, a FinOps platform monitoring more than 14,000 cloud accounts. This post shows how BMW added automated daily cost anomaly detection, moving from reactive dashboards to proactive alerts using Prophet forecasting, AWS Step Functions, and a serverless pipeline that processes every account for about $50 per month.  ( 121 min )

Positron, Posit's IDE for data science, now runs on Amazon SageMaker AI. This post shows how a data scientist explores an Amazon Athena table, validates features in R, trains an XGBoost model in Python, deploys a real-time SageMaker AI endpoint, and reports results with Quarto, all in one governed SageMaker Studio Space.  ( 120 min )

Learn how Benchling built a defense-in-depth security architecture to run untrusted, AI agent-generated scientific code across thousands of life sciences tenants using Amazon Bedrock AgentCore Code Interpreter in VPC mode, combined with Amazon Route 53 Resolver DNS Firewall and VPC endpoint policies to block data exfiltration, including through DNS.  ( 122 min )

EXL built an AI-powered Medical intelligent document processing (IDP) solution on AWS, combining IDP with domain-specific large language models on Amazon SageMaker and Amazon Bedrock to extract, summarize, and query medical records at enterprise scale and cut claims review time from over 100 minutes per case.  ( 122 min )

View on sreweekly.com A message from our sponsor, Planetscale: Neki brings horizontal sharding to Postgres. It handles the hard parts of running Postgres at scale: Online schema changes Version upgrades with no downtime Better connection pooling Resharding Graceful planned and unplanned failovers → Neki is available today. Learn more. Interning at incident.io: Rate Limiting, Resiliently […]  ( 4 min )

Amazon SageMaker AI shipped 13 inference launches in year-to-date across two deployment paths: fully managed endpoints and Amazon SageMaker HyperPod Inference. This post reviews each launch, from inference recommendations and capacity-aware instance pools to tiered KV caching and disaggregated prefill and decode.  ( 125 min )

Kimi K3 from Moonshot AI is now available on Amazon Bedrock, giving you a powerful new open-weight option for coding and knowledge work. It offers native vision, a 1-million-token context window, and explicit prompt caching to reduce latency and input costs.  ( 117 min )

Migrate a multi-model healthcare AI agent from self-managed Amazon ECS with AWS Fargate to Amazon Bedrock AgentCore runtime, preserving triple-model orchestration and vector-enhanced knowledge retrieval while reducing infrastructure management. The framework-agnostic pattern applies across healthcare, financial services, and manufacturing.  ( 119 min )

Today we are announcing the new AgentCore runtime, a capability of Amazon Bedrock AgentCore built for the speed, flexibility, and cost efficiency that production agents demand. It reclaims memory as sessions release it and delivers consistent cold starts regardless of image size or concurrency.  ( 121 min )

Deploy production-ready Hugging Face models on Amazon SageMaker AI using six open-source agent skills. Point a coding agent at a model and get back a real-time endpoint with the right serving container, autoscaling, Amazon CloudWatch alarms, and a verified teardown path.  ( 121 min )

Amazon SageMaker HyperPod Inference Gateway is a Kubernetes-native, GPU-aware routing add-on for Amazon EKS. It uses real-time GPU signals to send each inference request to the best-suited pod, cutting first-token latency by up to 82% with no changes to your model servers or client applications.  ( 118 min )

TL;DR Large Language Model (LLM) based Artificial Intelligence (AI) may be great at cranking out plausible sentences. But stringing those sentences together to form some kind of narrative doesn’t get a good story. That’s a problem, and an opportunity; because humans run on stories, and (for now at least) it seems that we still need […]  ( 14 min )

TL;DR Large Language Model (LLM) based Artificial Intelligence (AI) may be great at cranking out plausible sentences. But stringing those sentences together to form some kind of narrative doesn’t get a good story. That’s a problem, and an opportunity; because humans run on stories, and (for now at least) it seems that we still need […]  ( 14 min )

Amazon Connect Talent is an AI hiring solution built for talent acquisition leaders managing scaled hiring. It delivers AI-led interviews, data-driven assessments, and consistent evaluation, helping recruiters identify strong candidates more efficiently while providing applicants with a flexible interview experience. Informed by decades of Amazon's hiring science, Amazon Connect Talent provides transparency for every assessment, interview, and candidate score, enabling recruiters to stay in control of final hiring decisions.  ( 116 min )

Choosing the right vector store for your Amazon Bedrock Knowledge Bases RAG application affects performance and cost. This post compares Amazon OpenSearch Service, Amazon Aurora PostgreSQL with pgvector, and Amazon S3 Vectors across three RAG use cases, with benchmarks and a practical selection framework.  ( 129 min )

Learn how to build a fully serverless pipeline that automatically collects Git metrics from GitHub and GitLab and visualizes them in interactive Amazon Quick Sight dashboards, giving engineering teams near-real-time delivery analytics at low cost.  ( 121 min )

Wood Mackenzie built APEX, a shared agentic AI platform on Amazon Bedrock AgentCore so every team can ship production agents without rebuilding runtime, identity, observability, and guardrails from scratch. Learn why they chose AgentCore, how APEX Studio operates it, and where multi-agent systems go next.  ( 130 min )

