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Run Ray on TPU, Part 1: The foundations

Google Developers BlogLabsRun Ray on TPU, Part 1: The foundations Ray 2.55 introduces official, first-class support for Google Cloud TPUs, enabling developers to run distributed Python workloads on Google's accelerators using the familiar Ray task-and-actor APIs. To handle the strict n

Scaling Agentic RL: High-Throughput Agentic Training with Tunix

Google Developers BlogLabsScaling Agentic RL: High-Throughput Agentic Training with Tunix Tunix is Google’s new JAX-native post-training library designed to eliminate TPU idling bottlenecks when training multi-turn, tool-using LLM reasoning agents. It maximizes hardware throughput by combining highly concurre

Run Ray on TPU, Part 2: Ray AI libraries

Google Developers BlogLabsRun Ray on TPU, Part 2: Ray AI libraries This second installment explores how Ray’s higher-level libraries—Serve, Data, and Train—abstract the complexities of running AI workloads on Google's TPU slices. Ray Serve uses a simple topology configuration to correct

How to use Google microbenchmarks for evaluating TPU performance

Google Developers BlogLabsHow to use Google microbenchmarks for evaluating TPU performance Google's open-source TPU microbenchmark suite provides developers with granular performance metrics across Network, Compute, HBM, Host Transfer, and Attention components to validate real-world hardware capabilities. By l

Agent and Model Evaluations in Gemini Enterprise Agent Platform are now GA

Google Developers BlogLabsAgent and Model Evaluations in Gemini Enterprise Agent Platform are now GA Agent Platform's evaluation service is now generally available, providing developers with a unified engine to measure agent quality consistently across local development experiments and live production traffic. You can e

Enable on-demand expertise with Agent Skills in Genkit Go

Google Developers BlogLabsEnable on-demand expertise with Agent Skills in Genkit Go To prevent context window bloat and reduce token consumption, Genkit Go introduces Agent Skills based on a progressive disclosure architecture. Developers can package specialized instructions, scripts, and references int

Scaling real-time AI agents with session-aware load balancing

Google Developers BlogLabsScaling real-time AI agents with session-aware load balancing Real-time AI agents break traditional request-response load balancing paradigms because they rely on long-lived, stateful bidirectional streams that obscure true server capacity. To solve this, developers must implement

Model routing with Google Cloud API Gateway

Google Developers BlogLabsModel routing with Google Cloud API Gateway Google Cloud API Gateway now offers a model routing feature in Public Preview, allowing developers to dynamically route traffic to models like Gemini, Claude, or OpenAI OSS-GPT without hardcoding endpoints or managing op

Scaling AI Agent Infrastructure with the MCP Stateless updates

Google Developers BlogLabsScaling AI Agent Infrastructure with the MCP Stateless updates The 2026-07-28 Model Context Protocol (MCP) specification replaces legacy stateful constraints with a fully stateless core, enabling cloud-native horizontal scaling, serverless deployments, and standard round-robin load

Agent Plugins package your skills, tools, and more

Google Developers BlogLabsAgent Plugins package your skills, tools, and more Agent Plugins 1.0.0 is a new, vendor-neutral directory specification—backed by Google, Amazon, Microsoft, and others—for packaging Agent Skills and MCP servers into a single portable unit. By standardizing the manifest (

Mastering Edge AI on Raspberry Pi with LiteRT and Gemma

Google Developers BlogLabsMastering Edge AI on Raspberry Pi with LiteRT and Gemma Deploying secure, real-time Edge AI on Raspberry Pi is now simplified using LiteRT and lightweight Gemma open models. LiteRT optimizes CPU and GPU performance, delivering fast token speeds for models like Gemma4, enablin

Why Go is an Ideal Language for AI-Assisted Software Engineering

Google Developers BlogLabsWhy Go is an Ideal Language for AI-Assisted Software Engineering As AI coding assistants shift the developer's primary role from writing boilerplate to reviewing and maintaining systems, language choice becomes critical for long-term architectural integrity. Go directly addresses this

Introducing Credentio: Open Source C++ Library for C2PA Content Credentials from Google

Google Developers BlogLabsIntroducing Credentio: Open Source C++ Library for C2PA Content Credentials from Google Credentio is a newly released, open-source C++ library from Google that allows developers to integrate high-performance, local-first validation of C2PA Content Credentials into their client and server applications. By pr

Google Developers BlogLabsHeyGen x Google Cloud: Bringing Avatar IV to TPUs HeyGen ported their 18B+ parameter Avatar IV video generation model to Google Cloud's Trillium (v6e) TPUs via torchax and XLA, utilizing FSDP and Ulysses sequence parallelism across an eight-chip mesh. To achieve a 1.86x

Build zero-trust AI agents with Google's Agent Development Kit

Google Developers BlogLabsBuild zero-trust AI agents with Google's Agent Development Kit Building autonomous AI agents that mutate production state requires moving beyond soft system prompts to a robust zero-trust architecture. To secure Google Agent Development Kit (ADK) workflows against prompt injections

How to Evaluate Live & Voice Agents in ADK

Google Developers BlogLabsHow to Evaluate Live & Voice Agents in ADK Moving live voice agents from demo to production requires rigorous, automated testing to handle the unpredictability of real multi-turn conversations. ADK now provides native live evaluation, allowing developers to test

Enterprise-Grade Precision for Long-Context Multimodal Embedding Inference on Cloud TPU

Google Developers BlogLabsEnterprise-Grade Precision for Long-Context Multimodal Embedding Inference on Cloud TPU Google Cloud has natively integrated TPU support into the vLLM serving engine, allowing developers to elastically scale high-demand embedding pipelines using Google Kubernetes Engine (GKE). To handle massive 15K+ token c

Decoding cosmic signals with deep learning and Keras

Google Developers BlogLabsDecoding cosmic signals with deep learning and Keras Astroparticle physics sits at the exciting intersection of astrophysics and particle physics and stu...

4 engineering patterns behind the strongest AI Agents Challenge submissions

Google Developers BlogLabs4 engineering patterns behind the strongest AI Agents Challenge submissions The recent Google for Startups AI Agents Challenge revealed that the most successful multi-agent systems rely on foundational software engineering patterns rather than just raw model power. Winning architectures consiste

Driving Developer Excellence: Inside the Program Sprints

Google Developers BlogLabsDriving Developer Excellence: Inside the Program Sprints The Gemini Enterprise Developer Experience (DevEx) program conducts ongoing sprint testing of end-to-end developer workflows to identify and rapidly resolve friction points without relying on internal shortcuts. This rec

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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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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