The name is the button.

An agent writes the code now, and a human thumb hovers over Accept all a hundred times a day. The honest question of this decade is what, exactly, you just accepted. So I read the diff.

Eight years as a backend engineer in Stockholm, back in Tokyo since 2023, and I still ship something small most nights, usually badly. My one rule: the only real review of a model is the thing you built with it. That is why there is no leaderboard on this site.

Around a hundred and forty sources come through — the labs' own posts, the papers, the tools, the runtimes and languages nobody is watching yet, the chip under the demo, and the newsletters people actually forward. What is moving gets counted so the week reads at a glance, and every few days I explain one mechanism in plain words.

A story here is a headline, a short excerpt, one image and the link to whoever wrote it. We never reproduce the post; the images belong to their authors. A post written in Japanese appears in Japanese, exactly as it was published, and the link goes to the original.

— Yuki Halvorsen, Tokyo

← Accept All Archive

Google Cloud AILabs

What the Gemini agent means for startups

10.15

Small teams, short runway, and constant pressure to ship faster — it’s the reality we see every day among the founders we work with at Google for Startups.

Models & releases Agents & vibe coding AI & Machine Learning Customers Startups

Read at Google Cloud AI ↗

One letter a week, starting soon.

Latest

What the Gemini agent means for startups

Related

LabsGemini 4 Argon available on Google Cloud, built to help solve your business’ hardest problems Google Cloud AI

LabsWelcome to Gemini at Work 2026: Introducing the Gemini agent Google Cloud AI

LabsPower your agents: Gemini 3.8 Live with Live Avatar is now generally available Google Cloud AI

JapanClaude Codeデスクトップアプリ、並行作業を進めやすくするセッション管理の改善を案内 gihyo.jp

DeepSeek and what enterprises should learn from AI agent exploits AI Business

ToolsFinish RL Training Faster: Bitwise-Consistent, High-Performance, Agent-Driven vLLM Blog