Learn how MRH Trowe, one of Germany's leading commercial and industrial insurance brokers, gave about 400 employees secure, self-service access to AI agents in its first month of production - using Strands Agents, Amazon Bedrock AgentCore, and LibreChat to meet the security, data residency, and compliance requirements of the German financial sector.  ( 119 min )

Learn how to enforce defense-in-depth authorization for Model Context Protocol (MCP) tools on Amazon Quick. This walkthrough wires Microsoft Entra ID group and claims-based JWTs through an Amazon Bedrock AgentCore Gateway interceptor to apply per-user, per-tool role-based and attribute-based access control, with a server-side check and an immutable audit trail.  ( 128 min )

Learn how to build a synthetic data augmentation pipeline on Amazon SageMaker AI and Amazon Rekognition that generates photo-realistic, auto-labeled training images for industrial safety AI. This approach improved person detection by up to 160% without manual annotation or hazardous data collection near heavy machinery.  ( 124 min )

AI agents on foundation models often misapply healthcare and life sciences decision frameworks, citing the right guideline but applying it incorrectly. This post shares 38 open-source agent skills across 11 HCLS domains that close this gap, with installation steps, three worked use cases, and a 410-prompt evaluation showing a 70-86% win rate.  ( 125 min )

Integrate NVIDIA Resiliency Extension (NVRx) into PyTorch FSDP training on Amazon EKS to overlap checkpoint I/O with training and recover from GPU faults in seconds. This post covers async checkpointing, in-process restart, and ft_launcher in-job restart, with H100 benchmarks at 2 to 8 nodes showing 99%+ training efficiency and second-scale recovery.  ( 123 min )

AgentCore optimization turns production traces into proposed configuration changes, then validates them before promotion. This technical companion to the launch post explains how the system prompt optimizer's reflector engine works and shares benchmark results for the Single Agent and Sub-Agent Reflectors.  ( 119 min )

Learn how to automate end-to-end PII detection and redaction from scanned documents at scale using Amazon Bedrock Data Automation with a custom blueprint, AWS Step Functions, and AWS Lambda. A custom blueprint redacts sensitive fields with field-level precision, and a token matching quality check raises recall across degraded and handwritten documents.  ( 122 min )

Prompt caching in Amazon Bedrock can cut input token costs by up to 90% when you repeatedly send the same context to foundation models. This post walks through six practical prompt caching scenarios using the Converse API: message content, system prompt, tool definition, mixed TTL, tenant isolation, and LangChain integration.  ( 148 min )

Manually tagging thousands of catalog products is slow and inconsistent. This walkthrough shows how to customize Qwen3-8B with supervised fine-tuning (SFT) and reinforcement learning with verifiable rewards (RLVR) on Amazon SageMaker serverless model customization, then deploy it for asynchronous inference to build a cost-efficient product tagging system.  ( 120 min )

Amazon SageMaker AI now offers instance preference lists for training and processing jobs. Specify an ordered list of up to five instance types, and SageMaker AI automatically launches on the first type with available capacity, eliminating manual retry loops and capacity-watching scripts.  ( 120 min )

Learn how Abnormal AI deployed Amazon Bedrock AgentCore Code Interpreter as an ephemeral compute scratch pad for the agents behind its real-time email threat detection at billion-message scale, plus the sandbox design decisions and practical lessons for builders deploying Code Interpreter in production.  ( 117 min )

Amazon Bedrock AgentCore Identity now offers a Consent portal, a managed web experience and session binding endpoint for AgentCore Gateway. This post walks through provisioning a portal, configuring GitHub and Slack 3LO targets, and the end-user consent flow, and shows how to review activity in AWS CloudTrail.  ( 121 min )

Learn how Ninth Wave built Compass, a multi-agent AI onboarding assistant on Amazon Bedrock AgentCore that validates bank APIs against Financial Data Exchange (FDX) standards, scores compliance, and compresses open finance onboarding from weeks to minutes while meeting SOC 2 and PCI DSS requirements.  ( 120 min )

Pick the right generative AI customization approach on AWS with an 8-step decision framework, from prompt engineering and RAG to fine-tuning, continued pre-training, and Amazon Nova Forge. Start simple and escalate only when you must.  ( 125 min )

Foundation models made catalog-wide demand forecasting easy; the hard part is now acting on the forecast. This post builds a closed detect-decide-act loop on Databricks and Amazon Quick that reconciles demand surges against live supplier availability and places replenishment orders unattended, escalating to a human only when no supplier can cover a surge.  ( 125 min )

TL;DR Open source projects that I contribute to have adopted AI bots to ease the pull request (PR) process. It might just be me (though I doubt it), but somehow it feels less like a personal attack when a bot tells you what’s wrong with your PR than when it’s a person doing it. This […]  ( 13 min )

TL;DR Open source projects that I contribute to have adopted AI bots to ease the pull request (PR) process. It might just be me (though I doubt it), but somehow it feels less like a personal attack when a bot tells you what’s wrong with your PR than when it’s a person doing it. This […]  ( 13 min )

View on sreweekly.com A message from our sponsor, Planetscale: Neki brings horizontal sharding to Postgres. It handles the hard parts of running Postgres at scale: Online schema changes Version upgrades with no downtime Better connection pooling Resharding Graceful planned and unplanned failovers → Neki is available today. Learn more. AI handles incidents, engineers lose touch […]  ( 4 min )

