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19 stories

Deploy a multimodal WhatsApp ordering assistant with Amazon Bedrock AgentCore

AWS Machine LearningLabsDeploy a multimodal WhatsApp ordering assistant with Amazon Bedrock AgentCore 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

Build a Physical AI model factory with NVIDIA Cosmos 3 on SageMaker HyperPod

AWS Machine LearningLabsBuild a Physical AI model factory with NVIDIA Cosmos 3 on SageMaker HyperPod 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

Run agent-driven Amazon SageMaker HyperPod operations with InstantStart

AWS Machine LearningLabsRun agent-driven Amazon SageMaker HyperPod operations with InstantStart 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

Customizing your knowledge base on Amazon Bedrock for large and complex documents using Amazon Textract

AWS Machine LearningLabsCustomizing your knowledge base on Amazon Bedrock for large and complex documents using Amazon Textract 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 inge

How Intuit built an agentic disaster recovery assistant with Amazon Bedrock

AWS Machine LearningLabsHow Intuit built an agentic disaster recovery assistant with Amazon Bedrock 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 kee

AI-driven development lifecycle using Amazon Bedrock AgentCore

AWS Machine LearningLabsAI-driven development lifecycle using Amazon Bedrock AgentCore 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 Clau

Migrate agentic workloads to Amazon Bedrock AgentCore

AWS Machine LearningLabsMigrate agentic workloads to Amazon Bedrock AgentCore 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

Integrating Outlook with Amazon Quick for AI-powered email automation

AWS Machine LearningLabsIntegrating Outlook with Amazon Quick for AI-powered email automation 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 c

Set up OpenAI ChatGPT Codex with LiteLLM on Amazon ECS and Amazon Bedrock

AWS Machine LearningLabsSet up OpenAI ChatGPT Codex with LiteLLM on Amazon ECS and Amazon Bedrock 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

Best practices for building agentic automations with Amazon Quick Automate

AWS Machine LearningLabsBest practices for building agentic automations with Amazon Quick Automate 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, appl

Embed Quick Sight visuals using Cognito user authentication

AWS Machine LearningLabsEmbed Quick Sight visuals using Cognito user authentication 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 e

Accessing OpenAI models on Amazon Bedrock from Australia with global cross-Region inference

AWS Machine LearningLabsAccessing OpenAI models on Amazon Bedrock from Australia with global cross-Region inference 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

Modernizing and scaling support operations with generative AI on AWS

AWS Machine LearningLabsModernizing and scaling support operations with generative AI on AWS 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

How an AWS team detects dashboard content failures at scale using Amazon Bedrock

AWS Machine LearningLabsHow an AWS team detects dashboard content failures at scale using Amazon Bedrock 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 solu

From code to diagrams: Agentic architecture documentation with Amazon Bedrock AgentCore

AWS Machine LearningLabsFrom code to diagrams: Agentic architecture documentation with Amazon Bedrock AgentCore 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 documentat

Trinity: Agentic AI-powered transition planning for students with disabilities

AWS Machine LearningLabsTrinity: Agentic AI-powered transition planning for students with disabilities 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-align

Introducing Claude Fable 5.1 on AWS

AWS Machine LearningLabsIntroducing Claude Fable 5.1 on AWS 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 contro

From theory to delivery: How Atos upskilled 400 engineers in agentic AI

AWS Machine LearningLabsFrom theory to delivery: How Atos upskilled 400 engineers in agentic AI 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

Tokenomics at scale: How Jamf built real-time spend enforcement for Amazon Bedrock

AWS Machine LearningLabsTokenomics at scale: How Jamf built real-time spend enforcement for Amazon Bedrock 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, an

On the calendar

予定 · Conferences and launch events, this week's stories from each corner of the industry, and what its press is covering — in English

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This week, from that corner the newest stories from the corner of the industry you picked

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How code moves in 2026 from the industry's own reports

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About

Accept All is a magazine, a radar and a diary about artificial intelligence and the craft of code — read from Tokyo, for people who build.

The name is the button. Code is written by agents now and reviewed by a human thumb that hovers over Accept all a hundred times a day; the whole question of this decade is what, exactly, you just accepted. So we read the diff. A magazine, because every week one model, one tool or one idea is worth reading about slowly. A radar, because we count what the labs, the Valley, GitHub and the chip makers are talking about — releases, agents, open weights, compute, funding, rules — and show it as it moves. A diary, because a seal is set each day in that day's colour, and the days add up.

We read the research labs' own posts, the American and European tech press, the Japanese and Chinese developer sites and the newsletters people actually forward, and bring it together in English and Japanese. Everything here links back to the people who wrote it; the images belong to their authors.

Accept All will keep changing. New sources, new signals, new ways of looking — a little better each week, never finished. If something here made you open a terminal, that is enough.

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