Multi-agent systems fail in ways traditional monitoring misses. This post presents a dual-layer approach to monitoring production agents: Amazon Bedrock AgentCore Evaluations for continuous quality scoring and AWS DevOps Agent for autonomous infrastructure investigation, shown on a four-agent airline reservation system.  ( 129 min )

Comparing models on dollars per million tokens misses what production workloads actually pay for: outcomes. This post shares an open-source benchmarking harness that measures cost per correct answer, agent trajectory cost, and rubric-graded deliverable quality across OpenAI models on Amazon Bedrock.  ( 120 min )

Learn how to build and deploy an MCP App with interactive HTML widgets on Amazon Bedrock AgentCore. Because MCP Apps is a host-agnostic standard, the same server delivers the same rich experience across AI hosts like ChatGPT and Claude that support the extension.  ( 121 min )

Amazon SageMaker Inference now offers prefix-aware routing, a routing strategy that sends requests sharing the same prompt prefix to the same instance so the KV cache stays warm. In benchmarks on Llama 3.1 70B, it reduced P50 time-to-first-token by up to 77% and raised KV cache hit rates from about 25% to over 80%.  ( 119 min )

Amazon SageMaker HyperPod now supports model caching for inference, which pre-loads model weights and container images onto cluster nodes so pods read from local NVMe storage instead of downloading over the network. Learn how model caching cuts cold starts from tens of minutes to seconds, how it works, and how to enable it.  ( 119 min )

TwelveLabs Marengo Embed 3.0 is now generally available as an embedding model in Amazon Bedrock Knowledge Bases, bringing fully managed natural language search to video, image, and audio content. This walkthrough shows how to build a knowledge base powered by Marengo 3.0 and run semantic queries against your media.  ( 117 min )

Your teams get an AI assistant that handles real work while your data stays in your environment and your conversations stay private Today, the Amazon Quick desktop application is generally available on macOS and Windows. We’re also adding a new activity feed to the mobile experience on iOS and Android that consolidates email, calendar, CRM, […]  ( 117 min )

Learn how to build an end-to-end RFI questionnaire workflow with Amazon Quick Automate. Read a multi-tab RFI workbook from Amazon S3, use natural-language prompts to extract and structure the questionnaire data, refine the workflow through conversation, and write clean CSV output back to Amazon S3 — cutting development from days to hours.  ( 119 min )

A configurable, model-agnostic detector that turns any large language model on Amazon Bedrock into a PII detector. Because the entities to detect live in a prompt rather than in code, one detector adapts to new entity types without retraining, and it outperforms an off-the-shelf tool across five public corpora and nine LLM-based detectors.  ( 123 min )

Multi-turn agents fail in ways single-turn evaluation misses: one early mistake corrupts every later turn. This post introduces the Agent Evaluation Metric (AEM), a decomposable, turn-level way to measure agent quality, applied to its first dimension, correctness, to pinpoint the turn that caused a failure and separate it from the turns that inherited it.  ( 124 min )

AvioBook, a Thales Group Company, prototyped Connected Analytics on Amazon Bedrock AgentCore to turn AvioBook Connect's operational data into plain-language, evidence-based answers for airline managers and dispatchers, helping them find and act on the causes of flight turnaround delays.  ( 121 min )

Learn how to deploy Qwen3.8-2.4T-A95B, a 2.4-trillion-parameter open-weight model, on Amazon SageMaker HyperPod with vLLM. This walkthrough covers cluster provisioning, NVFP4 quantization, and an OpenAI-compatible endpoint with built-in reasoning, tool calling, and native MTP speculative decoding.  ( 126 min )

A recap of August 2026 launches for AI builders across Amazon Bedrock, Amazon Bedrock AgentCore, and Strands: million-token context for OpenAI models, cross-Region inference, agents that run for up to 14 days on dedicated compute, expanded AWS GovCloud availability, and Strands Robots for physical deployment.  ( 117 min )

Learn how Heurist built Heurist Finance, a conversational AI investment workbench, on Amazon Bedrock AgentCore. This customer story shows how AgentCore payments, Identity, Memory, Code Interpreter, and Observability let a small team buy premium market data per query, isolate analysis in a sandbox, and keep every action auditable.  ( 117 min )

TorchServe is no longer maintained, leaving teams to own the entire GPU inference stack. The AWS Ray Serve Deep Learning Container is a supported, pre-tested container with the framework, GPU drivers, and serving layer already assembled. This post walks through deploying a vision-language model on Amazon EKS using the Ray Serve DLC on a single GPU node.  ( 117 min )

Amazon Quick custom permissions let you enforce least-privilege access by toggling features per user. This post walks through four patterns to automate custom permissions across the user lifecycle: a RegisterUser API parameter, account and role defaults, event-driven Amazon EventBridge and AWS Lambda automation, and a retroactive batch update script.  ( 126 min )

GPT-6 Astra from OpenAI is now generally available on Amazon Bedrock. It brings deeper reasoning and sharper judgment to your most demanding tasks, running on the Amazon Bedrock inference engine built for high performance, security, and scale.  ( 116 min )

Pathway's Baby Dragon Hatchling (BDH) is a brain-inspired, post-transformer architecture that reasons in latent space instead of emitting chain-of-thought tokens. See how Pathway develops and scales BDH on Amazon SageMaker HyperPod, and how BDH-CQ set a new cost-efficiency mark on the ARC-AGI-1 benchmark.  ( 119 min )

Pathway's Baby Dragon Hatchling (BDH) is a brain-inspired, post-transformer architecture that reasons in latent space instead of emitting chain-of-thought tokens. See how Pathway develops and scales BDH on Amazon SageMaker HyperPod, and how BDH-CQ set a new cost-efficiency mark on the ARC-AGI-1 benchmark.  ( 119 min )

Amazon SageMaker Feature Store now supports feature-level writes. With the new UpdateRecord API, you can update one or more feature values in a single call without reading or rewriting the entire record. It is available for both the Standard (Amazon DynamoDB) and In-Memory (Amazon ElastiCache) online store tiers.  ( 120 min )

Governing models across accounts is the next step after automatic model registration. This post extends managed MLflow and Amazon SageMaker AI Model Registry sync to two cross-account governance topologies: a hub-and-spoke pattern that centralizes governance with AWS RAM, and a hybrid pattern that keeps development accounts isolated.  ( 121 min )

Managed MLflow on Amazon SageMaker AI now syncs richer model metadata (training metrics, evaluation results, inference specs, and lineage) into the SageMaker AI Model Registry, with lifecycle stage promotion. Part 1 shows how to govern candidate models in a single account using IAM guardrails.  ( 122 min )

Wire Amazon Bedrock AgentCore Evaluations into a GitHub Actions pipeline: deploy an AI agent and an OAuth-protected MCP server to AgentCore runtime, invoke the agent with test prompts, score the responses, and automatically block pull requests when agent behavior regresses.  ( 125 min )

Benchmark two 30B Mixture-of-Experts models, Qwen3-Coder-30B and NVIDIA Nemotron-3-Nano-30B, across G5, G6, G6e, and G7 GPU instances on Amazon SageMaker AI. Compare throughput, latency, and cost-per-token, and see how G7's NVIDIA Blackwell GPUs deliver measurable price-performance gains for real-time LLM inference.  ( 123 min )

HPE Zerto built an agentic troubleshooting system powered by Amazon Bedrock that runs on-premises inside the customer environment. This post describes the multi-agent architecture, the on-premises deployment model built with Strands Agents, and the engineering challenges of grounding agents in live disaster recovery data.  ( 121 min )

DiDi built a transparent, self-owned contact center quality assurance (QA) system on Amazon Bedrock, replacing an opaque third-party tool. Intent verification accuracy rose from 38% to 86%, compliance scoring topped 90%, and Voice of Customer trend analysis dropped from hours to minutes across Spanish and Portuguese support.  ( 122 min )

球场上的镜像神经元 昨天打羽毛球，我从一个刚输给我们的对手身上学到一件事：复盘不能只盯着自己的失误，也要研究对手为什么打得好。 打完两局双打，对面打得更好的那位球友径直走到我面前，问我在羽毛球群里叫什么名字。真正让我意外的，是他接下来谈的不是输赢。 一场酣畅淋漓的混双 昨晚的这球场，我和一位公司招聘团队的之前就认识的女生搭档。 球场上，她落落大方，动作干净利索，在前场左右横移，敢扑敢压，根本不在意动作是否好看。我在后场调动和下压，她在前场抽挡、拦截。我们一边打球一边说笑，第一次搭档却配合得相当默契。 对面是两个男生。其中一位打得不错，球风犀利，落点也很聪明；另一位的球路则直来直往，更喜欢硬碰硬。 我们没有跟他们比蛮力，而是不断变换落点，把他们前后左右调动起来。有时他们被拉得前后踉跄，有时又不得不左右飞奔。等空当出来，我就在后场追身重杀，或者把球吊到网前，让他们来不及上网，只能望球兴叹。 两局下来，四个人都满头大汗。我们打得非常尽兴。对面那位相对弱一些的球友，因为拖了队友后腿，偶尔会尴尬地笑一笑。另一位却既没有不服，也没有憋屈。他下场后的反应，反而让我刮目相看。 不只复盘自己，也要观察对手 他走到我面前，先问我在羽毛球群里的名字，然后直接说出了自己的观点： 球场上要交流。既要跟队友交流，也要跟对手交流。 这也是他下场后马上来认识我的原因。 他接着说，打完球不能只反思自己哪个球没打好、下次应该怎么改，也要留意对手打出了哪些好球。为对手喝彩的同时，也是在学习对手：这个球为什么打得好？他的动作、意识和球路有什么特别？以后自己能不能模仿？ 在他看来，提高不能只盯着自己。观察别人怎么打，同样是一条学习路径。 这番话让我意外。刚才在场上，我们一次次把他们调动得很被动。我原以为他下来后多少会有点懊恼，没想到他首先做的却是认识对手，主动交流，并且琢磨能从刚才的对抗中学到什么。 镜像神经元：观察也是一种练习 这让我联想起前段时间读的《智能简史》提到，即使只是观察别人完成动作，大脑也会对这个动作进行某种模拟。参与这一过程的神经元被称为“镜像神经元”（Mirror Neurons），也被认为与模仿有关。 这也让我重新理解那位球友的做法：盯住一个好球，观察对手的动作、意识和线路，在脑子里重新过一遍，再设法变成自己的东西。 想到这里这里，我又联想起自己曾经教孩子运动时常犯的错。 不能只是埋头苦练 每个孩子的运动天赋和学习节奏都不一样。看到别人一学就会，而自己的孩子练了很多遍，提高却不明显，大人很容易着急，甚至脱口而出：“为什么别人会，你还不会？”这种比较除了打击信心，并不能帮他找到问题。 我以前更容易把“多练”当作答案，觉得动作做得不够好，就再多做几遍。后来才意识到，不能只让孩子埋头苦练、独自琢磨。适当地让他看教程里的动作分解，看比赛视频中高手怎样移动、发力和处理球，再回到场上尝试，也可能带来提高。 当然，看懂不等于做到，观察也代替不了亲自练习。但练习并不只发生在自己挥拍的那一刻。认真看别人怎样完成一个动作，也是在给下一次尝试做准备。 这位球友让我看到，输掉一场球和学到一点东西并不矛盾。能从对手身上看到值得喝彩、值得模仿的地方，也许正是他越打越好的原因。  ( 1 min )

View on sreweekly.com A message from our sponsor, Planetscale: Most database incidents start with one expensive query, not the database being down. PlanetScale gives SRE teams high-availability Postgres and MySQL with automated failover, query insights, and Database Traffic Control to stop runaway queries before they page you. → Explore PlanetScale Incidents start before the response […]  ( 4 min )

Learn how to deploy a multimodal WhatsApp ordering assistant that takes customer orders through text, voice notes, and real-time voice calls on a single business number, built on Amazon Bedrock AgentCore with Amazon Nova 2. The channel and ordering layers stay separate, and one shared memory recognizes each customer across all three channels.  ( 126 min )

Long-running AI agents accumulate outdated memories that degrade quality and create compliance risk. Learn how to design memory lifecycle policies for Amazon Bedrock AgentCore: scoring, consolidating, and pruning agent memories on a nightly AWS Step Functions workflow, with a deployable AWS CDK stack.  ( 124 min )

Building a Physical AI system takes a continuous pipeline, not a single training job. This post shows how to run that model factory (synthetic data generation, post-training, and closed-loop evaluation with NVIDIA Cosmos 3) on a persistent, resilient Amazon SageMaker HyperPod cluster on Amazon EKS, with GPU goodput as the metric that matters.  ( 137 min )

HyperPod InstantStart is an open source control plane that composes Amazon EKS orchestration with the managed capabilities of Amazon SageMaker HyperPod. It drives the same guarded operations through both a web interface and an AI agent, turning cluster bootstrap, capacity, training, inference, and storage into dependable, agent-driven infrastructure.  ( 129 min )

Learn how to customize an Amazon Bedrock knowledge base for large, complex documents by combining the high-accuracy text extraction of Amazon Textract with the generative AI of Amazon Bedrock. This post shows how to ingest and preprocess PDFs and images, then query utility bills at scale for faster, more accurate customer interactions.  ( 118 min )

Disaster recovery at scale is hard. Learn how Intuit built EWOK Agent, an agentic disaster recovery assistant on Amazon Bedrock that lets on-call engineers run production failovers from a plain-language request while keeping every action audited, policy-compliant, and safe.  ( 127 min )

Pupdate We were back in the Lake District (more on that later), so the boys were able to get out for some nice long walks. Going a month later than usual meant that there were no grouse on the estate but there were loads of ripe blackberries, which the boys enjoyed browsing. Sadly Milo’s scan […]  ( 15 min )

Pupdate We were back in the Lake District (more on that later), so the boys were able to get out for some nice long walks. Going a month later than usual meant that there were no grouse on the estate but there were loads of ripe blackberries, which the boys enjoyed browsing. Sadly Milo’s scan […]  ( 15 min )

Engineering teams adopting the AI-Driven Development Lifecycle (AI-DLC) often struggle to turn concepts into working code. This post walks through two reference implementations on Amazon Bedrock AgentCore, Kiro, and Claude Code: an SQL-to-ER-diagram generator and a multi-agent code security analyzer that put the AI-DLC construction phase into practice.  ( 121 min )

An agent that works in a notebook is not an agent in production. This post walks through migrating a LangGraph customer support agent to Amazon Bedrock AgentCore in two stages: onto Runtime, Gateway, and Memory, then to model-driven planning on Strands Agents, retiring operational burdens along the way.  ( 126 min )

Integrate Microsoft Outlook with Amazon Quick to automate email management, calendar scheduling, and workflow coordination. This post walks through the end-to-end setup and shows automation scenarios using Amazon Quick chat agents, Amazon Quick Flows, and Amazon Quick Automate.  ( 117 min )

Deploy a customer-operated LiteLLM gateway on Amazon ECS with AWS Fargate, connect it to an OpenAI model on Amazon Bedrock, and configure Codex to route requests through the gateway's Responses API with scoped identities, budgets, rate limits, and telemetry. We also compare direct IAM Identity Center access and a managed Portkey deployment.  ( 124 min )

Learn best practices for building production-grade, agent-based business process automations with Amazon Quick Automate: choosing the right process, designing focused agents, combining them with deterministic steps, applying human-in-the-loop review, and building in evaluation and observability.  ( 121 min )

Learn how to embed individual Amazon Quick Sight visuals into a React application with per-user access control. This walkthrough uses Amazon Cognito authentication and a serverless AWS Lambda backend to generate scoped embed URLs, deployed with a single AWS CloudFormation stack.  ( 123 min )

Australian teams can now access OpenAI GPT-5.6 Sol, Terra, and Luna models on Amazon Bedrock with global cross-Region inference from the Asia Pacific (Sydney) and Asia Pacific (Melbourne) Regions. This post shows how to invoke the models, use prompt caching, set up Codex with OpenID Connect authentication, and monitor usage with Amazon CloudWatch.  ( 120 min )

Learn how to build a generative AI-based support operations platform on AWS that converts training videos into structured SOPs, applies Retrieval-Augmented Generation to guide ticket resolution, and uses machine learning to predict SLA risk and prioritize work.  ( 127 min )

Business intelligence dashboards can fail silently, showing blank, stale, or wrong data even when every infrastructure monitor reports healthy. Learn how an AWS team built an automated, AI-powered content validation solution on Amazon Bedrock that scans hundreds of dashboards and alerts owners, cutting mean time to detection from days to under an hour.  ( 120 min )

Learn how a global interdealer broker built an automated architecture documentation pipeline on Amazon Bedrock AgentCore that analyzes .NET code bases, generates architecture diagrams, and maintains searchable documentation through Amazon Bedrock Knowledge Bases and AWS CodePipeline.  ( 126 min )

Learn how University Startups and its AWS partner g/d/n/a scaled Trinity, a conversational AI solution for students with disabilities, into a serverless multi-agent architecture on Amazon Bedrock that produces IDEA-aligned transition plans for school districts across the US.  ( 118 min )

Claude Fable 5.1 is now available on Amazon Bedrock and Claude Platform on AWS. This post covers Claude Fable 5.1's improvements, the Enterprise Frontier Safeguards for keeping your data in a cloud environment you control, and how to start building with the model on Amazon Bedrock.  ( 116 min )

When Atos set out to upskill 400 engineers in agentic AI, hands-on learning was the missing ingredient. Over three days, engineers built multi-agent systems on AWS through an AI League event. This post explains why Atos chose the format, what engineers built and learned, and what other enterprises should consider.  ( 120 min )

As generative AI adoption scales, cost governance becomes a top challenge. Learn how Jamf built real-time, per-user spend enforcement for Amazon Bedrock using IAM Customer Managed Policies, an Amazon Athena cost view, and a serverless AWS Lambda loop that applies tiered model limits in near-real-time without disrupting active sessions.  ( 119 min )

Amazon Quick proof-of-concept projects often stall when security teams review the production plan. This post walks through designing dashboards, Spaces, knowledge bases, agents, and Flows with security controls that hold as you scale: dataset shaping, agent isolation, document classification, and approval gates.  ( 125 min )

t54 built x402-secure, a trust layer on Amazon Bedrock AgentCore payments that scores every endpoint before an autonomous agent pays it. See how session budgets, credential isolation, and a deterministic trust gate have governed more than 20 million agent-initiated transactions with no human in the loop.  ( 119 min )

Learn how ZS built a security-hardened Amazon SageMaker platform that balances developer agility with healthcare-grade governance, serving 1,000+ daily active users across 200+ SageMaker domains.  ( 120 min )

Boomi Scribe is an AI-powered agent on AWS that automatically generates documentation for enterprise integration workflows. Learn how Boomi uses Amazon Bedrock, Amazon SageMaker AI, Amazon S3, Amazon DynamoDB, and AWS Lambda to parse integration DAGs, generate detailed documentation, and compare component versions at scale.  ( 121 min )

In this post, you will learn how to deploy and host your MCP server in AgentCore Runtime and integrate it with Amazon Quick, along with the prerequisites. With this pattern, you promote reusability and avoid duplication of AI tools, so clients can reuse commonly used tools and agents exposed through an MCP server instead of authoring them from scratch again. Your customers get a way to use your product inside Amazon Quick (chat agents and workflows) without building custom connectors for every use case.  ( 122 min )

We're excited to share that AWS has been recognized as a Leader in The Forrester Wave: AI Infrastructure Solutions, Q4 2025. In this evaluation of 13 providers, AWS received the highest score in the Strategy category.  ( 114 min )

AWS Agent Registry is now generally available: a single, searchable, governed catalog for the agents, tools, skills, and custom resources across your organization. This post explains what Registry is and walks through its publishing, curation, and discovery workflows, plus enterprise considerations and what's next.  ( 130 min )

This post builds an enterprise agentic retrieval solution on the Amazon Bedrock Managed Knowledge Base and Amazon Bedrock AgentCore. An agent reasons, routes across multiple knowledge bases, and returns cited answers, with seven layers of observability and both on-demand and continuous evaluation, all deployed with a single AWS CloudFormation chain.  ( 123 min )

Learn how to build a multi-tenant agentic document chat application on Amazon Bedrock Managed Knowledge Base, where users upload documents and immediately ask grounded questions. This post covers the ingestion and retrieval flows, the asynchronous indexing lifecycle, per-user data isolation, and best practices for operating the solution at scale.  ( 122 min )

View on sreweekly.com A message from our sponsor, Planetscale: PlanetScale Metal runs Postgres and Vitess on dedicated NVMe inside AWS and GCP. Get data center speed next to your app, with unlimited IOPS and no throttling. Teams routinely see a 70% drop in p99 and p95 latency after migrating. → See the benchmarks When declaring […]  ( 3 min )

Amazon SageMaker Feature Store now supports two new APIs: BatchWriteRecord writes up to 25 records across multiple feature groups in a single call, and ListRecords enumerates record identifiers within a feature group. In this post, we walk through each API with code examples you can use to get started.  ( 120 min )

Decathlon, one of the world's largest sporting goods retailers, forecasts weekly demand for tens of thousands of products across multiple continents. Learn how they deployed Chronos-2 on AWS to improve forecast accuracy by 11-15 points while cutting operational complexity and running weekly inference for about $0.03 on CPU-only instances.  ( 120 min )

Learn how Salesforce used Amazon SageMaker AI Inference Component placement (the SchedulingConfig parameter) to distribute model copies across multiple Availability Zones, meeting their Multi-AZ high availability compliance requirements without sacrificing the cost efficiency of multi-model co-hosting.  ( 120 min )

芳姐的光荣退休欢送会 今天中午，我在芳姐的退休欢送会上，提前偷看了自己退休那天的样子。让我自己都有点不好意思的是——它并不苦，我甚至隐隐盼着它。 芳姐是单位网络组的同事，我 6 年前进公司时她就在了。这六年她一直在我身边：来得比我还早，走路低着头，风风火火，像永远赶着去处理下一个故障。可我们几乎没说过话，多是应用故障排查涉及网络时，在线上打个照面。 今天中午去茶水间倒水，恰好遇到视频组的头，拿着专业单反相机，匆匆朝会议室方向走去，会议室那头人头攒动，感觉有什么事情发生，他很激动地告诉我“今天芳姐退休”。 我当时心里一愣。大概数十天之前，我还去找芳姐修过一次连不上的 WiFi，那是我们唯一一次面对面打交道。她有条不紊地排查了几步，几下就好了，我连她做了什么都没记住。她在我身边六年，我却只在她要走的这天，才第一次认真看她。 我愣在那儿。替她高兴是真的，为一位老同事的突然离开发怵也是真的；可那点连自己都不好意思承认的兴奋，也是真的。那一刻我没想清楚这些感受从哪来，只是有股说不清的力量，把我也推向了会议室。 芳姐讲了几句，回顾自己的职业生涯，没想到她在惠普也待了不少年。之前分属不同部门，我们并不认识，竟到要分别了，才知道我们很巧地曾是同事。 她讲得很朴素，也很动情。最后几年，她感受到年轻人后浪推前浪的压力，拼命努力，不想掉队，心有不甘；可年岁又实实在在地压上来，让她不舍又无奈。组里最新来的 00 后，发现她岁数超过自己妈妈，开始叫她“阿姨”，她一开始很抵触，后来也就由它去了，连两鬓的白发也随之任之，不再染黑。 她反复地、近乎重复地讲着这团矛盾——我听着听着，忽然就被击中了。让我停不下来的，正是她那帽檐下两鬓的露出的白发，那是几十年职业生涯生动的注脚。她讲了那么多遍，我反倒觉得她并没有真和自己和解：一边为年轻人让出舞台，一边又对这里恋恋不舍。 长江后浪推前浪，每个人都会到站。这话我一直知道，今天却是第一次站在中场、看着一个人真的在我面前下车。我久久不能平静，说不清是舍不得她，还是在她身上撞见了那个终将轮到我的时刻——而我竟隐隐盼着它。仪式散了，我回工位继续干活。轮到我下车的那天，我不知道自己会像芳姐那样心有不甘，还是仍旧像今天这样，悄悄地盼着。  ( 1 min )

Creative teams produce more assets than ever, but fragmented tools and manual context transfer slow production. This post shows how to build a reusable agent harness with Amazon Quick and fal, connected through the Model Context Protocol (MCP), using two hands-on workflows: an eight-panel storyboard and a music-video concept prototype.  ( 120 min )

Amazon Bedrock now supports the OpenAI GPT-5.6 models, Terra and Luna, in India with India geographic cross-Region inference. If you have local data processing requirements, you can now use these models at scale while Amazon Bedrock keeps inference requests and data within India.  ( 122 min )

Amazon Bedrock now supports the OpenAI GPT-5.6 models, Terra and Luna, in India with India geographic cross-Region inference. If you have local data processing requirements, you can now use these models at scale while Amazon Bedrock keeps inference requests and data within India.  ( 122 min )

Self-hosted speech AI carries an observability trade-off: the numbers that drive capacity planning and cost management stay locked inside the vendor container. Deepgram closes that gap on Amazon SageMaker AI with two capabilities that land billing, usage, and per-GPU metrics directly in your own Amazon CloudWatch account.  ( 120 min )

Serving automatic speech recognition (ASR) models at scale is costly when each request uses only a fraction of a GPU. Learn how NVIDIA CUDA Multi-Process Service (MPS) with NVIDIA Triton Inference Server on Amazon EC2 GPU instances cuts GPU infrastructure by 75% while holding sub-second latency at 92.1 requests per second per GPU.  ( 123 min )

It’s been a couple of months since Milo finished his fourth (modified) CHOP/CEOP protocol, and he’s been able to enjoy the summer without any vet visits[1]. We’d been hoping for a nice long remission like last year, but that wasn’t to be. A scan at the start of this week found a lesion on his […]  ( 13 min )

It’s been a couple of months since Milo finished his fourth (modified) CHOP/CEOP protocol, and he’s been able to enjoy the summer without any vet visits[1]. We’d been hoping for a nice long remission like last year, but that wasn’t to be. A scan at the start of this week found a lesion on his […]  ( 14 min )

Amazon Bedrock AgentCore Evaluations decouples agent evaluation from the framework you build on. As long as your agent emits OpenTelemetry telemetry, the service can score it, whether you use LangGraph, LlamaIndex, the OpenAI Agents SDK, Google ADK, the Claude Agent SDK, or Strands Agents. This post explains how the framework-agnostic contract works.  ( 123 min )

In this post, you will learn how GoDaddy migrated from their legacy business intelligence (BI) tool to Amazon Quick. This was a two-year transformation that delivered results across every dimension of the business: 15,000 hours saved annually, 50% reduction in dashboard count, rendering times cut to under 5 seconds, and AI-powered self-service analytics now accessible to every employee.  ( 121 min )

Learn how Natera built an automated voice agent on Amazon Bedrock AgentCore that lets patients book mobile phlebotomy appointments through natural conversation. The post covers the dual-WebSocket bridge, event-driven latency masking, and progressive-trust authentication behind 100% tool-calling accuracy and sub-7-second latency.  ( 126 min )

The SageMaker Python SDK v3 redesigns script mode with unified ModelTrainer and ModelBuilder classes. This post walks through two end-to-end examples, a scikit-learn Random Forest and a multi-GPU Stable Diffusion 3.5 LoRA fine-tune, showing how SourceCode syncs your local code into any container at runtime so you can iterate without rebuilding Docker images.  ( 124 min )

The advanced side of supervised fine-tuning data prep. This second post in a two-part series covers evaluating data readiness with learning curves, selecting high-value data subsets, augmenting data with synthetic and distilled examples, and mixing data sources to prevent catastrophic forgetting.  ( 121 min )

Data preparation determines the ceiling of any supervised fine-tuning project. This first post in a two-part series covers the foundations of SFT data prep: quality checks, conversational (JSONL) formatting, reasoning and tool-calling schemas, and a representative train/evaluation split.  ( 121 min )

Learn how Amazon Bedrock AgentCore agents in one account can generate answers from an Amazon Bedrock knowledge base backed by Amazon Redshift Serverless in another account, without copying source data. This post covers the architecture, security boundary, and two orchestration models: a code-based Strands agent and a declarative AgentCore harness.  ( 118 min )

Amazon OpenSearch Service now supports MCP Apps, which return interactive visualizations alongside your AI agent's text responses. Learn how a single, locally run MCP server lets your agent move from alert to trace to logs to root cause in one conversation, and how you can verify every step inline without leaving your IDE.  ( 120 min )

Build a governed weekly reporting workflow with Amazon Quick Desktop and Amazon FSx for NetApp ONTAP. An Amazon S3 access point exposes an approved folder to a Quick knowledge base, and a custom skill drafts cited weekly reports and Slack summaries with human review before anything is shared.  ( 124 min )

Amazon SageMaker HyperPod now offers managed Ray support on Amazon EKS. Create and monitor Ray clusters, connect JupyterLab and Code Editor notebooks to live clusters, get out-of-the-box observability, and run resilient distributed training and accelerated inference from SageMaker Studio, all with open-source KubeRay and standard Ray APIs.  ( 120 min )

Learn how to build a customizable, smart-caching knowledge management system on AWS that captures and delivers institutional (tribal) knowledge through a voice-first AI avatar. The accelerator uses Amazon Bedrock Knowledge Bases for retrieval-augmented generation and deploys in hours with AWS CloudFormation.  ( 124 min )

AWS Agent Registry gives your organization a centralized, searchable catalog for agents, tools, and skills. It works with the open Agentic Resource Discovery (ARD) standard to enable cross-environment discovery and governance at scale.  ( 116 min )

Learn how to build a voice ordering system for restaurants that answers a phone call and takes an order end to end, with no app, no website, and no sign-in. It uses Amazon Connect for telephony, Amazon Connect Agentic Voice for real-time speech, an Amazon Connect AI agent for reasoning, and Amazon Bedrock AgentCore Gateway to reach backend tools through MCP.  ( 126 min )

Metadata harmonization (standardizing labels, identifiers, and formats so datasets can work together) is still largely manual. This post shows how AI-powered metadata correction works in practice, covering two approaches, human-in-the-loop validation and autonomous agent-driven workflows, plus governance considerations for production deployment.  ( 123 min )